WO2014168125A1 - 生活習慣病指標の評価方法、生活習慣病指標評価装置、生活習慣病指標評価方法、生活習慣病指標評価プログラム、生活習慣病指標評価システム、および情報通信端末装置 - Google Patents
生活習慣病指標の評価方法、生活習慣病指標評価装置、生活習慣病指標評価方法、生活習慣病指標評価プログラム、生活習慣病指標評価システム、および情報通信端末装置 Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2800/00—Detection or diagnosis of diseases
- G01N2800/04—Endocrine or metabolic disorders
- G01N2800/044—Hyperlipemia or hypolipemia, e.g. dyslipidaemia, obesity
Definitions
- the present invention relates to a lifestyle-related disease index evaluation method, a lifestyle-related disease index evaluation device, a lifestyle-related disease index evaluation method, a lifestyle-related disease index evaluation program, a lifestyle-related disease index evaluation system, and an information communication terminal device.
- Biomarker tests are rapidly progressing with the recent development of genome analysis and post-genome tests, and are being widely used in disease prevention, diagnosis, prognosis estimation, and the like.
- Biomarkers that have been actively tested include genomics and transcriptomics based on genetic information, proteomics based on protein information, and metabolomics based on metabolite information.
- Metabolomics is highly anticipated because it is a biomarker that reflects environmental factors in addition to genetic factors, but because of the large number of metabolites, there are still many problems in comprehensive analysis methods. There is a problem of being left behind.
- amino acids that are the central existence of metabolic pathways are attracting attention among metabolites in living bodies.
- Non-Patent Document 1-2 it has been reported that the amino acid concentration fluctuates in diseases such as liver failure and renal failure.
- Patent Documents 1-3 relating to a method for associating an amino acid concentration with a biological state are disclosed as prior patents.
- Patent Document 4 relating to a method for evaluating the state of metabolic syndrome using amino acid concentration
- Patent Document 5 relating to a method for evaluating the state of visceral fat accumulation using amino acid concentration
- glucose tolerance using amino acid concentration
- Patent Document 6 on a method for evaluating the state of dysfunction: Evaluating at least one of apparent obesity, hidden obesity and obesity defined by BMI (Body Mass Index) and VFA (Viseral Fat Area) using amino acid concentration
- Patent Document 7 relating to the method to perform, and less of fatty liver, NAFLD (non-alcoholic fatty liver disease), and NASH (non-alcoholic steatohepatitis) using amino acid concentration
- Patent Document 8 relates to a method for evaluating the condition of fatty liver disease comprising one are also published.
- lifestyle-related disease indicators for example, risk factors of lifestyle-related diseases that can occur mainly due to metabolic syndrome (eg, visceral fat accumulation, insulin resistance, fatty liver, etc.)
- metabolic syndrome e.g. visceral fat accumulation, insulin resistance, fatty liver, etc.
- the search for amino acids with high clinical significance that are useful for the evaluation of the state of the disease has not been made. Therefore, the state of the index of lifestyle-related diseases is highly accurately and systematically evaluated using the amino acid concentration.
- development was not carried out. For example, the progression of metabolic syndrome is known to cause serious diseases such as cardiovascular events and cerebrovascular events in the future, but the search for prevention methods for these events using the blood amino acid profile has been conducted. (See Non-Patent Documents 3 and 4).
- the present invention has been made in view of the above problems, and is a lifestyle-related disease index evaluation method and lifestyle that can provide highly reliable information that can be helpful in knowing the state of lifestyle-related disease indicators.
- An object of the present invention is to provide a disease index evaluation apparatus, a lifestyle-related disease index evaluation method, a lifestyle-related disease index evaluation program, a lifestyle-related disease index evaluation system, and an information communication terminal device.
- the lifestyle-related disease index evaluation method includes an acquisition step of acquiring amino acid concentration data relating to the concentration value of amino acids in blood collected from an evaluation target; An evaluation step of evaluating the state of an index of lifestyle-related diseases for the evaluation target using the amino acid concentration values of Gly and Tyr included in the amino acid concentration data of the evaluation target acquired in the acquisition step; It is characterized by including.
- the lifestyle-related disease index evaluation method is the aforementioned lifestyle-related disease index evaluation method, wherein, in the evaluation step, the amino acid concentration values of Gly, Tyr, and Asn, Gly, Tyr, and Ala Amino acid concentration values, Gly, Tyr, and Val amino acid concentration values, or Gly, Tyr, and Trp amino acid concentration values are used. Further, the lifestyle disease index evaluation method according to the present invention is characterized in that, in the lifestyle disease index evaluation method, the concentration values of amino acids of Gly, Tyr, Asn, and Ala are used in the evaluation step. And
- the lifestyle disease index evaluation method is the lifestyle disease index evaluation method, wherein the evaluation step evaluates at least one state of fatty liver, visceral fat, and insulin. It is characterized by.
- the lifestyle disease index evaluation method according to the present invention is the lifestyle disease index evaluation method, wherein the evaluation step evaluates at least two states of fatty liver, visceral fat, and insulin. It is characterized by. Further, the lifestyle disease index evaluation method according to the present invention is characterized in that, in the lifestyle disease index evaluation method, the evaluation step evaluates the states of fatty liver, visceral fat, and insulin. .
- the lifestyle-related disease index evaluation method is the above-described lifestyle-related disease index evaluation method, wherein, in the evaluation step, (i) Gly and Tyr amino acid concentration values, (ii) Gly, Tyr, And (iii) Gly, Tyr, and Ala amino acid concentration values, (iv) Gly, Tyr, and Val amino acid concentration values, (v) Gly, Tyr, and Trp amino acid concentration values.
- concentration value or (vi) the amino acid concentration values of Gly, Tyr, Asn, and Ala, to evaluate the degree of risk of developing lifestyle-related diseases (risk of developing lifestyle-related diseases), It is characterized by.
- the lifestyle-related disease index evaluation method is the aforementioned lifestyle-related disease index evaluation method, wherein in the evaluation step, the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp, and , Gly, Tyr, Asn, Ala, Val, and Trp are substituted for the amino acid concentration values (hereinafter may be referred to as evaluation formulas), and the values of the above formulas (below, In some cases, the state of insulin is evaluated by calculating a value of an evaluation formula or an evaluation value).
- the lifestyle-related disease index evaluation method is the above-described lifestyle-related disease index evaluation method, wherein in the evaluation step, (i) concentrations of amino acids of Gly, Tyr, Asn, Ala, Val, and Trp Using formulas that include values and variables into which the concentration values of amino acids Gly, Tyr, Asn, Ala, Val, and Trp are substituted, or (ii) Gly, Tyr, Asn, Ala, Val, and Trp The amino acid concentration value, the BMI (Body Mass Index) value obtained in advance of the evaluation object, and the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp and the evaluation object BMI value are substituted. And evaluating the visceral fat state by calculating the value of the equation using an equation including the following variables: That.
- the lifestyle-related disease index evaluation method is the above-described lifestyle-related disease index evaluation method, wherein, in the evaluation step, Gly, Tyr, Asn, Ala, Cit, and Leu amino acid concentration values, and , Gly, Tyr, Asn, Ala, Cit, and Leu using a formula including a variable to which the amino acid concentration value is substituted, to evaluate the state of fatty liver by calculating the value of the formula Features.
- the lifestyle-related disease index evaluation method is the aforementioned lifestyle-related disease index evaluation method, wherein in the evaluation step, the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp, and , Gly, Tyr, Asn, Ala, Val, and Trp to evaluate the state of insulin and visceral fat by calculating the value of the above expression using an expression that includes variables substituted It is characterized by.
- the lifestyle-related disease index evaluation method is the above-described lifestyle-related disease index evaluation method, wherein in the evaluation step, (i) concentrations of amino acids of Gly, Tyr, Asn, Ala, Val, and Trp Insulin status is evaluated by calculating the value of the above equation using a value and a variable that is substituted with the concentration values of amino acids Gly, Tyr, Asn, Ala, Val, and Trp, (Ii) Using an expression including variables in which the concentration values of amino acids Gly, Tyr, Asn, Ala, Val, and Trp and the amino acid concentrations of Gly, Tyr, Asn, Ala, Val, and Trp are substituted.
- the lifestyle-related disease index evaluation method is the above-described lifestyle-related disease index evaluation method, wherein in the evaluation step, (i) concentrations of amino acids of Gly, Tyr, Asn, Ala, Val, and Trp An expression containing values and variables to which the concentration values of amino acids Gly, Tyr, Asn, Ala, Val, and Trp are substituted; (ii) amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp And BMI (Body Mass Index) value obtained in advance, an expression including amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp and a variable into which the BMI value to be evaluated is substituted.
- BMI Body Mass Index
- the lifestyle-related disease index evaluation apparatus is a lifestyle-related disease index evaluation device that includes a control unit and a storage unit, and evaluates the state of the lifestyle-related disease index for an evaluation target, the control unit comprising: The Gly and Tyr amino acid concentration values included in the previously obtained amino acid concentration data of the evaluation target relating to the amino acid concentration values, and the variables to which the Gly and Tyr amino acid concentration values are substituted in advance
- An evaluation unit is provided that evaluates the state of the lifestyle-related disease index with respect to the evaluation target by calculating the value of the expression using an expression stored in a storage unit.
- the lifestyle-related disease index evaluation method is performed in an information processing apparatus including a control unit and a storage unit, and a lifestyle-related disease index evaluation method for evaluating the state of an index of lifestyle-related diseases for an evaluation target And the Gly and Tyr amino acid concentration values included in the previously obtained amino acid concentration data of the evaluation object related to the amino acid concentration value, and the Gly and Tyr amino acid values, which are executed in the control unit.
- An evaluation step for evaluating the state of the index of the lifestyle-related disease for the evaluation target by calculating the value of the expression using an expression stored in the storage unit in advance including a variable into which a concentration value is substituted. Including.
- the lifestyle-related disease index evaluation program is a lifestyle-related disease index evaluation that evaluates the state of an index of lifestyle-related diseases with respect to an evaluation target for execution in an information processing apparatus including a control unit and a storage unit.
- Evaluation that evaluates the state of the index of the lifestyle-related disease with respect to the evaluation target by calculating the value of the expression using an expression that is stored in the storage unit in advance, including a variable that is substituted with the amino acid concentration value Including a step.
- the recording medium according to the present invention is a non-transitory computer-readable recording medium, and includes a programmed instruction for causing an information processing apparatus to execute the lifestyle-related disease index evaluation method.
- the lifestyle-related disease index evaluation system includes a control unit and a storage unit, and includes a lifestyle-related disease index evaluation device that evaluates the state of an index of lifestyle-related diseases with respect to an evaluation target, a control unit, and an amino acid An information communication terminal device that provides amino acid concentration data of the evaluation object related to the concentration value of the lifestyle-related disease index evaluation system configured to be communicably connected via a network, the information communication terminal device
- the control unit transmits the amino acid concentration data of the evaluation target to the lifestyle-related disease index evaluation device, and the life of the evaluation target transmitted from the lifestyle-related disease index evaluation device
- a result receiving means for receiving an evaluation result relating to the state of the index of habitual disease, wherein the control unit of the lifestyle disease index evaluation apparatus is configured to transmit the information communication information.
- Amino acid concentration data receiving means for receiving the amino acid concentration data of the evaluation object transmitted from the terminal device, and Gly and Tyr included in the amino acid concentration data of the evaluation object received by the amino acid concentration data receiving means
- the evaluation object It is characterized by comprising evaluation means for evaluating the state of an indicator of lifestyle-related diseases, and result transmission means for transmitting the evaluation result obtained by the evaluation means to the information communication terminal device.
- the information communication terminal device is an information communication terminal device that includes a control unit and provides amino acid concentration data to be evaluated regarding the amino acid concentration value.
- a result acquisition means for acquiring an evaluation result relating to the state of an index of habitual disease, wherein the evaluation result is a concentration value of Gly and Tyr amino acids included in the amino acid concentration data to be evaluated; and Gly and Tyr Using a formula including a variable to which the amino acid concentration value is substituted, and calculating the value of the formula, thereby evaluating the state of the lifestyle-related disease index for the evaluation target, And
- the information communication terminal device is connected to the information communication terminal device so as to be communicable via a network with a lifestyle-related disease index evaluation device that evaluates the state of the lifestyle-related disease index for the evaluation target.
- the control unit further comprises amino acid concentration data transmitting means for transmitting the amino acid concentration data to be evaluated to the lifestyle-related disease index evaluation device, and the result obtaining means includes the lifestyle-related disease index. Receiving the evaluation result transmitted from the evaluation device.
- the lifestyle-related disease index evaluation apparatus includes a control unit and a storage unit that are communicably connected to an information communication terminal device that provides amino acid concentration data to be evaluated regarding amino acid concentration values via a network.
- a lifestyle-related disease index evaluation apparatus that evaluates the state of an index of lifestyle-related diseases with respect to the evaluation target, wherein the control unit uses the amino acid concentration data of the evaluation target transmitted from the information communication terminal device.
- Amino acid concentration data receiving means for receiving, Gly and Tyr amino acid concentration values included in the amino acid concentration data to be evaluated received by the amino acid concentration data receiving means, and Gly and Tyr amino acid concentration values
- Gly and Tyr amino acid concentration values By calculating the value of the formula using the formula stored in the storage unit in advance including the variable to be substituted, And evaluating means for valence interest to assess the indicators of the lifestyle-related diseases, that the evaluation results obtained in the evaluation unit with a, a result transmission means for transmitting to the information communication terminal apparatus, characterized by.
- amino acid concentration data relating to amino acid concentration values in blood collected from an evaluation object is acquired, and the amino acid concentration values of Gly and Tyr contained in the acquired evaluation object amino acid concentration data are used. Since the state of the index of lifestyle-related disease is evaluated for the evaluation target, it is possible to provide highly reliable information that can be used as a reference for knowing the state of the index of lifestyle-related disease.
- the evaluation object You may evaluate the state of an indicator of lifestyle-related diseases.
- the amino acid concentration value of Gly, Tyr, and Asn “the amino acid concentration value of Gly, Tyr, and Ala”, “the amino acid concentration value of Gly, Tyr, and Val”, or “ Since the amino acid concentration values of Gly, Tyr, and Trp are used, there is an effect that it is possible to further improve the reliability of information that can be used as a reference for knowing the state of the index of lifestyle-related diseases.
- the expression including the concentration values of the amino acids Gly, Tyr, and Asn and the variables into which the concentration values of the amino acids Gly, Tyr, and Asn are substituted “Gly, Tyr, and Ala's amino acid concentration values and equations containing variables to which Gly, Tyr, and Ala amino acid concentration values are substituted ",” Gly, Tyr, and Val amino acid concentration values, and Gly, Tyr, and Include an expression that includes a variable to which the concentration value of the amino acid of Val is substituted ", or" the concentration value of the amino acid value of Gly, Tyr, and Trp and the concentration value of the amino acid value of Gly, Tyr, and Trp are substituted.
- the state of the index of lifestyle-related diseases may be evaluated for the evaluation target by calculating the value of the expression using “expression”.
- the amino acid concentration values of Gly, Tyr, Asn, and Ala are used, it is possible to realize further improvement in the reliability of information that can be used as a reference for knowing the state of an index of lifestyle-related diseases. There is an effect.
- the expression including the concentration values of the amino acids Gly, Tyr, Asn, and Ala and the variables into which the concentration values of the amino acids Gly, Tyr, Asn, and Ala are substituted is used. By calculating this value, the state of the indicator of lifestyle-related diseases may be evaluated for the evaluation target.
- At least one state of fatty liver, visceral fat, and insulin is evaluated, at least one state of “fatty liver, visceral fat, and insulin” that is an index of lifestyle-related diseases It is possible to provide highly reliable information that can be used as a reference for knowing.
- the states of fatty liver, visceral fat, and insulin are evaluated, it is possible to provide highly reliable information that can be used as a reference in knowing the three states of fatty liver, visceral fat, and insulin. There is an effect that can be done.
- the concentration values of the amino acid values of Gly, Tyr, Asn, Ala, Val, and Trp and the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp are substituted. Since the state of insulin is evaluated by calculating the value of the equation using the equation, there is an effect that it is possible to further improve the reliability of information that can be used as a reference in knowing the insulin state. According to the present invention, the state of insulin may be evaluated using the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp.
- “variables into which the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp and the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp are substituted Containing formula "or" Gly, Tyr, Asn, Ala, Val, and Trp amino acid concentration values, BMI values to be evaluated previously obtained, and Gly, Tyr, Asn, Ala, Val, and Trp amino acid concentrations Since the status of the visceral fat is evaluated by calculating the value of the formula using the formula including the variable to which the value and the BMI value to be evaluated are substituted, information that can be used as a reference for knowing the status of the visceral fat There is an effect that further improvement in reliability can be realized.
- the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp or the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp, and evaluations obtained in advance.
- the BMI value of the subject may be used to assess visceral fat status.
- the amino acid concentration values of Gly, Tyr, Asn, Ala, Cit, and Leu and the variables into which the amino acid concentration values of Gly, Tyr, Asn, Ala, Cit, and Leu are substituted are included.
- the formula to calculate the value of the formula the status of fatty liver is evaluated, so the effect of further improving the reliability of information that can be helpful in knowing the status of fatty liver can be realized. Play.
- the concentration values of the amino acid values of Gly, Tyr, Asn, Ala, Val, and Trp and the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp are substituted.
- the state of insulin and visceral fat is evaluated, so that further improvement in the reliability of information that can be used as a reference for knowing the two states of insulin and visceral fat is realized. There is an effect that can be.
- the state of insulin and visceral fat may be evaluated using the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp.
- Insulin status is evaluated by calculating the value of the equation using an equation including variables, and (ii) “Gly, Tyr, Asn, Ala, Val, and Trp amino acid concentration values, and Gly, “Expression including variables to which the amino acid concentration values of Tyr, Asn, Ala, Val, and Trp are substituted” or “Gly, Tyr, Asn, Ala, Val, and Trp amino acid concentration values,
- the BMI value, the amino acid concentration value of Gly, Tyr, Asn, Ala, Val, and Trp and the BMI value to be evaluated are substituted.
- the value of the formula is calculated to evaluate the state of fatty liver.
- the concentration of amino acids Gly, Tyr, Asn, Ala, Val, and Trp is used to evaluate the state of insulin
- Gly, Tyr, Asn, Ala, Val and Trp amino acid concentration values, or Gly, Tyr, Asn, Ala, Val, and Trp amino acid concentration values and BMI values of evaluation targets obtained in advance were used to evaluate visceral fat status
- the status of fatty liver may be evaluated using the amino acid concentration values of Gly, Tyr, Asn, Ala, Cit, and Leu.
- evaluating the state of the index of lifestyle-related disease for the evaluation target may be qualitatively or quantitatively evaluating the degree of the state of the index of lifestyle-related disease in the evaluation target. This makes it possible to provide highly reliable information that can be used as a reference when knowing the state of the index of lifestyle-related diseases.
- qualitative evaluation of the state of the index of lifestyle-related diseases in the evaluation target means that “amino acid concentration value and one or more preset threshold values” or “amino acid concentration Value, an expression including a variable to which the amino acid concentration value is substituted, and one or more preset threshold values ”to define an evaluation target in consideration of at least the state of the index of lifestyle-related diseases It may be classified into any one of a plurality of divided sections. This makes it possible to provide highly reliable information that can be used as a reference for knowing the state of the index of lifestyle-related diseases in an easily understandable form.
- quantitatively evaluating the state of the index of lifestyle-related disease in the evaluation target means that when the index of lifestyle-related disease is measurable with a continuous numerical value, It may be possible to estimate the value of an index of lifestyle-related diseases in the evaluation target using an expression including a variable into which the concentration value and the amino acid concentration value are substituted. Thereby, it is possible to provide highly reliable numerical information that can be used as a reference in knowing the value of an index of lifestyle-related diseases.
- the value of the expression is converted by a predetermined method, and the evaluation object is classified into one of a plurality of categories using the converted value, or the lifestyle-related disease in the evaluation object Or the value of the index may be estimated. This makes it possible to provide highly reliable information that can be used as a reference in order to know the level of the index of lifestyle-related diseases, and to know the values of indicators of lifestyle-related diseases. The reliability of numerical information that can be used as a reference can be further improved.
- evaluating the state of insulin for an evaluation object means that the level of insulin in the evaluation object (for example, the amount of insulin present in the blood of the evaluation object) is qualitatively or quantitatively. It may be evaluated. Thereby, it is possible to provide highly reliable information that can be used as a reference in knowing the degree of the amount of insulin.
- qualitatively evaluating the degree of insulin amount in the evaluation target is “the amino acid concentration value and one or more preset threshold values” or “the amino acid concentration value, Using an expression including a variable to which a concentration value is substituted and one or more preset threshold values, the evaluation target is defined as any of a plurality of categories defined with at least the degree of insulin taken into account.
- a plurality of categories include a category for assigning subjects having a large amount of insulin (for example, an insulin value at 120 minutes of OGTT (oral glucose tolerance test) (insulin level after OGTT), etc.)
- OGTT oral glucose tolerance test
- insulin level after OGTT insulin level after OGTT
- a category to belong to subjects whose amount (eg, insulin value at 120 minutes of OGTT) is small, and a subject to which a subject whose amount of insulin (eg, insulin value at 120 minutes of OGTT) is medium belongs May be included.
- the plurality of categories include a category for assigning a subject whose amount of insulin (for example, insulin value at 120 minutes of OGTT) is equal to or higher than a reference value (for example, 40 ⁇ U / ml) and insulin amount (for example, OGTT) (For example, an insulin value at 120 minutes) may include a category for belonging to a subject having a reference value (for example, 40 ⁇ U / ml) or less.
- the plurality of sections include a section for belonging to a subject whose insulin value at 120 minutes of OGTT is likely to be 40 ⁇ U / ml or more, a section for belonging to a subject with a low possibility, and the above A division may be included for belonging to a subject with moderate likelihood.
- the plurality of categories include a category for belonging to a subject whose insulin value at 120 minutes of OGTT is likely to be 40 ⁇ U / ml or more, and a category for belonging to a subject with the low possibility It may be included.
- quantitatively evaluating the degree of the amount of insulin in the evaluation object means that the amino acid concentration value and an expression including a variable into which the amino acid concentration value is substituted are used in the evaluation object. It may be to estimate the amount of insulin. Thereby, it is possible to provide highly reliable numerical information that can serve as a reference in knowing the amount of insulin.
- the value of the expression is converted by a predetermined method, and using the converted value, the evaluation object is classified into one of a plurality of categories, or the insulin of the evaluation object
- the amount may be estimated.
- evaluating the status of visceral fat with respect to the evaluation target means qualitatively or quantitatively determining the degree of the amount of visceral fat in the evaluation target (for example, the area value of fat in the abdominal body axis section). It may be evaluated manually. As a result, it is possible to provide highly reliable information that can be used as a reference in knowing the level of visceral fat.
- the qualitative evaluation of the degree of visceral fat in the evaluation target means that “amino acid concentration value and one or more preset threshold values” or “amino acid concentration value, amino acid Using a formula including a variable to which the concentration value of the value is substituted and one or more preset threshold values ”, the evaluation target is selected from among a plurality of categories defined in consideration of at least the degree of visceral fat. It may be classified into one of these. This makes it possible to provide highly reliable information that can be used as a reference for knowing the degree of visceral fat in an easily understandable form.
- the plurality of categories include a category for assigning a subject having a large amount of visceral fat (eg, visceral fat area value) and a subject having a small amount of visceral fat (eg, visceral fat area value).
- a section for belonging and a section for belonging a subject having a medium amount of visceral fat (for example, visceral fat area value) may be included.
- the plurality of categories include a category for assigning a subject whose visceral fat amount (eg, visceral fat area value) is equal to or greater than a reference value (eg, 100 cm 2 ) and visceral fat amount (eg, visceral fat area value).
- Etc. may be included in order to belong to an object whose reference value (for example, 100 cm 2 ) or less.
- the plurality of categories include a category for belonging to a subject whose visceral fat area value is likely to be 100 cm 2 or more, a category for belonging to a subject with a low possibility, and a moderate possibility A section for belonging to a subject may be included.
- the plurality of categories may include a category for belonging to a subject whose visceral fat area value is likely to be 100 cm 2 or more, and a category for belonging to a subject with a low possibility Good.
- quantitative evaluation of the degree of visceral fat in the evaluation target means that the evaluation target is calculated using an expression including an amino acid concentration value and a variable into which the amino acid concentration value is substituted. It is also possible to estimate the amount of visceral fat. Thereby, it is possible to provide highly reliable numerical information that can serve as a reference in knowing the amount of visceral fat. Further, according to the present invention, the value of the expression is converted by a predetermined method, and using the converted value, the evaluation object is classified into one of a plurality of categories, or the visceral fat in the evaluation object May be estimated.
- evaluating the state of fatty liver with respect to the evaluation target means the degree of possibility of being a fatty liver, that is, the evaluation target liver has a certain amount or more of fat (for example, 5% of the weight of the liver).
- the amount of fat exceeding 30%, the amount of fat corresponding to 30% or more of the hepatocytes, or the amount of fat determined to be a fatty liver by the doctor) It may be to evaluate the degree of sex.
- the evaluation of the degree of possibility that the liver to be evaluated has a certain amount or more of fat means “the amino acid concentration value and one or more preset threshold values” ”Or“ Amino acid concentration value, an expression including a variable to which the amino acid concentration value is substituted, and one or more preset threshold values ”, and the possibility that the liver is in the state described above It may be classified into any one of a plurality of categories defined in consideration of at least the degree of. This makes it possible to provide highly reliable information that can be used as a reference for knowing the degree of possibility that the liver has a certain amount or more of fat.
- the plurality of categories include a category for belonging to a subject whose liver is likely to be in the state, a category for belonging to a subject whose liver is unlikely to be in the state, and a liver May include a category for assigning a target that is likely to be in the above state. Further, the plurality of categories include a category for belonging to a subject whose liver is likely to be in the state, and a category for belonging to a subject whose liver is unlikely to be in the state. It may be included. Further, according to the present invention, the value of the expression may be converted by a predetermined method, and the evaluation target may be classified into any one of a plurality of categories using the converted value. This makes it possible to provide highly reliable information that can be used as a reference for knowing the degree of possibility that the liver has a certain amount or more of fat.
- the formula is created by logistic regression, fractional formula, linear discriminant, multiple regression, formula created by support vector machine, formula created by Mahalanobis distance method, canonical discriminant analysis Any one of the created formula and the formula created by the decision tree may be used. As a result, it is possible to realize further improvement in the reliability of information that can be used as a reference in knowing the state of the index of lifestyle-related diseases.
- the formula used when evaluating the state of insulin may be Formula 1
- the formula used when evaluating the status of visceral fat may be Formula 2, when evaluating the status of fatty liver.
- Formula 3 may be used.
- Equation 2 a 2 , b 2 , c 2 , d 2 , e 2 , f 2 , and g 2 are arbitrary non-zero real numbers, and h 2 is an arbitrary real number.
- a 3 , b 3 , c 3 , d 3 , e 3 , and f 3 are arbitrary non-zero real numbers, and g 3 is an arbitrary real number.
- the present invention among the plurality of items defined as diagnostic criteria items for metabolic syndrome, using the amino acid concentration value and any one of Formula 1, Formula 2, and Formula 3.
- the number of items corresponding to the evaluation target may be evaluated. Thereby, it is possible to provide highly reliable information that can be used as a reference in knowing the number of hits in the diagnostic criteria items of metabolic syndrome.
- the number of lifestyle-related diseases possessed by the evaluation object is evaluated using the amino acid concentration value and any one of Formulas 1, 2, and 3. May be. Thereby, it is possible to provide highly reliable information that can be used as a reference in knowing the number of lifestyle-related diseases possessed.
- the degree of possibility that the evaluation target suffers from lifestyle-related diseases May be evaluated. This makes it possible to provide highly reliable information that can be used as a reference when knowing the degree of the possibility of suffering from lifestyle-related diseases.
- the value of the expression may be converted by a predetermined method, and the converted value may be determined to reflect the state of the lifestyle-related disease index for the evaluation target.
- a predetermined rule for evaluating the state of an indicator of lifestyle-related diseases which is visibly displayed on a display device such as a monitor or a physical medium such as paper (for example, a ruler with a scale shown).
- the position information related to the position of a predetermined mark corresponding to the value (for example, a circle mark or a star mark) is generated using the value of the formula or the value after conversion, and the generated position information is a lifestyle about the evaluation target. You may determine that it reflects the state of the disease index. As a result, it is possible to provide highly reliable information that can be used as a reference in knowing the state of an indicator of lifestyle-related diseases.
- the storage unit stores the amino acid concentration data and the index state information stored in advance in the storage unit including the lifestyle-related disease index data regarding the state of the lifestyle-related disease index (risk factor).
- An evaluation formula may be created. Specifically, (i) a candidate formula that is a candidate for an evaluation formula is created from index state information based on a predetermined formula creation method, and (ii) the created candidate formula is verified based on a predetermined verification method.
- amino acid concentration data relating to the concentration value of amino acids in blood collected from an evaluation object to which a desired substance group consisting of one or a plurality of substances is administered is obtained, and the acquired evaluation object amino acid
- the state of the index of lifestyle-related diseases is evaluated for the evaluation target, and the desired substance group is determined to be a lifestyle-related disease using the obtained evaluation results. It may be determined whether or not the condition of the index is improved.
- This improves the status of lifestyle-related disease indicators by applying a method for evaluating lifestyle-related disease indicators that can provide highly reliable information that can be helpful in knowing the status of lifestyle-related disease indicators. It can provide highly reliable information about substances.
- the concentration values of amino acids other than the 19 amino acids may be further used.
- other values related to biological information for example, the values listed in 1. to 4. below. You may use.
- the formula may further include one or a plurality of variables into which concentration values of amino acids other than the 19 kinds of amino acids are substituted.
- other biological information values for example, the values listed in 1. to 4. below
- One or more variables may be further included.
- Concentration values of blood metabolites other than amino acids (amino acid metabolites, sugars, lipids, etc.), proteins, peptides, minerals, hormones, etc. 2.
- Value obtained from image information such as ultrasonic echo, X-ray, CT, MRI, etc.
- the lifestyle-related disease is a disease group in which lifestyle habits such as eating habits, exercise habits, rest, smoking, alcohol drinking, etc. are involved in the onset and progression thereof, such as metabolic syndrome, sugar metabolism, etc.
- lifestyle habits such as eating habits, exercise habits, rest, smoking, alcohol drinking, etc.
- Abnormalities diabetes, borderline diabetes, impaired glucose tolerance, etc.), cerebrovascular disorders (stroke, microarteriosclerosis, etc.), heart diseases (myocardial infarction, etc.), dyslipidemia, hypertension, obesity, nephropathy (chronic) Nephropathy), liver disease, hyperuricemia and the like.
- the present invention evaluates the risk of developing a lifestyle-related disease (the degree of possibility of developing a lifestyle-related disease) or the risk that the lifestyle-related disease will progress in the future (the degree of possibility of the progression of lifestyle-related diseases). Can lead to the prevention of lifestyle-related diseases.
- the values of Formulas 1 to 3 can be used to evaluate lifestyle-related diseases. Can be evaluated (the degree of progression of lifestyle-related diseases (the degree of possibility that lifestyle-related diseases are progressing)).
- FIG. 1 is a principle configuration diagram showing the basic principle of the first embodiment.
- FIG. 2 is a flowchart illustrating an example of a lifestyle-related disease index evaluation method according to the first embodiment.
- FIG. 3 is a principle configuration diagram showing the basic principle of the second embodiment.
- FIG. 4 is a diagram illustrating an example of the overall configuration of the present system.
- FIG. 5 is a diagram showing another example of the overall configuration of the present system.
- FIG. 6 is a block diagram illustrating an example of the configuration of the lifestyle-related disease index evaluation apparatus 100 of the present system.
- FIG. 7 is a diagram illustrating an example of information stored in the user information file 106a.
- FIG. 8 is a diagram showing an example of information stored in the amino acid concentration data file 106b.
- FIG. 9 is a diagram illustrating an example of information stored in the index state information file 106c.
- FIG. 10 is a diagram illustrating an example of information stored in the designated index state information file 106d.
- FIG. 11 is a diagram illustrating an example of information stored in the candidate formula file 106e1.
- FIG. 12 is a diagram illustrating an example of information stored in the verification result file 106e2.
- FIG. 13 is a diagram illustrating an example of information stored in the selection index state information file 106e3.
- FIG. 14 is a diagram illustrating an example of information stored in the evaluation formula file 106e4.
- FIG. 15 is a diagram illustrating an example of information stored in the evaluation result file 106f.
- FIG. 16 is a block diagram illustrating a configuration of the evaluation formula creation unit 102h.
- FIG. 17 is a block diagram illustrating a configuration of the evaluation unit 102i.
- FIG. 18 is a block diagram illustrating an example of the configuration of the client device 200 of the present system.
- FIG. 19 is a block diagram showing an example of the configuration of the database apparatus 400 of this system.
- FIG. 20 is a flowchart illustrating an example of a lifestyle-related disease index evaluation service process performed in the present system.
- FIG. 21 is a flowchart illustrating an example of an evaluation formula creation process performed by the lifestyle-related disease index evaluation apparatus 100 of the present system.
- FIG. 22 is a diagram showing the correlation coefficient and ROC_AUC of each amino acid.
- FIG. 23 is a diagram showing the correlation coefficient of each amino acid with respect to the insulin resistance index, the blood glucose level at 120 minutes of OGTT, and the insulin value at 120 minutes of OGTT.
- FIG. 24 is a diagram showing ROC_AUC of each amino acid.
- FIG. 25 is a diagram showing the number of appearances of the 19 amino acids in the formula.
- FIG. 26 is a diagram illustrating the range of the correlation coefficient of the equation.
- FIG. 27 is a diagram illustrating the range of the correlation coefficient of the equation.
- FIG. 28 is a diagram illustrating the range of the correlation coefficient of the equation.
- FIG. 29 is a diagram showing the range of the correlation coefficient of the equation.
- FIG. 30 is a diagram illustrating the range of the correlation coefficient of the equation.
- FIG. 31 is a diagram showing the range of the correlation coefficient of the equation.
- FIG. 32 is a diagram showing the range of the correlation coefficient of the equation.
- FIG. 33 is a diagram showing the range of the correlation coefficient of the equation.
- FIG. 34 is a diagram illustrating the range of the correlation coefficient of the equation.
- FIG. 35 is a diagram illustrating the range of the correlation coefficient of the equation.
- FIG. 36 is a diagram showing the range of the correlation coefficient of the equation.
- FIG. 37 is a diagram showing the range of the correlation coefficient of the equation.
- FIG. 38 is a diagram illustrating the range of the correlation coefficient of the equation.
- FIG. 39 is a diagram showing the range of the correlation coefficient of the equation.
- FIG. 40 is a diagram illustrating the range of the correlation coefficient of the equation.
- FIG. 40 is a diagram illustrating the range of the correlation coefficient of the equation.
- FIG. 41 is a diagram showing the range of the correlation coefficient of the equation.
- FIG. 42 is a diagram illustrating the range of the correlation coefficient of the equation.
- FIG. 43 is a diagram showing the range of the correlation coefficient of the equation.
- FIG. 44 is a diagram illustrating a range of ROC_AUC in the equation.
- FIG. 45 is a diagram showing the range of ROC_AUC in the equation.
- FIG. 46 is a diagram showing the range of ROC_AUC in the equation.
- FIG. 47 is a diagram showing the range of ROC_AUC in the equation.
- FIG. 48 is a diagram showing the range of ROC_AUC in the equation.
- FIG. 49 is a diagram showing the range of ROC_AUC in the equation.
- FIG. 41 is a diagram showing the range of the correlation coefficient of the equation.
- FIG. 42 is a diagram illustrating the range of the correlation coefficient of the equation.
- FIG. 43 is a diagram showing the range of the correlation coefficient of the equation.
- FIG. 50 is a diagram showing correlation coefficients of index formulas 1, 2, and 3 with respect to the visceral fat area value, the insulin resistance index, the blood glucose level at 120 minutes of OGTT, and the insulin value at 120 minutes of OGTT.
- FIG. 51 is a diagram showing a visceral fat area value, an insulin value at 120 minutes of OGTT, and ROC_AUC of index formulas 1, 2, and 3 for fatty liver.
- FIG. 52 is a diagram illustrating correlation coefficients of index formulas 1, 2, and 3 with respect to the number of corresponding metabolic criteria diagnosis criteria items.
- FIG. 53 is a box-and-whisker diagram showing the relationship between the number of hits in the diagnostic criteria items of metabolic syndrome and the value of index formula 1.
- FIG. 51 is a diagram showing correlation coefficients of index formulas 1, 2, and 3 with respect to the visceral fat area value, the insulin resistance index, the blood glucose level at 120 minutes of OGTT, and the insulin value at 120 minutes of OGTT.
- FIG. 51 is a diagram showing
- FIG. 54 is a box-and-whisker diagram showing the relationship between the number of hits in the diagnostic criteria items of the metabolic syndrome and the value of the index formula 2.
- FIG. 55 is a box-and-whisker diagram showing the relationship between the number of hits in the diagnostic criteria items of the metabolic syndrome and the value of the index formula 3.
- FIG. 56 is a box-and-whisker diagram showing the relationship between the number of lifestyle-related diseases and the value of index formula 1.
- FIG. 57 is a box-and-whisker diagram showing the relationship between the number of lifestyle-related diseases and the value of index formula 2.
- FIG. 58 is a box-and-whisker diagram showing the relationship between the number of lifestyle-related diseases and the value of index formula 3.
- FIG. 60 shows the number of persons, person year, number of events, relative risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk when the disease event is “insulin resistant”. It is a figure shown for every index type
- FIG. 61 shows an index formula of the number of persons, person year, number of events, relative risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk when the disease event is “hypertension”. It is a figure shown for every and quantile.
- FIG. 62 shows the number of persons, person year, number of events, relative risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk when the disease event is “hypertension” as an index. It is a figure shown for every formula and every quantile.
- FIG. 63 shows the number of persons, person year, number of events, relative risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk when the disease event is “fatty liver” as an index. It is a figure shown for every formula and every quantile.
- FIG. 64 shows the number of persons, person year, number of events, relative risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk when the disease event is “high risk fatty liver”.
- FIG. 65 is an index formula showing the number of persons, person year, number of events, relative risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk when the disease event is “diabetes”. It is a figure shown for every and quantile.
- FIG. 66 shows the number of people, person year, number of events, relative risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk when the disease event is “abnormal glucose tolerance”. It is a figure shown for every index formula and every quantile.
- FIG. 67 is an index formula showing the number of persons, person year, number of events, relative risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk when the disease event is “obesity”. It is a figure shown for every and quantile.
- FIG. 68 shows the number of persons, person year, number of events, relative risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk when the disease event is “high obesity” as an index. It is a figure shown for every formula and every quantile.
- FIG. 69 shows the number of persons, person year, number of events, relative risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk when the disease event is “dyslipidemia”.
- FIG. 70 shows the number of persons, person years, number of events, relative risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk when the disease event is “chronic nephropathy”. It is a figure shown for every index formula and every quantile.
- FIG. 71 shows the number of people, person year, number of events, relative risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk when the disease event is “arteriosclerosis”. It is a figure shown for every index formula and every quantile.
- FIG. 72 shows the number of persons, person year, number of events, relative risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk when the disease event is “cerebral infarction” as an index. It is a figure shown for every formula and every quantile.
- FIG. 73 shows the number of persons, person year, number of events, relative risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk when the disease event is “with heart disease risk”. It is a figure shown for every index type
- 74 shows the number of persons, person year, number of events, relative risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk when the disease event is “metabolic syndrome” as an index. It is a figure shown for every formula and every quantile.
- a lifestyle-related disease index evaluation method according to the present invention (first embodiment), a lifestyle-related disease index evaluation device, a lifestyle-related disease index evaluation method, and a lifestyle-related disease index evaluation program according to the present invention
- Embodiment (2nd Embodiment) of a recording medium, a lifestyle-related disease index evaluation system, and an information communication terminal device is described in detail based on drawing. Note that the present invention is not limited to these embodiments.
- FIG. 1 is a principle configuration diagram showing the basic principle of the first embodiment.
- amino acid concentration data relating to the concentration value of amino acids in blood eg, including plasma, serum, etc.
- an evaluation target eg, an individual such as an animal or a human
- amino acid concentration data measured by a company or the like that measures amino acid concentration values may be acquired, and from blood collected from an evaluation target, for example, the following (A) or (B)
- the amino acid concentration data may be obtained by measuring the concentration value of the amino acid by the measurement method.
- the unit of the concentration value of the amino acid may be obtained, for example, by adding / subtracting / subtracting an arbitrary constant to / from these concentrations.
- Plasma was separated from blood by centrifuging the collected blood sample. All plasma samples were stored frozen at ⁇ 80 ° C. until measurement of amino acid concentration values.
- acetonitrile was added to remove protein, followed by precolumn derivatization using a labeling reagent (3-aminopyridyl-N-hydroxysuccinimidyl carbamate), and liquid chromatography mass
- the amino acid concentration value was analyzed by an analyzer (LC / MS) (see International Publication No. 2003/069328, International Publication No. 2005/116629).
- Plasma was separated from blood by centrifuging the collected blood sample. All plasma samples were stored frozen at ⁇ 80 ° C. until measurement of amino acid concentration values.
- amino acid concentration value sulfosalicylic acid was added to remove protein, and then the amino acid concentration value was analyzed by an amino acid analyzer based on the post-column derivatization method using a ninhydrin reagent.
- step S12 using the amino acid concentration values of Gly and Tyr included in the amino acid concentration data acquired in step S11 as an evaluation value for evaluating the state of an indicator of lifestyle-related diseases, lifestyle-related diseases are evaluated for the evaluation target.
- the state of the index is evaluated (step S12).
- data such as missing values and outliers may be removed from the amino acid concentration data acquired in step S11.
- the amino acid concentration data to be evaluated is acquired in step S11, and the amino acid concentrations of Gly and Tyr contained in the amino acid concentration data to be evaluated acquired in step S11 are obtained in step S12.
- the value as an evaluation value the state of the index of lifestyle-related diseases is evaluated for the evaluation target.
- step S12 “the amino acid concentration value of Gly, Tyr, and Asn”, “the amino acid concentration value of Gly, Tyr, and Ala”, “the amino acid concentration value of Gly, Tyr, and Val”, or By using “the amino acid concentration values of Gly, Tyr, and Trp”, the state of the index of lifestyle-related diseases may be evaluated for the evaluation target.
- step S12 the state of the index of lifestyle-related diseases may be evaluated for the evaluation target using the amino acid concentration values of Gly, Tyr, Asn, and Ala.
- step S12 at least one state of fatty liver, visceral fat, and insulin may be evaluated.
- the state of insulin may be evaluated using the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp.
- the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp, or the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp, and the BMI value of the evaluation target obtained in advance are used.
- the state of visceral fat may be evaluated.
- the state of fatty liver may be evaluated using the amino acid concentration values of Gly, Tyr, Asn, Ala, Cit, and Leu.
- step S12 at least two states of fatty liver, visceral fat, and insulin may be evaluated.
- the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp may be used to assess insulin and visceral fat status.
- step S12 the status of fatty liver, visceral fat, and insulin may be evaluated.
- Gly, Tyr, Asn, Ala, Val, and Trp amino acid concentration values are used to assess insulin status
- (iii) Gly, Tyr using the concentration value of Gly, Tyr, Asn, Ala, Val, and Trp, and the BMI value of the evaluation target obtained in advance and
- Gly, Tyr , Asn, Ala, Cit, and Leu amino acid concentration values may be used to assess fatty liver status.
- step S12 it may be determined that the concentration values of at least Gly and Tyr amino acids reflect the state of the index of lifestyle-related diseases for the evaluation target, and the concentration values are listed below, for example: It is possible to determine that the converted value reflects the state of the lifestyle-related disease index for the evaluation target by converting the value using a technique or the like. In other words, in step S12, the concentration value or the converted value itself may be treated as an evaluation result regarding the state of the lifestyle-related disease index for the evaluation target.
- the range of possible density values is a predetermined range (for example, a range from 0.0 to 1.0, a range from 0.0 to 10.0, a range from 0.0 to 100.0, or -10.0 to
- a predetermined range for example, a range from 0.0 to 1.0, a range from 0.0 to 10.0, a range from 0.0 to 100.0, or -10.0 to
- an arbitrary value is added / subtracted / divided / divided from / to the density value so that it falls within the range up to 10.0, etc.
- the density value is converted into a predetermined conversion method (for example, exponential conversion, logarithmic conversion, angular conversion). , Square root conversion, probit conversion, reciprocal conversion, etc.), or the density value may be converted by combining these calculations with respect to the density value.
- the value of an exponential function with the concentration value as the index and the Napier number as the base (specifically, the probability p that the lifestyle disease index is in a predetermined state (for example, a state exceeding the reference value, etc.) is defined.
- the natural logarithm ln (p / (1-p)) when the natural logarithm is equal to the concentration value may be further calculated, and the calculated exponential function value You may further calculate the value (specifically, the value of the probability p) obtained by dividing 1 by the sum of 1 and the value.
- the density value may be converted so that the value after conversion under a specific condition becomes a specific value. For example, the density value may be converted so that the converted value when the sensitivity is 80% is 4.0 and the converted value when the sensitivity is 60% is 8.0.
- a display device such as a monitor or a physical medium such as paper (for example, a ruler with a scale).
- a scale corresponding to the upper limit value and the lower limit value in a part of the range.
- Position information on the position of a predetermined landmark is generated using at least the amino acid concentration values of Gly and Tyr or the converted values when the concentration values are converted, You may determine that the produced
- step S12 the value of the expression is calculated using an expression including a variable into which the concentration value of the amino acid of Gly and Tyr and the concentration value of the amino acid of Gly and Tyr are substituted. You may evaluate the state of the parameter
- step S12 “the expression containing the variables in which the concentration values of the amino acids Gly, Tyr, and Asn and the amino acid concentrations of Gly, Tyr, and Asn are substituted”, “Gly, Tyr, and Ala” Expressions including amino acid concentration values and variables to which the amino acid concentration values of Gly, Tyr, and Ala are substituted ”,“ Gly, Tyr, and Val amino acid concentration values, and Gly, Tyr, and Val An expression including a variable to which the amino acid concentration value is substituted "or” an expression including a variable to which the amino acid concentration values of Gly, Tyr, and Trp and amino acid concentrations of Gly, Tyr, and Trp are substituted " May be used to evaluate the state of the index of lifestyle-related diseases for the evaluation target.
- step S12 the concentration value of the amino acid of Gly, Tyr, Asn, and Ala, and the value of the equation using an expression that includes a variable into which the concentration value of the amino acid value of Gly, Tyr, Asn, and Ala is substituted.
- the state of the index of lifestyle-related diseases may be evaluated for the evaluation target.
- step S12 at least one state of fatty liver, visceral fat, and insulin may be evaluated. For example, using an expression that includes a variable in which the concentration values of amino acids Gly, Tyr, Asn, Ala, Val, and Trp and the amino acid concentrations of Gly, Tyr, Asn, Ala, Val, and Trp are substituted.
- the insulin state may be evaluated by calculating the value of the equation.
- an expression including a variable into which the concentration values of amino acids Gly, Tyr, Asn, Ala, Val, and Trp and the amino acid concentrations of Gly, Tyr, Asn, Ala, Val, and Trp are substituted or “Gly, Tyr, Asn, Ala, Val, and Trp amino acid concentration values, BMI values of evaluation targets acquired in advance, and Gly, Tyr, Asn, Ala, Val, and Trp amino acid concentration values and evaluation targets
- the state of visceral fat may be evaluated by calculating the value of the expression using an expression including a variable to which the BMI value of is substituted.
- step S12 at least two states of fatty liver, visceral fat, and insulin may be evaluated. For example, using an expression that includes a variable in which the concentration values of amino acids Gly, Tyr, Asn, Ala, Val, and Trp and the amino acid concentrations of Gly, Tyr, Asn, Ala, Val, and Trp are substituted.
- the state of insulin and visceral fat may be evaluated by calculating the value of the equation.
- step S12 the status of fatty liver, visceral fat, and insulin may be evaluated.
- Gly, Tyr, Asn, Ala, Cit, and Leu amino acid concentration values may be used to evaluate the fatty liver condition by calculating the value of the expression using an expression including variables to which the amino acid concentration values are substituted.
- step S12 it may be determined that the calculated value of the expression reflects the state of the index of the lifestyle-related disease for the evaluation target, and further, the value of the expression is determined by, for example, the method described below. Conversion may be performed and the value after conversion may be determined to reflect the state of the index of lifestyle-related diseases for the evaluation target. In other words, in step S12, the value of the formula or the converted value itself may be treated as an evaluation result regarding the state of the index of lifestyle-related diseases for the evaluation target.
- a possible range of the value of the evaluation formula is a predetermined range (for example, a range from 0.0 to 1.0, a range from 0.0 to 10.0, a range from 0.0 to 100.0, or ⁇ 10.
- an arbitrary value is added / subtracted / divided / divided from / to the value of the evaluation expression so that it falls within the range from 0 to 10.0, etc. , Logarithmic conversion, angular conversion, square root conversion, probit conversion, or reciprocal conversion), or by combining these calculations with the evaluation expression value to convert the value of the evaluation expression May be.
- the value of an exponential function with the value of the evaluation formula as the index and the Napier number as the base (specifically, the probability p that the lifestyle-related disease index is in a predetermined state (for example, a state exceeding the reference value, etc.) And the natural logarithm ln (p / (1-p)) when defining is equal to the value of the evaluation formula) may be further calculated.
- a value obtained by dividing the value of the exponential function by the sum of 1 and the value (specifically, the value of probability p) may be further calculated.
- the value of the evaluation expression may be converted so that the value after conversion under a specific condition becomes a specific value.
- the value of the evaluation formula may be converted so that the value after conversion when the sensitivity is 80% is 4.0 and the value after conversion when the sensitivity is 60% is 8.0.
- the evaluation value in this specification may be the value of the evaluation formula itself, or may be a value after converting the value of the evaluation formula.
- Position information related to the position of the corresponding predetermined mark is generated using the value of the expression or the converted value when the value of the expression is converted, and the generated position You may determine that information reflects the state of the index of the lifestyle related disease about evaluation object.
- step S12 you may evaluate qualitatively or quantitatively the degree of the state of the parameter
- the evaluation target may be classified into any one of a plurality of categories defined in consideration of at least the degree of the lifestyle-related disease state using “a plurality of threshold values”.
- the evaluation is performed using an amino acid concentration value and an expression including a variable into which the amino acid concentration value is substituted.
- step S12 the density value or the value of the expression is converted by a predetermined method, and the evaluation object is classified into one of a plurality of categories using the converted value, or the lifestyle in the evaluation object The value of a disease index may be estimated.
- the degree of insulin in the evaluation target may be evaluated qualitatively or quantitatively.
- the evaluation target may be classified into any one of a plurality of categories defined in consideration of at least the degree of the amount of insulin using “a plurality of threshold values”.
- a plurality of categories include a category for assigning a subject having a large amount of insulin (for example, insulin value at 120 minutes of OGTT), and an amount of insulin (for example, insulin value at 120 minutes of OGTT).
- a section for belonging to a subject with a small and a section for belonging to a subject with a moderate amount of insulin may be included.
- the plurality of categories include a category for assigning a subject whose amount of insulin (for example, insulin value at 120 minutes of OGTT) is equal to or higher than a reference value (for example, 40 ⁇ U / ml) and insulin amount (for example, OGTT) (For example, an insulin value at 120 minutes) may include a category for belonging to a subject having a reference value (for example, 40 ⁇ U / ml) or less.
- the plurality of sections include a section for belonging to a subject whose insulin value at 120 minutes of OGTT is likely to be 40 ⁇ U / ml or more, a section for belonging to a subject with a low possibility, and the above A division may be included for belonging to a subject with moderate likelihood.
- the plurality of categories include a category for belonging to a subject whose insulin value at 120 minutes of OGTT is likely to be 40 ⁇ U / ml or more, and a category for belonging to a subject with the low possibility It may be included.
- the amount of insulin in the evaluation target may be estimated using an amino acid concentration value and an equation including a variable into which the amino acid concentration value is substituted.
- the concentration value or the expression value is converted by a predetermined method, and the evaluation object is classified into one of a plurality of categories using the converted value, or the insulin in the evaluation object is classified. May be estimated.
- step S12 the amount of visceral fat in the evaluation target (for example, the area value of fat in the abdominal body axis section) may be evaluated.
- the evaluation target may be classified into any one of a plurality of categories defined in consideration of at least the degree of the amount of visceral fat.
- the plurality of categories include a category for assigning a subject having a large amount of visceral fat (eg, visceral fat area value) and a subject having a small amount of visceral fat (eg, visceral fat area value).
- a section for belonging and a section for belonging a subject having a medium amount of visceral fat (for example, visceral fat area value) may be included.
- the plurality of categories include a category for assigning a subject whose visceral fat amount (eg, visceral fat area value) is equal to or greater than a reference value (eg, 100 cm 2 ) and visceral fat amount (eg, visceral fat area value).
- Etc. may be included in order to belong to an object whose reference value (for example, 100 cm 2 ) or less.
- the plurality of categories include a category for belonging to a subject whose visceral fat area value is likely to be 100 cm 2 or more, a category for belonging to a subject with a low possibility, and a moderate possibility A section for belonging to a subject may be included.
- the plurality of categories may include a category for belonging to a subject whose visceral fat area value is likely to be 100 cm 2 or more, and a category for belonging to a subject with a low possibility Good.
- the amount of visceral fat in the evaluation target may be estimated using an expression including an amino acid concentration value and a variable into which the amino acid concentration value is substituted.
- the density value or the value of the expression is converted by a predetermined method, and the evaluation target is classified into one of a plurality of categories using the converted value, or the internal organs in the evaluation target are included.
- the amount of fat may be estimated.
- an expression further including a BMI value to be evaluated or a variable into which the BMI value is substituted may be used.
- the degree of possibility of fatty liver is a certain amount or more of fat (for example, an amount of fat exceeding 5% of the weight of the liver, 30% or more of hepatocytes. Or the like, or the amount of fat that is judged to be a fatty liver by a doctor, etc.).
- the evaluation target may be classified into any one of a plurality of categories defined in consideration of at least the degree of possibility that the liver is in the state.
- the plurality of categories include a category for belonging to a subject whose liver is likely to be in the state, a category for belonging to a subject whose liver is unlikely to be in the state, and a liver May include a category to which a subject having a moderate possibility of being in the state belongs. Further, the plurality of categories include a category for belonging to a subject whose liver is likely to be in the state, and a category for belonging to a subject whose liver is unlikely to be in the state. It may be included.
- the density value or the expression value may be converted by a predetermined method, and the evaluation target may be classified into one of a plurality of categories using the converted value.
- formulas are logistic regression formula, fractional formula, linear discriminant formula, multiple regression formula, formula created by support vector machine, formula created by Mahalanobis distance method, formula created by canonical discriminant analysis, and decision It may be any one of the expressions created with trees.
- the formula used when evaluating the state of insulin may be Formula 1
- the formula used when evaluating the visceral fat status may be Formula 2
- the formula used when evaluating the status of fatty liver is Formula 3.
- Equation 3 Equation 1
- Equation 2 a 2 , b 2 , c 2 , d 2 , e 2 , f 2 , and g 2 are arbitrary non-zero real numbers, and h 2 is an arbitrary real number.
- a 3 , b 3 , c 3 , d 3 , e 3 , and f 3 are arbitrary non-zero real numbers, and g 3 is an arbitrary real number.
- step S12 evaluation is performed among a plurality of items defined as diagnostic criteria items for metabolic syndrome using the amino acid concentration value and any one of Equations 1, 2, and 3.
- the number of items to which the subject applies may be evaluated.
- step S12 the number of lifestyle-related diseases possessed by the evaluation object can be evaluated using the amino acid concentration value and any one of Equations 1, 2, and 3. Good.
- step S12 the degree of possibility that the evaluation target suffers from a lifestyle-related disease is evaluated using the amino acid concentration value and any one of Equations 1, 2, and 3. May be.
- the formula adopted as the evaluation formula is described in, for example, the method described in International Publication No. 2004/052191 that is an international application by the present applicant or International Publication No. 2006/098192 that is an international application by the present applicant. You may create by the method of.
- the formula is suitably used for evaluating the state of the index of lifestyle-related diseases regardless of the unit of the amino acid concentration value in the amino acid concentration data as input data. be able to.
- the formula adopted as the evaluation formula generally means the format of the formula used in multivariate analysis, and examples of formulas adopted as the evaluation formula include fractional expressions, multiple regression formulas, multiple logistic regression formulas, Examples include linear discriminants, Mahalanobis distances, canonical discriminant functions, support vector machines, decision trees, and formulas represented by the sum of different types of formulas.
- a coefficient and a constant term are added to each variable.
- the coefficient and the constant term are preferably real numbers, and more preferably May be any value belonging to the range of the 99% confidence interval of the coefficient and constant term obtained for performing the various classifications from the data, and more preferably, the value obtained for performing the various classifications from the data. Any value may be used as long as it falls within the 95% confidence interval of the obtained coefficient and constant term. Further, the value of each coefficient and its confidence interval may be obtained by multiplying it by a real number, and the value of the constant term and its confidence interval may be obtained by adding / subtracting / multiplying / dividing an arbitrary real constant thereto. When logistic regression, linear discriminant, multiple regression, etc.
- the fractional expression means that the numerator of the fractional expression is represented by the sum of amino acids A, B, C,... And / or the denominator of the fractional expression is the sum of amino acids a, b, c,. It is represented by
- the fractional expression includes a sum of fractional expressions ⁇ , ⁇ , ⁇ ,.
- the fractional expression also includes a divided fractional expression.
- An appropriate coefficient may be attached to each amino acid used in the numerator and denominator.
- amino acids used in the numerator and denominator may overlap.
- an appropriate coefficient may be attached to each fractional expression.
- the value of the coefficient of each variable and the value of the constant term may be real numbers.
- the fractional expression includes one in which the numerator variable and the denominator variable are interchanged.
- the concentration value of amino acids other than the said 19 types of amino acids when evaluating the state of an index of lifestyle-related diseases, in addition to the amino acid concentration value, values related to other biological information (for example, values listed in 1. to 4. below) May be further used.
- the formula employed as the evaluation formula may further include one or a plurality of variables into which the concentration values of amino acids other than the 19 kinds of amino acids are substituted.
- the expression employed as the evaluation expression is a value related to other biological information (for example, the values listed in 1. to 4.
- Concentration values of blood metabolites other than amino acids may be further included.
- Value obtained from image information such as ultrasonic echo, X-ray, CT, MRI, etc.
- step S11 a desired substance group consisting of one or more substances is administered to the evaluation object, blood is collected from the evaluation object, and in step S11, the amino acid concentration of the evaluation object
- step S12 the amino acid concentration of the evaluation object
- an appropriate combination of existing drugs, amino acids, foods, and supplements that can be administered to humans for example, it is known to be effective in improving indicators of lifestyle-related diseases
- Drugs for example, gemcitabine, erlotinib, TS-1 etc.
- a predetermined period for example, a range of 1 day to 12 months
- a predetermined frequency / timing for example, 3 times a day
- You may administer by a predetermined administration method (for example, oral administration) in a round and a meal.
- the administration method, dose, and dosage form may be appropriately combined depending on the disease state.
- the dosage form may be determined based on a known technique.
- the dose is not particularly defined, but may be given, for example, in a form containing 1 ug to 100 g as an active ingredient.
- the administered substance group is searched for as a substance that improves the state of the lifestyle-related disease index. May be.
- Examples of the substance group searched by this searching method include an amino acid group containing at least Gly and Tyr amino acids among the 19 kinds of amino acids.
- the substance that normalizes the concentration value and the value of the evaluation formula of the amino acid group including at least Gly and Tyr amino acids among the 19 kinds of amino acids is used as the lifestyle-related disease index evaluation method of the first embodiment and the second It can select using the lifestyle-related disease parameter
- Searching for a substance that improves the state of the index of lifestyle-related diseases not only finds new substances that are effective in improving the index of lifestyle-related diseases, but also new uses for improving the indicators of lifestyle-related diseases of known substances
- FIG. 2 is a flowchart for explaining a specific example of the first embodiment.
- amino acid concentration data relating to the concentration value of amino acids in blood collected from individuals such as animals and humans is acquired (step SA11).
- amino acid concentration data measured by a company or the like that measures amino acid concentration values may be acquired, and measurement such as (A) or (B) described above is performed from blood collected from an individual.
- the amino acid concentration data may be obtained by measuring the amino acid concentration value by a method.
- step SA12 data such as missing values and outliers are removed from the amino acid concentration data of the individual obtained in step SA11 (step SA12).
- step SA12 using the amino acid concentration data of the individual from which data such as missing values and outliers have been removed in step SA12, the insulin value, visceral fat area value, and liver at a fixed time of 120 minutes of OGTT are obtained for the individual.
- the degree of possibility of having the above fat is evaluated (step SA13).
- a 1 , b 1 , c 1 , d 1 , e 1 , and f 1 are arbitrary non-zero real numbers
- g 1 is an arbitrary real number.
- Gly, Tyr, Asn, Ala, Val, and Trp amino acid concentration values and BMI values of individuals obtained in advance or Gly, Tyr, Asn, Ala, Val, and Trp amino acid concentration values, obtained in advance.
- the visceral fat area value of the individual is estimated using the BMI value of the obtained individual and Equation 2.
- Equation 2 a 2 ⁇ Asn + b 2 ⁇ Gly + c 2 ⁇ Ala + d 2 ⁇ Val + e 2 ⁇ Tyr + f 2 ⁇ Trp + g 2 ⁇ BMI + h 2 (Formula 2)
- a 2 , b 2 , c 2 , d 2 , e 2 , f 2 , and g 2 are arbitrary non-zero real numbers
- h 2 is an arbitrary real number.
- the concentration value of amino acids Gly, Tyr, Asn, Ala, Cit, and Leu, or the amino acid concentration values of Gly, Tyr, Asn, Ala, Cit, and Leu and Equation 3 Is classified into any one of a plurality of categories defined in consideration of at least the degree of the possibility of having a certain amount or more of fat.
- the plurality of categories include a category for belonging to a subject whose liver is likely to be in the state, a category for belonging to a subject whose liver is unlikely to be in the state, and a liver May include a category to which a subject having a moderate possibility of being in the state belongs.
- the plurality of categories include a category for belonging to a subject whose liver is likely to be in the state, and a category for belonging to a subject whose liver is unlikely to be in the state. It may be included.
- a 3 , b 3 , c 3 , d 3 , e 3 , and f 3 are arbitrary non-zero real numbers
- g 3 is an arbitrary real number.
- FIG. 3 is a principle configuration diagram showing the basic principle of the second embodiment.
- the control unit includes Gly and Tyr amino acid concentration values, and Gly and Tyr amino acid concentrations, which are included in the amino acid concentration data of an evaluation object (for example, an individual such as an animal or a human) acquired in advance regarding the amino acid concentration value.
- an evaluation object for example, an individual such as an animal or a human
- the state of the lifestyle-related disease index is evaluated for the evaluation target (step S21).
- step S21 the concentration values of the amino acids Gly and Tyr included in the amino acid concentration data to be evaluated, and the values of Gly and Tyr stored in the storage unit as the evaluation formula
- the evaluation formula By calculating the value of the evaluation formula using an expression including a variable into which the amino acid concentration value is substituted, the state of the index of lifestyle-related diseases is evaluated for the evaluation target.
- step S21 “concentration values of amino acids Gly, Tyr, and Asn, and variables including variables to which the amino acid concentration values of Gly, Tyr, and Asn are substituted”, “Gly, Tyr, and Ala” Expressions including amino acid concentration values and variables to which the amino acid concentration values of Gly, Tyr, and Ala are substituted ”,“ Gly, Tyr, and Val amino acid concentration values, and Gly, Tyr, and Val An expression including a variable to which the amino acid concentration value is substituted "or” an expression including a variable to which the amino acid concentration values of Gly, Tyr, and Trp and amino acid concentrations of Gly, Tyr, and Trp are substituted " May be used to evaluate the state of the index of lifestyle-related diseases for the evaluation target.
- step S21 the concentration value of the amino acid of Gly, Tyr, Asn, and Ala, and the value of the equation using an expression including a variable into which the concentration value of the amino acid value of Gly, Tyr, Asn, and Ala is substituted.
- the state of the index of lifestyle-related diseases may be evaluated for the evaluation target.
- step S21 at least one state of fatty liver, visceral fat, and insulin may be evaluated. For example, using an expression that includes a variable in which the concentration values of amino acids Gly, Tyr, Asn, Ala, Val, and Trp and the amino acid concentrations of Gly, Tyr, Asn, Ala, Val, and Trp are substituted.
- the insulin state may be evaluated by calculating the value of the equation.
- an expression including a variable into which the concentration values of amino acids Gly, Tyr, Asn, Ala, Val, and Trp and the amino acid concentrations of Gly, Tyr, Asn, Ala, Val, and Trp are substituted or “Gly, Tyr, Asn, Ala, Val, and Trp amino acid concentration values, BMI values of evaluation targets acquired in advance, and Gly, Tyr, Asn, Ala, Val, and Trp amino acid concentration values and evaluation targets
- the state of visceral fat may be evaluated by calculating the value of the expression using an expression including a variable to which the BMI value of is substituted.
- step S21 at least two states of fatty liver, visceral fat, and insulin may be evaluated. For example, using an expression that includes a variable in which the concentration values of amino acids Gly, Tyr, Asn, Ala, Val, and Trp and the amino acid concentrations of Gly, Tyr, Asn, Ala, Val, and Trp are substituted.
- the state of insulin and visceral fat may be evaluated by calculating the value of the equation.
- step S21 the states of fatty liver, visceral fat, and insulin may be evaluated.
- Gly, Tyr, Asn, Ala, Cit, and Leu amino acid concentration values may be used to evaluate the fatty liver condition by calculating the value of the expression using an expression including variables to which the amino acid concentration values are substituted.
- step S21 it may be determined that the value of the calculated expression reflects the state of the lifestyle-related disease index for the evaluation target, and further, the value of the expression is determined by, for example, the following method. Conversion may be performed and the value after conversion may be determined to reflect the state of the index of lifestyle-related diseases for the evaluation target. In other words, in step S21, the value of the expression or the converted value itself may be treated as an evaluation result regarding the state of the lifestyle-related disease index for the evaluation target.
- a possible range of the value of the evaluation formula is a predetermined range (for example, a range from 0.0 to 1.0, a range from 0.0 to 10.0, a range from 0.0 to 100.0, or ⁇ 10.
- an arbitrary value is added / subtracted / divided / divided from / to the value of the evaluation expression so that it falls within the range from 0 to 10.0, etc. , Logarithmic conversion, angular conversion, square root conversion, probit conversion, or reciprocal conversion), or by combining these calculations with the evaluation expression value to convert the value of the evaluation expression May be.
- the value of an exponential function with the value of the evaluation formula as the index and the Napier number as the base (specifically, the probability p that the lifestyle-related disease index is in a predetermined state (for example, a state exceeding the reference value, etc.) And the natural logarithm ln (p / (1-p)) when defining is equal to the value of the evaluation formula) may be further calculated.
- a value obtained by dividing the value of the exponential function by the sum of 1 and the value (specifically, the value of probability p) may be further calculated.
- the value of the evaluation expression may be converted so that the value after conversion under a specific condition becomes a specific value.
- the value of the evaluation formula may be converted so that the value after conversion when the sensitivity is 80% is 4.0 and the value after conversion when the sensitivity is 60% is 8.0.
- the evaluation value in this specification may be the value of the evaluation formula itself, or may be a value after converting the value of the evaluation formula.
- Position information related to the position of the corresponding predetermined mark is generated using the value of the expression or the converted value when the value of the expression is converted, and the generated position You may determine that information reflects the state of the index of the lifestyle related disease about evaluation object.
- the state of the lifestyle-related disease index in the evaluation target may be evaluated qualitatively or quantitatively. Further, in step S21, the evaluation target is set to the state of the index of lifestyle-related diseases using an amino acid concentration value, an expression including a variable to which the amino acid concentration value is substituted, and one or more preset threshold values. It may be classified into any one of a plurality of categories defined in consideration of at least the degree of. Further, in step S21, when the lifestyle-related disease index is measurable with a continuous numerical value, the evaluation is performed using an expression including an amino acid concentration value and a variable into which the amino acid concentration value is substituted. You may estimate the value of the parameter
- the degree of insulin in the evaluation target may be qualitatively or quantitatively evaluated.
- the evaluation target is evaluated at least in consideration of the amount of insulin using the amino acid concentration value, an expression including a variable to which the amino acid concentration value is substituted, and one or more preset threshold values. It may be classified into any one of a plurality of categories defined as above.
- a plurality of categories include a category for assigning a subject having a large amount of insulin (for example, insulin value at 120 minutes of OGTT), and an amount of insulin (for example, insulin value at 120 minutes of OGTT).
- a section for belonging to a subject with a small and a section for belonging to a subject with a moderate amount of insulin may be included.
- the plurality of categories include a category for assigning a subject whose amount of insulin (for example, insulin value at 120 minutes of OGTT) is equal to or higher than a reference value (for example, 40 ⁇ U / ml) and insulin amount (for example, OGTT) (For example, an insulin value at 120 minutes) may include a category for belonging to a subject having a reference value (for example, 40 ⁇ U / ml) or less.
- the plurality of sections include a section for belonging to a subject whose insulin value at 120 minutes of OGTT is likely to be 40 ⁇ U / ml or more, a section for belonging to a subject with a low possibility, and the above A division may be included for belonging to a subject with moderate likelihood.
- the plurality of categories include a category for belonging to a subject whose insulin value at 120 minutes of OGTT is likely to be 40 ⁇ U / ml or more, and a category for belonging to a subject with the low possibility It may be included.
- the amount of insulin in the evaluation target may be estimated using an amino acid concentration value and an equation including a variable into which the amino acid concentration value is substituted.
- the value of the expression is converted by a predetermined method, and the evaluation target is classified into one of a plurality of categories using the converted value, or the amount of insulin in the evaluation target is determined. Or may be estimated.
- the degree of visceral fat in the evaluation target (for example, the area value of fat in the abdominal body axis section) may be evaluated. Further, in step S21, the evaluation target is set to at least the degree of visceral fat using an amino acid concentration value, an expression including a variable to which the amino acid concentration value is substituted, and one or more preset threshold values. You may classify
- the plurality of categories include a category for assigning a subject having a large amount of visceral fat (eg, visceral fat area value) and a subject having a small amount of visceral fat (eg, visceral fat area value).
- a section for belonging and a section for belonging a subject having a medium amount of visceral fat may be included.
- the plurality of categories include a category for assigning a subject whose visceral fat amount (eg, visceral fat area value) is equal to or greater than a reference value (eg, 100 cm 2 ) and visceral fat amount (eg, visceral fat area value). Etc.) may be included in order to belong to an object whose reference value (for example, 100 cm 2 ) or less.
- the plurality of categories include a category for belonging to a subject whose visceral fat area value is likely to be 100 cm 2 or more, a category for belonging to a subject with a low possibility, and a moderate possibility A section for belonging to a subject may be included. Further, the plurality of categories may include a category for belonging to a subject whose visceral fat area value is likely to be 100 cm 2 or more, and a category for belonging to a subject with a low possibility Good. Further, in step S21, the amount of visceral fat in the evaluation target may be estimated using an expression including an amino acid concentration value and a variable into which the amino acid concentration value is substituted.
- step S21 the value of the expression is converted by a predetermined method, and the evaluation target is classified into one of a plurality of categories using the converted value, or the amount of visceral fat in the evaluation target Or may be estimated.
- classification or estimation an expression further including a BMI value to be evaluated or a variable into which the BMI value is substituted may be used.
- the degree of possibility of fatty liver is a certain amount or more of fat (for example, an amount of fat exceeding 5% of the weight of the liver, 30% or more of hepatocytes. Or the like, or the amount of fat that is judged to be a fatty liver by a doctor, etc.).
- the liver is in the above-described state using the amino acid concentration value, an expression including a variable to which the amino acid concentration value is substituted, and one or more preset threshold values. You may classify
- the plurality of categories include a category for belonging to a subject whose liver is likely to be in the state, a category for belonging to a subject whose liver is unlikely to be in the state, and a liver May include a category to which a subject having a moderate possibility of being in the state belongs. Further, the plurality of categories include a category for belonging to a subject whose liver is likely to be in the state, and a category for belonging to a subject whose liver is unlikely to be in the state. It may be included.
- the value of the expression may be converted by a predetermined method, and the evaluation target may be classified into one of a plurality of categories using the converted value.
- formulas are logistic regression formula, fractional formula, linear discriminant formula, multiple regression formula, formula created by support vector machine, formula created by Mahalanobis distance method, formula created by canonical discriminant analysis, and decision It may be any one of the expressions created with trees.
- the formula used when evaluating the state of insulin may be Formula 1
- the formula used when evaluating the visceral fat status may be Formula 2
- the formula used when evaluating the status of fatty liver is Formula 3.
- Equation 3 Equation 1
- Equation 2 a 2 , b 2 , c 2 , d 2 , e 2 , f 2 , and g 2 are arbitrary non-zero real numbers, and h 2 is an arbitrary real number.
- a 3 , b 3 , c 3 , d 3 , e 3 , and f 3 are arbitrary non-zero real numbers, and g 3 is an arbitrary real number.
- step S21 evaluation is performed among a plurality of items defined as diagnostic criteria items for metabolic syndrome using the amino acid concentration value and any one of Equations 1, 2, and 3.
- the number of items to which the subject applies may be evaluated.
- step S21 the number of lifestyle-related diseases possessed by the evaluation object can be evaluated using the amino acid concentration value and any one of Equations 1, 2, and 3. Good.
- step S21 the degree of possibility that the evaluation target suffers from a lifestyle-related disease is evaluated using the amino acid concentration value and any one of Equations 1, 2, and 3. May be.
- the formula adopted as the evaluation formula is described in, for example, the method described in International Publication No. 2004/052191 that is an international application by the present applicant or International Publication No. 2006/098192 that is an international application by the present applicant. You may create by the method of.
- the formula is suitably used for evaluating the state of the index of lifestyle-related diseases regardless of the unit of the amino acid concentration value in the amino acid concentration data as input data. be able to.
- the formula adopted as the evaluation formula generally means the format of the formula used in multivariate analysis, and examples of formulas adopted as the evaluation formula include fractional expressions, multiple regression formulas, multiple logistic regression formulas, Examples include linear discriminants, Mahalanobis distances, canonical discriminant functions, support vector machines, decision trees, and formulas represented by the sum of different types of formulas.
- a coefficient and a constant term are added to each variable.
- the coefficient and the constant term are preferably real numbers, and more preferably May be any value belonging to the range of the 99% confidence interval of the coefficient and constant term obtained for performing the various classifications from the data, and more preferably, the value obtained for performing the various classifications from the data. Any value may be used as long as it falls within the 95% confidence interval of the obtained coefficient and constant term. Further, the value of each coefficient and its confidence interval may be obtained by multiplying it by a real number, and the value of the constant term and its confidence interval may be obtained by adding / subtracting / multiplying / dividing an arbitrary real constant thereto. When logistic regression, linear discriminant, multiple regression, etc.
- the fractional expression means that the numerator of the fractional expression is represented by the sum of amino acids A, B, C,... And / or the denominator of the fractional expression is the sum of amino acids a, b, c,. It is represented by
- the fractional expression includes a sum of fractional expressions ⁇ , ⁇ , ⁇ ,.
- the fractional expression also includes a divided fractional expression.
- An appropriate coefficient may be attached to each amino acid used in the numerator and denominator.
- amino acids used in the numerator and denominator may overlap.
- an appropriate coefficient may be attached to each fractional expression.
- the value of the coefficient of each variable and the value of the constant term may be real numbers.
- the fractional expression includes one in which the numerator variable and the denominator variable are interchanged.
- the concentration value of amino acids other than the said 19 types of amino acids when evaluating the state of an indicator of lifestyle-related diseases, in addition to the amino acid concentration value, values related to other biological information (for example, values listed in 1. to 4. below) May be further used.
- the formula employed as the evaluation formula may further include one or a plurality of variables into which the concentration values of amino acids other than the 19 kinds of amino acids are substituted.
- the expression employed as the evaluation expression is a value related to other biological information (for example, the values listed in 1. to 4.
- Concentration values of blood metabolites other than amino acids (amino acid metabolites, sugars, lipids, etc.), proteins, peptides, minerals, hormones, etc.
- Value obtained from image information such as ultrasonic echo, X-ray, CT, MRI, etc.
- step 1 to step 4 the outline of the evaluation formula creation process (step 1 to step 4) will be described in detail. Note that the processing described here is merely an example, and the method of creating the evaluation formula is not limited to this.
- control unit is a candidate for an evaluation formula based on a predetermined formula creation method from index state information stored in the storage unit in advance including amino acid concentration data and lifestyle-related disease index data regarding the status of an index of lifestyle-related disease
- step 1 a number of different formula creation methods (principal component analysis, discriminant analysis, support vector machine, multiple regression analysis, logistic regression analysis, k-means method, cluster analysis, decision tree, etc.)
- a plurality of candidate formulas may be created in combination with those related to variable analysis. Specifically, amino acid concentration data and lifestyle habits obtained by analyzing blood obtained from a group of healthy groups and groups whose lifestyle disease index is in a predetermined state (for example, a state exceeding a reference value, etc.)
- a plurality of groups of candidate formulas may be created in parallel using a plurality of different algorithms for index state information that is multivariate data composed of disease index data. For example, discriminant analysis and logistic regression analysis may be performed simultaneously using different algorithms to create two different candidate formulas.
- the candidate formulas may be created by converting index state information using candidate formulas created by performing principal component analysis and performing discriminant analysis on the converted index status information. Thereby, finally, an optimal evaluation formula can be created.
- the candidate formula created using principal component analysis is a linear formula including each amino acid variable that maximizes the variance of all amino acid concentration data.
- Candidate formulas created using discriminant analysis are higher-order formulas (including exponents and logarithms) that contain amino acid variables that minimize the ratio of the sum of variances within each group to the variance of all amino acid concentration data. ).
- the candidate formula created using the support vector machine is a high-order formula (including a kernel function) including each amino acid variable that maximizes the boundary between groups.
- the candidate formula created using multiple regression analysis is a high-order formula including each amino acid variable that minimizes the sum of the distances from all amino acid concentration data.
- the candidate formula created using the logistic regression analysis is a linear model that represents the log odds of the probability, and is a linear formula that includes each amino acid variable that maximizes the likelihood of the probability.
- the k-means method searches k neighborhoods of each amino acid concentration data, defines the largest group among the groups to which the neighboring points belong as the group to which the data belongs, This is a method of selecting an amino acid variable that best matches the group to which the group belongs.
- Cluster analysis is a method of clustering (grouping) points that are closest to each other in all amino acid concentration data. Further, the decision tree is a technique for predicting a group of amino acid concentration data from patterns that can be taken by amino acid variables having higher ranks by adding ranks to amino acid variables.
- control unit verifies (mutually verifies) the candidate formula created in step 1 based on a predetermined verification method (step 2).
- Candidate expressions are verified for each candidate expression created in step 1.
- step 2 the discrimination rate, sensitivity, specificity, information criterion, ROC_AUC (reception of candidate expressions) based on at least one of the bootstrap method, holdout method, N-fold method, leave one-out method, etc.
- the area under the curve of the person characteristic curve may be verified.
- the discrimination rate means that the state of the index of lifestyle-related diseases evaluated in the present embodiment is evaluated as negative as a true state (for example, the result of a definitive diagnosis), and positive as a true state. It is the ratio which evaluates the thing of correctly as positive.
- Sensitivity is the rate at which a life-style related disease index state evaluated in the present embodiment is correctly evaluated as positive as a true state.
- specificity is a ratio of correctly evaluating negative as a true state of the index of lifestyle-related diseases evaluated in the present embodiment.
- the Akaike Information Criterion is a standard that expresses how closely the observed data matches the statistical model in the case of regression analysis, etc., and is expressed as “ ⁇ 2 ⁇ (maximum log likelihood of statistical model) + 2 ⁇ (statistics).
- the model having the smallest value defined by “the number of free parameters of the model)” is determined to be the best.
- ROC_AUC area under the curve of the receiver characteristic curve
- ROC receiver characteristic curve
- the value of ROC_AUC is 1 in complete discrimination, and the closer this value is to 1, the higher the discriminability.
- the predictability is an average of the discrimination rate, sensitivity, and specificity obtained by repeating the verification of candidate formulas.
- Robustness is the variance of discrimination rate, sensitivity, and specificity obtained by repeating verification of candidate formulas.
- control unit selects a candidate formula variable based on a predetermined variable selection method, thereby combining the amino acid concentration data included in the index state information used when creating the candidate formula Is selected (step 3).
- Amino acid variables may be selected for each candidate formula created in step 1. Thereby, the amino acid variable of a candidate formula can be selected appropriately. Then, Step 1 is executed again using the index state information including the amino acid concentration data selected in Step 3.
- the candidate expression amino acid variable may be selected from the verification result in step 2 based on at least one of the stepwise method, the best path method, the neighborhood search method, and the genetic algorithm.
- the best path method is a method of selecting amino acid variables by sequentially reducing the amino acid variables included in the candidate formula one by one and optimizing the evaluation index given by the candidate formula.
- the control unit repeatedly executes the above-described step 1, step 2, and step 3, and adopts it as an evaluation formula from a plurality of candidate formulas based on the verification results accumulated thereby.
- An evaluation formula is created by selecting candidate formulas (step 4).
- the selection of candidate formulas includes, for example, selecting an optimal formula from candidate formulas created by the same formula creation method and selecting an optimal formula from all candidate formulas.
- evaluation formula creation process processing related to creation of candidate formulas, verification of candidate formulas and selection of variables of candidate formulas is systematized (systemized) based on the index status information.
- the amino acid concentration is used for multivariate statistical analysis, and the variable selection method and cross-validation are combined in order to select an optimal and robust set of variables.
- the evaluation formula logistic regression, linear discrimination, support vector machine, Mahalanobis distance method, multiple regression analysis, cluster analysis, Cox proportional hazard model, or the like can be used.
- FIG. 4 is a diagram showing an example of the overall configuration of the present system.
- FIG. 5 is a diagram showing another example of the overall configuration of the present system.
- this system includes a lifestyle-related disease index evaluation apparatus 100 that evaluates the state of an index of lifestyle-related diseases in an individual to be evaluated, and a client that provides individual amino acid concentration data related to the amino acid concentration value.
- the apparatus 200 (corresponding to the information communication terminal apparatus of the present invention) is configured to be communicably connected via the network 300.
- this system uses index state information used when creating an evaluation formula in the lifestyle disease index evaluation device 100
- the database device 400 that stores an evaluation formula used when evaluating the state of an indicator of habitual disease may be configured to be communicably connected via the network 300.
- the lifestyle-related disease index is transmitted from the lifestyle-related disease index evaluation device 100 to the client device 200 or the database device 400 or from the client device 200 or the database device 400 to the lifestyle-related disease index evaluation device 100 via the network 300.
- Information that can be used as a reference to know the status is provided.
- the information that is helpful in knowing the state of the index of lifestyle-related diseases is, for example, information about values measured for specific items related to the state of indicators of lifestyle-related diseases of living organisms including humans.
- information that is useful for knowing the state of the index of lifestyle-related diseases is generated by the lifestyle-related disease index evaluation device 100, the client device 200, and other devices (for example, various measuring devices), and is mainly a database device. 400 is accumulated.
- FIG. 6 is a block diagram showing an example of the configuration of the lifestyle-related disease index evaluation apparatus 100 of this system, and conceptually shows only the portion related to the present invention in the configuration.
- the lifestyle-related disease index evaluation apparatus 100 includes a control unit 102 such as a CPU that centrally controls the lifestyle-related disease index evaluation apparatus, a communication device such as a router, and a wired or wireless communication line such as a dedicated line.
- a communication interface unit 104 that connects the lifestyle-related disease index evaluation apparatus to the network 300 to be communicable, a storage unit 106 that stores various databases, tables, files, and the like, and an input / output interface that connects to the input device 112 and the output device 114 Are connected to each other via an arbitrary communication path.
- the lifestyle-related disease index evaluation device 100 may be configured in the same housing as various analysis devices (for example, an amino acid analyzer or the like).
- the storage unit 106 is a storage means, and for example, a memory device such as a RAM / ROM, a fixed disk device such as a hard disk, a flexible disk, an optical disk, or the like can be used.
- the storage unit 106 stores a computer program for giving instructions to the CPU and performing various processes in cooperation with an OS (Operating System).
- the storage unit 106 includes a user information file 106a, an amino acid concentration data file 106b, an index state information file 106c, a specified index state information file 106d, an evaluation formula related information database 106e, and an evaluation result file 106f. And store.
- the user information file 106a stores user information related to users.
- FIG. 7 is a diagram illustrating an example of information stored in the user information file 106a.
- the information stored in the user information file 106a includes a user ID for uniquely identifying a user and authentication for whether or not the user is a valid person.
- the amino acid concentration data file 106b stores amino acid concentration data relating to amino acid concentration values.
- FIG. 8 is a diagram showing an example of information stored in the amino acid concentration data file 106b. As shown in FIG. 8, the information stored in the amino acid concentration data file 106b is configured by associating an individual number for uniquely identifying an individual (sample) to be evaluated with amino acid concentration data. Yes.
- amino acid concentration data is treated as a numerical value, that is, a continuous scale, but the amino acid concentration data may be a nominal scale or an order scale. In the case of a nominal scale or an order scale, analysis may be performed by giving an arbitrary numerical value to each state.
- amino acid concentration data may be combined with amino acid concentration values other than the 19 amino acids and values related to other biological information (for example, values listed in 1. to 4. below).
- Concentration values of blood metabolites other than amino acids (amino acid metabolites, sugars, lipids, etc.), proteins, peptides, minerals, hormones, etc.
- Image information such as ultrasonic echo, X-ray, CT, MRI, etc.
- FIG. 9 is a diagram illustrating an example of information stored in the index state information file 106c.
- Information stored in the index state information file 106c as shown in FIG. 9, the individual number and an indication of the lifestyle-related diseases (index T 1, index T 2, index T 3 ⁇ ⁇ ⁇ ) lifestyle diseases relating to the state of The index data (T) and the amino acid concentration data are associated with each other.
- the lifestyle-related disease index data and the amino acid concentration data are treated as numerical values (that is, a continuous scale), but the lifestyle-related disease index data and the amino acid concentration data may be a nominal scale or an order scale. In the case of a nominal scale or an order scale, analysis may be performed by giving an arbitrary numerical value to each state.
- the lifestyle-related disease index data is a known index of lifestyle-related diseases, and numerical data may be used.
- the designated index status information file 106d stores the index status information designated by the index status information designation unit 102g described later.
- FIG. 10 is a diagram illustrating an example of information stored in the designated index state information file 106d. As shown in FIG. 10, the information stored in the designated index state information file 106d is configured by associating an individual number, designated lifestyle-related disease index data, and designated amino acid concentration data with each other.
- the evaluation formula related information database 106e stores a candidate formula file 106e1 for storing a candidate formula created by a candidate formula creation unit 102h1 described later and a verification result for storing a verification result by a candidate formula verification unit 102h2 described later.
- a file 106e2 a selection index state information file 106e3 that stores index state information including a combination of amino acid concentration data selected by a variable selection unit 102h3 described later, and an evaluation that stores an evaluation formula created by an evaluation formula creation unit 102h described later
- the candidate formula file 106e1 stores candidate formulas created by a candidate formula creation unit 102h1 described later.
- FIG. 11 is a diagram illustrating an example of information stored in the candidate formula file 106e1. As shown in FIG. 11, the information stored in the candidate formula file 106e1 includes the rank, the candidate formula (in FIG. 11, F 1 (Gly, Leu, Phe,%), F 2 (Gly, Leu, Phe). , etc, F 3 (Gly, Leu, Phe,%)) And the like.
- FIG. 12 is a diagram illustrating an example of information stored in the verification result file 106e2.
- the information stored in the verification result file 106e2 includes ranks, candidate expressions (in FIG. 12, F k (Gly, Leu, Phe,%) And F m (Gly, Leu, Phe). ,...), F l (Gly, Leu, Phe, etc)
- the verification result of each candidate expression for example, the evaluation value of each candidate expression
- the selection index state information file 106e3 stores index state information including a combination of amino acid concentration data corresponding to variables selected by the variable selection unit 102h3 described later.
- FIG. 13 is a diagram illustrating an example of information stored in the selection index state information file 106e3. As shown in FIG. 13, the information stored in the selection index state information file 106e3 is selected by an individual number, lifestyle disease index data specified by an index state information specifying unit 102g described later, and a variable selecting unit 102h3 described later. The amino acid concentration data is correlated with each other.
- FIG. 14 is a diagram illustrating an example of information stored in the evaluation formula file 106e4.
- the information stored in the evaluation formula file 106e4 includes the rank, the evaluation formula (in FIG. 14, F p (Phe,%), F p (Gly, Leu, Phe), F k. (Gly, Leu, Phe,...)), A threshold corresponding to each formula creation method, and a verification result of each evaluation formula (for example, an evaluation value of each evaluation formula) are associated with each other. Yes.
- FIG. 15 is a diagram illustrating an example of information stored in the evaluation result file 106f.
- Information stored in the evaluation result file 106f includes an individual number for uniquely identifying an individual (sample) to be evaluated, an amino acid concentration data of the individual acquired in advance, and an evaluation result regarding the state of an indicator of lifestyle-related diseases (For example, the value of the evaluation formula calculated by the calculation unit 102i1 described later, the value after converting the value of the evaluation formula by the conversion unit 102i2 described later, the position information generated by the generation unit 102i3 described later, or the classification unit described later.
- the classification results obtained in 102i4, etc. are associated with each other.
- the storage unit 106 stores various types of Web data for providing the Web site to the client device 200, a CGI program, and the like as other information in addition to the information described above.
- the Web data includes data for displaying various Web pages, which will be described later, and the data is formed as a text file described in, for example, HTML or XML.
- a part file, a work file, and other temporary files for creating Web data are also stored in the storage unit 106.
- the storage unit 106 stores audio for transmission to the client device 200 as an audio file such as WAVE format or AIFF format, and stores still images and moving images as image files such as JPEG format or MPEG2 format as necessary. Or can be stored.
- the communication interface unit 104 mediates communication between the lifestyle-related disease index evaluation device 100 and the network 300 (or a communication device such as a router). That is, the communication interface unit 104 has a function of communicating data with other terminals via a communication line.
- the input / output interface unit 108 is connected to the input device 112 and the output device 114.
- a monitor including a home television
- a speaker or a printer can be used as the output device 114 (hereinafter, the output device 114 may be described as the monitor 114).
- the input device 112 a monitor that realizes a pointing device function in cooperation with a mouse can be used in addition to a keyboard, a mouse, and a microphone.
- the control unit 102 has an internal memory for storing a control program such as an OS (Operating System), a program that defines various processing procedures, and necessary data, and performs various information processing based on these programs. Execute. As shown in the figure, the control unit 102 is roughly divided into a request interpretation unit 102a, a browsing processing unit 102b, an authentication processing unit 102c, an e-mail generation unit 102d, a web page generation unit 102e, a reception unit 102f, and an index state information designation unit 102g.
- An evaluation formula creation unit 102h, an evaluation unit 102i, a result output unit 102j, and a transmission unit 102k are provided.
- the control unit 102 removes data with missing values, removes data with many outliers, and has missing values with respect to index state information transmitted from the database device 400 and amino acid concentration data transmitted from the client device 200. Data processing such as removal of variables with a lot of data is also performed.
- the request interpretation unit 102a interprets the request content from the client device 200 or the database device 400, and passes the processing to each unit of the control unit 102 according to the interpretation result.
- the browsing processing unit 102b Upon receiving browsing requests for various screens from the client device 200, the browsing processing unit 102b generates and transmits Web data for these screens.
- the authentication processing unit 102c makes an authentication determination.
- the e-mail generation unit 102d generates an e-mail including various types of information.
- the web page generation unit 102e generates a web page that the user browses on the client device 200.
- the receiving unit 102f receives information (specifically, amino acid concentration data, index state information, evaluation formulas, etc.) transmitted from the client device 200 or the database device 400 via the network 300.
- the index state information designating unit 102g designates target lifestyle-related disease index data and amino acid concentration data when creating the evaluation formula.
- the evaluation formula creating unit 102h creates an evaluation formula based on the index status information received by the receiving unit 102f and the index status information specified by the index status information specifying unit 102g. Specifically, the evaluation formula creation unit 102h uses a plurality of verification results accumulated by repeatedly executing the candidate formula creation unit 102h1, the candidate formula verification unit 102h2, and the variable selection unit 102h3 from the index state information. An evaluation formula is created by selecting candidate formulas to be adopted as evaluation formulas from the candidate formulas.
- the evaluation formula creation unit 102h creates the evaluation formula by selecting a desired evaluation formula from the storage unit 106. Also good. Further, the evaluation formula creation unit 102h may create an evaluation formula by selecting and downloading a desired evaluation formula from another computer device (for example, the database device 400) that stores the evaluation formula in advance.
- FIG. 16 is a block diagram showing the configuration of the evaluation formula creation unit 102h, and conceptually shows only the portion related to the present invention.
- the evaluation formula creation unit 102h further includes a candidate formula creation unit 102h1, a candidate formula verification unit 102h2, and a variable selection unit 102h3.
- the candidate formula creation unit 102h1 creates a candidate formula that is a candidate for an evaluation formula based on a predetermined formula creation method from the index state information.
- the candidate formula creation unit 102h1 may create a plurality of candidate formulas from the index state information by using a plurality of different formula creation methods.
- the candidate formula verification unit 102h2 verifies the candidate formula created by the candidate formula creation unit 102h1 based on a predetermined verification method.
- the candidate expression verifying unit 102h2 determines the candidate expression discrimination rate, sensitivity, specificity, information criterion, ROC_AUC based on at least one of the bootstrap method, holdout method, N-fold method, and leave one out method. Verification may be made with respect to at least one of (area under the receiver characteristic curve).
- the variable selection unit 102h3 selects a combination of amino acid concentration data included in the index state information used when creating a candidate expression by selecting a variable of the candidate expression based on a predetermined variable selection method. Note that the variable selection unit 102h3 may select a candidate expression variable based on at least one of the stepwise method, the best path method, the neighborhood search method, and the genetic algorithm from the verification result.
- the evaluation unit 102 i receives the expression obtained in advance (for example, the evaluation expression created by the evaluation expression creation unit 102 h or the evaluation expression received by the reception unit 102 f) and the reception unit 102 f.
- the expression obtained in advance for example, the evaluation expression created by the evaluation expression creation unit 102 h or the evaluation expression received by the reception unit 102 f
- the reception unit 102 f By calculating the value of the evaluation formula using the amino acid concentration data of the individual, the state of the index of lifestyle-related diseases is evaluated for the individual.
- FIG. 17 is a block diagram showing the configuration of the evaluation unit 102i, and conceptually shows only the portion related to the present invention.
- the evaluation unit 102i further includes a calculation unit 102i1, a conversion unit 102i2, a generation unit 102i3, and a classification unit 102i4.
- the calculating unit 102i1 calculates the value of the evaluation formula using an evaluation formula including a variable into which the concentration value of at least Gly and Tyr amino acids and the concentration value of at least Gly and Tyr amino acids are substituted.
- the evaluation unit 102i may store the value of the evaluation formula calculated by the calculation unit 102i1 as an evaluation result in a predetermined storage area of the evaluation result file 106f.
- the evaluation formulas are logistic regression formula, fractional formula, linear discriminant formula, multiple regression formula, formula created with support vector machine, formula created with Mahalanobis distance method, formula created with canonical discriminant analysis, and Any one of the formulas created by the decision tree may be used.
- the evaluation unit 102i may use the value of the evaluation formula calculated by the calculation unit 102i1 as the estimated value of the index.
- the conversion unit 102i2 converts the value of the evaluation formula calculated by the calculation unit 102i1 using, for example, the conversion method described above.
- the evaluation unit 102i may store the value after conversion by the conversion unit 102i2 as an evaluation result in a predetermined storage area of the evaluation result file 106f.
- the evaluation unit 102i may use the value after conversion by the conversion unit 102i2 as the estimated value of the index.
- the generation unit 102i3 is a predetermined ruler (for example, a ruler with a scale shown) for evaluating the state of a lifestyle-related disease index that is visibly displayed on a display device such as a monitor or a physical medium such as paper. Corresponds to the value of the expression or the value after the conversion on the expression value or the range that the converted value can take or at least a scale corresponding to the upper and lower limits in a part of the range.
- the position information related to the position of a predetermined mark (for example, a circle or a star) is generated using the value of the formula calculated by the calculation unit 102i1 or the value after conversion by the conversion unit 102i2.
- the evaluation unit 102i may store the position information generated by the generation unit 102i3 in a predetermined storage area of the evaluation result file 106f as an evaluation result.
- the classification unit 102i4 uses a value of the evaluation formula calculated by the calculation unit 102i1 or a value after conversion by the conversion unit 102i2 to define an individual by considering at least the degree of the state of an indicator of lifestyle-related diseases Into one of the categories.
- the result output unit 102 j outputs the processing results (including the evaluation results obtained by the evaluation unit 102 i) in each processing unit of the control unit 102 to the output device 114.
- the transmission unit 102k transmits the evaluation result to the client device 200 that is the transmission source of the individual amino acid concentration data, and the evaluation formula and the evaluation result created by the lifestyle-related disease index evaluation device 100 to the database device 400. Or send.
- FIG. 18 is a block diagram showing an example of the configuration of the client device 200 of the present system, and conceptually shows only the portion related to the present invention in the configuration.
- the client device 200 includes a control unit 210, a ROM 220, an HD 230, a RAM 240, an input device 250, an output device 260, an input / output IF 270, and a communication IF 280. These units are communicably connected via an arbitrary communication path. Has been.
- the control unit 210 includes a web browser 211, an electronic mailer 212, a reception unit 213, and a transmission unit 214.
- the web browser 211 interprets the web data and performs a browsing process for displaying the interpreted web data on a monitor 261 described later. Note that the web browser 211 may be plugged in with various software such as a stream player having a function of receiving, displaying, and feedbacking the stream video.
- the electronic mailer 212 transmits and receives electronic mail according to a predetermined communication protocol (for example, SMTP (Simple Mail Transfer Protocol), POP3 (Post Office Protocol version 3), etc.).
- the receiving unit 213 receives various types of information such as evaluation results transmitted from the lifestyle-related disease index evaluation apparatus 100 via the communication IF 280.
- the transmission unit 214 transmits various information such as individual amino acid concentration data to the lifestyle-related disease index evaluation apparatus 100 via the communication IF 280.
- the input device 250 is a keyboard, a mouse, a microphone, or the like.
- a monitor 261 which will be described later, also realizes a pointing device function in cooperation with the mouse.
- the output device 260 is an output unit that outputs information received via the communication IF 280, and includes a monitor (including a home television) 261 and a printer 262. In addition, the output device 260 may be provided with a speaker or the like.
- the input / output IF 270 is connected to the input device 250 and the output device 260.
- the communication IF 280 connects the client device 200 and the network 300 (or a communication device such as a router) so that they can communicate with each other.
- the client device 200 is connected to the network 300 via a communication device such as a modem, TA, or router and a telephone line, or via a dedicated line.
- the client apparatus 200 can access the lifestyle-related disease index evaluation apparatus 100 according to a predetermined communication protocol.
- an information processing device for example, a known personal computer, workstation, home game device, Internet TV, PHS terminal, portable terminal, mobile body
- peripheral devices such as a printer, a monitor, and an image scanner as necessary.
- the client apparatus 200 may be realized by mounting software (including programs, data, and the like) that realizes a Web data browsing function and an electronic mail function in a communication terminal / information processing terminal such as a PDA.
- control unit 210 of the client device 200 may be realized by a CPU and a program that is interpreted and executed by the CPU and all or any part of the processing performed by the control unit 210.
- the ROM 220 or the HD 230 stores computer programs for giving instructions to the CPU in cooperation with an OS (Operating System) and performing various processes.
- the computer program is executed by being loaded into the RAM 240, and constitutes the control unit 210 in cooperation with the CPU.
- the computer program may be recorded in an application program server connected to the client apparatus 200 via an arbitrary network, and the client apparatus 200 may download all or a part thereof as necessary. .
- all or any part of the processing performed by the control unit 210 may be realized by hardware such as wired logic.
- control unit 210 is an evaluation unit 210a (calculation unit 210a1, conversion unit 210a2, generation unit) having the same function as the function of the evaluation unit 102i provided in the control unit 102 of the lifestyle-related disease index evaluation apparatus 100. 210a3 and classification unit 210a4).
- the evaluation unit 210a converts the conversion unit 210a2 according to the information included in the evaluation result transmitted from the lifestyle-related disease index cancer evaluation device 100.
- the value of the expression is converted by the generation unit 210a3, the position information corresponding to the value of the expression or the converted value is generated by the generation unit 210a3, and the individual using the value of the expression or the converted value by the classification unit 210a4 It may be classified into any one of the categories.
- the network 300 has a function of connecting the lifestyle-related disease index evaluation apparatus 100, the client apparatus 200, and the database apparatus 400 so that they can communicate with each other.
- the Internet 300 intranet, LAN (including both wired / wireless), and the like.
- the network 300 includes a VAN, a personal computer communication network, a public telephone network (including both analog / digital), a dedicated line network (including both analog / digital), a CATV network, and a mobile line switching network.
- mobile packet switching network including IMT2000 system, GSM (registered trademark) system or PDC / PDC-P system
- wireless paging network including local wireless network such as Bluetooth (registered trademark)
- PHS network including CS, BS or ISDB
- satellite A communication network including CS, BS or ISDB
- FIG. 19 is a block diagram showing an example of the configuration of the database apparatus 400 of the present system, and conceptually shows only the portion related to the present invention in the configuration.
- the database device 400 includes the index state information used when creating an evaluation formula with the lifestyle-related disease index evaluation device 100 or the database device, the evaluation formula created with the lifestyle-related disease index evaluation device 100, and the lifestyle-related disease index evaluation device 100. It has a function to store the evaluation result etc.
- the database device 400 includes a control unit 402 such as a CPU that controls the database device in an integrated manner, a communication device such as a router, and a wired or wireless communication circuit such as a dedicated line.
- a communication interface unit 404 that connects the apparatus to the network 300 to be communicable, a storage unit 406 that stores various databases, tables, and files (for example, files for Web pages), and an input unit that connects to the input unit 412 and the output unit 414.
- the output interface unit 408 is configured to be communicable via an arbitrary communication path.
- the storage unit 406 is a storage means, and for example, a memory device such as a RAM / ROM, a fixed disk device such as a hard disk, a flexible disk, an optical disk, or the like can be used.
- the storage unit 406 stores various programs used for various processes.
- the communication interface unit 404 mediates communication between the database device 400 and the network 300 (or a communication device such as a router). That is, the communication interface unit 404 has a function of communicating data with other terminals via a communication line.
- the input / output interface unit 408 is connected to the input device 412 and the output device 414.
- the output device 414 in addition to a monitor (including a home television), a speaker or a printer can be used as the output device 414 (hereinafter, the output device 414 may be described as the monitor 414).
- the input device 412 can be a monitor that realizes a pointing device function in cooperation with the mouse.
- the control unit 402 has an internal memory for storing a control program such as an OS (Operating System), a program that defines various processing procedures, and necessary data, and performs various information processing based on these programs. Execute. As shown in the figure, the control unit 402 is roughly divided into a request interpretation unit 402a, a browsing processing unit 402b, an authentication processing unit 402c, an email generation unit 402d, a Web page generation unit 402e, and a transmission unit 402f.
- OS Operating System
- the request interpretation unit 402a interprets the request content from the lifestyle-related disease index evaluation apparatus 100, and passes the processing to each unit of the control unit 402 according to the interpretation result.
- the browsing processing unit 402b Upon receiving browsing requests for various screens from the lifestyle-related disease index evaluation apparatus 100, the browsing processing unit 402b generates and transmits Web data for these screens.
- the authentication processing unit 402c makes an authentication determination.
- the e-mail generation unit 402d generates an e-mail including various types of information.
- the web page generation unit 402e generates a web page that the user browses on the client device 200.
- the transmission unit 402f transmits various types of information such as index state information and evaluation formulas to the lifestyle-related disease index evaluation apparatus 100.
- FIG. 20 is a flowchart illustrating an example of a lifestyle-related disease index evaluation service process according to the second embodiment.
- the amino acid concentration data used in this treatment is obtained from specialized blood collected from blood (including plasma, serum, etc.) previously collected from individuals such as animals and humans using the following measurement methods such as (A) or (B). Is related to the concentration value of amino acids obtained by analysis or independent analysis.
- the unit of the concentration value of the amino acid may be obtained, for example, by adding / subtracting / subtracting an arbitrary constant to / from these concentrations.
- Plasma was separated from blood by centrifuging the collected blood sample. All plasma samples were stored frozen at ⁇ 80 ° C. until measurement of amino acid concentration values.
- acetonitrile was added to remove protein, followed by precolumn derivatization using a labeling reagent (3-aminopyridyl-N-hydroxysuccinimidyl carbamate), and liquid chromatography mass
- concentration value of amino acids was analyzed by an analyzer (LC / MS) (see International Publication No. 2003/069328 and International Publication No. 2005/116629).
- Plasma was separated from blood by centrifuging the collected blood sample. All plasma samples were stored frozen at ⁇ 80 ° C. until measurement of amino acid concentration values.
- amino acid concentration value sulfosalicylic acid was added to remove protein, and then the amino acid concentration value was analyzed by an amino acid analyzer based on a post-column derivatization method using a ninhydrin reagent.
- the client device 200 displays the lifestyle-related disease index. Access the evaluation device 100.
- the Web browser 211 uses the predetermined communication protocol to specify the address of the Web site provided by the lifestyle-related disease index evaluation device 100.
- a transmission request for a Web page corresponding to the amino acid concentration data transmission screen is made to the lifestyle-related disease index evaluation apparatus 100 by routing based on the address.
- the lifestyle-related disease index evaluation device 100 receives the transmission from the client device 200 by the request interpretation unit 102a, analyzes the content of the transmission, and moves the processing to each unit of the control unit 102 according to the analysis result.
- the lifestyle-related disease index evaluation apparatus 100 is a predetermined memory stored in the storage unit 106 mainly by the browsing processing unit 102b. Web data for displaying the Web page stored in the area is acquired, and the acquired Web data is transmitted to the client device 200.
- the lifestyle-related disease index evaluation apparatus 100 first uses the control unit 102 to change the user ID and the user password. Is requested from the user.
- the lifestyle-related disease index evaluation apparatus 100 causes the authentication processing unit 102c to input the input user ID and password and the user ID stored in the user information file 106a. And authentication with user password.
- the lifestyle-related disease index evaluation apparatus 100 transmits web data for displaying a web page corresponding to the amino acid concentration data transmission screen to the client apparatus 200 by the browsing processing unit 102b only when authentication is possible.
- the client device 200 is identified by the IP address transmitted from the client device 200 together with the transmission request.
- the client apparatus 200 receives the Web data (for displaying a Web page corresponding to the amino acid concentration data transmission screen) transmitted from the lifestyle-related disease index evaluation apparatus 100 by the receiving unit 213, and receives the received Web The data is interpreted by the Web browser 211, and the amino acid concentration data transmission screen is displayed on the monitor 261.
- the client device 200 uses the transmission unit 214.
- the amino acid concentration data and the BMI value of the individual are transmitted to the lifestyle-related disease index evaluation apparatus 100 (step SA21).
- the transmission of amino acid concentration data in step SA21 may be realized by an existing file transfer technique such as FTP.
- the request interpretation unit 102a interprets the request content of the client apparatus 200 by interpreting the identifier transmitted from the client apparatus 200, and sends the evaluation formula transmission request to the database apparatus 400. To do.
- the request interpretation unit 402a interprets the transmission request from the lifestyle-related disease index evaluation device 100 and stores the evaluation formula (for example, the updated latest one) stored in a predetermined storage area of the storage unit 406. ) Is transmitted to the lifestyle-related disease index evaluation apparatus 100 (step SA22).
- the evaluation formula for example, the updated latest one
- the lifestyle-related disease index evaluation apparatus 100 step SA22.
- one or a plurality of evaluation formulas for example, logistic regression formula, fractional formula, linear discriminant formula, multiple regression formula, formula created with support vector machine, Mahalanobis distance formula was used. Any one of the formula, the formula created by the canonical discriminant analysis, and the formula created by the decision tree) is transmitted to the lifestyle-related disease index evaluation apparatus 100.
- step SA22 equation 1 for estimating the insulin value at 120 minutes of OGTT, equation 2 for estimating the visceral fat area value, and the liver may be in a state of having a certain amount or more of fat. It is assumed that Equation 3 for evaluating the degree of sex is transmitted.
- Equation 2 a 2 , b 2 , c 2 , d 2 , e 2 , f 2 , and g 2 are arbitrary non-zero real numbers, and h 2 is an arbitrary real number.
- a 3 , b 3 , c 3 , d 3 , e 3 , and f 3 are arbitrary non-zero real numbers, and g 3 is an arbitrary real number.
- the lifestyle-related disease index evaluation device 100 receives and receives the amino acid concentration data and BMI value of the individual transmitted from the client device 200 and the evaluation formula transmitted from the database device 400 by the receiving unit 102f.
- the amino acid concentration data and the BMI value are stored in a predetermined storage area of the amino acid concentration data file 106b, and the received evaluation formula is stored in a predetermined storage area of the evaluation formula file 106e4 (step SA23).
- control unit 102 removes data such as missing values and outliers from the individual amino acid concentration data received in step SA23 (step SA24).
- the evaluation unit 102i uses the calculation unit 102i1 to determine the amino acid concentration data and BMI value of the individual from which data such as missing values and outliers have been removed in step SA24, and the equations 1, 2 and 2 received in step SA23. And the value of the evaluation formula is calculated using Formula 3 (Step SA25).
- the value of Formula 1 is calculated using the concentration values of amino acids Gly, Tyr, Asn, Ala, Val, and Trp and Formula 1.
- the value of Equation 2 is calculated using the amino acid concentration values of Gly, Tyr, Asn, Ala, Val, and Trp, the BMI value of the individual, and Equation 2.
- the value of Equation 3 is calculated using the concentration values of amino acids Gly, Tyr, Asn, Ala, Cit, and Leu and Equation 3.
- the evaluation unit 102i estimates the insulin value at 120 minutes of the OGTT of the individual using the value of Formula 1 calculated in Step SA25, or uses the value of Formula 2 calculated in Step SA25 to By using the value of the evaluation formula (evaluation value) calculated in step SA25 and a preset threshold value in the classification unit 102i4, the individual has a liver with a certain amount or more of fat. Classify into one of multiple categories defined taking into account at least the degree of possibility of being in a state, and then evaluate the results including the estimation results and the classification results obtained It is stored in a predetermined storage area of the file 106f (step SA26).
- the lifestyle-related disease index evaluation apparatus 100 transmits the evaluation result obtained in step SA26 to the client apparatus 200 and the database apparatus 400 that are the transmission source of amino acid concentration data, in the transmission unit 102k (step). SA27). Specifically, first, the lifestyle-related disease index evaluation apparatus 100 creates a web page for displaying the evaluation result in the web page generation unit 102e, and stores the web data corresponding to the created web page in the storage unit 106. Store in a predetermined storage area. Next, after the user inputs a predetermined URL to the Web browser 211 of the client device 200 via the input device 250 and undergoes the above-described authentication, the client device 200 sends a browsing request for the Web page to the lifestyle-related disease index evaluation device. To 100.
- the browsing processing unit 102b interprets the browsing request transmitted from the client device 200, and stores Web data corresponding to the Web page for displaying the evaluation result in the storage unit 106. Read from the storage area.
- the lifestyle-related disease index evaluation apparatus 100 transmits the read Web data to the client apparatus 200 and transmits the Web data or the evaluation result to the database apparatus 400 by the transmission unit 102k.
- the lifestyle-related disease index evaluation apparatus 100 may notify the evaluation result to the client apparatus 200 of the user by e-mail at the control unit 102.
- the lifestyle-related disease index evaluation apparatus 100 refers to the user information stored in the user information file 106a based on the user ID or the like according to the transmission timing in the e-mail generation unit 102d. Get the user's email address.
- the lifestyle-related disease index evaluation apparatus 100 uses the e-mail generation unit 102d to generate data related to e-mail including the name and evaluation result of the user with the acquired e-mail address as the destination.
- the lifestyle-related disease index evaluation device 100 transmits the generated data to the client device 200 of the user by the transmission unit 102k.
- the lifestyle-related disease index evaluation apparatus 100 may transmit the evaluation result to the user client apparatus 200 using an existing file transfer technology such as FTP.
- control unit 402 receives the evaluation result or Web data transmitted from the lifestyle-related disease index evaluation device 100, and stores the received evaluation result or Web data in the storage unit 406. (Stored) in the storage area (step SA28).
- the client device 200 receives the Web data transmitted from the lifestyle-related disease index evaluation device 100 by the receiving unit 213, interprets the received Web data by the Web browser 211, and stores the individual evaluation results.
- the page screen is displayed on the monitor 261 (step SA29).
- the client apparatus 200 is an e-mail transmitted from the lifestyle-related disease index evaluation apparatus 100 by a known function of the electronic mailer 212. Is received at an arbitrary timing, and the received electronic mail is displayed on the monitor 261.
- the user can check the evaluation result by browsing the Web page displayed on the monitor 261.
- the user may print the display content of the Web page displayed on the monitor 261 with the printer 262.
- the user can check the evaluation result by browsing the e-mail displayed on the monitor 261.
- the user may print the content of the e-mail displayed on the monitor 261 with the printer 262.
- the client apparatus 200 transmits the individual amino acid concentration data (including the BMI value) to the lifestyle-related disease index evaluation apparatus 100, and the database apparatus 400 requests from the lifestyle-related disease index evaluation apparatus 100.
- the evaluation formulas (Formula 1, Formula 2, and Formula 3) are transmitted to the lifestyle-related disease index evaluation apparatus 100.
- the lifestyle-related disease index evaluation device 100 (i) receives amino acid concentration data from the client device 200 and receives an evaluation formula from the database device 400, and (ii) evaluates using the received amino acid concentration data and evaluation formula.
- the insulin value and visceral fat area value at 120 minutes of the OGTT of the individual are estimated, or the calculated evaluation value and threshold are used to Or (iv) the obtained evaluation result is transmitted to the client device 200 or the database device 400.
- the client apparatus 200 receives and displays the evaluation result transmitted from the lifestyle-related disease index evaluation apparatus 100, and the database apparatus 400 receives and stores the evaluation result transmitted from the lifestyle-related disease index evaluation apparatus 100.
- the lifestyle-related disease index evaluation device 100 receives the amino acid concentration data, calculates the value of the evaluation formula, estimates the insulin value and visceral fat area value, classifies the individual into classifications, and the evaluation result.
- the client apparatus 200 executes the transmission and the reception of the evaluation result
- the lifestyle-related disease index evaluation apparatus 100 evaluates the evaluation formula. It is sufficient to perform calculation of the value of, for example, conversion of the value of the evaluation formula, generation of position information, estimation of insulin value and visceral fat area value, and classification into individual categories, etc.
- the evaluation apparatus 100 and the client apparatus 200 may be appropriately shared and executed.
- the evaluation unit 210a converts the value of the expression in the conversion unit 210a2, or the value of the expression or the value after conversion Is used to estimate the insulin value and visceral fat area value, to generate position information corresponding to the value of the expression or the converted value in the generation unit 210a3, or to calculate the value of the expression or the converted value in the classification unit 210a4
- the individual may be classified into any one of a plurality of categories related to fatty liver.
- the evaluation unit 210a estimates the insulin value and the visceral fat area value using the converted value
- the generation unit 210a3 generates position information corresponding to the converted value
- the classification unit 210a4 uses the converted value to classify the individual into any one of a plurality of sections related to fatty liver. Also good.
- the evaluation unit 210a uses the expression value or the converted value.
- the insulin value and the visceral fat area value may be estimated, or the classification unit 210a4 may classify the individual into one of a plurality of categories related to fatty liver using the value of the formula or the value after conversion. .
- the illustrated components are functionally conceptual and do not necessarily need to be physically configured as illustrated.
- the processing functions provided in the lifestyle-related disease index evaluation apparatus 100 are interpreted and executed by a CPU (Central Processing Unit) and the CPU. It may be realized by a program to be executed, or may be realized as hardware by wired logic.
- the program is recorded on a non-transitory computer-readable recording medium including programmed instructions for causing the information processing apparatus to execute the lifestyle-related disease index evaluation method according to the present invention. It is mechanically read by the lifestyle-related disease index evaluation apparatus 100. That is, in the storage unit 106 such as a ROM or an HDD, computer programs for performing various processes by giving instructions to the CPU in cooperation with an OS (Operating System) are recorded. This computer program is executed by being loaded into the RAM, and constitutes a control unit in cooperation with the CPU.
- OS Operating System
- the computer program may be stored in an application program server connected to the lifestyle-related disease index evaluation apparatus 100 via an arbitrary network, and the computer program may be downloaded in whole or in part as necessary. Is also possible.
- the lifestyle-related disease index evaluation program may be stored in a computer-readable recording medium that is not temporary, or may be configured as a program product.
- the “recording medium” means a memory card, USB memory, SD card, flexible disk, magneto-optical disk, ROM, EPROM, EEPROM (registered trademark), CD-ROM, MO, DVD, and Blu-ray. (Registered trademark) It shall include any “portable physical medium” such as Disc.
- the “program” is a data processing method described in an arbitrary language or description method, and may be in the form of source code or binary code. Note that the “program” is not necessarily limited to a single configuration, but is distributed in the form of a plurality of modules and libraries, or in cooperation with a separate program typified by an OS (Operating System). Including those that achieve the function. In addition, a well-known structure and procedure can be used about the specific structure and reading procedure for reading a recording medium in each apparatus shown to embodiment, the installation procedure after reading, etc.
- Various databases and the like stored in the storage unit 106 are storage devices such as a memory device such as a RAM and a ROM, a fixed disk device such as a hard disk, a flexible disk, and an optical disk. Programs, tables, databases, web page files, and the like.
- the lifestyle-related disease index evaluation apparatus 100 may be configured as an information processing apparatus such as a known personal computer or workstation, or may be configured as the information processing apparatus connected to an arbitrary peripheral device. Moreover, the lifestyle-related disease index evaluation apparatus 100 may be realized by installing software (including a program or data) that realizes the lifestyle-related disease index evaluation method of the present invention in the information processing apparatus.
- the specific form of distribution / integration of the devices is not limited to that shown in the figure, and all or a part of them may be functionally or physically in arbitrary units according to various additions or according to functional loads. It can be configured to be distributed and integrated. That is, the above-described embodiments may be arbitrarily combined and may be selectively implemented.
- FIG. 21 is a flowchart illustrating an example of the evaluation formula creation process.
- the evaluation formula creation process may be performed by the database device 400 that manages the index state information.
- the lifestyle-related disease index evaluation device 100 stores the index state information acquired in advance from the database device 400 in a predetermined storage area of the index state information file 106c.
- the lifestyle-related disease index evaluation apparatus 100 includes index state information including lifestyle-related disease index data and amino acid concentration data (including those 19 amino acid concentration values) specified in advance by the index state information specifying unit 102g. Assume that the data is stored in a predetermined storage area of the designated index state information file 106d.
- the evaluation formula creation unit 102h is a candidate formula creation unit 102h1 that creates a candidate formula based on a predetermined formula creation method from index status information stored in a predetermined storage area of the designated index status information file 106d.
- the created candidate formula is stored in a predetermined storage area of the candidate formula file 106e1 (step SB21).
- the evaluation formula creating unit 102h is a candidate formula creating unit 102h1, and a plurality of different formula creating methods (principal component analysis, discriminant analysis, support vector machine, multiple regression analysis, logistic regression analysis, k-means, Method, cluster analysis, multivariate analysis such as decision tree, etc.) Select one of the desired ones from the selected formula creation method (form formula) To decide.
- the evaluation formula creation unit 102h performs various calculations (for example, average and variance) corresponding to the selected formula selection method based on the index state information in the candidate formula creation unit 102h1.
- the evaluation formula creating unit 102h determines the calculation result and the parameters of the determined candidate formula in the candidate formula creating unit 102h1.
- a candidate formula is created based on the selected formula creation method. Note that when a plurality of different formula creation methods are used in combination to create candidate formulas simultaneously and in parallel (in parallel), the above processing may be executed in parallel for each selected formula creation method.
- index status information is converted using candidate formulas created by performing principal component analysis, and the converted index status Candidate expressions may be created by performing discriminant analysis on information.
- the evaluation formula creation unit 102h uses the candidate formula verification unit 102h2 to verify (mutually verify) the candidate formula created in step SB21 based on a predetermined verification method, and store the verification result in a predetermined storage of the verification result file 106e2. Store in the area (step SB22).
- the evaluation formula creation unit 102h is a verification used when the candidate formula verification unit 102h2 verifies the candidate formula based on the index status information stored in a predetermined storage area of the designated index status information file 106d. Data is created, and candidate expressions are verified based on the created verification data.
- the evaluation formula creation unit 102h uses the candidate formula verification unit 102h2 for each candidate formula corresponding to each formula creation method. Verification is performed based on a predetermined verification method.
- the candidate expression discrimination rate, sensitivity, specificity, information criterion, ROC_AUC (based on at least one of the bootstrap method, holdout method, N-fold method, leave one out method, etc. It may be verified with respect to at least one of the area under the receiver characteristic curve).
- the evaluation formula creation unit 102h selects the variable of the candidate formula based on a predetermined variable selection method in the variable selection unit 102h3, whereby the amino acid included in the index state information used when creating the candidate formula A combination of concentration data is selected, and index state information including the selected combination of amino acid concentration data is stored in a predetermined storage area of the selection index state information file 106e3 (step SB23).
- the evaluation formula creation unit 102h may select a variable of the candidate formula based on a predetermined variable selection method for each candidate formula in the variable selection unit 102h3.
- the variable of the candidate expression may be selected based on at least one of the stepwise method, the best path method, the neighborhood search method, and the genetic algorithm from the verification result.
- the best path method is a method of selecting variables by sequentially reducing the variables included in the candidate formula one by one and optimizing the evaluation index given by the candidate formula.
- the evaluation formula creation unit 102h selects a combination of amino acid concentration data based on the index state information stored in the predetermined storage area of the designated index state information file 106d by the variable selection unit 102h3. Also good.
- the evaluation formula creation unit 102h determines whether or not all combinations of amino acid concentration data included in the index state information stored in the predetermined storage area of the specified index state information file 106d have been completed. If the result is “end” (step SB24: Yes), the process proceeds to the next step (step SB25). If the determination result is not “end” (step SB24: No), the process returns to step SB21.
- the evaluation formula creation unit 102h determines whether or not the preset number of times has ended, and if the determination result is “end” (step SB24: Yes), the process proceeds to the next step (step SB25). If the determination result is not “end” (step SB24: No), the process may return to step SB21.
- the evaluation formula creating unit 102h determines whether the combination of the amino acid concentration data selected in step SB23 is the combination of the amino acid concentration data included in the index state information stored in the predetermined storage area of the designated index state information file 106d or the previous time. It is determined whether or not the combination of the amino acid concentration data selected in step SB23 is the same. If the determination result is “same” (step SB24: Yes), the process proceeds to the next step (step SB25). When the determination result is not “same” (step SB24: No), the process may return to step SB21.
- the evaluation formula creation unit 102h based on the comparison result between the evaluation value and a predetermined threshold corresponding to each formula creation method, Whether to proceed to step SB25 or to return to step SB21 may be determined.
- the evaluation formula creation unit 102h determines an evaluation formula by selecting a candidate formula to be adopted as an evaluation formula from a plurality of candidate formulas based on the verification result, and determines the determined evaluation formula (selected candidate formula ) Is stored in a predetermined storage area of the evaluation formula file 106e4 (step SB25).
- step SB25 for example, an optimal one is selected from candidate formulas created by the same formula creation method, and an optimal one is selected from all candidate formulas.
- the blood sample of the examinee collected at the Ningen Dock and the visceral fat area value of the examinee measured in the abdominal CT image diagnosis conducted at the Ningen Dock were obtained (total of 865 people). From the blood sample, 19 amino acids (Ala, Arg, Asn, Cit, Gln, Gly, His, Ile, Leu, Lys, Met, Orn, Phe, Pro, Ser, Thr, The blood concentration value (nmol / ml) of Trp, Tyr, Val) was measured.
- FIG. 22 shows the correlation coefficient between the visceral fat area value and the concentration value of each amino acid, and the determination of each amino acid in the determination (classification) of whether the visceral fat area value is equal to or greater than a reference value (100 cm 2 ).
- ROC_AUC area value under the curve of the receiver characteristic curve (ROC)), which is an index for evaluating performance, is shown.
- the amino acid whose correlation coefficient is significant is Thr, Ser, Pro, Gly, Ala, Val. Met, Ile, Leu, Tyr, Phe, His, Trp, Orn, Lys.
- FIG. 23 shows a correlation coefficient between the insulin resistance index, the blood glucose level at 120 minutes of OGTT, the insulin value at 120 minutes of OGTT, and the concentration value of each amino acid.
- the amino acid whose correlation coefficient with the blood glucose level at 120 minutes of OGTT is significant is Pro , Gly, Ala, Val, Met, Ile, Leu, Tyr, Phe, Trp, Orn, Lys.
- FIG. 24 shows ROC_AUC that serves as an index for evaluating the discriminating ability of each amino acid in determining whether or not a person has been diagnosed with fatty liver.
- the blood sample of the examinee collected at the Ningen Dock and the blood glucose level at 120 minutes of the OGTT of the examinee measured at the Ningen Dock were obtained (total of 650 people).
- the blood sample of the examinee collected at the Ningen Dock and the visceral fat area value of the examinee measured in the abdominal CT image diagnosis carried out at the Ningen Dock were obtained (total of 650 people).
- the blood sample of the examinee collected at the Ningen Dock and the diagnostic results on fatty liver by the ultrasonography performed at the Ningen Dock (diagnosis result of fatty liver (465 persons) or not fatty liver (1535)) (2000 people in total).
- 2 or more and 6 or less amino acids are selected from the 19 kinds of amino acids using the variable coverage method, and the selected amino acids are included as variables.
- “Multiple regression correlating with insulin value at 120 minutes of OGTT” “Equation”, “Multiple regression equation correlating with visceral fat area value”, and “Logistic regression equation for determining whether or not it is fatty liver” were searched.
- BMI was also included as a variable in addition to the selected amino acid.
- FIG. 25 shows the number of appearances of the 19 kinds of amino acids in the top 1000 formulas having high fitness with the OGTT's 120 minute insulin value among the searched formulas, and the internal organs of the searched formulas.
- the top 1000 formulas having a high degree of fitness between the number of appearances of the 19 amino acids in the top 1000 formulas having a high degree of fitness with the fat area value and whether or not they are fatty livers in the searched formulas
- the number of appearances of the 19 amino acids is shown.
- FIG. 26 shows a visceral fat area value of a multiple regression equation including “two or more and six or less amino acids including Gly and Tyr” selected from the above 19 amino acids using a variable coverage method as a variable.
- a range of correlation coefficients is shown.
- FIG. 27 shows the visceral fat area of the multiple regression equation including “3 or more and 6 or less amino acids including Gly, Tyr, and Asn” selected from the above 19 amino acids using the variable coverage method as a variable.
- the range of correlation coefficients for the values is shown.
- FIG. 28 shows the visceral fat area of the multiple regression equation including “three or more and six or less amino acids including Gly, Tyr, and Ala” selected from the above 19 amino acids using the variable coverage method as a variable.
- the range of correlation coefficients for the values is shown.
- the visceral fat area of the multiple regression equation including “three or more and six or less amino acids including Gly, Tyr, and Val” selected from the above 19 amino acids using the variable coverage method as a variable.
- the range of correlation coefficients for the values is shown.
- FIG. 30 shows a visceral fat area of a multiple regression equation including “three or more and six or less amino acids including Gly, Tyr, and Trp” selected as a variable from the above 19 kinds of amino acids using a variable coverage method.
- the range of correlation coefficients for the values is shown.
- FIG. 31 shows an internal organ of a multiple regression equation that includes “four or more and six or less amino acids including Gly, Tyr, Asn, and Ala” selected from the above 19 amino acids using a variable coverage method as a variable.
- the range of correlation coefficients for fat area values is shown.
- FIG. 32 shows the visceral fat area of the multiple regression equation that includes BMI as a variable and “2 or more and 6 or less amino acids including Gly and Tyr” selected from the 19 amino acids using the variable coverage method.
- the range of correlation coefficients for the values is shown.
- FIG. 33 shows the internal organs of a multiple regression equation including “3 or more and 6 or less amino acids including Gly, Tyr and Asn” selected from the above 19 amino acids using a variable coverage method and BMI as variables.
- the range of correlation coefficients for fat area values is shown.
- FIG. 34 shows an internal organ of a multiple regression equation including “3 or more and 6 or less amino acids including Gly, Tyr, and Ala” selected from the above 19 amino acids using the variable coverage method and BMI as variables.
- FIG. 35 shows an internal organ of a multiple regression equation including “3 or more and 6 or less amino acids including Gly, Tyr, and Val” selected from the above 19 amino acids using a variable coverage method and BMI as variables.
- the range of correlation coefficients for fat area values is shown.
- FIG. 36 shows an internal organ of a multiple regression equation including “3 or more and 6 or less amino acids including Gly, Tyr, and Trp” selected from the 19 amino acids using the variable coverage method and BMI as variables.
- the range of correlation coefficients for fat area values is shown.
- the multiple regression equation using a plurality of amino acids and BMI as variables in Example 2 was found to have a higher correlation coefficient than in the case of using one amino acid as a variable, and thus the visceral fat area was higher. It proved useful for the evaluation of the value status.
- FIG. 38 shows an OGTT at 120 minutes of a multiple regression equation including “two or more and six or less amino acids including Gly and Tyr” selected from the above 19 amino acids using the variable coverage method as a variable.
- the range of correlation coefficients for the insulin values is shown.
- FIG. 39 shows an OGTT of 120, which is a multiple regression equation including “three or more and six or less amino acids including Gly, Tyr, and Asn” selected from the above 19 amino acids using a variable coverage method as a variable.
- a range of correlation coefficients for insulin values in minutes is shown.
- FIG. 40 shows an OGTT of 120, which is a multiple regression equation including “three or more and six or less amino acids including Gly, Tyr, and Ala” selected from the above 19 amino acids using a variable coverage method as a variable. A range of correlation coefficients for insulin values in minutes is shown.
- FIG. 41 shows an OGTT of 120 using a multiple regression equation including “three or more and six or less amino acids including Gly, Tyr, and Val” selected from the above 19 amino acids using a variable coverage method as a variable. A range of correlation coefficients for insulin values in minutes is shown.
- FIG. 120 is a multiple regression equation including “three or more and six or less amino acids including Gly, Tyr, and Val” selected from the above 19 amino acids using a variable coverage method as a variable.
- FIG. 42 shows an OGTT of 120, which is a multiple regression equation including “3 or more and 6 or less amino acids including Gly, Tyr, and Trp” selected from the 19 amino acids using a variable coverage method as a variable.
- a range of correlation coefficients for insulin values in minutes is shown.
- FIG. 43 shows an OGTT of a multiple regression equation including, as a variable, “4 or more and 6 or less amino acids including Gly, Tyr, Asn, and Ala” selected from the above 19 amino acids using the variable coverage method.
- the range of correlation coefficients for the insulin value at 120 minutes is shown.
- Example 2 The sample data used in Example 2 was used.
- whether or not it is fatty liver of the logistic regression equation including “two or more and six or less amino acids including Gly and Tyr” selected from the above 19 amino acids using the variable coverage method as a variable The range of ROC_AUC that is an index when evaluating the discriminability regarding the discrimination of whether or not is shown.
- a logistic regression equation including “3 or more and 6 or less amino acids including Gly, Tyr, and Asn” selected from the above 19 amino acids using a variable coverage method as a variable is shown for fatty liver.
- the range of ROC_AUC that serves as an index when evaluating the discriminability regarding whether or not there is is shown.
- a logistic regression equation including “3 or more and 6 or less amino acids including Gly, Tyr, and Ala” selected as a variable from the above 19 kinds of amino acids using the variable coverage method is shown for fatty liver.
- the range of ROC_AUC that serves as an index when evaluating the discriminability regarding whether or not there is is shown.
- a logistic regression equation including “3 or more and 6 or less amino acids including Gly, Tyr, and Val” selected from the above 19 amino acids using a variable coverage method as a variable is shown for fatty liver.
- the range of ROC_AUC that serves as an index when evaluating the discriminability regarding whether or not there is is shown.
- a logistic regression equation including “3 or more and 6 or less amino acids including Gly, Tyr, and Trp” selected from the 19 types of amino acids using a variable coverage method as a variable is shown for fatty liver.
- the range of ROC_AUC that serves as an index when evaluating the discriminability regarding whether or not there is is shown.
- the range of ROC_AUC that is an index when evaluating the discriminating ability regarding the discrimination of whether or not the liver is shown is shown.
- Example 2 The sample data used in Example 2 was used. About the insulin value at 120 minutes of OGTT using the variable coverage method from the four amino acids of Gly, Tyr, Asn, and Ala, and 15 amino acids obtained by removing the four amino acids from the 19 amino acids. The degree of freedom is adjusted from a plurality of multiple regression equations including “two amino acids” selected from the viewpoint of the correlation of the two as variables and the p-value in the likelihood ratio test of the covariate (age) being greater than 0.05. As a result of selecting the multiple regression equation having the highest determined coefficient, the following index formula 1 was selected.
- Index formula 1 “a 1 ⁇ Asn + b 1 ⁇ Gly + c 1 ⁇ Ala + d 1 ⁇ Val + e 1 ⁇ Tyr + f 1 ⁇ Trp + g 1 ”
- Index formula 2 “a 2 ⁇ Asn + b 2 ⁇ Gly + c 2 ⁇ Ala + d 2 ⁇ Val + e 2 ⁇ Tyr + f 2 ⁇ Trp + g 2 ⁇ BMI + h 2 ”
- Index formula 3 “a 3 ⁇ Asn + b 3 ⁇ Gly + c 3 ⁇ Ala + d 3 ⁇ Cit + e 3 ⁇ Leu + f 3 ⁇ Tyr + g 3 ” ⁇
- a 1, b 1, c 1, d 1, e 1, f 1 is a real number not zero
- g 1 is a real number.
- index formula 2 a 2, b 2, c 2, d 2, e 2, f 2, g 2 are real numbers not zero, h 2 are real numbers. * In index formula 3, a 3 , b 3 , c 3 , d 3 , e 3 , and f 3 are non-zero real numbers, and g 3 is a real number.
- index formulas 1, 2, and 3 are useful indexes with high evaluation ability.
- the value of each coefficient in the index formulas 1, 2, and 3 may be a real number multiple thereof, and the value of the constant term in the index formulas 1, 2, and 3 is obtained by adding / subtracting / multiplying an arbitrary real constant to it. It may be a thing.
- FIG. 51 shows ROC_AUC that is an index for evaluating the discriminability of index formulas 1, 2, and 3 for determining whether or not the visceral fat area value is equal to or greater than the reference value (100 cm 2 ), and 120 minutes of OGTT.
- ROC_AUC that serves as an index for evaluating the discriminability of index formulas 1, 2, and 3 for discriminating whether or not the insulin value at the time is greater than or equal to the reference value (40 ⁇ U / ml), and whether or not it is fatty liver ROC_AUC that is an index for evaluating the discriminability of index formulas 1, 2, and 3 relating to discrimination is shown.
- Example 1 The sample data used in Example 1 was used. Subjects who received the insulin resistance index, blood glucose level at 120 minutes of OGTT, and insulin level at 120 minutes of OGTT (the number of relevant criteria of the diagnostic criteria of metabolic syndrome is 0: 361, 1: 335) Person, 2: 272, 3: 158, 4: 34, totaling 1160.) Correlation analysis was performed between the value of index formula 1 and the corresponding number of diagnostic criteria items of metabolic syndrome. Examination subjects who have acquired visceral fat area values (the number of corresponding criteria of metabolic syndrome is 0: 255, 1: 244, 2: 220, 3, 119, 4: 27) (A total of 865 people) was subjected to a correlation analysis between the value of index formula 2 and the corresponding number of diagnostic criteria items of metabolic syndrome.
- the diagnostic criteria items for metabolic syndrome are the following items 1 to 4, and the diagnostic criteria are “when the following items 1 are met, and when at least two of the following items 2 to 4 are met, the diagnosis is metabolic syndrome” It is said that.
- Item 1 “Waist is 85 cm or more in the case of men and 90 cm or more in the case of women” (an indication that the visceral fat area value is 100 cm 2 or more) or “BMI is 25 or more”
- Item 2 “Neutral fat (triglyceride) is 150 mg / dl or more” and / or “HDL cholesterol is less than 40 mg / dl”
- Item 3 “systolic blood pressure is 130 mmHg or more” and / or “diastolic blood pressure is 85 mmHg or more”
- Item 4 “Fasting blood glucose is 110 mg / dl or more”
- index formulas 1, 2, and 3 increases stepwise as the number of corresponding metabolic syndrome diagnosis criteria items increases.
- the values of index formulas 1, 2, and 3 in terms of numbers were significant by the Kruskal-Wallis test and Dunns test.
- index formulas 1, 2, and 3 can evaluate the number of relevant metabolic syndrome diagnostic criteria items.
- Example 1 The sample data used in Example 1 was used. Subjects who received insulin resistance index, blood glucose level at 120 minutes of OGTT, and insulin level at 120 minutes of OGTT (the number of lifestyle diseases was 0: 368, 1: 430, 2: 263, 3:77, 4:22, 1160 in total.) The value of index formula 1 and the number of lifestyle-related diseases (having diseases that fall under lifestyle-related diseases) Analysis). Patients who have acquired visceral fat area values (the number of lifestyle-related diseases is 0: 266, 1: 318, 2: 205, 3: 58, 4: 18) 865 people)) was subjected to a correlation analysis between the value of index formula 2 and the number of lifestyle diseases.
- Example 10 Patients who have been diagnosed for fatty liver (the number of lifestyle-related diseases is 0: 1527, 1: 1503, 2: 827, 3: 255, 4: 48) (A total of 4160 people) was subjected to a correlation analysis between the value of index formula 3 and the number of lifestyle diseases.
- five diseases of chronic nephropathy, hyperuricemia, hypertension, dyslipidemia, and glucose metabolism disorder were considered as diseases corresponding to lifestyle-related diseases.
- the diagnostic criteria for chronic nephropathy is “when the estimated glomerular filtration rate (eGFR) is less than 60, a diagnosis of chronic nephropathy is made”.
- the diagnostic criteria for hyperuricemia is that “when the uric acid level is 7 mg / dL or more, hyperuricemia is diagnosed”.
- the diagnostic criteria for hypertension is that “when hypertensive is diagnosed when systolic blood pressure is 140 mmHg or higher or diastolic blood pressure is 90 mmHg or higher”.
- Diagnosis criteria for dyslipidemia are as follows: “Dyslipidemia is diagnosed when triglyceride (TG) is 150 mg / dL or more, HDL cholesterol is less than 40 mg / dL, or LDL cholesterol is 140 mg / dL or more. It is said.
- the diagnostic criteria for a glucose metabolism disorder are “diagnosis of a glucose metabolism disorder when fasting blood glucose is 126 mg / dL or more or HbA1c (JDS) is 6.1% or more”.
- the value of the index formulas 1, 2, and 3 increases stepwise as the number of lifestyle-related diseases increases.
- the values of the index formulas 1, 2, and 3 were significant in the Kruskal-Wallis test and Dunns test.
- Example 1 The sample data used in Example 1 was used. Subjects who received insulin resistance index, blood glucose level at 120 minutes of OGTT, and insulin value at 120 minutes of OGTT Diabetes: 256 people, chronic nephropathy: 142 people, small arteriosclerosis: 68 people, stroke: 25 people, myocardial infarction: 8 people) To 6. The discriminating ability of the index formula 1 relating to the discrimination shown in FIG. The number of examinees who received visceral fat area values (the number of examinees who received a definitive diagnosis of diabetes was 135, borderline diabetes: 187, chronic nephropathy: 126, small arteriosclerosis: 67 Stroke: 23 people, myocardial infarction: 8 people) To 6.
- the discriminating ability of the index formula 2 relating to the discrimination shown in FIG. The number of examinees who have been diagnosed with fatty liver (the number of those who have received a definitive diagnosis of diabetes is 394, borderline diabetes: 243, chronic nephropathy: 452, small arteriosclerosis: 201, stroke: 64, myocardial infarction: 16) To 6.
- a diagnosis of diabetes is received Borderline diabetes (specifically, impaired glucose tolerance (blood glucose level at 120 g of 75 gOGTT is 140 mg / dl or more and 199 mg / dl or less) and / or fasting blood glucose abnormality (fasting blood glucose level is 110 mg / dl) 2. whether or not a definitive diagnosis has been received)). 3. Determining whether or not a definitive diagnosis of chronic nephropathy has been received 4. Determining whether or not a definitive diagnosis of small arteriosclerosis has been received 5. Determining whether or not a definite diagnosis of a stroke has been received Determining whether or not you have received a definitive diagnosis of myocardial infarction
- ROC_AUC that is an index for evaluating the discriminating ability of index formulas 1, 2, and 3 for discrimination of diabetes, borderline diabetes, chronic nephropathy, microarteriosclerosis, stroke, and myocardial infarction is shown. It is shown.
- the index formulas 1, 2, and 3 indicate not only the status of lifestyle-related diseases such as visceral fat area, insulin, and fatty liver, but also diabetes, borderline diabetes, chronic nephropathy, microarteriosclerosis, stroke It was also found that lifestyle diseases such as myocardial infarction can also be evaluated.
- Example 1 Of the sample data used in Example 1, subjects (2996 people) who had received a medical checkup for 5 consecutive years were targeted. From the subject examinee, the following 1. To 15. For each disease event shown in Fig. 1, subjects who did not have a disease event in the first year were extracted. For each disease event, the values of index formulas 1, 2, and 3 were calculated using the extracted sample data of the examinees. For each disease event and each index formula 1, 2, 3, the quintile ("1st Quintile”, “2nd Quintile”, “3rd Quintile”, “4th Quintile", and "5th Quintile") in ascending order of the calculated values. And class divided into five).
- the disease event occurrence rate (absolute risk and relative risk) was calculated by the human year method, and the calculated values were compared. In addition, the presence or absence of a disease event was judged based on the following diagnostic criteria.
- Relative risk “n-th Quintile” disease event rate / “1st Quintile” disease event rate
- Diabetes Diabetes is diagnosed if any of items 1 to 3 below and item 4 are confirmed.
- Item 1 Early morning fasting blood glucose level is 126 mg / dL or higher
- Item 2 Blood glucose level at 120 g of 75 g OGTT is 200 mg / dL or higher
- Item 3 Blood glucose level is 200 mg / dL or higher at any time
- Item 4 HbA1C (JDS value) is 6.1 % Or more [HbA1C (international standard value) is 6.5% or more] 7).
- HbA1C JDS value
- HbA1C international standard value
- Obesity When the waist is 85 cm or more for men and 90 cm or more for women (an indication that the visceral fat area value is 100 cm 2 or more) or “BMI is 25 or more” Diagnosed as obesity. 9. Severe obesity * If BMI is 30 or more, severe obesity is diagnosed. 10. Dyslipidemia * A diagnosis of dyslipidemia is made when “triglyceride (TG) is 150 mg / dL or more, HDL cholesterol is less than 40 mg / dL, or LDL cholesterol is 140 mg / dL or more”.
- Chronic nephropathy Chronic nephropathy is diagnosed when the estimated glomerular filtration rate (eGFR) is less than 60.
- Arteriosclerosis When sclerosis is observed in the arteriosclerosis dock, it is diagnosed as arteriosclerosis.
- Cerebral infarction When cerebral infarction is observed by head MRI and MRA, cerebral infarction is diagnosed.
- Risk of heart disease If the Minnesota code is outside the normal range, the patient is diagnosed as having heart disease risk. 15. Metabolic Syndrome * In the case of corresponding to the following item 1, a metabolic syndrome is diagnosed when corresponding to at least two of the following items 2 to 4.
- Item 1 “Waist is 85 cm or more in the case of men and 90 cm or more in the case of women” (an indication that the visceral fat area value is 100 cm 2 or more) or “BMI is 25 or more”
- Item 2 “Neutral fat (triglyceride) is 150 mg / dl or more” and / or “HDL cholesterol is less than 40 mg / dl”
- Item 3 “systolic blood pressure is 130 mmHg or more” and / or “diastolic blood pressure is 85 mmHg or more”
- Item 4 Fasting blood glucose is 110 mg / dl or more.
- 60 to 74 show the number of patients who have not had a disease event in the first year (“number of people”), the total number of observation years (“person year”), the number of disease event occurrences (“number of events”), relative Risk, upper limit of 95% confidence interval of relative risk, and lower limit of 95% confidence interval of relative risk are shown.
- “*” indicates that the calculated value of the relative risk is significant.
- “-” indicates that there is no calculated value of relative risk because the number of events of “1st Quintile” is 0.
- the absolute risk of “5th Quintile” in index formula 2 is significant with respect to the absolute risk of “1st Quintile” in index formula 2.
- the absolute risk of “2nd Quintile”, “3rd Quintile”, “4th Quintile”, and “5th Quintile” of Index Formula 2 is significant with respect to the absolute risk of “1st Quintile” of Index Formula 2.
- the method for evaluating a lifestyle-related disease index according to the present invention can be widely implemented in many industrial fields, particularly in fields such as pharmaceuticals, foods, and medical care. This is extremely useful for evaluating the condition.
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Abstract
Description
(略称) (正式名称)
Ala Alanine
Arg Arginine
Asn Asparagine
Cit Citrulline
Gln Glutamine
Gly Glycine
His Histidine
Ile Isoleucine
Leu Leucine
Lys Lysine
Met Methionine
Orn Ornithine
Phe Phenylalanine
Pro Proline
Ser Serine
Thr Threonine
Trp Tryptophan
Tyr Tyrosine
Val Valine
なお、本発明によれば、GlyおよびTyrのアミノ酸の濃度値、および、GlyおよびTyrのアミノ酸の濃度値が代入される変数を含む式を用いて、式の値を算出することで、評価対象について生活習慣病の指標の状態を評価してもよい。
なお、本発明によれば、「Gly、Tyr、およびAsnのアミノ酸の濃度値、および、Gly、Tyr、およびAsnのアミノ酸の濃度値が代入される変数を含む式」、「Gly、Tyr、およびAlaのアミノ酸の濃度値、および、Gly、Tyr、およびAlaのアミノ酸の濃度値が代入される変数を含む式」、「Gly、Tyr、およびValのアミノ酸の濃度値、および、Gly、Tyr、およびValのアミノ酸の濃度値が代入される変数を含む式」、または「Gly、Tyr、およびTrpのアミノ酸の濃度値、および、Gly、Tyr、およびTrpのアミノ酸の濃度値が代入される変数を含む式」を用いて、式の値を算出することで、評価対象について生活習慣病の指標の状態を評価してもよい。
なお、本発明によれば、Gly、Tyr、Asn、およびAlaのアミノ酸の濃度値、および、Gly、Tyr、Asn、およびAlaのアミノ酸の濃度値が代入される変数を含む式を用いて、式の値を算出することで、評価対象について生活習慣病の指標の状態を評価してもよい。
なお、本発明によれば、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値を用いて、インスリンの状態を評価してもよい。
なお、本発明によれば、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値、または、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値および予め取得した評価対象のBMI値を用いて、内臓脂肪の状態を評価してもよい。
なお、本発明によれば、Gly、Tyr、Asn、Ala、Cit、およびLeuのアミノ酸の濃度値を用いて、脂肪肝の状態を評価してもよい。
なお、本発明によれば、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値を用いて、インスリンおよび内臓脂肪の状態を評価してもよい。
なお、本発明によれば、(i)Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値を用いて、インスリンの状態を評価し、(ii)Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値、または、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値および予め取得した評価対象のBMI値を用いて、内臓脂肪の状態を評価し、(iii)Gly、Tyr、Asn、Ala、Cit、およびLeuのアミノ酸の濃度値を用いて、脂肪肝の状態を評価してもよい。
また、本発明によれば、評価対象における生活習慣病の指標の状態の程度を定性的に評価するとは、「アミノ酸の濃度値および予め設定された1つまたは複数の閾値」または「アミノ酸の濃度値、アミノ酸の濃度値が代入される変数を含む式、および予め設定された1つまたは複数の閾値」を用いて、評価対象を、生活習慣病の指標の状態の程度を少なくとも考慮して定義された複数の区分のうちのどれか1つに分類すること、でもよい。これにより、生活習慣病の指標の状態の程度を知る上で参考となり得る信頼性の高い情報を、理解し易い形で提供することができる。
また、本発明によれば、評価対象における生活習慣病の指標の状態の程度を定量的に評価するとは、生活習慣病の指標が連続的な数値で計測可能なものである場合に、アミノ酸の濃度値、および、アミノ酸の濃度値が代入される変数を含む式を用いて、評価対象における生活習慣病の指標の値を推定すること、でもよい。これにより、生活習慣病の指標の値を知る上で参考となり得る信頼性の高い数値情報を提供することができる。
また、本発明によれば、式の値を所定の手法で変換し、変換後の値を用いて評価対象を複数の区分のうちのどれか1つに分類したり、評価対象における生活習慣病の指標の値を推定したりしてもよい。これにより、生活習慣病の指標の状態の程度を知る上で参考となり得る信頼性の高い情報を、更に理解し易い形で提供することができたり、生活習慣病の指標の値を知る上で参考となり得る数値情報の更なる信頼性向上を実現できたりする。
また、本発明によれば、評価対象におけるインスリンの量の程度を定性的に評価するとは、「アミノ酸の濃度値および予め設定された1つまたは複数の閾値」または「アミノ酸の濃度値、アミノ酸の濃度値が代入される変数を含む式、および予め設定した1つまたは複数の閾値」を用いて、評価対象を、インスリンの量の程度を少なくとも考慮して定義された複数の区分のうちのどれか1つに分類すること、でもよい。これにより、インスリンの量の程度を知る上で参考となり得る信頼性の高い情報を、理解し易い形で提供することができる。なお、複数の区分には、インスリンの量(例えばOGTT(経口糖負荷試験)の120分時のインスリン値(OGTT後のインスリン値)など)が大である対象を属させるための区分、インスリンの量(例えばOGTTの120分時のインスリン値など)が小である対象を属させるための区分、およびインスリンの量(例えばOGTTの120分時のインスリン値など)が中である対象を属させるための区分が含まれていてもよい。また、複数の区分には、インスリンの量(例えばOGTTの120分時のインスリン値など)が基準値(例えば40μU/mlなど)以上である対象を属させるための区分およびインスリンの量(例えばOGTTの120分時のインスリン値など)が基準値(例えば40μU/mlなど)以下である対象を属させるための区分が含まれていてもよい。また、複数の区分には、OGTTの120分時のインスリン値が40μU/ml以上である可能性が高い対象を属させるための区分、前記可能性が低い対象を属させるための区分、および前記可能性が中程度である対象を属させるための区分が含まれていてもよい。また、複数の区分には、OGTTの120分時のインスリン値が40μU/ml以上である可能性が高い対象を属させるための区分、および、前記可能性が低い対象を属させるための区分が含まれていてもよい。
また、本発明によれば、評価対象におけるインスリンの量の程度を定量的に評価するとは、アミノ酸の濃度値、および、アミノ酸の濃度値が代入される変数を含む式を用いて、評価対象におけるインスリンの量を推定すること、でもよい。これにより、インスリンの量を知る上で参考となり得る信頼性の高い数値情報を提供することができる。
また、本発明によれば、式の値を所定の手法で変換し、変換後の値を用いて、評価対象を複数の区分のうちのどれか1つに分類したり、評価対象におけるインスリンの量を推定したりしてもよい。これにより、インスリンの量の程度を知る上で参考となり得る信頼性の高い情報を、更に理解し易い形で提供することができたり、インスリンの量を知る上で参考となり得る数値情報の更なる信頼性向上を実現できたりする。
また、本発明によれば、評価対象における内臓脂肪の量の程度を定性的に評価するとは、「アミノ酸の濃度値および予め設定された1つまたは複数の閾値」または「アミノ酸の濃度値、アミノ酸の濃度値が代入される変数を含む式、および予め設定した1つまたは複数の閾値」を用いて、評価対象を、内臓脂肪の量の程度を少なくとも考慮して定義された複数の区分のうちのどれか1つに分類すること、でもよい。これにより、内臓脂肪の量の程度を知る上で参考となり得る信頼性の高い情報を、理解し易い形で提供することができる。なお、複数の区分には、内臓脂肪の量(例えば内臓脂肪面積値など)が大である対象を属させるための区分、内臓脂肪の量(例えば内臓脂肪面積値など)が小である対象を属させるための区分、および内臓脂肪の量(例えば内臓脂肪面積値など)が中である対象を属させるための区分が含まれていてもよい。また、複数の区分には、内臓脂肪の量(例えば内臓脂肪面積値など)が基準値(例えば100cm2など)以上である対象を属させるための区分および内臓脂肪の量(例えば内臓脂肪面積値など)が基準値(例えば100cm2など)以下である対象を属させるための区分が含まれていてもよい。また、複数の区分には、内臓脂肪面積値が100cm2以上である可能性が高い対象を属させるための区分、前記可能性が低い対象を属させるための区分、および前記可能性が中程度である対象を属させるための区分が含まれていてもよい。また、複数の区分には、内臓脂肪面積値が100cm2以上である可能性が高い対象を属させるための区分、および、前記可能性が低い対象を属させるための区分が含まれていてもよい。
また、本発明によれば、評価対象における内臓脂肪の量の程度を定量的に評価するとは、アミノ酸の濃度値、および、アミノ酸の濃度値が代入される変数を含む式を用いて、評価対象における内臓脂肪の量を推定すること、でもよい。これにより、内臓脂肪の量を知る上で参考となり得る信頼性の高い数値情報を提供することができる。
また、本発明によれば、式の値を所定の手法で変換し、変換後の値を用いて、評価対象を複数の区分のうちのどれか1つに分類したり、評価対象における内臓脂肪の量を推定したりしてもよい。これにより、内臓脂肪の量の程度を知る上で参考となり得る信頼性の高い情報を、更に理解し易い形で提供することができたり、内臓脂肪の量を知る上で参考となり得る数値情報の更なる信頼性向上を実現できたりする。
また、本発明によれば、内臓脂肪の量を評価する際、評価対象のBMI値や、BMI値が代入される変数をさらに含む式をさらに用いてもよい。これにより、内臓脂肪の量の程度を知る上で参考となり得る情報の更なる信頼性向上を実現することができる。
また、本発明によれば、評価対象の肝臓が一定量以上の脂肪を有した状態となっている可能性の程度を評価するとは、「アミノ酸の濃度値および予め設定した1つまたは複数の閾値」または「アミノ酸の濃度値、アミノ酸の濃度値が代入される変数を含む式、および予め設定した1つまたは複数の閾値」を用いて、評価対象を、肝臓が前記状態となっている可能性の程度を少なくとも考慮して定義された複数の区分のうちのどれか1つに分類すること、でもよい。これにより、肝臓が一定量以上の脂肪を有した状態となっている可能性の程度を知る上で参考となり得る信頼性の高い情報を、理解し易い形で提供することができる。なお、複数の区分には、肝臓が前記状態となっている可能性が高い対象を属させるための区分、肝臓が前記状態となっている可能性が低い対象を属させるための区分、および肝臓が前記状態となっている可能性が中程度である対象を属させるための区分が含まれていてもよい。また、複数の区分には、肝臓が前記状態となっている可能性が高い対象を属させるための区分、および、肝臓が前記状態となっている可能性が低い対象を属させるための区分が含まれていてもよい。
また、本発明によれば、式の値を所定の手法で変換し、変換後の値を用いて評価対象を複数の区分のうちのどれか1つに分類してもよい。これにより、肝臓が一定量以上の脂肪を有した状態となっている可能性の程度を知る上で参考となり得る信頼性の高い情報を、更に理解し易い形で提供することができる。
a1×Asn+b1×Gly+c1×Ala+d1×Val+e1×Tyr+f1×Trp+g1 ・・・(式1)
a2×Asn+b2×Gly+c2×Ala+d2×Val+e2×Tyr+f2×Trp+g2×BMI+h2 ・・・(式2)
a3×Asn+b3×Gly+c3×Ala+d3×Cit+e3×Leu+f3×Tyr+g3 ・・・(式3)
式1において、a1,b1,c1,d1,e1,f1はゼロではない任意の実数であり、g1は任意の実数である。
式2において、a2,b2,c2,d2,e2,f2,g2はゼロではない任意の実数であり、h2は任意の実数である。
式3において、a3,b3,c3,d3,e3,f3はゼロではない任意の実数であり、g3は任意の実数である。
1.アミノ酸以外の他の血中の代謝物(アミノ酸代謝物・糖類・脂質等)、タンパク質、ペプチド、ミネラル、ホルモン等の濃度値
2.アルブミン、総蛋白、トリグリセリド、HbA1c、糖化アルブミン、インスリン抵抗性指数、総コレステロール、LDLコレステロール、HDLコレステロール、アミラーゼ、総ビリルビン、クレアチニン、推算糸球体濾過量(eGFR)、尿酸等の血液検査値
3.超音波エコー、X線、CT、MRI等の画像情報から得られる値
4.年齢、身長、体重、BMI、腹囲、収縮期血圧、拡張期血圧、性別、喫煙情報、食事情報、飲酒情報、運動情報、ストレス情報、睡眠情報、家族の既往歴情報、疾患歴情報(糖尿病等)等の生体指標に関する値
また、本発明を利用することにより、生活習慣病の指標を把握することが可能となり、生活習慣病を発症する前段階または生活習慣病の初期段階でリスクを把握することができる。よって、本発明は、生活習慣病を発症するリスク(生活習慣病を発症する可能性の程度)または生活習慣病が今後進行するリスク(生活習慣病が今後進行する可能性の程度)を評価することができ、生活習慣病の予防に繋がる。
また、式1~3で、メタボリックシンドロームの診断基準項目の該当数を評価でき、また、生活習慣病を保有している数を評価できることより、式1~3の値を用いて、生活習慣病の重篤度(生活習慣病の進行度合い(生活習慣病が進行している可能性の程度))を評価することができる。
[1-1.第1実施形態の概要]
ここでは、第1実施形態の概要について図1を参照して説明する。図1は第1実施形態の基本原理を示す原理構成図である。
(A)採取した血液サンプルを遠心することにより血液から血漿を分離した。全ての血漿サンプルは、アミノ酸濃度値の測定時まで-80℃で凍結保存した。アミノ酸濃度値測定時には、アセトニトリルを添加し除蛋白処理を行った後、標識試薬(3-アミノピリジル-N-ヒドロキシスクシンイミジルカルバメート)を用いてプレカラム誘導体化を行い、そして、液体クロマトグラフ質量分析計(LC/MS)によりアミノ酸濃度値を分析した(国際公開第2003/069328号、国際公開第2005/116629号を参照)。
(B)採取した血液サンプルを遠心することにより血液から血漿を分離した。全ての血漿サンプルは、アミノ酸濃度値の測定時まで-80℃で凍結保存した。アミノ酸濃度値測定時には、スルホサリチル酸を添加し除蛋白処理を行った後、ニンヒドリン試薬を用いたポストカラム誘導体化法を原理としたアミノ酸分析計によりアミノ酸濃度値を分析した。
濃度値の取り得る範囲が所定範囲(例えば0.0から1.0までの範囲、0.0から10.0までの範囲、0.0から100.0までの範囲、又は-10.0から10.0までの範囲、など)に収まるように、例えば、濃度値に対して任意の値を加減乗除したり、また、濃度値を所定の変換手法(例えば、指数変換、対数変換、角変換、平方根変換、プロビット変換、又は逆数変換など)で変換したり、また、濃度値に対してこれらの計算を組み合わせて行ったりすることで、濃度値を変換してもよい。例えば、濃度値を指数としネイピア数を底とする指数関数の値(具体的には、生活習慣病の指標が所定の状態(例えば、基準値を超えた状態、など)である確率pを定義したときの自然対数ln(p/(1-p))が濃度値と等しいとした場合におけるp/(1-p)の値)をさらに算出してもよく、また、算出した指数関数の値を1と当該値との和で割った値(具体的には、確率pの値)をさらに算出してもよい。
また、特定の条件のときの変換後の値が特定の値となるように、濃度値を変換してもよい。例えば、感度が80%のときの変換後の値が4.0となり且つ感度が60%のときの変換後の値が8.0となるように濃度値を変換してもよい。
評価式の値の取り得る範囲が所定範囲(例えば0.0から1.0までの範囲、0.0から10.0までの範囲、0.0から100.0までの範囲、又は-10.0から10.0までの範囲、など)に収まるように、例えば、評価式の値に対して任意の値を加減乗除したり、また、評価式の値を所定の変換手法(例えば、指数変換、対数変換、角変換、平方根変換、プロビット変換、又は逆数変換など)で変換したり、また、評価式の値に対してこれらの計算を組み合わせて行ったりすることで、評価式の値を変換してもよい。例えば、評価式の値を指数としネイピア数を底とする指数関数の値(具体的には、生活習慣病の指標が所定の状態(例えば、基準値を超えた状態、など)である確率pを定義したときの自然対数ln(p/(1-p))が評価式の値と等しいとした場合におけるp/(1-p)の値)をさらに算出してもよく、また、算出した指数関数の値を1と当該値との和で割った値(具体的には、確率pの値)をさらに算出してもよい。
また、特定の条件のときの変換後の値が特定の値となるように、評価式の値を変換してもよい。例えば、感度が80%のときの変換後の値が4.0となり且つ感度が60%のときの変換後の値が8.0となるように評価式の値を変換してもよい。
なお、本明細書における評価値は、評価式の値そのものであってもよく、評価式の値を変換した後の値であってもよい。
また、ステップS12では、「アミノ酸の濃度値および予め設定された1つまたは複数の閾値」または「アミノ酸の濃度値、アミノ酸の濃度値が代入される変数を含む式、および予め設定された1つまたは複数の閾値」を用いて、評価対象を、生活習慣病の指標の状態の程度を少なくとも考慮して定義された複数の区分のうちのどれか1つに分類してもよい。
また、ステップS12では、生活習慣病の指標が連続的な数値で計測可能なものである場合に、アミノ酸の濃度値、および、アミノ酸の濃度値が代入される変数を含む式を用いて、評価対象における生活習慣病の指標の値を推定してもよい。
また、ステップS12では、濃度値又は式の値を所定の手法で変換し、変換後の値を用いて評価対象を複数の区分のうちのどれか1つに分類したり、評価対象における生活習慣病の指標の値を推定したりしてもよい。
また、ステップS12では、「アミノ酸の濃度値および予め設定された1つまたは複数の閾値」または「アミノ酸の濃度値、アミノ酸の濃度値が代入される変数を含む式、および予め設定した1つまたは複数の閾値」を用いて、評価対象を、インスリンの量の程度を少なくとも考慮して定義された複数の区分のうちのどれか1つに分類してもよい。なお、複数の区分には、インスリンの量(例えばOGTTの120分時のインスリン値など)が大である対象を属させるための区分、インスリンの量(例えばOGTTの120分時のインスリン値など)が小である対象を属させるための区分、およびインスリンの量(例えばOGTTの120分時のインスリン値など)が中である対象を属させるための区分が含まれていてもよい。また、複数の区分には、インスリンの量(例えばOGTTの120分時のインスリン値など)が基準値(例えば40μU/mlなど)以上である対象を属させるための区分およびインスリンの量(例えばOGTTの120分時のインスリン値など)が基準値(例えば40μU/mlなど)以下である対象を属させるための区分が含まれていてもよい。また、複数の区分には、OGTTの120分時のインスリン値が40μU/ml以上である可能性が高い対象を属させるための区分、前記可能性が低い対象を属させるための区分、および前記可能性が中程度である対象を属させるための区分が含まれていてもよい。また、複数の区分には、OGTTの120分時のインスリン値が40μU/ml以上である可能性が高い対象を属させるための区分、および、前記可能性が低い対象を属させるための区分が含まれていてもよい。
また、ステップS12では、アミノ酸の濃度値、および、アミノ酸の濃度値が代入される変数を含む式を用いて、評価対象におけるインスリンの量を推定してもよい。
また、ステップS12では、濃度値又は式の値を所定の手法で変換し、変換後の値を用いて、評価対象を複数の区分のうちのどれか1つに分類したり、評価対象におけるインスリンの量を推定したりしてもよい。
また、ステップS12では、「アミノ酸の濃度値および予め設定された1つまたは複数の閾値」または「アミノ酸の濃度値、アミノ酸の濃度値が代入される変数を含む式、および予め設定した1つまたは複数の閾値」を用いて、評価対象を、内臓脂肪の量の程度を少なくとも考慮して定義された複数の区分のうちのどれか1つに分類してもよい。なお、複数の区分には、内臓脂肪の量(例えば内臓脂肪面積値など)が大である対象を属させるための区分、内臓脂肪の量(例えば内臓脂肪面積値など)が小である対象を属させるための区分、および内臓脂肪の量(例えば内臓脂肪面積値など)が中である対象を属させるための区分が含まれていてもよい。また、複数の区分には、内臓脂肪の量(例えば内臓脂肪面積値など)が基準値(例えば100cm2など)以上である対象を属させるための区分および内臓脂肪の量(例えば内臓脂肪面積値など)が基準値(例えば100cm2など)以下である対象を属させるための区分が含まれていてもよい。また、複数の区分には、内臓脂肪面積値が100cm2以上である可能性が高い対象を属させるための区分、前記可能性が低い対象を属させるための区分、および前記可能性が中程度である対象を属させるための区分が含まれていてもよい。また、複数の区分には、内臓脂肪面積値が100cm2以上である可能性が高い対象を属させるための区分、および、前記可能性が低い対象を属させるための区分が含まれていてもよい。
また、ステップS12では、アミノ酸の濃度値、および、アミノ酸の濃度値が代入される変数を含む式を用いて、評価対象における内臓脂肪の量を推定してもよい。
また、ステップS12では、濃度値又は式の値を所定の手法で変換し、変換後の値を用いて、評価対象を複数の区分のうちのどれか1つに分類したり、評価対象における内臓脂肪の量を推定したりしてもよい。
なお、分類又は推定を行う際には、評価対象のBMI値や、BMI値が代入される変数をさらに含む式をさらに用いてもよい。
また、ステップS12では、「アミノ酸の濃度値および予め設定した1つまたは複数の閾値」または「アミノ酸の濃度値、アミノ酸の濃度値が代入される変数を含む式、および予め設定した1つまたは複数の閾値」を用いて、評価対象を、肝臓が前記状態となっている可能性の程度を少なくとも考慮して定義された複数の区分のうちのどれか1つに分類してもよい。なお、複数の区分には、肝臓が前記状態となっている可能性が高い対象を属させるための区分、肝臓が前記状態となっている可能性が低い対象を属させるための区分、および肝臓が前記状態となっている可能性が中程度である対象を属させるための区分が含まれていてもよい。また、複数の区分には、肝臓が前記状態となっている可能性が高い対象を属させるための区分、および、肝臓が前記状態となっている可能性が低い対象を属させるための区分が含まれていてもよい。
また、ステップS12では、濃度値又は式の値を所定の手法で変換し、変換後の値を用いて評価対象を複数の区分のうちのどれか1つに分類してもよい。
a1×Asn+b1×Gly+c1×Ala+d1×Val+e1×Tyr+f1×Trp+g1 ・・・(式1)
a2×Asn+b2×Gly+c2×Ala+d2×Val+e2×Tyr+f2×Trp+g2×BMI+h2 ・・・(式2)
a3×Asn+b3×Gly+c3×Ala+d3×Cit+e3×Leu+f3×Tyr+g3 ・・・(式3)
式1において、a1,b1,c1,d1,e1,f1はゼロではない任意の実数であり、g1は任意の実数である。
式2において、a2,b2,c2,d2,e2,f2,g2はゼロではない任意の実数であり、h2は任意の実数である。
式3において、a3,b3,c3,d3,e3,f3はゼロではない任意の実数であり、g3は任意の実数である。
1.アミノ酸以外の他の血中の代謝物(アミノ酸代謝物・糖類・脂質等)、タンパク質、ペプチド、ミネラル、ホルモン等の濃度値
2.アルブミン、総蛋白、トリグリセリド、HbA1c、糖化アルブミン、インスリン抵抗性指数、総コレステロール、LDLコレステロール、HDLコレステロール、アミラーゼ、総ビリルビン、クレアチニン、推算糸球体濾過量(eGFR)、尿酸等の血液検査値
3.超音波エコー、X線、CT、MRI等の画像情報から得られる値
4.年齢、身長、体重、BMI、腹囲、収縮期血圧、拡張期血圧、性別、喫煙情報、食事情報、飲酒情報、運動情報、ストレス情報、睡眠情報、家族の既往歴情報、疾患歴情報(糖尿病等)等の生体指標に関する値
なお、ステップS11を実行する前に、例えば、ヒトに投与可能な既存の薬物・アミノ酸・食品・サプリメントを適宜組み合わせたもの(例えば、生活習慣病の指標の改善に効果があること知られている薬物(例えば、ゲムシタビン、エルロチニブ、TS-1など)などを適宜組み合わせたもの)を、所定の期間(例えば1日から12ヶ月の範囲)にわたり、所定量ずつ所定の頻度・タイミング(例えば1日3回・食後)で、所定の投与方法(例えば経口投与)により投与してもよい。ここで、投与方法や用量、剤形は、病状に応じて適宜組み合わせてもよい。なお、剤形は、公知の技術に基づいて決めてもよい。また、用量は、特に定めは無いが、例えば有効成分として1ugから100gを含有した形態で与えてもよい。
また、投与した物質群が生活習慣病の指標の状態を改善させるものであるという判定結果が得られた場合には、投与した物質群が生活習慣病の指標の状態を改善させる物質として探索されてもよい。なお、この探索方法によって探索された物質群として、例えば、前記19種のアミノ酸のうちの少なくともGlyおよびTyrのアミノ酸を含むアミノ酸群が挙げられる。
また、前記19種類のアミノ酸のうちの少なくともGlyおよびTyrのアミノ酸を含むアミノ酸群の濃度値や評価式の値を正常化させる物質を、第1実施形態の生活習慣病指標の評価方法や第2実施形態の生活習慣病指標評価装置を用いて選択することができる。
また、生活習慣病の指標の状態を改善させる物質を探索するとは、生活習慣病の指標の改善に有効な新規物質を見出すことのみならず、公知物質の生活習慣病の指標の改善用途を新規に見出すことや、生活習慣病の指標の改善に有効性を期待できる既存の薬剤・サプリメント等を組み合わせた新規組成物を見出すことや、上記した適切な用法・用量・組み合わせを見出し、それをキットとすることや、食事・運動等も含めた予防・治療メニューを提示することや、当該予防・治療メニューの効果をモニタリングし、必要に応じて個人ごとにメニューの変更を提示すること等が含まれる。
ここでは、第1実施形態の具体例について図2を参照して説明する。図2は、第1実施形態の具体例を説明するためのフローチャートである。
a1×Asn+b1×Gly+c1×Ala+d1×Val+e1×Tyr+f1×Trp+g1 ・・・(式1)
式1において、a1,b1,c1,d1,e1,f1はゼロではない任意の実数であり、g1は任意の実数である。
a2×Asn+b2×Gly+c2×Ala+d2×Val+e2×Tyr+f2×Trp+g2×BMI+h2 ・・・(式2)
式2において、a2,b2,c2,d2,e2,f2,g2はゼロではない任意の実数であり、h2は任意の実数である。
a3×Asn+b3×Gly+c3×Ala+d3×Cit+e3×Leu+f3×Tyr+g3 ・・・(式3)
式3において、a3,b3,c3,d3,e3,f3はゼロではない任意の実数であり、g3は任意の実数である。
[2-1.第2実施形態の概要]
ここでは、第2実施形態の概要について図3を参照して説明する。図3は第2実施形態の基本原理を示す原理構成図である。
評価式の値の取り得る範囲が所定範囲(例えば0.0から1.0までの範囲、0.0から10.0までの範囲、0.0から100.0までの範囲、又は-10.0から10.0までの範囲、など)に収まるように、例えば、評価式の値に対して任意の値を加減乗除したり、また、評価式の値を所定の変換手法(例えば、指数変換、対数変換、角変換、平方根変換、プロビット変換、又は逆数変換など)で変換したり、また、評価式の値に対してこれらの計算を組み合わせて行ったりすることで、評価式の値を変換してもよい。例えば、評価式の値を指数としネイピア数を底とする指数関数の値(具体的には、生活習慣病の指標が所定の状態(例えば、基準値を超えた状態、など)である確率pを定義したときの自然対数ln(p/(1-p))が評価式の値と等しいとした場合におけるp/(1-p)の値)をさらに算出してもよく、また、算出した指数関数の値を1と当該値との和で割った値(具体的には、確率pの値)をさらに算出してもよい。
また、特定の条件のときの変換後の値が特定の値となるように、評価式の値を変換してもよい。例えば、感度が80%のときの変換後の値が4.0となり且つ感度が60%のときの変換後の値が8.0となるように評価式の値を変換してもよい。
なお、本明細書における評価値は、評価式の値そのものであってもよく、評価式の値を変換した後の値であってもよい。
また、ステップS21では、アミノ酸の濃度値、アミノ酸の濃度値が代入される変数を含む式、および予め設定された1つまたは複数の閾値を用いて、評価対象を、生活習慣病の指標の状態の程度を少なくとも考慮して定義された複数の区分のうちのどれか1つに分類してもよい。
また、ステップS21では、生活習慣病の指標が連続的な数値で計測可能なものである場合に、アミノ酸の濃度値、および、アミノ酸の濃度値が代入される変数を含む式を用いて、評価対象における生活習慣病の指標の値を推定してもよい。
また、ステップS21では、式の値を所定の手法で変換し、変換後の値を用いて評価対象を複数の区分のうちのどれか1つに分類したり、評価対象における生活習慣病の指標の値を推定したりしてもよい。
また、ステップS21では、アミノ酸の濃度値、アミノ酸の濃度値が代入される変数を含む式、および予め設定した1つまたは複数の閾値を用いて、評価対象を、インスリンの量の程度を少なくとも考慮して定義された複数の区分のうちのどれか1つに分類してもよい。なお、複数の区分には、インスリンの量(例えばOGTTの120分時のインスリン値など)が大である対象を属させるための区分、インスリンの量(例えばOGTTの120分時のインスリン値など)が小である対象を属させるための区分、およびインスリンの量(例えばOGTTの120分時のインスリン値など)が中である対象を属させるための区分が含まれていてもよい。また、複数の区分には、インスリンの量(例えばOGTTの120分時のインスリン値など)が基準値(例えば40μU/mlなど)以上である対象を属させるための区分およびインスリンの量(例えばOGTTの120分時のインスリン値など)が基準値(例えば40μU/mlなど)以下である対象を属させるための区分が含まれていてもよい。また、複数の区分には、OGTTの120分時のインスリン値が40μU/ml以上である可能性が高い対象を属させるための区分、前記可能性が低い対象を属させるための区分、および前記可能性が中程度である対象を属させるための区分が含まれていてもよい。また、複数の区分には、OGTTの120分時のインスリン値が40μU/ml以上である可能性が高い対象を属させるための区分、および、前記可能性が低い対象を属させるための区分が含まれていてもよい。
また、ステップS21では、アミノ酸の濃度値、および、アミノ酸の濃度値が代入される変数を含む式を用いて、評価対象におけるインスリンの量を推定してもよい。
また、ステップS21では、式の値を所定の手法で変換し、変換後の値を用いて、評価対象を複数の区分のうちのどれか1つに分類したり、評価対象におけるインスリンの量を推定したりしてもよい。
また、ステップS21では、アミノ酸の濃度値、アミノ酸の濃度値が代入される変数を含む式、および予め設定した1つまたは複数の閾値を用いて、評価対象を、内臓脂肪の量の程度を少なくとも考慮して定義された複数の区分のうちのどれか1つに分類してもよい。なお、複数の区分には、内臓脂肪の量(例えば内臓脂肪面積値など)が大である対象を属させるための区分、内臓脂肪の量(例えば内臓脂肪面積値など)が小である対象を属させるための区分、および内臓脂肪の量(例えば内臓脂肪面積値など)が中である対象を属させるための区分が含まれていてもよい。また、複数の区分には、内臓脂肪の量(例えば内臓脂肪面積値など)が基準値(例えば100cm2など)以上である対象を属させるための区分および内臓脂肪の量(例えば内臓脂肪面積値など)が基準値(例えば100cm2など)以下である対象を属させるための区分が含まれていてもよい。また、複数の区分には、内臓脂肪面積値が100cm2以上である可能性が高い対象を属させるための区分、前記可能性が低い対象を属させるための区分、および前記可能性が中程度である対象を属させるための区分が含まれていてもよい。また、複数の区分には、内臓脂肪面積値が100cm2以上である可能性が高い対象を属させるための区分、および、前記可能性が低い対象を属させるための区分が含まれていてもよい。
また、ステップS21では、アミノ酸の濃度値、および、アミノ酸の濃度値が代入される変数を含む式を用いて、評価対象における内臓脂肪の量を推定してもよい。
また、ステップS21では、式の値を所定の手法で変換し、変換後の値を用いて、評価対象を複数の区分のうちのどれか1つに分類したり、評価対象における内臓脂肪の量を推定したりしてもよい。
なお、分類又は推定を行う際には、評価対象のBMI値や、BMI値が代入される変数をさらに含む式をさらに用いてもよい。
また、ステップS21では、アミノ酸の濃度値、アミノ酸の濃度値が代入される変数を含む式、および予め設定した1つまたは複数の閾値を用いて、評価対象を、肝臓が前記状態となっている可能性の程度を少なくとも考慮して定義された複数の区分のうちのどれか1つに分類してもよい。なお、複数の区分には、肝臓が前記状態となっている可能性が高い対象を属させるための区分、肝臓が前記状態となっている可能性が低い対象を属させるための区分、および肝臓が前記状態となっている可能性が中程度である対象を属させるための区分が含まれていてもよい。また、複数の区分には、肝臓が前記状態となっている可能性が高い対象を属させるための区分、および、肝臓が前記状態となっている可能性が低い対象を属させるための区分が含まれていてもよい。
また、ステップS21では、式の値を所定の手法で変換し、変換後の値を用いて評価対象を複数の区分のうちのどれか1つに分類してもよい。
a1×Asn+b1×Gly+c1×Ala+d1×Val+e1×Tyr+f1×Trp+g1 ・・・(式1)
a2×Asn+b2×Gly+c2×Ala+d2×Val+e2×Tyr+f2×Trp+g2×BMI+h2 ・・・(式2)
a3×Asn+b3×Gly+c3×Ala+d3×Cit+e3×Leu+f3×Tyr+g3 ・・・(式3)
式1において、a1,b1,c1,d1,e1,f1はゼロではない任意の実数であり、g1は任意の実数である。
式2において、a2,b2,c2,d2,e2,f2,g2はゼロではない任意の実数であり、h2は任意の実数である。
式3において、a3,b3,c3,d3,e3,f3はゼロではない任意の実数であり、g3は任意の実数である。
1.アミノ酸以外の他の血中の代謝物(アミノ酸代謝物・糖類・脂質等)、タンパク質、ペプチド、ミネラル、ホルモン等の濃度値
2.アルブミン、総蛋白、トリグリセリド、HbA1c、糖化アルブミン、インスリン抵抗性指数、総コレステロール、LDLコレステロール、HDLコレステロール、アミラーゼ、総ビリルビン、クレアチニン、推算糸球体濾過量(eGFR)、尿酸等の血液検査値
3.超音波エコー、X線、CT、MRI等の画像情報から得られる値
4.年齢、身長、体重、BMI、腹囲、収縮期血圧、拡張期血圧、性別、喫煙情報、食事情報、飲酒情報、運動情報、ストレス情報、睡眠情報、家族の既往歴情報、疾患歴情報(糖尿病等)等の生体指標に関する値
ここでは、第2実施形態にかかる生活習慣病指標評価システム(以下では本システムと記す場合がある。)の構成について、図4から図19を参照して説明する。なお、本システムはあくまでも一例であり、本発明はこれに限定されない。
1.アミノ酸以外の他の血中の代謝物(アミノ酸代謝物・糖類・脂質等)、タンパク質、ペプチド、ミネラル、ホルモン等の濃度値
2.アルブミン、総蛋白、トリグリセリド、HbA1c、糖化アルブミン、インスリン抵抗性指数、総コレステロール、LDLコレステロール、HDLコレステロール、アミラーゼ、総ビリルビン、クレアチニン、推算糸球体濾過量(eGFR)、尿酸等の血液検査値
3.超音波エコー、X線、CT、MRI等の画像情報から得られる値
4.年齢、身長、体重、BMI、腹囲、収縮期血圧、拡張期血圧、性別、喫煙情報、食事情報、飲酒情報、運動情報、ストレス情報、睡眠情報、家族の既往歴情報、疾患歴情報(糖尿病等)等の生体指標に関する値
ここでは、第2実施形態の具体例について図20を参照して説明する。図20は、第2実施形態にかかる生活習慣病指標評価サービス処理の一例を示すフローチャートである。
(A)採取した血液サンプルを遠心することにより血液から血漿を分離した。全ての血漿サンプルは、アミノ酸濃度値の測定時まで-80℃で凍結保存した。アミノ酸濃度値測定時には、アセトニトリルを添加し除蛋白処理を行った後、標識試薬(3-アミノピリジル-N-ヒドロキシスクシンイミジルカルバメート)を用いてプレカラム誘導体化を行い、そして、液体クロマトグラフ質量分析計(LC/MS)によりアミノ酸の濃度値を分析した(国際公開第2003/069328号、国際公開第2005/116629号を参照)。
(B)採取した血液サンプルを遠心することにより血液から血漿を分離した。全ての血漿サンプルは、アミノ酸濃度値の測定時まで-80℃で凍結保存した。アミノ酸濃度値測定時には、スルホサリチル酸を添加し除蛋白処理を行った後、ニンヒドリン試薬を用いたポストカラム誘導体化法を原理としたアミノ酸分析計によりアミノ酸の濃度値を分析した。
a1×Asn+b1×Gly+c1×Ala+d1×Val+e1×Tyr+f1×Trp+g1 ・・・(式1)
a2×Asn+b2×Gly+c2×Ala+d2×Val+e2×Tyr+f2×Trp+g2×BMI+h2 ・・・(式2)
a3×Asn+b3×Gly+c3×Ala+d3×Cit+e3×Leu+f3×Tyr+g3 ・・・(式3)
式1において、a1,b1,c1,d1,e1,f1はゼロではない任意の実数であり、g1は任意の実数である。
式2において、a2,b2,c2,d2,e2,f2,g2はゼロではない任意の実数であり、h2は任意の実数である。
式3において、a3,b3,c3,d3,e3,f3はゼロではない任意の実数であり、g3は任意の実数である。
また、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値、個体のBMI値、および式2を用いて、式2の値を算出する。
また、Gly、Tyr、Asn、Ala、Cit、およびLeuのアミノ酸の濃度値および式3を用いて、式3の値を算出する。
例えば、クライアント装置200は、生活習慣病指標評価装置100から式の値を受信した場合には、評価部210aは、変換部210a2で式の値を変換したり、式の値又は変換後の値を用いてインスリン値および内臓脂肪面積値を推定したり、生成部210a3で式の値又は変換後の値に対応する位置情報を生成したり、分類部210a4で式の値又は変換後の値を用いて個体を脂肪肝に関する複数の区分のうちのどれか1つに分類したりしてもよい。
また、クライアント装置200は、生活習慣病指標評価装置100から変換後の値を受信した場合には、評価部210aは、変換後の値を用いてインスリン値および内臓脂肪面積値を推定したり、生成部210a3で変換後の値に対応する位置情報を生成したり、分類部210a4で変換後の値を用いて個体を脂肪肝に関する複数の区分のうちのどれか1つに分類したりしてもよい。
また、クライアント装置200は、生活習慣病指標評価装置100から式の値又は変換後の値と位置情報とを受信した場合には、評価部210aは、式の値又は変換後の値を用いてインスリン値および内臓脂肪面積値を推定したり、分類部210a4で式の値又は変換後の値を用いて個体を脂肪肝に関する複数の区分のうちのどれか1つに分類したりしてもよい。
本発明にかかる生活習慣病指標評価装置、生活習慣病指標評価方法、生活習慣病指標評価プログラム、生活習慣病指標評価システム、および情報通信端末装置は、上述した第2実施形態以外にも、特許請求の範囲に記載した技術的思想の範囲内において種々の異なる実施形態にて実施されてよいものである。
指標式1:「a1×Asn+b1×Gly+c1×Ala+d1×Val+e1×Tyr+f1×Trp+g1」
指標式2:「a2×Asn+b2×Gly+c2×Ala+d2×Val+e2×Tyr+f2×Trp+g2×BMI+h2」
指標式3:「a3×Asn+b3×Gly+c3×Ala+d3×Cit+e3×Leu+f3×Tyr+g3」
※指標式1において、a1,b1,c1,d1,e1,f1はゼロではない実数であり、g1は実数である。
※指標式2において、a2,b2,c2,d2,e2,f2,g2はゼロではない実数であり、h2は実数である。
※指標式3において、a3,b3,c3,d3,e3,f3はゼロではない実数であり、g3は実数である。
項目1:「ウエストが、男性の場合で85cm以上、女性の場合で90cm以上である」(内臓脂肪面積値が100cm2以上になっていることの目安)又は「BMIが25以上である」
項目2:「中性脂肪(トリグリセライド)が150mg/dl以上である」及び/又は「HDLコレステロールが40mg/dl未満である」
項目3:「収縮期血圧が130mmHg以上である」及び/又は「拡張期血圧が85mmHg以上である」
項目4:「空腹時血糖が110mg/dl以上である」
内臓脂肪面積値を取得された受診者(糖尿病であるとの確定診断を受けた受診者の数は135人、境界型糖尿病:187人、慢性腎症:126人、細小動脈硬化症:67人、脳卒中:23人、心筋梗塞:8人)について、下記1.から6.に示す判別に関する指標式2の判別能を、ROC_AUCで評価した。
脂肪肝についての診断結果を取得された受診者(糖尿病であるとの確定診断を受けた受診者の数は394人、境界型糖尿病:243人、慢性腎症:452人、細小動脈硬化症:201人、脳卒中:64人、心筋梗塞:16人)について、下記1.から6.に示す判別に関する指標式3の判別能を、ROC_AUCで評価した。
1.糖尿病であるとの確定診断を受けたか否かの判別
2.境界型糖尿病である(具体的には、耐糖能異常(75gOGTT120分時の血糖値が140mg/dl以上且つ199mg/dl以下である)及び/又は空腹時血糖異常(空腹時血糖値が110mg/dl以上且つ125mg/dl以下である)を有する)との確定診断を受けたか否かの判別
3.慢性腎症であるとの確定診断を受けたか否かの判別
4.細小動脈硬化症であるとの確定診断を受けたか否かの判別
5.脳卒中であるとの確定診断を受けたか否かの判別
6.心筋梗塞であるとの確定診断を受けたか否かの判別
疾患イベント発生率(「絶対リスク」)=疾患イベント発生総数/観察年数総和(「人年」)
相対リスク=「n-th Quintile」の疾患イベント発生率/「1st Quintile」の疾患イベント発生率
※インスリン抵抗性指数であるHOMA-Rが2.5以上である場合、インスリン抵抗性ありと診断される。
2.高血圧
※収縮期血圧が130mmHg以上である及び/又は拡張期血圧が85mmHg以上である場合、高血圧と診断される。
3.高血圧症
※収縮期血圧が140mmHg以上である又は拡張期血圧が90mmHg以上である場合に、高血圧症と診断される。
4.脂肪肝
※腹部超音波検査にて肝腎コントラスト比より脂肪肝の所見が観察された場合に、脂肪肝と診断される。
5.高リスク脂肪肝
※脂肪肝と診断され且つAST(GOT)が38U/Lより高値である場合に、高リスク脂肪肝と診断される。
※下記項目1~3のいずれかと項目4が確認された場合に、糖尿病と診断される。
項目1:早朝空腹時血糖値が126mg/dL以上
項目2:75gOGTT120分時の血糖値が200mg/dL以上
項目3:随時血糖値が200mg/dL以上
項目4:HbA1C(JDS値)が6.1%以上[HbA1C(国際標準値)が6.5%以上]
7.耐糖能異常
※75gOGTT120分時の血糖値が140mg/dl以上且つ199mg/dl以下である場合に、耐糖能異常と診断される。
8.肥満
※「ウエストが、男性の場合で85cm以上、女性の場合で90cm以上である」(内臓脂肪面積値が100cm2以上になっていることの目安)又は「BMIが25以上である」場合に、肥満と診断される。
9.高度肥満
※BMIが30以上である場合に、高度肥満と診断される。
10.脂質異常症
※「トリグリセライド(TG)が150mg/dL以上である、HDLコレステロールが40mg/dL未満である、又はLDLコレステロールが140mg/dL以上である」場合に、脂質異常症と診断される。
※推算糸球体濾過量(eGFR)が60未満である場合に、慢性腎症と診断される。
12.動脈硬化症
※動脈硬化ドックにて硬化の所見が観察された場合、動脈硬化症と診断される。
13.脳梗塞
※頭部MRI,MRA検査により脳梗塞の所見が観察された場合、脳梗塞と診断される。
14.心疾患リスクあり
※ミネソタコードが正常範囲外の場合、心疾患リスクありと診断される。
15.メタボリックシンドローム
※下記項目1に該当する場合において、さらに下記項目2から4のうちの少なくとも2つに該当するときに、メタボリックシンドロームと診断される。
項目1:「ウエストが、男性の場合で85cm以上、女性の場合で90cm以上である」(内臓脂肪面積値が100cm2以上になっていることの目安)又は「BMIが25以上である」
項目2:「中性脂肪(トリグリセライド)が150mg/dl以上である」及び/又は「HDLコレステロールが40mg/dl未満である」
項目3:「収縮期血圧が130mmHg以上である」及び/又は「拡張期血圧が85mmHg以上である」
項目4:空腹時血糖が110mg/dl以上である。
102 制御部
102a 要求解釈部
102b 閲覧処理部
102c 認証処理部
102d 電子メール生成部
102e Webページ生成部
102f 受信部
102g 指標状態情報指定部
102h 評価式作成部
102h1 候補式作成部
102h2 候補式検証部
102h3 変数選択部
102i 評価部
102i1 算出部
102i2 変換部
102i3 生成部
102i4 分類部
102j 結果出力部
102k 送信部
104 通信インターフェース部
106 記憶部
106a 利用者情報ファイル
106b アミノ酸濃度データファイル
106c 指標状態情報ファイル
106d 指定指標状態情報ファイル
106e 評価式関連情報データベース
106e1 候補式ファイル
106e2 検証結果ファイル
106e3 選択指標状態情報ファイル
106e4 評価式ファイル
106f 評価結果ファイル
108 入出力インターフェース部
112 入力装置
114 出力装置
200 クライアント装置(情報通信端末装置)
300 ネットワーク
400 データベース装置
Claims (18)
- 評価対象から採取した血液中のアミノ酸の濃度値に関するアミノ酸濃度データを取得する取得ステップと、
前記取得ステップで取得した前記評価対象の前記アミノ酸濃度データに含まれているGlyおよびTyrのアミノ酸の濃度値を用いて、前記評価対象について生活習慣病の指標の状態を評価する評価ステップと、
を含むことを特徴とする生活習慣病指標の評価方法。 - 前記評価ステップでは、Gly、Tyr、およびAsnのアミノ酸の濃度値、Gly、Tyr、およびAlaのアミノ酸の濃度値、Gly、Tyr、およびValのアミノ酸の濃度値、または、Gly、Tyr、およびTrpのアミノ酸の濃度値を用いること、
を特徴とする請求項1に記載の生活習慣病指標の評価方法。 - 前記評価ステップでは、Gly、Tyr、Asn、およびAlaのアミノ酸の濃度値を用いること、
を特徴とする請求項2に記載の生活習慣病指標の評価方法。 - 前記評価ステップでは、脂肪肝、内臓脂肪、およびインスリンのうちの少なくとも1つの状態を評価すること、
を特徴とする請求項1から3のいずれか1つに記載の生活習慣病指標の評価方法。 - 前記評価ステップでは、脂肪肝、内臓脂肪、およびインスリンのうちの少なくとも2つの状態を評価すること、
を特徴とする請求項4に記載の生活習慣病指標の評価方法。 - 前記評価ステップでは、脂肪肝、内臓脂肪、およびインスリンの状態を評価すること、
を特徴とする請求項5に記載の生活習慣病指標の評価方法。 - 前記評価ステップでは、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値、および、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値が代入される変数を含む式を用いて、前記式の値を算出することで、インスリンの状態を評価すること、
を特徴とする請求項4に記載の生活習慣病指標の評価方法。 - 前記評価ステップでは、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値、および、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値が代入される変数を含む式を用いて、または、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値、予め取得した前記評価対象のBMI(Body Mass Index)値、および、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値および前記評価対象のBMI値が代入される変数を含む式を用いて、前記式の値を算出することで、内臓脂肪の状態を評価すること、
を特徴とする請求項4に記載の生活習慣病指標の評価方法。 - 前記評価ステップでは、Gly、Tyr、Asn、Ala、Cit、およびLeuのアミノ酸の濃度値、および、Gly、Tyr、Asn、Ala、Cit、およびLeuのアミノ酸の濃度値が代入される変数を含む式を用いて、前記式の値を算出することで、脂肪肝の状態を評価すること、
を特徴とする請求項4に記載の生活習慣病指標の評価方法。 - 前記評価ステップでは、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値、および、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値が代入される変数を含む式を用いて、前記式の値を算出することで、インスリンおよび内臓脂肪の状態を評価すること、
を特徴とする請求項5に記載の生活習慣病指標の評価方法。 - 前記評価ステップでは、
Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値、および、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値が代入される変数を含む式を用いて、前記式の値を算出することで、インスリンの状態を評価し、
Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値、および、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値が代入される変数を含む式を用いて、または、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値、予め取得した前記評価対象のBMI(Body Mass Index)値、および、Gly、Tyr、Asn、Ala、Val、およびTrpのアミノ酸の濃度値および前記評価対象のBMI値が代入される変数を含む式を用いて、前記式の値を算出することで、内臓脂肪の状態を評価し、
Gly、Tyr、Asn、Ala、Cit、およびLeuのアミノ酸の濃度値、および、Gly、Tyr、Asn、Ala、Cit、およびLeuのアミノ酸の濃度値が代入される変数を含む式を用いて、前記式の値を算出することで、脂肪肝の状態を評価すること、
を特徴とする請求項6に記載の生活習慣病指標の評価方法。 - 制御部と記憶部とを備え、評価対象について生活習慣病の指標の状態を評価する生活習慣病指標評価装置であって、
前記制御部は、
アミノ酸の濃度値に関する予め取得された前記評価対象のアミノ酸濃度データに含まれているGlyおよびTyrのアミノ酸の濃度値、および、GlyおよびTyrのアミノ酸の濃度値が代入される変数を含む予め前記記憶部に記憶された式を用いて、前記式の値を算出することで、前記評価対象について前記生活習慣病の指標の状態を評価する評価手段
を備えたこと、
を特徴とする生活習慣病指標評価装置。 - 制御部と記憶部とを備えた情報処理装置において実行される、評価対象について生活習慣病の指標の状態を評価する生活習慣病指標評価方法であって、
前記制御部において実行される、
アミノ酸の濃度値に関する予め取得された前記評価対象のアミノ酸濃度データに含まれているGlyおよびTyrのアミノ酸の濃度値、および、GlyおよびTyrのアミノ酸の濃度値が代入される変数を含む予め前記記憶部に記憶された式を用いて、前記式の値を算出することで、前記評価対象について前記生活習慣病の指標の状態を評価する評価ステップ
を含むこと、
を特徴とする生活習慣病指標評価方法。 - 制御部と記憶部とを備えた情報処理装置において実行させるための、評価対象について生活習慣病の指標の状態を評価する生活習慣病指標評価プログラムであって、
前記制御部において実行させるための、
アミノ酸の濃度値に関する予め取得された前記評価対象のアミノ酸濃度データに含まれているGlyおよびTyrのアミノ酸の濃度値、および、GlyおよびTyrのアミノ酸の濃度値が代入される変数を含む予め前記記憶部に記憶された式を用いて、前記式の値を算出することで、前記評価対象について前記生活習慣病の指標の状態を評価する評価ステップ
を含むこと、
を特徴とする生活習慣病指標評価プログラム。 - 制御部と記憶部とを備え、評価対象について生活習慣病の指標の状態を評価する生活習慣病指標評価装置と、制御部を備え、アミノ酸の濃度値に関する前記評価対象のアミノ酸濃度データを提供する情報通信端末装置とを、ネットワークを介して通信可能に接続して構成された生活習慣病指標評価システムであって、
前記情報通信端末装置の前記制御部は、
前記評価対象の前記アミノ酸濃度データを前記生活習慣病指標評価装置へ送信するアミノ酸濃度データ送信手段と、
前記生活習慣病指標評価装置から送信された、前記評価対象についての前記生活習慣病の指標の状態に関する評価結果を受信する結果受信手段と
を備え、
前記生活習慣病指標評価装置の前記制御部は、
前記情報通信端末装置から送信された前記評価対象の前記アミノ酸濃度データを受信するアミノ酸濃度データ受信手段と、
前記アミノ酸濃度データ受信手段で受信した前記評価対象の前記アミノ酸濃度データに含まれているGlyおよびTyrのアミノ酸の濃度値、および、GlyおよびTyrのアミノ酸の濃度値が代入される変数を含む予め前記記憶部に記憶された式を用いて、前記式の値を算出することで、前記評価対象について前記生活習慣病の指標の状態を評価する評価手段と、
前記評価手段で得られた前記評価結果を前記情報通信端末装置へ送信する結果送信手段と、
を備えたこと、
を特徴とする生活習慣病指標評価システム。 - 制御部を備え、アミノ酸の濃度値に関する評価対象のアミノ酸濃度データを提供する情報通信端末装置であって、
前記制御部は、前記評価対象についての生活習慣病の指標の状態に関する評価結果を取得する結果取得手段を備え、
前記評価結果は、前記評価対象の前記アミノ酸濃度データに含まれているGlyおよびTyrのアミノ酸の濃度値、および、GlyおよびTyrのアミノ酸の濃度値が代入される変数を含む式を用いて、前記式の値を算出することで、前記評価対象についての前記生活習慣病の指標の状態を評価した結果であること、
を特徴とする情報通信端末装置。 - 前記評価対象について前記生活習慣病の指標の状態を評価する生活習慣病指標評価装置とネットワークを介して通信可能に接続して構成されており、
前記制御部は、前記評価対象の前記アミノ酸濃度データを前記生活習慣病指標評価装置へ送信するアミノ酸濃度データ送信手段をさらに備え、
前記結果取得手段は、前記生活習慣病指標評価装置から送信された前記評価結果を受信すること、
を特徴とする請求項16に記載の情報通信端末装置。 - アミノ酸の濃度値に関する評価対象のアミノ酸濃度データを提供する情報通信端末装置とネットワークを介して通信可能に接続された、制御部と記憶部とを備え、前記評価対象について生活習慣病の指標の状態を評価する生活習慣病指標評価装置であって、
前記制御部は、
前記情報通信端末装置から送信された前記評価対象の前記アミノ酸濃度データを受信するアミノ酸濃度データ受信手段と、
前記アミノ酸濃度データ受信手段で受信した前記評価対象の前記アミノ酸濃度データに含まれているGlyおよびTyrのアミノ酸の濃度値、および、GlyおよびTyrのアミノ酸の濃度値が代入される変数を含む予め前記記憶部に記憶された式を用いて、前記式の値を算出することで、前記評価対象について前記生活習慣病の指標を評価する評価手段と、
前記評価手段で得られた評価結果を前記情報通信端末装置へ送信する結果送信手段と、
を備えたこと、
を特徴とする生活習慣病指標評価装置。
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