KR102576596B1 - Method and system for providing information to evaluate immune aging - Google Patents

Abstract

The present invention relates to a method and system for providing information for immune aging assessment that predicts or calculates an immune aging evaluation index by analyzing the relationship between lymphocyte subtypes and birth age. Aging markers that are expressed on the surface of immune cells and change with age. By presenting an immune aging evaluation index that can express comprehensive aging immunity in objective numbers, immunity can be managed systematically, and furthermore, it is possible to promote health by preparing for immune aging and immune response abnormalities.

Description

{Method and system for providing information to evaluate immune aging}

The present invention relates to a method and system for providing information for immune aging assessment that calculates an immune aging evaluation index by analyzing the relationship between lymphocyte subtypes and birth age.

As people age, they experience aging. Aging causes deterioration and degeneration of body functions, making people vulnerable to cancer or infections caused by bacteria, viruses, etc. However, the degree of aging is different for each individual, and aging is divided into healthy aging and unhealthy aging, so unhealthy aging increases susceptibility to disease more than healthy aging. Unhealthy aging is accompanied by inflammation, which is chronic low grade inflammation and immune disorders, including cancer, various autoimmune diseases, dementia, and Alzheimer's disease. It is the cause of almost all chronic diseases such as degenerative brain and nerve diseases, high blood pressure, diabetes, and cardiovascular diseases. This type of inflammatory aging is mainly caused by complex causes such as an individual's poor eating habits, environmental and genetic factors, and is caused by pro-inflammatory cytokines, oxidative stress, gene damage, and epigenetic changes that accumulate inside the body. This causes a rapid decline in immune function due to immune aging or impaired immunity such as immune hypersensitivity.

In particular, modern people are exposed to various risk factors that can cause problems with immunity, such as nutritional imbalance, obesity, smoking and drinking, stress and overwork, lack of exercise and sleep, etc. Depending on individual differences in these complex risk factors, immunity may decline with aging or It can be said that the degree of degradation is different.

However, the immune system is very complex, and there is currently no technology to comprehensively and scientifically diagnose and evaluate immunity, which varies from individual to individual, and most immunity management is actually carried out based on individual feelings, which has the problem of being inaccurate. .

For this reason, as you age, it is difficult to recognize even if a problem occurs with your immune system or a problem occurs due to rapid aging of your immune system, so you miss the golden time to intensively manage your immunity, which can lead to cancer or infectious diseases in the future. Alternatively, it may be the starting point of severe senile immune diseases such as various autoimmune diseases. Therefore, as the world has entered an aging era, there is an urgent need for the development of comprehensive and systematic immune diagnosis technology and immunity management systems to properly understand and manage immunity.

Japanese Patent No. 5030109 US Patent No. 8815524

The purpose of the present invention is to provide a method of providing information for evaluating immune aging to calculate an immune aging evaluation index using lymphocyte subtypes whose expression level changes due to aging.

Additionally, the purpose of the present invention is to provide a system for evaluating immune aging to calculate an immune aging evaluation index using lymphocyte subtypes whose expression level changes due to aging.

The present inventors focused on the phenomenon that immunity also ages, just as body tissues and organs age with age, and developed a comprehensive aging immunity system based on specific aging markers of immune cells that significantly decrease or increase depending on birth age. The present invention regarding a method and system for providing information for evaluating immune aging was completed by developing an immune aging evaluation index that can quantify .

One aspect of the invention includes the steps of a) obtaining birth age and biological samples from a subject; b) measuring lymphocyte subtypes from the biological sample; c) conducting a correlation analysis between the lymphocyte subtype and birth age to first select a lymphocyte subtype with a coefficient of determination (r ² ) ≥ 0.01 and a significance probability (p value) <0.05; d) performing multicollinearity diagnosis among the first selected lymphocyte subtypes to secondarily select lymphocyte subtypes with variance inflation factor (VIF) <10 or tolerance limit ≥ 0.1; e) performing a linear multiple regression analysis on the second selected lymphocyte subtypes and determining the one with the highest coefficient of determination as the immunosenescent cell subtype; and f) calculating an immune senescence evaluation index using the immune senescence cell subtype.

“Immune aging assessment” used in the present invention means predicting or measuring the degree to which immune function changes due to aging, that is, the degree to which immune aging progresses. In the present invention, the relationship between lymphocyte subtypes and birth age is analyzed. Immunity can be evaluated through the immune aging evaluation index, which can objectively indicate immunity.

The “immune aging evaluation index” used in the present invention refers to an objective measure that quantifies the degree to which immune function changes due to aging or the degree to which immune aging progresses. In the present invention, the immune aging evaluation index includes immune age and immune aging. , immune aging score, immune aging index, and immune age differences are presented.

The above steps a) to f) will be discussed in detail below.

Step a) is a process of obtaining birth age and biological samples as information for calculating the immune aging evaluation index.

As used herein, “subject” refers to a subject in need of immune aging evaluation. In the present invention, they may be healthy adult men and women, high-risk elderly people suspected of having a disease, or patients diagnosed with a disease, but are not limited thereto.

As used in the present invention, “chronological age” refers to the age that increases every year since birth, and corresponds to the number of years the subject has survived at the time of calculating the immune aging evaluation index.

For example, if the subject is 30 years old, the birth age is 30 years old.

“Biological samples” used in the present invention include cells and tissues as well as organic biomolecules such as nucleic acids, genes, peptides, amino acids, proteins, lipids, sugars, glycolipids, and glycoproteins that are derived from living organisms and can detect biological changes. It refers to the sample containing. In the present invention, there is no limitation as long as the sample contains immune cells.

According to one embodiment of the present invention, the biological sample in step a) may be one or more types selected from the group consisting of blood, plasma, serum, lymph fluid, tissue fluid, lymph nodes, and cancer tissue.

The biological sample is preferably blood containing lymphocytes among immune cells.

Step b) is a process of measuring lymphocyte subtypes among immune cells included in the biological sample.

“Lymphocyte” used in the present invention is a type of white blood cell created by differentiating and maturing hematopoietic stem cells into lymphoid progenitor cells during the differentiation of blood cells from stem cells in the bone marrow. Mature lymphocytes are largely produced in the bone marrow. They can be divided into B lymphocytes derived from the thymus, T lymphocytes derived from the thymus, and natural killer (NK) cells. In the present invention, lymphocytes such as T lymphocytes and NK cells are targeted for measurement of lymphocyte subtypes for the evaluation of immune aging. .

The T lymphocytes include naive T cells that have not yet encountered an antigen, helper T cells that have differentiated by function after encountering an antigen, cytotoxic T cells, and natural killer T cells. killer T cells), memory T cells, regulatory T cells, etc., but are not limited thereto.

“Lymphocyte subtype” as used in the present invention refers to a cell group classified according to antigen molecules, i.e. markers, present on the surface of lymphocytes. Main markers include surface immunoglobulin and differentiation-related There are differentiation antigens and membrane receptors, and they are mainly called CD (cluster of differentiation) antigens.

According to one embodiment of the present invention, the lymphocyte subtype in step b) is 1 selected from the group consisting of CD3, CD8, CD56, CD27, CD28, CD45RO, CD57, CD62L, CD70, CD95, CD197, TIGIT, VISTA and CD85j. It may or may not express a species abnormality.

More specifically, the lymphocyte subtype expresses or does not express two or more types selected from the group consisting of CD3, CD8, CD56, CD27, CD28, CD45RO, CD57, CD62L, CD70, CD95, CD197, TIGIT, VISTA and CD85j. You can.

For example, the lymphocyte subtype may include lymphocytes that do not express TIGIT (TIGIT-), express both CD3 and CD8 (CD3+CD8+), or express CD28 but not TIGIT (CD28+TIGIT-). ).

In the process of measuring the lymphocyte subtype, markers corresponding to lymphocytes among immune cells contained in a biological sample are recognized and separated, and the ratio of lymphocyte subtypes with a specific marker is measured. To measure lymphocyte subtypes, antibodies that can specifically bind to markers can be used.

According to one embodiment of the present invention, the measurement in step b) may be performed using a flow cytometer.

The flow cytometry uses an antigen-antibody reaction to quickly measure the mean fluorescence intensity of fluorescent substances bound to each particle or cell when cells in a fluid state pass through a certain detection area. With this equipment, cell-specific characteristics such as cell size, cell internal composition, and cell function recognition can be measured and only specific cells can be sorted. Through this flow cytometer, the distribution of total immune cells and the relative ratios between immune cells can be measured.

Steps c) to e) are a process of analyzing the relationship between lymphocyte subtypes and birth age to select effective lymphocyte subtypes containing aging markers that can be used to evaluate immune aging.

The above lymphocyte subtypes can come in dozens to hundreds of combinations depending on the expression of 14 aging markers. Among the many lymphocyte subtypes, the lymphocyte subtype that is highly related to immunity or immunosenescence, that is, the immunosenescence cell subtype, has a relationship with birth age. It is advisable to conduct analysis.

The immune senescent cell subtype is a lymphocyte with a coefficient of determination (r ² ) ≥ 0.01 and a significance probability (p value) < 0.05 by performing correlation analysis between all lymphocyte subtypes and birth age (cAge). A subtype is selected first, and multicollinearity among the first selected lymphocyte subtypes is diagnosed, and lymphocyte subtypes with a variation inflation factor (VIF) < 10 or tolerance limit ≥ 0.1 are selected as secondary subtypes. After selection, linear multiple regression analysis is performed on the second selected lymphocyte subtypes, and the one with the highest coefficient of determination is selected. Here, if the coefficient of determination is 0.5 or more, it can be considered a valid lymphocyte subtype that can be used to evaluate immune aging.

This correlation analysis between lymphocyte subtypes and birth age can be performed using a common statistical program.

Step f) is a process of calculating an immunosenescence evaluation index by statistically analyzing immunosenescence cell subtypes with reference to birth age.

According to one embodiment of the present invention, step f) may include a series of statistical processing to calculate the immune aging evaluation index, that is, immune age, immune senescence degree, immune senescence score, immune senescence index, and immune age difference. .

More specifically, step f) includes i) unstandardized predicted values for the constants and aging markers obtained from the multiple linear regression analysis of the immunosenescent cell subtypes performed in step e). It may include the step of calculating U-value, which is a non-standardized predicted value, by applying Equation 1 below.

In Equation 1, β ₀ is a constant, βn is the unnormalized coefficient for the nth aging marker, and Xn is the distribution percentage value of the immunosenescence cell subtype including the nth aging marker obtained through flow cytometry.

The U-value represents the comprehensive aging immunity obtained by combining the results of aging markers into a single number.

For example, blood was obtained from a total of 200 test participants, including 100 healthy adult men and 100 women aged between 20 and 85 years old, flow cytometry was performed, selected aging markers were analyzed, and then their By setting the result as an independent variable and the birth age of the test population as a dependent variable, a multiple linear regression analysis that can predict birth age is performed to obtain an unstandardized prediction value.

Table 1 below shows the flow cytometry results for four aging markers (X3, X5, X7, and It is expressed in percentage distribution, and Figure 3 shows the coefficient of determination of four aging markers, showing that the coefficient of determination gradually increases.

birth age Distribution rate (%) X3 X5 X7 X9 20 26 12 12 12 40 12 30 24 16 50 20 18 17 24 60 54 24 46 32 70 42 54 32 46 80 36 36 54 54

Table 2 below shows the U-value obtained by creating a linear regression model using the data set in Table 1 and applying the % distribution rate of aging markers, and Figure 4 is a scatter plot of U-value and birth age.

birth age U-value X3 X5 X7 X9 20 49 36 33 30 40 38 54 46 35 50 44 42 38 45 60 71 48 70 55 70 61 79 55 72 80 57 61 79 82

Here, as a result of analyzing the minimum and maximum values of the U-value distribution for each aging marker, X3 (R ² =0.312) was 38 and 71, respectively, X5 (R ² =0.519) was 36 and ⁷⁹ , and = ^0.712 ) are 33 and 79, respectively, and It can be seen that the larger the value, the narrower the observation range of U-value becomes. Therefore, as the coefficient of determination of the multiple linear regression model created using aging markers decreases, the observed U-value is not suitable as an immune aging evaluation index.

In addition, step f) may further include, after step i), ii) calculating a standardized S-value by applying the U-value to Equation 2 below.

In Equation 2 above,

The S-value is a converted U-value into a standardized predicted value that can be expressed between -4 and +4 with the number 0 as the center, and is an integer expressed to three decimal places. This means that as the S-value increases in the positive direction, aging occurs.

Table 3 below shows the S-value obtained by standardizing the U-value of Table 2 above.

birth age S-value X3 X5 X7 X9 20 -0.404 -1.250 -1.250 -1.227 40 -1.403 0.074 -1.454 -0.964 50 -0.832 -0.809 -0.919 -0.438 60 1.593 -0.368 1.007 0.088 70 0.737 1.838 0.077 1.008 80 0.309 0.515 1.538 1.533

In addition, step f) may further include iii) calculating a normalized Z-score by applying the S-value to Equation 3 below.

In Equation 3 above, X is the S-value of each individual in the test population, Xmin is the minimum S-value of the entire test population, and Xmax is the maximum S-value of the entire test population.

The Z-score is converted by normalizing the S-value to be expressed between 0 and 1, and is a real number expressed up to three decimal places.

Table 4 below shows the Z-score obtained by normalizing the S-value in Table 3 above.

birth age Z-score X3 X5 X7 X9 20 0.333 0.000 0.000 0.000 40 0.000 0.429 0.286 0.095 50 0.190 0.143 0.119 0.286 60 1.000 0.286 0.810 0.476 70 0.714 1.000 0.476 0.810 80 0.571 0.571 1.000 1.000

In addition, step f) may further include step iv) calculating immune age (cellular immune age, ciAge) by applying the Z-score and birth age to Equation 4 below.

The immune age is a one-to-one correspondence with the Z-score by considering 20 years of age at birth as 0 and 85 years of age as 1, under the premise that there is a linear relationship between relative aging immunity expressed in Z-score and birth age. It is an immune aging evaluation index obtained through a bijective function assuming that This immune age can be converted to between 20 and 85 years, with all Z-scores observed between 0 and 1.

In Table 4 above, assuming that the Z-score is 0 is the aging immunity of the 20-year-old with the lowest birth age among the 6 test samples, and that the Z-score is 1 is the aging immunity of the highest birth age of 80, The immune age is obtained through bijective functions (Equation 4) that correspond one-to-one to each other (Table 5). Figure 5 is a scatter plot of immune age and birth age.

birth age Immune age (ciAge) X3 X5 X7 X9 20 40 20 20 20 40 20 46 37 26 50 31 29 27 37 60 80 37 69 49 70 63 80 49 69 80 54 54 80 80

Here, the distribution range of immune age all converges within the actual birth age range of 20 to 80 years, regardless of whether the coefficient of determination is large or small, so it is more reasonable to use immune age rather than U-value as an immune aging evaluation index. .

In addition, step f) may further include step v) calculating the degree of immune senescence (ri-Degree) by applying the Z-score to Equation 5 below.

The degree of immune senescence is a Z-score value converted into a percentage, and is observed in the range of 0 to 100%.

In addition, step f) may further include the step vi) of calculating an immune aging score (ri-Score) by applying the S-value to Equation 6 below.

The immune aging score is an integer in the range of -4 to +4, and as the immune aging score increases in the positive direction, it means that the immune system is less aged and healthy.

In addition, step f) may further include the step of calculating the immune aging index (ri-Index) by applying the immune age (ciAge) and birth age (cAge) to Equation 7 below.

The immune aging index refers to the ratio between immune age and birth age. As the immune age is greater than the birth age, the immune aging index increases, and conversely, as the immune age is smaller than the birth age, the immune aging index decreases.

In addition, step f) may further include step viii) calculating the immune age difference (Immune Age Difference, IAD) by applying the immune age (ciAge) and birth age (cAge) to Equation 8 below.

The immune aging difference means the arithmetically subtracted birth age from the immune age. As the immune age difference becomes a positive number, the expression of markers related to immune suppression among the selected aging markers increases, while the expression of markers related to immune activity increases. This means that as the immune age difference becomes smaller and more negative, the expression of markers related to immune suppression among the selected aging markers decreases, while the expression of markers related to immune activity increases.

These differences in immune aging can be classified into 6 sections and used as a reference for immune diagnosis management, and can be used to predict risk diseases such as autoimmune diseases, allergies, cancer, and infectious diseases and establish prevention plans to prepare for them. there is.

More specifically, the difference in immune aging is less than -14, which is the N3 range of hyperimmune caution, which is a state of excessive immune activity. If it is more than -14 and less than -7, it is the N2 range of managed immunity, which is a healthy normal range but a state of strong immune activity, - If it is above 7 and below 0, it is in the N1 range of stable immunity and is in a state of mild immune activity dominance. If it is above 0 and below +7, it is in the P1 range of stable immunity and is in a state of mild immunosuppression. If it is above +7 and below +14, it is in the P2 range of managed immunity. Although it is within the healthy normal range, it is in a state of strong immunity. If it exceeds +14, it can be classified as excessively low immunity, in the P3 range of warning for low immunity.

The method of providing information for assessing immune aging according to one embodiment of the present invention may be implemented as a system using a computer device.

Another aspect of the present invention provides an information processing system for assessing immune aging as described above.

More specifically, with reference to FIG. 2, the system 100 includes an input unit 110 for inputting information about the subject's birth age and lymphocyte subtype; a processing unit 120 that selects immune senescent cell subtypes using the information; And it may include a calculation unit 130 that calculates an immune senescence evaluation index using the immune senescence cell subtype.

Here, descriptions of content common to the above-mentioned content are omitted to avoid excessive complexity.

The input unit 110 receives subject information that serves as a basis for evaluating immune aging. The information may be collected regarding age at birth and lymphocyte subtype at the time of assessment.

According to one embodiment of the present invention, the information about the lymphocyte subtype may be obtained from a flow cytometer.

This information may be collected from user input or storage media, or may be collected through linkage with a flow cytometer.

The processing unit 120 is the most core component of the system for evaluating immune aging, and analyzes the relationship between input information to determine effective lymphocyte subtypes containing aging markers that can be used to evaluate immune aging, that is, immunosenescent cells. Select the subtype.

According to one embodiment of the present invention, the processing unit is composed of a series of processing units for analyzing the relationship between lymphocyte subtypes and birth age and for selecting immunosenescent cell subtypes.

More specifically, the processing unit 120 conducts a correlation analysis between lymphocyte subtypes and birth age to first select a lymphocyte subtype with a coefficient of determination (r ² ) ≥ 0.01 and a significance probability (p value) < 0.05. Processing unit 121; a second processing unit 122 that performs multicollinearity diagnosis among the first selected lymphocyte subtypes to secondarily select lymphocyte subtypes with a variance inflation factor (VIF) <10 or a tolerance limit ≥0.1; and a third processing unit 123 that performs a linear multiple regression analysis on the second selected lymphocyte subtypes and selects the one with the highest coefficient of determination as the immunosenescent cell subtype.

These first to third processing sections present immunosenescent cell subtypes containing aging markers highly correlated with immunosenescence among all lymphocyte subtypes.

The calculation unit 130 calculates an immune senescence evaluation index through statistical analysis of immune senescence cell subtypes.

According to one embodiment of the present invention, the calculation unit is composed of a series of calculation units that calculate the immune aging evaluation index, that is, immune age, immune senescence degree, immune senescence score, immune senescence index, and immune age difference.

More specifically, the calculation unit 130 includes a first calculation unit 131 that calculates U-value through linear multiple regression analysis of immune senescent cell subtypes and normalizes it to calculate S-value; a second calculation unit 132 that normalizes the S-value to calculate a Z-score; a third calculation unit 133 that calculates immune age (ciAge) by performing a one-to-one correspondence between the Z-score and birth age; a fourth calculation unit 134 that converts the Z-score into a percentage to calculate an immune senescence degree (ri-Degree); A fifth calculation unit 135 that calculates an immune aging score (ri-Score) by multiplying the S-value by -1; a sixth calculation unit 136 that calculates an immune aging index (ri-Index) based on the ratio between the immune age and birth age; and a seventh calculation unit 137 that calculates an immune age difference (IAD) as the difference between the immune age and birth age.

The first calculation unit 131 calculates the U-value through Equation 1 from the constant obtained by performing linear multiple regression analysis on the immune senescent cell subtype and the unstandardized coefficient for the aging marker, and Equation 2 The S-value is calculated by standardizing the U-value.

The second calculation unit 132 normalizes the S-value through Equation 3 and calculates the Z-score.

The third calculation unit 133 calculates the immune age through Equation 4 based on the linear relationship between Z-score and birth age.

The fourth calculation unit 134 calculates the degree of immune aging by converting the Z-score obtained from the second processing unit through Equation 5.

The fifth calculation unit 135 calculates the immune aging score from the S-value obtained from the first processing unit through Equation 6.

The sixth calculation unit 136 calculates the immune aging index through Equation 7 based on the immune age and birth age.

The seventh calculation unit 137 calculates the immune age difference through Equation 8 based on the immune age and birth age.

The system 100 for assessing immune aging including an input unit, a processing unit, and a calculating unit may further include a display unit 140 that displays the result calculated from the processing unit and the calculating unit, that is, an immune aging evaluation index.

The display unit 140 may be a separate display screen, and outputs results including the immune aging evaluation index obtained from the processing unit and the calculation unit in a designated user interface format. The immune aging evaluation index may be displayed as individual result values, or may be displayed as a single number that combines immune age, immune aging degree, immune aging score, immune aging index, and immune age difference through an algorithm.

The system according to one embodiment of the present invention can run one or more programs and be stored in a recording medium, etc., and can be built as a device such as a computer or server.

The program may include code coded in various computer languages that can be executed by a processor of a computer or server. The code may include codes such as functions that define the functions necessary to calculate the immune aging evaluation index and control codes that can control them.

In addition, the recording medium on which the program is stored is a medium that can be read by a computer or server, such as ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical disk, USB memory, SD card, and micro SD card. , but is not limited to this.

The system of the present invention is preferably implemented as a single hardware device, but if necessary, it can be implemented as an embedded device accommodated in an existing hardware device, or as an application that is downloaded and installed in software form.

In the present invention, immunity can be systematically managed by presenting an immune aging evaluation index that can express comprehensive aging immunity in objective numbers using aging markers that are expressed on the surface of immune cells and change with age. Furthermore, immune aging and You can improve your health by preparing for immune response abnormalities.

Figure 1 is a flowchart showing a method of providing information for assessing immune aging according to an embodiment of the present invention.
Figure 2 is a diagram showing functional elements constituting a system for assessing immune aging according to an embodiment of the present invention.
Figure 3 shows the relationship between the distribution rate (%) and birth age (cAge) for four aging markers (X3, X5, X7, and X9) in a test population according to an embodiment of the present invention.
Figure 4 shows the relationship between U-value and birth age (cAge) for four aging markers (X3, X5, X7, and X9) of a test population according to an embodiment of the present invention.
Figure 5 shows the relationship between immune age (ciAge) and birth age (cAge) for four aging markers (X3, X5, X7, and X9) in a test population according to an embodiment of the present invention.
Figure 6 shows the relationship between U-value and birth age for immunosenescent cell subtypes (CD95+ and TIGIT-) according to an embodiment of the present invention.
Figure 7 shows the relationship between S-value and birth age for immunosenescent cell subtypes (CD95+ and TIGIT-) according to an embodiment of the present invention.
Figure 8 shows the relationship between Z-score and birth age for immunosenescent cell subtypes (CD95+ and TIGIT-) according to an embodiment of the present invention.
Figure 9 shows the relationship between immune age and birth age for immunosenescent cell subtypes (CD95+ and TIGIT-) according to an embodiment of the present invention.
Figure 10 shows the relationship between the degree of immune senescence and age at birth for immunosenescent cell subtypes (CD95+ and TIGIT-) according to an embodiment of the present invention.
Figure 11 shows the relationship between the immunosenescence score and birth age for immunosenescence cell subtypes (CD95+ and TIGIT-) according to an embodiment of the present invention.
Figure 12 shows the relationship between the immunosenescence index and birth age for immunosenescence cell subtypes (CD95+ and TIGIT-) according to an embodiment of the present invention.
Figure 13 shows the difference between immune age and birth age for immune senescent cell subtypes (CD95+ and TIGIT-) according to an embodiment of the present invention, classified into 6 sections.
Figure 14 shows the flow of calculating an immune aging evaluation index according to an embodiment of the present invention.

Hereinafter, the present invention will be described in more detail with reference to the attached drawings. However, this description is merely provided as an example to aid understanding of the present invention, and the scope of the present invention is not limited by this example description.

Example 1. Lymphocyte subtype analysis

1-1. Immune cell isolation and staining

Blood collected from 360 healthy adult men and women aged 20 years or older with their consent was used for flow cytometry. All blood was collected between 8 and 10 am on the day of flow cytometry analysis and stored in EDTA tubes, and all blood was used in the experiment within a maximum of 3 hours after blood collection.

To stain markers expressed on the surface of lymphocytes, a fluorescent dye conjugated mouse anti-human antibody that can specifically bind to the marker was used. Antibodies used here include CD3 (BD, 557835), CD8 (BD, 557746), CD56 (BD, 562751), CD27 (BD, 746908), CD28 (BD, 555728), CD45RO (BD, 559865), and CD57 ( BioLegend, 359622), CD62L (BioLegend, 104421), CD70 (BD, 565338), CD95 (BD, 564596), CD197 (BD, 560765), TIGIT (BD, 747840), VISTA (BD, 566670) and CD85j (BD) , 746434).

As a dyeing method, a lyse/wash method known in the art was used, which is briefly explained as follows. First, the blood in the EDTA tube transported to the laboratory was mixed well and then 100 uL was transferred to a test tube for flow cytometry using a micropipette. Then, referring to the antibody manufacturer's instructions, an antibody mix was prepared, mixed well with blood, and blood immune cells were fluorescently stained for 30 minutes at room temperature with light blocked. After staining, red blood cells (RBCs) were removed for smooth flow cytometric analysis of only immune cells. For this purpose, 2 mL of RBC lysis buffer (BD FACSTM Lysing Solution, 349202) was added to each test tube and reacted for 30 minutes at room temperature while blocking light. After completing the reaction, the test tube was centrifuged at 1,500 rpm (RCF 220 to 270) at room temperature for 5 minutes. Then, the supernatant in the test tube containing broken RBCs was removed. Afterwards, 2 mL of phosphate buffered saline (PBS) was added to the test tube with the remaining pellet, and centrifugation was performed under the same conditions as described above. Likewise, after centrifugation was completed, all supernatants were discarded, 300 uL of PBS was added to the test tube, and the tube was stored at 4°C with light blocked until flow cytometry.

1-2. flow cytometry

The stained blood immune cells were flow cytometrically measured and analyzed using a flow cytometer Aurora (Cytek®). On the monitor screen of the flow cytometry system, the immune cell subtype was expressed as a single dot on a graph consisting of the X and Y axes. Immune cells, expressed as dots on the graph, are divided into forward scatter (FSC-A) on the X axis and side scatter (SSC-A) on the Y axis, depending on the size and granularity of the cells. Depending on the size and degree of wrinkles, they were divided into lymphocytes, monocytes, and granulocytes and expressed on the graph. Lymphocyte subtypes were analyzed using a combination of aging markers CD3, CD8, CD56, CD27, CD28, CD45RO, CD57, CD62L, CD70, CD95, CD197, TIGIT, VISTA, and CD85j.

Example 2. Determination of immunosenescent cell subtypes

For the lymphocyte subtypes analyzed in Example 1, the correlation between each distribution rate (%) and birth age was analyzed.

First, lymphocyte subtype and birth age were set as variables, and correlation coefficient (r) and coefficient of determination (r ² ) values were obtained through correlation analysis (Pearson's correlation test). Then, a statistical significance test was performed to select lymphocyte subtypes with a coefficient of determination (r ² ) ≥ 0.01 and a probability of significance (p value) < 0.05. When multicollinearity was diagnosed for these lymphocyte subtypes, none of the variance inflation coefficients exceeded 10, confirming that there were no lymphocyte subtypes causing collinearity problems. Subsequently, linear multiple regression analysis was performed to determine CD95+ and TIGIT-, the lymphocyte subtypes with the highest coefficients of determination, as the immunosenescent cell subtype.

Example 3. Calculation of immune aging evaluation index

Using the immune senescence cell subtypes CD95+ and TIGIT- determined in Example 2, immune senescence evaluation indices, namely, immune age, immune senescence degree, immune senescence score, immune senescence index, and immune age difference, were calculated.

3-1. Immune age calculation

Linear regression models for immunosenescent cell subtypes CD95+ and TIGIT- were confirmed (Table 6).

immune aging
cell subtype unstandardized coefficient standardized coefficient
(β) t Probability of significance
( p ) correlation coefficient
(r) coefficient of determination
(r ² ) B standard error CD95+ 0.416 0.051 0.440 8.196 0.000 0.746 0.556 TIGIT- -0.359 0.050 -0.385 -7.176 0.000 -0.714 0.509

The constant value obtained from the above model and the unstandardized coefficient value (B) for each aging marker (immune senescence cell subtype) were substituted into [Equation 1] to obtain an unstandardized prediction value, which was named U-value.

[Equation 1]

(In Equation 1 above, β ₀ is a constant, βn is the unnormalized coefficient for the nth aging marker, and Xn is the distribution percentage value of the immunosenescent cell subtype including the nth aging marker obtained through flow cytometry)

Figure 6 shows a scatter plot of U-value and birth age. Among the 360 people, the youngest was 20 years old and the oldest was 85, and it was confirmed that the minimum U-value was 27 and the maximum was 68. U-value refers to the overall aging immunity obtained by combining the results of aging markers into a single number, but it was found to be significantly different from birth age.

And the U-value was standardized using [Equation 2], and the S-value was obtained through this.

[Equation 2]

(In Equation 2 above,

Figure 7 shows a scatter plot of S-value and birth age.

And the S-value was normalized again through [Equation 3] and converted to Z-score.

[Equation 3]

(In Equation 3 above, X is the S-value of each individual in the test population, Xmin is the minimum S-value of the entire test population, and

Figure 8 shows a scatter plot of Z-score and birth age.

In addition, assuming that a one-to-one correspondence between Z-score and birth age was established, the final immune age (ciAge) was obtained through [Equation 4], which represents a bijective function.

[Equation 4]

Figure 9 shows the immune age and actual birth age expressed as a scatter plot, and it was observed that the minimum value of the immune age was 20 and the maximum value was 83. These results suggest that the calculated immune age reflects the age at birth rather than the U-value, which is the first aging immunity value, and can be used as an index representing the level of immunity more realistically.

3-2. Calculate immune aging

Using Z-score, the degree of immune senescence (ri-Degree) was obtained through [Equation 5].

[Equation 5]

Figure 10 shows a scatter plot of immune aging and birth age.

3-3. Calculation of immune aging score

Using S-value, the immune aging score (ri-Score) was obtained through [Equation 6].

[Equation 6]

Figure 11 is a scatterplot representation of the immune aging score and birth age.

3-4. Calculation of immune aging index

Using the immune age and birth age, the immune aging index (ri-Index) was calculated through [Equation 7].

[Equation 7]

Figure 12 is a scatterplot representation of the immune aging index and birth age.

3-5. Immune age difference calculation

Using the immune age (ciAge) and birth age (cAge), the immune age difference (IAD) was calculated through [Equation 8].

[Equation 8]

The difference in immune age can be classified into 6 sections as shown in Table 7 and Figure 13 below and can be used to diagnose immunological status and predict risk diseases.

immune age difference
range Immunity section immunological status Target risk disease less than -14 Beware of hyperimmunity (N3) excessive immune activation Autoimmune disease, allergy -14 and above -7 and above Controlled immunity (N2) Healthy normal range, but strong immune activity doesn't exist -7 or more and 0 or less Stable immunity (N1) Mild immune activity predominance Above 0 but below +7 Stable immunity (P1) Mild immunosuppression predominates. Above +7 and below +14 Controlled Immunity (P2) Healthy normal range, but strongly weakened immune system +14 over Beware of decreased immunity (P3) excessively low immunity Cancer, infectious diseases

The algorithm for calculating the immune aging evaluation index is summarized as shown in FIG. 14.

Taken together, immunosenescence, immunosenescence degree, and immunosenescence, which represent the level of immunity reflecting birth age based on specific aging markers or lymphocyte subtypes containing them, were selected to assess immunosenescence by analyzing the relationship between lymphocyte subtypes and birth age. Scores, immune aging indices, and immune age differences can be calculated, and these indices are provided as information to evaluate immune aging and can be usefully used to predict immunity.

So far, the present invention has been examined focusing on its preferred embodiments. A person skilled in the art to which the present invention pertains will understand that the present invention may be implemented in a modified form without departing from the essential characteristics of the present invention. Therefore, the disclosed embodiments should be considered from an illustrative rather than a restrictive perspective. The scope of the present invention is indicated in the claims rather than the foregoing description, and all differences within the equivalent scope should be construed as being included in the present invention.

100: system 110: input unit
120: processing unit 121: first processing unit
122: second processing unit 123: third processing unit
130: calculation unit 131: first calculation unit
132: second calculation unit 133: third calculation unit
134: fourth calculation unit 135: fifth calculation unit
136: 6th calculation unit 137: 7th calculation unit
140: display unit

Claims (15)

a) Obtaining birth age and biological samples from the subject;
b) measuring lymphocyte subtypes from the biological sample;
c) conducting a correlation analysis between the lymphocyte subtype and birth age to first select a lymphocyte subtype with a coefficient of determination (r ² ) ≥ 0.01 and a significance probability (p value) <0.05;
d) performing multicollinearity diagnosis among the first selected lymphocyte subtypes to secondarily select lymphocyte subtypes with variance inflation factor (VIF) <10 or tolerance limit ≥ 0.1;
e) performing a linear multiple regression analysis on the second selected lymphocyte subtypes and determining the one with the highest coefficient of determination as the immunosenescent cell subtype; and
f) calculating an immune senescence evaluation index using the immunosenescence cell subtype,
Step f) includes i) calculating a U-value, which is an unstandardized predictive value, by applying the constant obtained from the linear multiple regression analysis of the immune senescent cell subtype and the unstandardized coefficient for the aging marker to Equation 1 below;
[Equation 1]

(In Equation 1 above, β ₀ is a constant, βn is the unnormalized coefficient for the nth aging marker, and Xn is the distribution percentage value of the immunosenescent cell subtype including the nth aging marker obtained through flow cytometry)
ii) calculating a standardized S-value by applying the U-value to Equation 2 below;
[Equation 2]

(In Equation 2 above,
iii) calculating a normalized Z-score by applying the S-value to Equation 3 below;
[Equation 3]

(In Equation 3 above, X is the S-value of each individual in the test population, Xmin is the minimum S-value of the entire test population, and
iv) calculating the immune age (ciAge) by applying the Z-score and birth age to Equation 4 below;
[Equation 4]

v) calculating the immune senescence degree (ri-Degree) by applying the Z-score to Equation 5 below;
[Equation 5]

vi) calculating an immune aging score (ri-Score) by applying the S-value to Equation 6 below;
[Equation 6]

vii) calculating the immune aging index (ri-Index) by applying the immune age (ciAge) and birth age (cAge) to Equation 7 below; and
[Equation 7]

viii) Calculating the immune age difference (IAD) by applying the immune age (ciAge) and birth age (cAge) to Equation 8 below.
[Equation 8]

Methods for providing information for the assessment of immune aging. In claim 1,
A method wherein the biological sample in step a) is one or more selected from the group consisting of blood, plasma, serum, lymph fluid, tissue fluid, lymph nodes, and cancer tissue. In claim 1,
The lymphocyte subtype in step b) expresses or does not express one or more types selected from the group consisting of CD3, CD8, CD56, CD27, CD28, CD45RO, CD57, CD62L, CD70, CD95, CD197, TIGIT, VISTA and CD85j. How to do it. In claim 1,
The method of measuring step b) using a flow cytometer. delete delete delete delete delete delete delete An input unit for inputting information about the subject's birth age and lymphocyte subtype;
a processing unit that selects immunosenescent cell subtypes using the information; and
It includes a calculation unit that calculates an immune senescence evaluation index using the immune senescence cell subtype,
The processing unit includes a first processing unit that performs a correlation analysis between lymphocyte subtypes and birth age to first select a lymphocyte subtype with a determination coefficient (r ² ) ≥ 0.01 and a significance probability (p value) <0.05;
a second processing unit that performs multicollinearity diagnosis among the first selected lymphocyte subtypes to secondarily select lymphocyte subtypes with a variance inflation factor (VIF) <10 or a tolerance limit ≥0.1; and
A third processing unit that performs linear multiple regression analysis on the second selected lymphocyte subtypes and selects the one with the highest coefficient of determination as the immune senescent cell subtype,
The calculation unit includes a first calculation unit that calculates a U-value through linear multiple regression analysis for the immune senescent cell subtype and normalizes it to calculate an S-value;
a second calculation unit that normalizes the S-value to calculate a Z-score;
a third calculation unit that calculates immune age (ciAge) by performing a one-to-one correspondence between the Z-score and birth age;
a fourth calculation unit that converts the Z-score into a percentage to calculate an immune senescence degree (ri-Degree);
a fifth calculation unit that calculates an immune aging score (ri-Score) by multiplying the S-value by -1;
a sixth calculation unit that calculates an immune aging index (ri-Index) based on the ratio between the immune age and birth age; and
A seventh calculation unit that calculates an immune age difference (IAD) as the difference between the immune age and birth age.
A system for assessing immune aging. In claim 12,
A system wherein the information about the lymphocyte subtype is obtained from flow cytometry. delete In claim 12,
The system further includes a display unit that displays the immune aging evaluation index calculated by the processing unit and the calculation unit.