CN104573408B - Single nucleotide polymorphism disease incidence prediction system - Google Patents
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Abstract
The invention provides a single nucleotide polymorphism disease incidence prediction system, which mainly comprises a prediction server, a frequency database, a data processing module and a data processing module, wherein the prediction server collects more than one group of personal data and gene data, respectively transmits the personal data and the gene data to the personal database for storage and a gene risk database for data exchange; the prediction server generates genetic risk data after calculation according to the single nucleotide polymorphism data, the risk data and the frequency data, acquires a plurality of prevalence rate data through a prevalence rate database, and rapidly generates a prediction report according to the prevalence rate data and the genetic risk data, thereby achieving the purpose of facilitating a user to acquire reference data of the incidence rate of diseases related to the gene in a more efficient manner.
Description
Technical field
The present invention is on a kind of disease incident forecasting system, espespecially a kind of multitype database with predictive server
Data carry out computing, with the system being predicted for the related disease incident of single nucleotides polymorphism (SNP).
Background technology
Modern is relatively easy to suffer from ciril disease, especially hyperglycaemia, high fat of blood, hypertension (being commonly called as three high), according to mesh
Preceding medical research points out, three is high relevant with gene, and in each species diversity of human inheritance's gene, and having 90% all can attribution
In the genetic mutation caused by single nucleotides polymorphism (Single Nucleotide Polymorphism, SNP), that is,
The variation of single nucleotide acid on DNA sequence dna, research related SNP in medical domain is fairly common at present, it is known that part SNP
The structure function of protein can be influenceed, changes the performance amount or physiological trend of gene sometimes, and then influence to the easy of disease
Perception or the reaction to some drugses and metabolic capability.
Such as TaiWan, China patent for invention the I357442nd, " hypertension, triglyceride be higher and wind of metabolic syndrome
Danger prediction ", it includes investigating lipoprotein catabolic enzyme (LPL) gene order of a patient, and forementioned gene sequence is selected from two lists
Cover genotype, its respectively, metabolic syndrome higher with hypertension, triglyceride it is relevant, wherein a single set genotype contains three
Individual SNP and hypertension, triglyceride is higher significant correlation, and another single set genotype contains four SNP and hypertension
Also there is significant correlation with reference to triglyceride is higher.The offer of foregoing invention patent right is a kind of to be examined to lpl gene sequence
The mode of survey, can be used to assess the risk for producing the medical conditions such as hypertension, the higher, metabolic syndrome of triglyceride.
And for example TaiWan, China patent for invention the I383776th " forecast body weight system and method ", wherein the body weight is pre-
Examining system includes one first input block, a first processing units, one second input block, a second processing unit, an output
Unit and a memory cell；First input block is to receive multiple regional user's information, user's packet
Include the size (such as height, waistline, hip circumference) of basic physiological data (such as identification code, name, sex, age), body；This
One processing unit is connected with the first input block, and with a neural network and a fuzzy logic system, passes through class nerve net
Network handles user's information, to obtain the parameter of correspondence each department user, then via fuzzy logic system to user's information
After further processing, parameter is verified and adjusted, and then produce a Prediction Parameters；
Second input block receive user's information, the second processing unit respectively with first, second input block
Connection, and user's information handled according to the Prediction Parameters to obtain an information of forecasting, then by the information of forecasting
It is sent in the output unit and the memory cell and stores, and is supplied to user to refer to.Foregoing invention patent is to pass through
Its Forecasting Methodology is performed in forecast body weight system, carrying out multiple intersection to user's information compares analysis, and passes through class
The current physiologic information of user estimates following body weight state of user for neutral net, fuzzy logic system, is carried with reaching
The purpose that awake user notes self health status and prevents relevant disease to occur.
However, by way of being analyzed (such as investigation lpl gene sequence) medical science unit or record analysis physiology is believed
Cease to estimate the following body weight of user, it is quite inconvenient for user and be difficult to, divide through medical science unit
It is long to provide in the way of artificial judgment the time that suggestion spent after analysis again, still lacks efficiency, and only with physiologic information estimation not
The mode for carrying out body weight is to reach the generation of prevention relevant disease, and reliability is still lacked for user.Therefore, it is above-mentioned
Prior art needs to be proposed the necessity of more preferably solution really.
The content of the invention
In view of above-mentioned the deficiencies in the prior art, present invention is primarily intended to provide a kind of single nucleotides polymorphism
(SNP) disease incident forecasting system, by carrying out exchanging for data between personal data, gene data and multiple databases,
The data of exchange are subjected to computing via forecasting system and prediction address is produced, user is provided in quick and efficient mode
Reference data on autogene relevant disease incidence.
To be to make foregoing single nucleotides polymorphism disease incident pre- up to the technical way that above-mentioned purpose is taken
Examining system includes：
One predictive server, personal data, gene data to collect more than one group, and entered by the predictive server
Row data exchange, produces collected data one pre- the observing and predicting for supplying user's reference via data exchange after calculation process
Accuse；
One individual database, is connected with the predictive server, to receive personal data and store；
One gene vulnerability database, with multiple SNP data corresponding with forementioned gene data respectively, risk data,
And it is connected with foregoing predictive server；
One antithesis gene frequency database, is connected with predictive server, with it is multiple respectively with foregoing SNP data, risk
The corresponding frequency data of data；
One rate database prevailing, is connected with foregoing predictive server, and with multiple prevalence rate data, to be supplied to
Predictive server computing produces prediction address and used.
The present invention is performed after a detection project via user, by the predictive server by the personal data being collected into, base
Factor data is transferred to individual database storage, gene vulnerability database and carries out data exchange respectively, according to gene data by gene
Corresponding SNP data and risk data are obtained in vulnerability database, then SNP data and risk data are sent to the reciproccal basis
Because of frequency database, to exchange corresponding frequency data, and obtain related to the detection project by rate database prevailing
Prevalence rate data；When predictive server via above-mentioned data exchange process obtains SNP data, risk data, frequency data,
And using a genetic risk data are produced after foregoing each data operation, according to the genetic risk data and foregoing prevalence rate data
To produce the prediction address related to the detection project, using above-mentioned technology can easily and fast, efficient provide user side
Just the reference data with autogene relevant disease incidence is obtained, to take preventive measures ahead of time.
Brief description of the drawings
Fig. 1 is a preferred embodiment of the present invention system architecture block diagram；
Fig. 2 is application mode schematic diagram of the invention；
Fig. 3 is prediction address statistical chart of the invention；
Fig. 4 is another application mode schematic diagram of the invention；
Fig. 5 is another prediction address statistical chart of the invention；
Fig. 6 is another application schematic diagram of the present invention；
Fig. 7 is another prediction address statistical chart of the invention.
Reference
The individual database 20 of predictive server 10
The SNP data fields 31 of gene vulnerability database 30
The allel frequency database 40 of risk data area 32
The user's terminal 60 of rate database 50 prevailing
Prediction address data out terminal 70
Embodiment
On a preferred embodiment of single nucleotides polymorphism (SNP) disease incident forecasting system of the invention, it please join
Examine shown in Fig. 1, including a predictive server 10, an individual database 20, a gene vulnerability database 30, an allel
Frequency database 40, a rate database 50 prevailing.
The predictive server 10 is connected by network with more than one user's terminal 60, and user's terminal 60 is for making
User inputs more than one group of personal data, gene data, the predictive server 10 respectively with foregoing rate database 50 prevailing, right
Even gene frequency database 40, gene vulnerability database 30 and individual database 20 are connected, by predictive server 10 with it is foregoing
Each database 20,30,40,50 carries out data exchange, passes through calculation process to produce by collected data via data exchange
The prediction address that one confession user refers to, the prediction address, by data output, is incited somebody to action by a prediction address data out terminal 70
It is quickly supplied to user to refer to.
Foregoing individual database 20 is to receive the personal data that predictive server 10 is transmitted, and by all numbers
According to storing respectively, it can be taken at any time with providing when the evaluating server 10 needs.
The gene vulnerability database 30 receives the gene data that foregoing predictive server 10 is sent out, the gene risk data
Storehouse 30 has multiple SNP data corresponding with forementioned gene data respectively, risk data, and the predictive server 10 is according to gene
Data carry out data exchange to obtain corresponding SNP data, risk data with gene vulnerability database 30.
In the present embodiment, the gene vulnerability database 30 further comprises a SNP data fields 31, a risk data area 32；
The SNP data fields 31 include multiple genotype for accessing above-mentioned SNP data, the SNP data, and each genotype is mainly respectively by two pairs
Even gene is constituted, and one pair of which idol gene comes from father, and another allel comes from mother, for example：Pair in a certain SNP data
Even gene is G and A, then the genotype that may be constituted just has three kinds of combinations such as GG, GA, AA.
The risk data area 32 refers to that an odds compares data for accessing above-mentioned risk data, the risk data
(OddsRatio, OR), the odds than data is made comparisons according to the odds of two pieces thing to calculate the odds than data, in
In the present embodiment, the odds represents genotype than data or allel can influence the risk whether fallen ill.
Above-mentioned allel frequency database 40 receives the SNP data for storing the predictive server 10 and being sent out, risk number
There are multiple frequency data corresponding with foregoing SNP data, risk data respectively according to, the allel frequency database 40,
The predictive server 10 carries out after data exchange obtaining the frequency data with allel frequency database 40；The present embodiment
In, the frequency data refer to an antithesis gene frequency data, and it refers to the ratio shared by allel and genotype in a certain group
Rate, for example：Assuming that totally 3 people have GG genotype among 6 people, then GG genotype frequencies are 0.5, if wherein 2 people have GA genotype,
GA genotype frequencies are 0.333, and AA genotype only has 1 people, therefore AA genotype frequencies are 0.167, thus can be deduced, antithesis
When gene number is 12, wherein there is 8 G allels, its allel frequency is 0.667, and A allels totally 4, then
A allels frequency is 0.333.
The rate database 50 prevailing has multiple prevalence rate data, and predictive server 10 is obtained by rate database 50 prevailing
The prevalence rate data related to a detection project；When predictive server 10 via above-mentioned data exchange process obtain SNP data,
Risk data, frequency data, and go out multiple relative risk data (Relative Risk, RR) using foregoing each data operation
Afterwards, then by each relative risk data a genetic risk data (Genetic Risk) are produced, according to the relative risk data with before
State prevalence rate data and carry out computing, the prediction address related to the detection project is produced with quick.
In the present embodiment, the gene vulnerability database 30, the allel frequency database 40, the rate database 50 prevailing
All can be an external data base, the predictive server 10 with the grade external data base by being connected, after being updated at any time
Multiple SNP data, risk data, frequency data, the prevalence rate data deposited respectively in each external data base.
In the present embodiment, the predictive server 10 collects related to any detection project by user's terminal 60
Personal data, gene data, be transferred to respectively individual database 20 store, gene vulnerability database 30 carry out data exchange, foundation
Gene data obtains corresponding SNP data in gene vulnerability database 30 and represents the odds of risk data than data, then
SNP data and odds are sent to the allel frequency database 40 than data, to exchange corresponding frequency data, and
The prevalence rate data related to the detection project are obtained further through rate database 50 prevailing；
When predictive server 10 via above-mentioned data exchange process obtains grade SNP data, the odds than data, frequency number
According to, and gone out using foregoing each data operation in multiple relative risk data, the present embodiment, the further root of predictive server 10
Genetic risk data are produced according to all relative risk data, are transported by the genetic risk data with foregoing prevalence rate data
Calculate with the prediction data of each physiological periods of the quick generation person of being suitable for use with, using easily and fast, efficient way,
User is provided the convenient reference data obtained with autogene relevant disease incidence, to reach what is taken preventive measures ahead of time
Purpose.
A concrete application mode of single nucleotides polymorphism (SNP) disease incident forecasting system to illustrate the invention,
It refer to shown in Fig. 2, in the present embodiment, when having a testee (for example：Chinese) and carried out a detection in a medical science unit
After the project physical examination related to the second patients with type Ⅰ DM, the medical science unit can obtain personal data (such as nationality, year of testee
Age, identity documents etc.), gene data, testee or healthcare givers can be linked by user's terminal 60 with predictive server 10,
And logined with a voucher for representing testee's status, it can be obtained after logining by prediction address data out terminal 70 by above-mentioned prediction
Server 10 produces the prediction address referred to for testee or healthcare givers, and offer testee or medical treatment in the form of tables of data
Information below personnel：
The SNP data related to the second patients with type Ⅰ DM are most genes and its SNP site, including SLC30A8 genes
Rs13266634, KCNQ1 gene rs2237895, PTPED gene rs17584499, SRR gene rs391300, KCNJ11 gene
Rs5219, CDKAL1 gene rs10946398, CDKN2A/B gene rs10811661, TCF7L2 gene rs7903146, HHEX base
Because of rs1111875, PPARG gene rs1801282 etc.；Each gene in the SNP data is respectively to that should have testee's multiple
Gene data (such as genotype) and relative risk data (RR), and the genetic risk data on testee are provided
(Genetic Risk)。
Multiple prevalence rate data (such as Chinese's average originating rate) are provided by rate database 50 prevailing, it is respectively Second-Type sugar
The prevalence rate data of the related all ages of urine disease, testee's phase is produced according to the prevalence rate data and genetic risk data
Incidence is predicted for the second patients with type Ⅰ DM of all ages.
It refer to shown in Fig. 3 curve map, be one second patients with type Ⅰ DM prediction Incidence result；Wherein include a generation
The trunnion axis of table age level and the vertical axis for representing incidence percentage, the age level of the trunnion axis stopped by 20 years old to 79 years old
And with 10 years old for age level, when the average incidence percentage between 40 years old to 59 years old of Chinese by 5.7 rises to 14.3
When, the second patients with type Ⅰ DM incidence percentage that testee is predicted between 40 years old to 59 years old is equally risen to by 3.75
9.41, although it follows that testee is average less than Chinese in the incidence of 40 years old to 49 years old, display testee's genetic prerequisite compared with
It is good, but still similar to the averagely soaring amplitude of Chinese to the soaring amplitude of its incidence between 59 years old, therefore testee still must
Note in itself in situations such as posteriori diet, work and rest, life styles, to take preventive measures ahead of time.
Another concrete application mode, refer to shown in Fig. 4 in the present embodiment, wherein being a Chinese testee in the medical science list
Position one detection project of progress is related to hypertension, and testee or healthcare givers can be supplied by prediction address data out terminal 70
Testee or the prediction address of healthcare givers's reference, and to provide the letter below testee or healthcare givers in the form of tables of data
Breath：
The SNP data related on hypertension are most genes and its SNP site, including AGT genes rs699,
ADD1 gene rs4961, NOS3 gene rs1799983, CYP17A1 gene rs11191548, FGF5 genes rs16998073,
AGTR1 gene rs5186, NEDD4L gene rs3865418, STK39 gene rs3754777, CALCA genes rs3781719 etc.；
The multiple gene datas (such as genotype) and relative risk data (RR) phase of each gene respectively with testee in tables of data
Correspondence, and the genetic risk data (Genetic Risk) on testee are provided；There is provided multiple by rate database 50 prevailing
Prevalence rate data (such as Chinese's average originating rate), multiple prevalence rate data are respectively the prevalence rate of the related all ages of hypertension
Data, the hypertension that testee is produced according to the prevalence rate data and genetic risk data relative to all ages predicts hair
Raw rate.
It refer to shown in Fig. 5 curve map, be hypertension prediction Incidence result；It represents age level comprising one
Trunnion axis and represent the vertical axis of incidence percentage, the age level of the trunnion axis stopped and with 10 years old by 20 years old ing to 79 years old
For an age level, when Chinese is average increases to 11.9 by 3.7 in the mortality of hypertension percentage between 20 years old to 39 years old,
The mortality of hypertension percentage that testee is predicted between 20 years old to 39 years old is to increase to 11.21 by 3.49, it follows that
Testee is average close in mortality of hypertension and the Chinese of 20 years old to 39 years old, incidence at even 70 years old to 79 years old all with
Chinese is average similar, therefore testee need to pay special attention to the situations such as diet, work and rest, life style usually.
Another concrete application mode, refer to shown in Fig. 6 in the present embodiment, and its application mode and aforementioned applications mode are substantially
Identical, only detection project is different, and the detection project is related to high fat of blood, and testee or healthcare givers are by prediction address number
The prediction address for obtaining referring to for testee or healthcare givers according to outlet terminal 70, and provided in the form of tables of data testee or
Information below healthcare givers：
The SNP data related to high fat of blood are most genes and its SNP site, including LDLR genes rs1003723,
APOB gene rs1367117, APOA5 genes rs2075291, lpl gene rs326, APOE gene rs4420638, GCKR gene
Rs780094, GALNT2 gene rs4846914, LIPC gene rs1800588, HMGCR gene rs12654264, CETP gene
Rs3764261, MLXIPL gene rs17145738 etc.；The grade gene corresponds to the multiple gene datas relevant with testee respectively
(such as genotype) and relative risk data (RR), and the genetic risk data (Genetic on testee is provided
Risk)；Multiple prevalence rate data (such as Chinese's average originating rate) are provided by rate database 50 prevailing, it is respectively that high fat of blood is related
All ages prevalence rate data, produce testee relative to each year according to the prevalence rate data and genetic risk data
The high fat of blood prediction incidence of age layer.
It refer to shown in Fig. 7 curve map, be the analysis result that a high fat of blood predicts incidence；Wherein year is represented comprising one
The trunnion axis of age layer and the vertical axis of incidence percentage is represented, the age level of the trunnion axis was stopped simultaneously to 79 years old by 20 years old ing
It was an age level with 10 years old, when the average high fat of blood incidence percentage between 40 years old to 59 years old of Chinese is risen to by 19.7
When 28.6, the incidence percentage that testee is predicted between 40 years old to 59 years old only increases to 13.93 by 9.59, therefore, by
Survey person is average far below Chinese in the incidence of 40 years old to 59 years old, and display testee's genetic prerequisite is preferable so that 40 years old extremely
The amplitude that rises of high fat of blood prediction incidence is smaller between 59 years old, but testee's still notably weather itself.
From the foregoing, single nucleotides polymorphism (SNP) disease incident forecasting system of the invention, mainly pre- by this
Survey server 10 and the personal data being collected into, gene data are transferred to individual database storage 20, gene risk data respectively
Storehouse 30 carries out data exchange, and the allel frequency database 40 is sent to according to by acquired SNP data and risk data
To exchange corresponding frequency data, and prevalence rate data are obtained by rate database 50 prevailing；When predictive server 10 is passed through
SNP data, risk data, frequency data are obtained by above-mentioned data exchange process, and lost using being produced after aforementioned data computing
Risk data is passed, the genetic risk data produce prediction address with prevalence rate data after computing again, i.e., easily and fast had again
The reference data that user and autogene relevant disease incidence are provided of efficiency, to take preventive measures ahead of time.
It is described above, only it is presently preferred embodiments of the present invention, any formal limitation, Ren Hesuo not is made to the present invention
Belong to those of ordinary skill in technical field, if not departing from the range of the present invention carries technical characteristic, taken off using of the invention
Show made by technology contents the equivalent embodiment for locally changing or modifying, in the range of still falling within the technology of the present invention feature.
Claims (5)
1. a kind of single nucleotides polymorphism disease incident forecasting system, it is characterised in that the single nucleotides polymorphism
Disease incident forecasting system includes：
One predictive server, personal data, gene data to collect more than one group, and carried out by the predictive server
Data exchange, produces collected data one pre- the observing and predicting for supplying user's reference via data exchange after calculation process
Accuse；
One individual database, is connected with the predictive server, to receive personal data and store；
One gene vulnerability database, with multiple single nucleotides polymorphism data corresponding with the gene data respectively,
Risk data, and be connected with the predictive server；
One antithesis gene frequency database, is connected with predictive server, with it is multiple respectively with the single nucleotides polymorphism
The corresponding frequency data of data, risk data；
One rate database prevailing, is connected with the predictive server, and with multiple prevalence rate data, to be supplied to prediction
Server operation produces prediction address；
The gene vulnerability database further comprises a single nucleotides polymorphism data field, a risk data area；The list
One nucleotides polymorphism data field is for accessing the single nucleotides polymorphism data, the single nucleotides polymorphism packet
Include multiple genotype；The risk data area is to access the risk data, and the risk data refers to an odds ratio
Data；
The frequency data refer to an antithesis gene frequency data；
The allel frequency data are the allel in a group and the ratio shared by genotype；
The predictive server obtains single nucleotides polymorphism data, risk data, frequency via the data exchange process
Data, and go out multiple relative wind using the single nucleotides polymorphism data, risk data and frequency data data operation
Dangerous data, then produce a genetic risk data by each relative risk data；
Computing is carried out by the genetic risk data and the prevalence rate data to produce prediction incidence data.
2. single nucleotides polymorphism disease incident forecasting system according to claim 1, it is characterised in that the list
One nucleotides polymorphism data include：SLC30A8 gene rs13266634, KCNQ1 gene rs2237895, PTPED genes
Rs17584499, SRR gene rs391300, KCNJ11 gene rs5219, CDKAL1 gene rs10946398, CDKN2A/B gene
Rs10811661, TCF7L2 gene rs7903146, HHEX gene rs1111875, PPARG gene rs1801282.
3. single nucleotides polymorphism disease incident forecasting system according to claim 1, it is characterised in that the list
One nucleotides polymorphism packet contains：AGT gene rs699, ADD1 gene rs4961, NOS3 genes rs1799983, CYP17A1
Gene rs11191548, FGF5 gene rs16998073, AGTR1 gene rs5186, NEDD4L gene rs3865418, STK39 base
Because of rs3754777, CALCA gene rs3781719.
4. single nucleotides polymorphism disease incident forecasting system according to claim 1, it is characterised in that the list
One nucleotides polymorphism data include LDLR gene rs1003723, APOB gene rs1367117, APOA5 genes rs2075291,
Lpl gene rs326, APOE gene rs4420638, GCKR gene rs780094, GALNT2 gene rs4846914, LIPC gene
Rs1800588, HMGCR gene rs12654264, CETP gene rs3764261, MLXIPL gene rs17145738.
5. single nucleotides polymorphism disease incident forecasting system according to any one of claim 1 to 4, its feature
It is, the single nucleotides polymorphism disease incident forecasting system further provides for more than one user's terminal, institute
State user's terminal to be connected with predictive server, user's terminal supplies more than one group of personal data, gene data；
Collected data are passed through into calculation process to produce a prediction address referred to for user via the data exchange, it is described
Prediction address is by a prediction address data out terminal by data output.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| TW102137606 | 2013-10-18 | ||
| TW102137606A TW201516725A (en) | 2013-10-18 | 2013-10-18 | Single nucleotide polymorphism disease incidence prediction system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104573408A CN104573408A (en) | 2015-04-29 |
| CN104573408B true CN104573408B (en) | 2017-08-25 |
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| CN105354444B (en) * | 2015-11-24 | 2018-06-19 | 华南理工大学 | Method based on the susceptible SNP combinations of susceptible SNP screenings complex disease |
| CN106202996A (en) * | 2016-07-16 | 2016-12-07 | 广州泰因生物科技有限公司 | A kind of for the evaluation methodology of analysis of biological information technology used by high-flux sequence SNP |
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| US20060051790A1 (en) * | 2004-07-01 | 2006-03-09 | The Regents Of The University Of California | Genetic risk factor for neurodegenerative disease |
| AU2007325021B2 (en) * | 2006-11-30 | 2013-05-09 | Navigenics, Inc. | Genetic analysis systems and methods |
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