CN111424079A - Health aging diagnosis circRNA marker and application - Google Patents

Abstract

The invention discloses a healthy aging diagnosis circRNA marker and application thereof, wherein the healthy aging diagnosis circRNA marker comprises 22 circRNAs, nucleotide sequences of the circRNAs are shown as SEQ ID NO.1-22, the circRNA markers have the characteristics of high accuracy and high sensitivity, and the area AUC under a prediction line reaches 0.914, so that the healthy aging diagnosis circRNA marker is prompted to have higher accuracy and sensitivity, and can be directly used as an index of healthy old people.

Description

Health aging diagnosis circRNA marker and application

Technical Field

The invention belongs to the technical field of biomedicine, and particularly relates to a healthy aging diagnosis circRNA marker and application thereof.

Background

Chinese walk into the aging society of the population is a visible trend, and the derived support problems and high medical care cost of the senile diseases are a disproportionate burden for individuals and countries. The social circles have also started active discussion and response to the problems caused by aging of the population, and research on the prevention and treatment of senile diseases and healthy aging is an important task. The health aging characteristics of the aged population are evaluated by exploring the health aging markers, and the method is an essential part in the scientific research of health aging.

At present, in the research on health aging and longevity, the mainstream research thought in the world is to search for longevity-related genetic variation starting from genome, but the information obtained by genetic research to date is very limited. Based on the existing research, the transcriptome information and epigenetic factors have important regulation and control functions on the healthy aging process. Therefore, the search of markers capable of indicating healthy aging characteristics from the perspective of transcriptomics has an important propulsion role for the whole healthy aging research work. The circRNA is a special RNA molecule with a closed ring structure in transcriptome information, and due to the special structure, the circRNA has strong stability and specificity and is an excellent choice as a molecular diagnostic marker. Notably, various studies have found that circRNA plays an important regulatory role in some senile diseases, such as alzheimer's disease, parkinson's disease, atherosclerosis, tumors, etc., and therefore, there is a need to develop new healthy aging markers based on circRNA.

Disclosure of Invention

In view of the above, the present invention provides a healthy aging diagnosis circRNA marker and applications thereof.

In order to solve the above technical problems, the present invention discloses a healthy aging diagnosis circRNA marker, which comprises one or more of hsa _ circ _0005838, hsa _ circ _0001788, hsa _ circ _0007883, hsa _ circ _0000396, hsa _ circ _0069399, hsa _ circ _0024193, hsa _ circ _0132409, hsa _ circ _0001392, hsa _ circ _0007132, hsa _ circ _0006037, hsa _ circ _0001317, hsa _ circ _0000267, hsa _ circ _0000497, hsa _ circ _0067716, hsa _ circ _0000311, hsa _ circ _0008234 a _ circ _ cihs _0001386, hsa _ circ _0000330, hsa _ circ _0001346, hsa _ circ _ 5 _0003496, and hsa _ circ _ 0000259.

Alternatively, the nucleotide sequence of the healthy aging diagnostic circRNA marker is shown in SEQ ID NO. 1-22.

The invention also discloses application of the healthy aging diagnosis circRNA marker in preparing a healthy aging early diagnosis product, wherein the diagnosis product comprises a reagent for detecting the one or more markers, and the reagent is used for judging whether the subject has the possibility of healthy aging by detecting the expression value of the one or more markers in the body of the subject.

Optionally, in particular detecting the expression value of one or more markers in the blood of the subject.

Optionally, the expression of the markers hsa _ circ _0005838, hsa _ circ _0007883, hsa _ circ _0069399, hsa _ circ _0001392, hsa _ circ _0007132, hsa _ circ _0000267, hsa _ circ _0000311, hsa _ circ _0001386, hsa _ circ _0000330 is significantly increased in healthy elderly.

Optionally, the markers hsa _ circ _0001788, hsa _ circ _0000396, hsa _ circ _0024193, hsa _ circ _0132409, hsa _ circ _0006037, hsa _ circ _0001317, hsa _ circ _0000497, hsa _ circ _0067716, hsa _ circ _0008234, hsa _ circ _0001346, hsa _ circ _0006965, hsa _ circ _0000259, and hsa _ circ _0003496 are significantly reduced in expression in the healthy elderly.

Optionally, the diagnostic product is a kit, chip or assay platform.

The invention also discloses an application of the healthy aging diagnosis circRNA marker in healthy aging diagnosis.

Optionally, the method comprises the following steps:

step 1, taking fresh anticoagulated blood of an old aged over 65 years old, and extracting total RNA of leucocytes;

step 2, removing rRNA from the obtained RNA sample, preparing the sample according to an Illumina RNA-seq library preparation manual, and performing sequencing on an Illumina Hiseq-2500 platform after the preparation is finished and the quality detection is qualified; identifying and quantifying circRNA according to the sequencing data by using a procedure of CIRCCexplor software, and finally obtaining expression data of all circRNA;

and 3, extracting expression value data of the 22 circRNA markers from the circRNA expression data, introducing the expression value data into a healthy aging diagnosis model, and analyzing the obtained score numerical value, wherein if the numerical value is more than 0.5 and is closer to 1, the characteristic tendency of healthy aging of the testee is higher, and conversely, the characteristic tendency of healthy aging is lower as the numerical value is closer to 0.

Alternatively, the healthy aging diagnostic model is: score is the sum of the coefficients for each circRNA marker plus 0.162271651 for the sample expression values.

Compared with the prior art, the invention can obtain the following technical effects:

the novel blood health aging diagnosis circRNA marker multiple linear regression model provided by the invention has the characteristics of high accuracy and high sensitivity, the area AUC under the prediction line reaches 0.914, and the prediction line has higher accuracy and sensitivity, so that the model can be directly used as an index of health aging.

Of course, it is not necessary for any one product in which the invention is practiced to achieve all of the above-described technical effects simultaneously.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention and not to limit the invention. In the drawings:

FIG. 1 is a ROC curve of a healthy aging diagnostic model based on 22 circRNA markers according to the present invention;

FIG. 2 is the model accuracy judgment of healthy aging diagnosis based on 22 circRNA markers in the present invention.

Detailed Description

The following embodiments are described in detail with reference to the accompanying drawings, so that how to implement the technical features of the present invention to solve the technical problems and achieve the technical effects can be fully understood and implemented.

The invention further analyzes and compares the circRNA expression profiles of the centenarian and normal control population based on transcriptome data of China's family of centenarian, and searches for a key circRNA molecular marker capable of representing healthy aging.

Among them, the world health organization defines healthy aging as: in the elderly stage, the process of maintaining a series of functional abilities (including self-satisfying self-needs; learning and making decisions; acting, establishing and maintaining interpersonal relationships; contributing to society) to make self-life valuable (https:// www.who.int/serving/health-serving/en /)

To achieve healthy aging, it is essential that senile diseases (aged disease [ M ]. scientific press, 2011, 1/1) and serious diseases (defined in "standard for defining disease for insurance of serious diseases" started from 4/3/2007) be avoided during aging, and that the elderly stage is passed with little morbidity and extremely low hospitalization rate.

Example 1 healthy aging diagnosis circRNA marker

The invention discloses a healthy aging diagnosis circRNA marker, which can be used for carrying out healthy early diagnosis by single or combination of two or more than two, and comprises one or more of hsa _ circ _0005838, hsa _ circ _0001788, hsa _ circ _0007883, hsa _ circ _0000396hsa _ circ _0069399, hsa _ circ _0024193, hsa _ circ _0132409, hsa _ circ _0001392, hsa _ circ _0007132, hsa _ circ _0006037, hsa _ circ _0001317, hsa _ circ _0000267, hsa _ circ _0000497, hsa _ circ _0067716, hsa _ circ _0000311, hsa _ circ _0008234 _ circ _0001386, hsa _ circ _0000330, hsa _ circ _0001346, hsa _ circ _0003496 and hsa _ 0000259.

Through the analysis of the whole transcriptome data of 71 centuries (the age range is 93-111 years, the average age is 98.3 years) and 115 control groups (the age range is 23-86 years, the average age is 54.4 years) such as 21 healthy elderly people with long lives and 29 common people in Hainan Ming county (86 common people) and Hainan Lingshui county (50 healthy elderly with long lives) in China, a plurality of circrnas are subjected to variable screening and L ASSO regression modeling, a healthy aging diagnosis model fitted by 22 circRNA markers is obtained, the coefficients of the L O regression model of the 22 healthy aging diagnosis circRNA markers are shown in table 1, the expression quantity of the measured circrnas is calculated in the multivariate regression model according to the coefficients corresponding to the 22 circrnas in table 1, the finally obtained result value is compared with the value "1", and the result is closer to 1, so that the healthy aging state of the subject is better.

TABLE 1 coefficients of regression model for 22 healthy aging diagnosis circRNA markers L ASSO

Wherein, compared with a control group, the 22 blood health aging diagnosis circRNA markers have increased expression in healthy and long-lived elderly people as follows: hsa _ circ _0005838, hsa _ circ _0007883, hsa _ circ _0069399, hsa _ circ _0001392, hsa _ circ _0007132, hsa _ circ _0000267, hsa _ circ _0000311, hsa _ circ _0001386, hsa _ circ _0000330, 9 in total.

Compared with a control group, the 22 circRNA markers for diagnosing blood health aging have reduced expression in healthy and long-lived elderly: hsa _ circ _0001788, hsa _ circ _0000396, hsa _ circ _0024193, hsa _ circ _0132409, hsa _ circ _0006037, hsa _ circ _0001317, hsa _ circ _0000497, hsa _ circ _0067716, hsa _ circ _0008234, hsa _ circ _0001346, hsa _ circ _0006965, hsa _ circ _0000259, hsa _ circ _0003496, 13 in total.

The ROC curve and accuracy judgment of the healthy aging prediction by the 22 healthy aging diagnosis circRNA marker L ASSO regression model are shown in FIG. 1 and FIG. 2, wherein FIG. 1 is the ROC curve of the healthy aging prediction, the area AUC under the line reaches 0.914, which shows that the diagnosis of the healthy aging by the regression model is very high in indication, FIG. 2 is a judgment of the model prediction accuracy, based on the model, the score value of the centenarian is mostly greater than 0.5, but the score value of the non-centenarian is basically less than 0.5, and the two groups of data have statistical significance, and p is less than 2.2 e-16.

Example 2 diagnosis of healthy aging use of circRNA marker for diagnosis of healthy aging

Step 1, taking fresh anticoagulated blood of the old aged over 65 years old, and extracting total RNA of leucocytes.

And 2, removing rRNA from the obtained RNA sample, preparing the sample according to an Illumina RNA-seq library preparation manual, and performing sequencing on an Illumina Hiseq-2500 platform after the preparation is finished and the quality detection is qualified. And identifying and quantifying circRNA according to the sequencing data by using a procedure of CIRCCexplor software, and finally obtaining the expression quantity data of all circRNA.

And 3, extracting expression value data of the 22 circRNA markers from the circRNA expression data, introducing the expression value data into the healthy aging diagnosis model, and analyzing the obtained score numerical value, wherein if the numerical value is more than 0.5 and is closer to 1, the characteristic tendency of healthy aging of the testee is higher, and conversely, the characteristic tendency of healthy aging is lower as the numerical value is closer to 0.

Wherein, the health aging diagnosis model is as follows: score is the sum of the coefficients for each circRNA marker plus 0.162271651 for the sample expression values.

The following table 2 lists the expression values of the 22 circRNA markers in this example 2.

TABLE 2 expression values of 22 circRNA markers in example 2

The circRNA expression data listed in table 2 above were included in the prediction model and score values were calculated.

Score＝0.004813506*-2.8893159+-0.00602057*-1.2924478+0.054268028*-1.0886325+-0.043346135*-2.0680898+0.182245403*-0.3867061+-0.076498721*-1.7936834+-0.007908873*-23.5163253+0.030864014*-4.1989216+0.004586626*-2.5476627+-0.033309414*-2.695194+-0.020810454*-2.479106+0.043764647*-2.0763841+-0.12122826*-2.4648689+-0.02394792*-3.3713666+0.034194114*-2.3551334+-0.052395858*-5.1824166+0.058133963*-2.7962934+0.021816504*-1.883381+-0.003974949*-1.4069132+-0.004109221*-3.1118399+-0.019001008*-2.2118892+-0.01426827*-2.8124718+s0(0.162271651)＝0.816

From the above, the sample has a score of 0.816, which is greater than 0.5 and close to 1, indicating a healthy aging propensity of the sample.

While the foregoing description shows and describes several preferred embodiments of the invention, it is to be understood, as noted above, that the invention is not limited to the forms disclosed herein, but is not to be construed as excluding other embodiments and is capable of use in various other combinations, modifications, and environments and is capable of changes within the scope of the inventive concept as expressed herein, commensurate with the above teachings, or the skill or knowledge of the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.

SEQUENCE LISTING

<110> Kunming animal research institute of Chinese academy of sciences

<120> healthy aging diagnosis circRNA marker and application

<130>2020

<160>22

<170>PatentIn version 3.3

<210>1

<211>959

<212>DNA

<213> human (human)

<400>1

gacagattga ttcactttgg agctgtaagt actgatgtat tagggtgcag cgctcattgt 60

tccttgacgc agagtcccaa aatgaatatc caagagcagg gtttcccctt ggacctcgga 120

gcaagtttca ccgaagatgc tccccgaccc ccagtgcctg gtgaggaggg agaactggtg 180

tccacagacc cgaggcccgc cagctacagt ttctgctccg ggaaaggtgt tggcattaaa 240

ggtgagactt cgacggccac tccgaggcgc tcggatctgg acctggggta tgagcctgag 300

ggcagtgcct cccccacccc accatacttg aagtgggctg agtcactgca ttccctgctg 360

gatgaccaag atgggataag cctgttcagg actttcctga agcaggaggg ctgtgccgac 420

ttgctggact tctggtttgc ctgcactggc ttcaggaagc tggagccctg tgactcgaac 480

gaggagaaga ggctgaagct ggcgagagcc atctaccgaa agtacattct tgataacaat 540

ggcatcgtgt cccggcagac caagccagcc accaagagct tcataaaggg ctgcatcatg 600

aagcagctga tcgatcctgc catgtttgac caggcccaga ccgaaatcca ggccactatg 660

gaggaaaaca cctatccctc cttccttaag tctgatattt atttggaata tacgaggaca 720

ggctcggaga gccccaaagt ctgtagtgac cagagctctg ggtcagggac agggaagggc 780

atatctggat acctgccgac cttaaatgaa gatgaggaat ggaagtgtga ccaggacatg 840

gatgaggacg atggcagaga cgctgctccc cccggaagac tccctcagaa gctgctcctg 900

gagacagctg ccccgagggt ctcctccagt agacggtaca gcgaaggcagagagttcag 959

<210>2

<211>220

<212>DNA

<213> human (human)

<400>2

gatctcccag ccatccagcc ccggctagtg gcggtcagca aaaccaaacc tgcagacatg 60

gtgatcgagg cctatggaca tgggcagcgc acttttggcg agaactacgt tcaggaactg 120

ctagaaaaag catcaaatcc caaaattctg tctttgtgtc ctgagatcaa atggcacttc 180

attggccacc tacagaaaca aaatgtcaac aaattgatgg 220

<210>3

<211>1634

<212>DNA

<213> human (human)

<400>3

gggtggcact gaatcaacaa gacaagcaac tcaattgatt aatgctttga tcaaggatcc 60

agacaaagaa attgatgaac ttattccaaa gaatcgtttg aaaagctcct cagcaaattc 120

caaaataggg tcatcagcac ctaccaccac tgctgctaac acttccttaa tgggaattaa 180

aatgacaact gtagctctgt catcaacatc tcaaactgcc acagcactca ctgtgcctgc 240

aatttcttct gcatccactc acaaaaccat taagaaccca gtgaataatg tgaggcctgg 300

ttttccagtt tctcttccat tagcatatcc tcctccacag tttgcacatg ctttgcttgc 360

tgctcagact ttccagcaga tccgtccacc aaggttgccc atgacccact ttggaggtac 420

ttttccacca gctcaatcca cttggggtcc gtttcctgtc aggcctttga gccctgccag 480

agctactaac tcgcctaagc ctcacatggt gcctcgccat agcaatcaga atagcagtgg 540

ttctcaggtg aattcagcag gttctttaac ttcaagccca acaactacaa ccagttcatc 600

agcttcaacg gtgcctggta catctacaaa tggcagtcca agttcacctt ctgtccgaag 660

gcagcttttt gtcacagttg tgaagacatc caatgccacc acaacaacag tcacaaccac 720

ggcaagcaac aacaacactg cacccacaaa tgccacatat cctatgccta ctgccaaaga 780

acactatcca gtatcatccc catcttcccc atcaccacca gcccagccag gaggggtttc 840

tagaaacagc cctttggatt gtggatcagc atctccaaat aaagtggcat cttcctccga 900

acaggaagca ggtagtccac cagtagtaga aacaacaaac actagacctc caaacagcag 960

cagttcttct gggagttcat cagctcattc taatcagcaa caacctccgg gatctgtttc 1020

tcaggaacca agaccacctc ttcagcagtc tcaggttcct cccccggaag ttagaatgac 1080

tgttcctcct ttagcaacaa gttctgctcc agtggcggtg ccttctactg ccccagtgac 1140

ttaccctatg cctcagacac caatgggatg cccccagcct actcctaaaa tggaaacccc 1200

tgctattaga ccaccccctc atggcacaac tgcccctcac aagaattcag cttcagtgca 1260

aaattcatct gttgcagtcc tcagtgtcaa tcacattaaa agacctcaca gtgttccctc 1320

ttctgtccag ctaccttcga ccttaagtac acaaagtgct tgtcagaatt cagtacatcc 1380

agcaaataag cctattgctc ccaatttcag tgccccctta ccatttgggc cctttagcac 1440

attgtttgaa aacagcccta cttctgctca tgccttctgg ggaggatctg ttgtttcatc 1500

tcagtcaaca ccagaatcta tgctatcagg aaaatcctca tatttgccaa attcagatcc 1560

tttacatcag tctgatactt ccaaagctcc aggttttaga ccaccattac agagacctgc 1620

tccaagtccc tcag 1634

<210>4

<211>522

<212>DNA

<213> human (human)

<400>4

atatttattg agtgtctact gtgtgccagg cactatatct atgtgcatag aaaaaccctg 60

gaaggccata caacaatata tatagagtga tcgtctctgc ttgctgagct aacaggggtg 120

tcaagcttcc attttggtat ctacttctaa atacactcag aacaggagaa atttggacta 180

attttcaaac tacagacact ttctaatcat gatgcatttc aaaagtggac tcgaattaac 240

tgagttgcaa aacatgacag tgcccgagga tgataacatt agcaatgact ccaatgattt 300

caccgaagta gaaaatggtc agataaatag caagtttatt tctgatcgtg aaagtagaag 360

aagtctcaca aacagccatt tggaaaaaaa gaagtgtgat gagtatattc caggtacaac 420

ctccttaggc atgtctgttt ttaacctaag caacgccatt atgggcagtg ggattttggg 480

actcgccttt gccctggcaa acactggaat cctacttttt ct 522

<210>5

<211>1064

<212>DNA

<213> human (human)

<400>5

gcttaagcag gtaaagcagt cactgtgaag aaaataacat tttaagaaac ttttctgtca 60

caattgatag aggaaaagcc agtagagaag tacatcttct tgtgtgtgtg tctcatcgtg 120

ccactttttg taactcagct tagtaatgaa gccaccatta tgtcctcagt cagtgaagta 180

aatgtggata taaaagattt cctaatgagc attaatttgg agcagtatct cttacatttc 240

catgagtctg gttttactac tgtgaaggac tgtgcagcaa taaatgacag cctgctgcag 300

aaaattggaa tatcacctac aggtcaccgt aggaggatac ttaaacagtt acagataatc 360

ttgtcaaaaa tgcaagatat tccaatatat gcaaatgttc ataaaactaa gaagaatgat 420

gacccttcaa aggattacca tgttccatct tctgatcaga atatctgcat agaactttcc 480

aattctggta gtgttcagac atctagccca ccgcagttgg agactgttag aaaaaatctt 540

gaagacagtg atgcaagtgt ggaaagaagc cagtatcctc aatcagatga taagctgtct 600

cctcctaaac gcgacttccc cactgcagag gaaccacacc tgaatttggg ttctttgaat 660

gattctttat ttggtagtga caatattaaa atagaatcat tgattacaaa gaagactgtg 720

gatcacacag ttgaagaaca acaaacagaa aaagttaaat tgatcacaga aaatctcagt 780

aagctcccta atgcagactc tgaatgcctt tcttttgttg gctgttcaac atcaggaaca 840

aattctggaa atggaacaaa tggtttatta gaaggatcac caccatcccc attctttaag 900

tttcaaggag aaatgattgt aaatgacttg tatgttccat catcaccaat cctagcacct 960

gtgagaagtc gtagcaagtt ggtttcaaga ccatctcgat cttttctgct aagacatcga 1020

cctgtaccag agattccagg gtcaacaaaa ggagtttctg ggag 1064

<210>6

<211>361

<212>DNA

<213> human (human)

<400>6

acagtgatgt gtgttctgaa attgtgaacc atgagtctag tacttaatga tctgcttatc 60

tgctgccgtc aactagaaca tgatagagct acagaacgaa agaaagaagt tgagaaattt 120

aagcgcctga ttcgagatcc tgaaacaatt aaacatctag atcggcattc agattccaaa 180

caaggaaaat atttgaattg ggatgctgtt tttagatttt tacagaaata tattcagaaa 240

gaaacagaat gtctgagaat agcaaaacca aatgtatcag cctcaacaca agcctccagg 300

cagaaaaaga tgcaggaaat cagtagtttg gtcaaatact tcatcaaatg tgcaaacaga 360

a 361

<210>7

<211>466

<212>DNA

<213> human (human)

<400>7

gaaggaacac acaagtagtt atctttcagg ctgtctttga atacttccat gaccctgaac 60

actagctgag gagagtttca accactgcta acagtaatga ctttacatga gtttggaact 120

ggtctctagt gggaagttgt gggaggatga acacagaaga gctggagtta ttgagtgact 180

ccaaatacag aaactatgta gcagcaattg acaaagcact aaagaatttt gaatactcca 240

gtgaatgggc agatttgata tcagcacttg gaaaacttaa taaggtttta caaaataatg 300

caaagtacca agtagtaccc aaaaagctga ccataggcaa acgcctagct caatgtctac 360

atccagcatt accaggtgga gttcatcgga aggcgcttga aacatatgaa attatcttca 420

aaataattgg acctaagcga cttgccaaag atcttttttt atatag 466

<210>8

<211>484

<212>DNA

<213> human (human)

<400>8

aaagaaagaa ctttcagcta ccaagaaaga ccgtgtgaat cattgtctga caatatgtga 60

aaacatagtg gcacagtctg tcagaaattc tccagaattt cagaaacttc tgggcatcgc 120

tatggaactt tttctgctgt gcagtgatga cgcagagtca gatgtcagga tggtggctga 180

cgaatgcctc aacaaagtta tcaaagcttt gatggattct aatcttccaa ggttacagct 240

cgagctctat aaggaaatta aaaagaatgg tgcccctcgg agtttgcgtg ctgccctgtg 300

gaggtttgct gagctggctc acctggttcg gcctcagaaa tgcaggcctt acctggtgaa 360

ccttctgccg tgcctgactc gaacaagcaa gagacccgaa gaatcagtcc aggagacctt 420

ggctgcagct gttcccaaaa ttatggcttc ttttggcaat tttgcaaatg acaatgaaat 480

taag 484

<210>9

<211>2077

<212>DNA

<213> human (human)

<400>9

catccagagc tgctgttggc ggattgtacc cacggggaga tgattcctca tgaagagcct 60

ggatccccta cagaaatcaa atgtgacttt ccgtttatca gactaaaatc agagccatcc 120

agacagtgaa acagtcaccg tggagggggg acggcgaaaa atgaaatcca accaagagcg 180

gagcaacgaa tgcctgcctc ccaagaagcg cgagatcccc gccaccagcc ggtcctccga 240

ggagaaggcc cctaccctgc ccagcgacaa ccaccgggtg gagggcacag catggctccc 300

gggcaaccct ggtggccggg gccacggggg cgggaggcat gggccggcag ggacctcggt 360

ggagcttggt ttacaacagg gaataggttt acacaaagca ttgtccacag ggctggacta 420

ctccccgccc agcgctccca ggtctgtccc cgtggccacc acgctgcctg ccgcgtacgc 480

caccccgcag ccagggaccc cggtgtcccc cgtgcagtac gctcacctgc cgcacacctt 540

ccagttcatt gggtcctccc aatacagtgg aacctatgcc agcttcatcc catcacagct 600

gatcccccca accgccaacc ccgtcaccag tgcagtggcc tcggccgcag gggccaccac 660

tccatcccag cgctcccagc tggaggccta ttccactctg ctggccaaca tgggcagtct 720

gagccagacg ccgggacaca aggctgagca gcagcagcag cagcagcagc agcagcagca 780

gcagcatcag catcagcagc agcagcagca gcagcagcag cagcagcagc agcagcacct 840

cagcagggct ccggggctca tcaccccggg gtccccccca ccagcccagc agaaccagta 900

cgtccacatt tccagttctc cgcagaacac cggccgcacc gcctctcctc cggccatccc 960

cgtccacctc cacccccacc agacgatgat cccacacacg ctcaccctgg ggcccccctc 1020

ccaggtcgtc atgcaatacg ccgactccgg cagccacttt gtccctcggg aggccaccaa 1080

gaaagctgag agcagccggc tgcagcaggc catccaggcc aaggaggtcc tgaacggtga 1140

gatggagaag agccggcggt acggggcccc gtcctcagcc gacctgggcc tgggcaaggc 1200

aggcggcaag tcggttcctc acccgtacga gtccaggcac gtggtggtcc acccgagccc 1260

ctcagactac agcagtcgtg atccttcggg ggtccgggcc tctgtgatgg tcctgcccaa 1320

cagcaacacg cccgcagctg acctggaggt gcaacaggcc actcatcgtg aagcctcccc 1380

ttctaccctc aacgacaaaa gtggcctgca tttagggaag cctggccacc ggtcctacgc 1440

gctctcaccc cacacggtca ttcagaccac acacagtgct tcagagccac tcccggtggg 1500

actgccagcc acggccttct acgcagggac tcaaccccct gtcatcggct acctgagcgg 1560

ccagcagcaa gcaatcacct acgccggcag cctgccccag cacctggtga tccccggcac 1620

acagcccctg ctcatcccgg tcggcagcac tgacatggaa gcgtcggggg cagccccggc 1680

catagtcacg tcatcccccc agtttgctgc agtgcctcac acgttcgtca ccaccgccct 1740

tcccaagagc gagaacttca accctgaggc cctggtcacc caggccgcct acccagccat 1800

ggtgcaggcc cagatccacc tgcctgtggt gcagtccgtg gcctccccgg cggcggctcc 1860

ccctacgctg cctccctact tcatgaaagg ctccatcatc cagttggcca acggggagct 1920

aaagaaggtg gaagacttaa aaacagaaga tttcatccag agtgcagaga taagcaacga 1980

cctgaagatc gactccagca ccgtagagag gattgaagac agccatagcc cgggcgtggc 2040

cgtgatacag ttcgccgtcg gggagcaccg agcccag 2077

<210>10

<211>392

<212>DNA

<213> human (human)

<400>10

ggtatgttag agcccaccaa ggaaccactg aaaccacttt ctgctgcaga aaaaatagct 60

tccatcggtc agacagccac catgtcacca gatatgaaca catgtacatc tgatcagttc 120

caggagtctc taccacccgt ccagtttgac tggagtagca gtggccttac taacccttta 180

gatgctagtg gaggttccac tcttctgaac cttgatttct ttgggcccgt ggatgacagt 240

agctctagca gcagcaccac aatcccaggt gtggatccgg agttgtatga gttaacaact 300

tctaagctgg aaatctccac ctcaagcctc aaagtgactg atgcatttgc aagactcatg 360

tctacagtagagaagacaag cacatctacc ag 392

<210>11

<211>448

<212>DNA

<213> human (human)

<400>11

atcatgatgc tgcgattaat agatatagcc gtttatcaaa aaaaagagaa aatgacaagg 60

tgaagtatga agtaacagaa gatgtgtaca catccagaaa gaaacaacac cagaccatga 120

tgcattattt ttgtgcatta aatactcttc agtacaagaa gaaaatagca ttgttagaac 180

ctctacttgg gtacatgcaa gctcagataa gtttctttaa gatgggttct gaaaatctta 240

atgaacaact ggaagaattt ttagctaata ttggaacaag cgttcagaat gttcgcaggg 300

aaatggacag tgatatagag accatgcaac agacaataga ggatttggaa gtagccagtg 360

atcccttata tgtgcctgac ccagacccca ccaaatttcc tgttaatcga aatttaaccc 420

gaaaggctgg ataccttaat gctaggaa 448

<210>12

<211>773

<212>DNA

<213> human (human)

<400>12

aaaatgacag atggcgagac ctggacagga aatgccctct tcagattgac caaccgagca 60

ccagcatctg ggaatgcctg cctgaaaagg acagctcact atggcaccgg gaggcagtga 120

ccgcctgcgc tgtgaccagt ctgatcaaag acctcagcat cagcgaccac aacgggaacc 180

cctcagcacc ccctagcaag cgccagtgcc gctcactgtc cttctccgat gagatgtcca 240

gttgccggac atcatggagg cccttgggct ccaaagtctg gactcccgtg gaaaagagac 300

gctgctacag cgggggcagc gtccagcgct attccaacgg cttcagcacc atgcagagga 360

gttccagctt cagcctccct tcccgggcca acgtgctctc ctcaccctgc gaccaggcag 420

gactccacca ccgatttgga gggcagccct gccaaggggt gccaggctca gccccgtgtg 480

gacaggcagg tgacacctgg agccctgacc tgcaccccgt gggaggaggc cggctggacc 540

tgcagcggtc cctctcttgc tcacatgagc agttttcctt tgtggaatac tgtcctccct 600

cagccaacag cacacctgcc tcaacaccag agctggcgag acgctccagc ggcctttccc 660

gcagccgctc ccagccgtgt gtccttaacg acaagaaggt cggtgttaaa aggcggcgcc 720

ctgaagaagt gcaagagcag aggccttctc tagaccttgc caagatggca cag 773

<210>13

<211>788

<212>DNA

<213> human (human)

<400>13

gttatacatt ggctcttcaa agacgttcac ctcatcagag aaatccctga ctcctttgca 60

gtggtgtaga catgtcctag ataacccaac tcctgagatg gaagcagcga gacgttccct 120

gtgctttaga ctggagcaag gttacacttc caggggctcc ccactcagtc cccagtcatc 180

tatcgacagt gagctgagta cttcagaatt ggaggatgat tctatctcca tgggatataa 240

attacaggac ctcactgatg ttcagatcat ggctcgtctg caagaagaaa gtctcaggca 300

agattatgct tctacttcag catctgtatc aagacatagt tccagtgtgt cattgagttc 360

aggaaaaaaa gggacatgta gtgatcaaga atatgaccaa tacagtctgg aggatgaaga 420

ggaatttgat catttgccac cacctcagcc tcgtcttcca agatgttccc ctttccaaag 480

aggaattccc cattcacaga ctttctccag cattcgggag tgtaggagga gccccagttc 540

ccagtatttt ccttcaaata attaccagca gcaacagtat tattcacctc aagcccaaac 600

tccagatcag caaccaaata ggaccaatgg agataagctc cgaagaagta tgcctaacct 660

agcccggatg ccaagtacaa ctgccattag tagcaacatt agttctccgg tcaccgtgcg 720

aaatagtcag agttttgact caagcttgca tggagctgga aatggaattt caagaataca 780

atcttgta 788

<210>14

<211>337

<212>DNA

<213> human (human)

<400>14

gtgattttac aacgagatgc tgctctccat agggatgctc atgctgtcag ccacacaagt 60

ctacaccatc ttgactgtcc agctctttgc attcttaaac ctactgcctg tagaagcaga 120

cattttagca tataactttg aaaatgcatc tcagacattt gatgacctcc ctgcaagatt 180

tggttataga cttccagctg aaggtttaaa gggttttttg attaactcaa aaccagagaa 240

tgcctgtgaa cccatagtgc ctccaccagt aaaagacaat tcatctggca ctttcatcgt 300

gttaattaga agacttgatt gtaattttga tataaag 337

<210>15

<211>334

<212>DNA

<213> human (human)

<400>15

atgcttgctc tgtcaaggca cagcctattg tctcctttgc tcagtgtgac atcattcaga 60

cgcttctaca gaggtgacag cccaacagat tcccaaaagg acatgattga aatccctttg 120

cctccatggc aggagagaac tgatgaatcc atagaaacca aaagagcccg cctgctctat 180

gagagcagaa agaggggaat gttggaaaac tgcattcttc ttagtctttt tgctaaagaa 240

catctgcagc acatgacaga aaagcagctg aacctctatg accgcctgat taacgagcct 300

agtaatgact gggatattta ctactgggcc acag 334

<210>16

<211>587

<212>DNA

<213> human (human)

<400>16

gttcccgtgt cagtggctat gatgacacct caagttatca ctccccagca aatgcagcag 60

atcctccagc aacaagtgct gagccctcag cagctccagg ttctcctcca gcagcagcag 120

gccctcatgc ttcaacagca gcagcttcaa gagttttata aaaaacaaca ggaacagttg 180

cagcttcaac ttttacaaca acaacatgct ggaaaacagc ctaaagagca acagcaggtg 240

gctacccagc agttggcttt tcagcagcag cttttacaga tgcagcagtt acagcagcag 300

cacctcctgt ctttgcagcg ccaaggcctt ctgacaattc agcccgggca gcctgccctt 360

ccccttcaac ctcttgctca aggcatgatt ccaacagaac tgcagcagct ctggaaagaa 420

gtgacaagtg ctcatactgc agaagaaacc acaggcaaca atcacagcag tttggatctg 480

accacgacat gtgtctcctc ctctgcacct tccaagacct ccttaataat gaacccacat 540

gcctctacca atggacagct ctcagtccac actcccaaaa gggaaag 587

<210>17

<211>702

<212>DNA

<213> human (human)

<400>17

taagactttg accccgacgc aggcttcagt gattgccgcg gatcagaagc ctgagcactt 60

tggctcgaga caattaagga cgtgggatga ggctccgaga caggacgcgg ttctgcctgg 120

ggatcctgaa gataaaaagc tttgaaaagt cgaattcatg gtcgtggaag ctgagcccat 180

attaagagat gtcaggcgtc cgacctccga tcatgaacgg gcccctgcac ccgcggcccc 240

tggtggcatt gctggatggc cgggactgca cagtggagat gcccatcctg aaggacgtgg 300

ccactgtggc cttctgcgac gcgcagtcca cgcaggagat ccatgagaag gtcctgaacg 360

aggctgtggg ggccctgatg taccacacca tcactctcac cagggaggac ctggagaagt 420

tcaaagccct ccgcatcatc gtccggattg gcagtggttt tgacaacatc gacatcaagt 480

cggccgggga tttaggcatt gccgtctgca acgtgcccgc ggcgtctgtg gaggagacgg 540

ccgactcgac gctgtgccac atcctgaacc tgtaccggcg ggccacctgg ctgcaccagg 600

cgctgcggga gggcacacga gtccagagcg tcgagcagat ccgcgaggtg gcgtccggcg 660

ctgccaggat ccgcggggag accttgggca tcatcggact tg 702

<210>18

<211>424

<212>DNA

<213> human (human)

<400>18

gctcttgtca ggatggtgaa gctgttcatc ggaaacctgc cccgggaggc tacagagcag 60

gagattcgct cactcttcga gcagtatggg aaggtgctgg aatgtgacat cattaagaat 120

tacggctttg tgcacataga agacaagacg gcagctgagg atgccatacg caacctgcac 180

cattacaagc ttcatggggt gaacatcaac gtggaagcca gcaagaataa gagcaaaacc 240

tcaacaaagt tgcatgtggg caacatcagt cccacctgca ccaataagga gcttcgagcc 300

aagtttgagg agtatggtcc ggtcatcgaa tgtgacatcg tgaaagatta tgccttcgta 360

cacatggagc gggcagagga tgcagtggag gccatcaggg gccttgataa cacagagttt 420

caag 424

<210>19

<211>716

<212>DNA

<213> human (human)

<400>19

gtgattttac aacgagatgc tgctctccat agggatgctc atgctgtcag ccacacaagt 60

ctacaccatc ttgactgtcc agctctttgc attcttaaac ctactgcctg tagaagcaga 120

cattttagca tataactttg aaaatgcatc tcagacattt gatgacctcc ctgcaagatt 180

tggttataga cttccagctg aaggtttaaa gggttttttg attaactcaa aaccagagaa 240

tgcctgtgaa cccatagtgc ctccaccagt aaaagacaat tcatctggca ctttcatcgt 300

gttaattaga agacttgatt gtaattttga tataaaggtt ttaaatgcac agagagcagg 360

atacaaggca gccatagttc acaatgttga ttctgatgac ctcattagca tgggatccaa 420

cgacattgag gtactaaaga aaattgacat tccatctgtc tttattggtg aatcatcagc 480

taattctctg aaagatgaat tcacatatga aaaagggggc caccttatct tagttccaga 540

atttagtctt cctttggaat actacctaat tcccttcctt atcatagtgg gcatctgtct 600

catcttgata gtcattttca tgatcacaaa atttgtccag gatagacata gagctagaag 660

aaacagactt cgtaaagatc aacttaagaa acttcctgta cataaattca agaaag 716

<210>20

<211>443

<212>DNA

<213> human (human)

<400>20

caaaagagaa gaaaaaacct gaagattctc cctcagatga tgatgttctc attgtatatg 60

aactaactcc aaccgctgag cagaaagccc ttgcaaccaa acttaaactt cctccaactt 120

tcttctgcta caagaataga ccagattatg ttagtgaaga agaggaggat gatgaagatt 180

tcgaaacagc tgtcaagaaa cttaatggaa aactatattt ggatggctca gaaaaatgta 240

gacccttgga agaaaataca gcagataatg agaaagaatg tattattgtt tgggaaaaga 300

aaccaacagt tgaagagaag gcaaaagcag atacgttaaa acttccacct acattttttt 360

gtggagtctg tagtgatact gatgaagaca atggaaatgg ggaggacttt caatcagagc 420

ttcaaaaagt tcaggaagct caa 443

<210>21

<211>528

<212>DNA

<213> human (human)

<400>21

agtaaaaagc gacaatatga ccaggaaatt gagaatctag aaaaacagca gaaacagact 60

atcgaacgcc tggaacaaga gcacacaaat cgcttgcgag atgaagccaa acgcatcaaa 120

ggagaacaag agaaagagtt gtccaaattt cagaatatgc tgaagaaccg aaagaaggag 180

gttataaatg aagtggagaa agcacccaaa gagctgagaa aagagctcat gaaacgcagg 240

aaagaggagc ttgcacaaag ccagcatgct caggaacaag agtttgttca gaaacaacag 300

caagaattag atggctctct gaaaaagatc atccagcagc agaaggcaga gttagctaat 360

attgagagag agtgcctgaa taacaagcaa cagctcatga gagctcgaga agctgcaatt 420

tgggagctcg aagaacgaca cttacaagaa aaacaccagc tgctcaaaca gcagcttaaa 480

gatcagtatt tcatgcaaag acatcagcta cttaagcgcc acgagaag 528

<210>22

<211>404

<212>DNA

<213> human (human)

<400>22

cattgatctg gtagccttgc tccagaagcc tgttcctcac agtcaagcct cagaagccaa 60

ctcctttgaa acttcccaac agcagggctt tggccaagcc cttgtcttca caaattcgca 120

acacaacaat cagatggcac cagggactgg cagctccact gccgtcaact cctgttctcc 180

tcagagcctg tcatccgtcc ttggctcagg atttggagag cttgcaccac caaaaatggc 240

aaacatcacc agctcccaga ttttggacca gttgaaagct ccgagtttgg gccagtttac 300

caccacccca agtacacagc agaatagtac aagtcaccct acaactacta cttcttggga 360

cctcaagccc ccaacatccc agtcctcagt cctcagtcat cttg 404

Claims (10)

1. A healthy aging diagnosis circRNA marker, which comprises one or more of hsa _ circ _0005838, hsa _ circ _0001788, hsa _ circ _0007883, hsa _ circ _0000396, hsa _ circ _0069399, hsa _ circ _0024193, hsa _ circ _0132409, hsa _ circ _0001392, hsa _ circ _0007132, hsa _ circ _0006037, hsa _ circ _0001317, hsa _ circ _0000267, hsa _ circ _0000497, hsa _ circ _0067716, hsa _ circ _ 84, hsa _ circ _0008234 a _ circ _0001386, hsa _ circ _0000330, hsa _ circ _0001346, hsa _ circ _ 5 _ circ _0000259, and hsa _ circ _ 0000259.

2. The healthy aging diagnostic circRNA marker of claim 1, wherein the sequence of hsa _ circ _0005838, hsa _ circ _0001788, hsa _ circ _0007883, hsa _ circ _0000396hsa _ circ _0069399, hsa _ circ _0024193, hsa _ circ _0132409, hsa _ circ _0001392, hsa _ circ _0007132, hsa _ circ _0006037, hsa _ circ _0001317, hsa _ circ _0000267, hsa _ circ _0000497, hsa _ circ _0067716, hsa _ circ _ 84, hsa _ circ _0008234, hsa _ circ _0001386, hsa _ circ _0000330, hsa _ circ _0001346, hsa _ circ _ 5 _ circ _0000259, and SEQ id No. 22-5822.

3. Use of the healthy aging diagnostic circRNA marker in the preparation of a healthy aging early diagnosis product according to claim 1, wherein the diagnosis product comprises a reagent for detecting the one or more markers, and the reagent judges whether the subject has a healthy aging possibility by detecting the expression value of the one or more markers in the subject.

4. Use according to claim 3, in particular for detecting the expression value of one or more markers in the blood of a subject.

5. Use according to claim 3, wherein the expression of the markers hsa _ circ _0005838, hsa _ circ _0007883, hsa _ circ _0069399, hsa _ circ _0001392, hsa _ circ _0007132, hsa _ circ _0000267, hsa _ circ _0000311, hsa _ circ _0001386, hsa _ circ _0000330 is significantly increased in healthy elderly.

6. Use according to claim 3, wherein the markers hsa _ circ _0001788, hsa _ circ _0000396, hsa _ circ _0024193, hsa _ circ _0132409, hsa _ circ _0006037, hsa _ circ _0001317, hsa _ circ _0000497, hsa _ circ _0067716, hsa _ circ _0008234, hsa _ circ _0001346, hsa _ circ _0006965, hsa _ circ _0000259, hsa _ circ _0003496 are expressed significantly in the elderly of healthy aging.

7. The use according to any one of claims 3 to 6, wherein the diagnostic product is a kit, chip or assay platform.

8. Use of the healthy aging diagnostic circRNA marker of claim 1 for diagnosing healthy aging.

9. Use according to claim 8, characterized in that it comprises the following steps:

step 1, taking fresh anticoagulated blood of an old aged over 65 years old, and extracting total RNA of leucocytes;

step 2, removing rRNA from the obtained RNA sample, preparing the sample according to an Illumina RNA-seq library preparation manual, and performing sequencing on an Illumina Hiseq-2500 platform after the preparation is finished and the quality detection is qualified; identifying and quantifying circRNA according to the sequencing data by using a procedure of CIRCCexplor software, and finally obtaining expression data of all circRNA;

and 3, extracting expression value data of the 22 circRNA markers from the circRNA expression data, introducing the expression value data into a healthy aging diagnosis model, and analyzing the obtained score numerical value, wherein if the numerical value is more than 0.5 and is closer to 1, the characteristic tendency of healthy aging of the testee is higher, and conversely, the characteristic tendency of healthy aging is lower as the numerical value is closer to 0.

10. The use according to claim 9, wherein the healthy aging diagnostic model is: score is the sum of the coefficients for each circRNA marker plus 0.162271651 for the sample expression values.

Images