Genome-wide study of the longevity phenomenon in the Russian Federation
https://doi.org/10.37586/2949-4745-4-2024-218-222
Abstract
BACKGROUND. More than one hundred candidate genes have been associated with longevity, including APOE, FOXO1A, GF1, IGF1, INCR, TP53, etc. Despite extensive research, the precise molecular and genetic underpinnings remain elusive due to the low reproducibility of the findings. Moreover, most studies have focused on exomes and have neglected intergenic regulatory regions of DNA.
AIM. To examine the genetic and molecular basis of longevity and create a prognostic model that assesses the chance of reaching the age of 90.
MATERIALS AND METHODS. To study the genetic predictors of longevity, 10,157 people were recruited, including 3,066 long-living individuals (90+ years). The recruitment of long-living individuals was carried out jointly with the Russian Clinical Research Center for Gerontology; other participants have been included from the database of the Center for Strategic Planning and Management of Biomedical Health Risks” of the Federal Medical-Biological Agency. A comprehensive medical history was collected for all participants (including data on chronic conditions), and wholegenome sequencing of blood cell DNA was performed. When determining the healthy long-living individuals, we have utilized the machine learningbased calculator of aging phenotype previously developed by us [1].
RESULTS. A genome-wide association study (GWAS) involving 3,066 longliving individuals (90+ years) and 7,091 people aged 18 to 75 years confirmed the known association of APOE gene variants with longevity. Additionally, we discovered new associations in the TMEM59, LRRC7, FHIT, CPLX1, DDX31, GRIN1, DHX32, CACNA1C, FBXO21 and UBBP4 genes. The obtained results helped construct a polygenic score, which assesses an individual chance of becoming a long-living individual (ROC AUC = 0.78). However, long-living individuals are a phenotypically heterogeneous group, so determining only the chance of living to 90 years may not be enough. The functional status at this age should also be addressed. The genomes of healthy long-living individuals were compared with the genomes of ailing long-living individuals and those of a healthy population sample. Healthy longevity is mediated by completely different molecular mechanisms than the broader phenotype, and is associated with the genes NAV1, SDK1, ARHGAP39 and ITGAE. Regulatory RNAs, particularly the antisense RNA to the mRNA of the IPO9 gene product, were shown to significantly affect healthy longevity.
CONCLUSIONS. This study of the genetic basis of longevity has shown that there is no single mechanism that would be a single and key predictor for life expectancy. Longevity has been and remains a multifactorial phenomenon. However, this work confirmed the association of variants in the APOE gene with life expectancy in the Russian population, as well as detected many new polymorphisms associated with longevity. A polygenic scale was proposed that predicts the chance of reaching the age of longevity with an accuracy of over 78%. The important role of regulatory regions of the genome in the phenotype formation was specifically highlighted. Moreover, the achievement of healthy longevity turned out to be mediated by completely different molecular mechanisms than the broader phenotype, and is associated with the genes NAV1, SDK1, ARHGAP39, and ITGAE.
About the Authors
A. A. MamchurРоссия
Moscow
D. A. Kashtanova
Россия
Moscow
V. V. Daniel
Россия
Moscow
M. V. Ivanov
Россия
Moscow
E. A. Zelenova
Россия
Moscow
M. V. Bruttan
Россия
Moscow
I. Kh. Dzhumaniyazova
Россия
Moscow
L. R. Matkava
Россия
Moscow
M. V. Terekhov
Россия
Moscow
A. M. Rumyantseva
Россия
Moscow
K. S. Grammatikati
Россия
Moscow
S. I. Mitrofanov
Россия
Moscow
V. S. Yudin
Россия
Moscow
V. V. Maksyutina
Россия
Moscow
E. D. Maralova
Россия
Moscow
A. A. Ivashechkin
Россия
Moscow
A. I. Nekrasova
Россия
Moscow
I. D. Strazhesko
Россия
Moscow
V. V. Makarov
Россия
Moscow
A. A. Keskinov
Россия
Moscow
O. N. Tkacheva
Россия
Moscow
S. M. Yudin
Россия
Moscow
V. I. Skvortsova
Россия
Moscow
References
1. Mamchur A., Sharashkina N., Erema V., Kashtanova D., Ivanov M., Bruttan M., Zelenova E., Shelly E., Ostapenko V., Dzhumaniiazova I., Matkava L., Yudin V., Akopyan A., Strazhesko I., Maytesyan L., Tarasova I., Beloshevskaya O., Keskinov A., Tkacheva O., Yudin S. Machine Learning-Based Decision-Making in Geriatrics: Aging Phenotype Calculator and Survival Prognosis. Aging and disease. 2024. https://doi.org/10.14336/AD.2024.0120
Review
For citations:
Mamchur A.A., Kashtanova D.A., Daniel V.V., Ivanov M.V., Zelenova E.A., Bruttan M.V., Dzhumaniyazova I.Kh., Matkava L.R., Terekhov M.V., Rumyantseva A.M., Grammatikati K.S., Mitrofanov S.I., Yudin V.S., Maksyutina V.V., Maralova E.D., Ivashechkin A.A., Nekrasova A.I., Strazhesko I.D., Makarov V.V., Keskinov A.A., Tkacheva O.N., Yudin S.M., Skvortsova V.I. Genome-wide study of the longevity phenomenon in the Russian Federation. Problems of Geroscience. 2024;(4):218-222. (In Russ.) https://doi.org/10.37586/2949-4745-4-2024-218-222
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