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Integrated genetic analyses revealed novel human longevity loci and reduced risks of multiple diseases in a cohort study of 15,651 Chinese individuals

There is growing interest in studying the genetic contributions to longevity, but limited relevant genes have been identified. In this study, we performed a genetic association study of longevity in a total of 15,651 Chinese individuals. Novel longevity loci, BMPER (rs17169634; p = 7.91 × 10(−15)) a...

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Detalles Bibliográficos
Autores principales: Liu, Xiaomin, Song, Zijun, Li, Yan, Yao, Yao, Fang, Mingyan, Bai, Chen, An, Peng, Chen, Huashuai, Chen, Zhihua, Tang, Biyao, Shen, Juan, Gao, Xiaotong, Zhang, Mingrong, Chen, Pengyu, Zhang, Tao, Jia, Huijue, Liu, Xiao, Hou, Yong, Yang, Huanming, Wang, Jian, Wang, Fudi, Xu, Xun, Min, Junxia, Nie, Chao, Zeng, Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7963337/
https://www.ncbi.nlm.nih.gov/pubmed/33657282
http://dx.doi.org/10.1111/acel.13323
Descripción
Sumario:There is growing interest in studying the genetic contributions to longevity, but limited relevant genes have been identified. In this study, we performed a genetic association study of longevity in a total of 15,651 Chinese individuals. Novel longevity loci, BMPER (rs17169634; p = 7.91 × 10(−15)) and TMEM43/XPC (rs1043943; p = 3.59 × 10(−8)), were identified in a case–control analysis of 11,045 individuals. BRAF (rs1267601; p = 8.33 × 10(−15)) and BMPER (rs17169634; p = 1.45 × 10(−10)) were significantly associated with life expectancy in 12,664 individuals who had survival status records. Additional sex‐stratified analyses identified sex‐specific longevity genes. Notably, sex‐differential associations were identified in two linkage disequilibrium blocks in the TOMM40/APOE region, indicating potential differences during meiosis between males and females. Moreover, polygenic risk scores and Mendelian randomization analyses revealed that longevity was genetically causally correlated with reduced risks of multiple diseases, such as type 2 diabetes, cardiovascular diseases, and arthritis. Finally, we incorporated genetic markers, disease status, and lifestyles to classify longevity or not‐longevity groups and predict life span. Our predictive models showed good performance (AUC = 0.86 for longevity classification and explained 19.8% variance of life span) and presented a greater predictive efficiency in females than in males. Taken together, our findings not only shed light on the genetic contributions to longevity but also elucidate correlations between diseases and longevity.