Polygenic prediction of human longevity on the supposition of pervasive pleiotropy
Abstract The highly polygenic nature of human longevity renders pleiotropy an indispensable feature of its genetic architecture. Leveraging the genetic correlation between aging-related traits (ARTs), we aimed to model the additive variance in lifespan as a function of the cumulative liability from...
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Nature Portfolio
2024-08-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-69069-0 |
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| author | M. Reza Jabalameli Jhih-Rong Lin Quanwei Zhang Zhen Wang Joydeep Mitra Nha Nguyen Tina Gao Mark Khusidman Sanish Sathyan Gil Atzmon Sofiya Milman Jan Vijg Nir Barzilai Zhengdong D. Zhang |
| author_facet | M. Reza Jabalameli Jhih-Rong Lin Quanwei Zhang Zhen Wang Joydeep Mitra Nha Nguyen Tina Gao Mark Khusidman Sanish Sathyan Gil Atzmon Sofiya Milman Jan Vijg Nir Barzilai Zhengdong D. Zhang |
| author_sort | M. Reza Jabalameli |
| collection | DOAJ |
| description | Abstract The highly polygenic nature of human longevity renders pleiotropy an indispensable feature of its genetic architecture. Leveraging the genetic correlation between aging-related traits (ARTs), we aimed to model the additive variance in lifespan as a function of the cumulative liability from pleiotropic segregating variants. We tracked allele frequency changes as a function of viability across different age bins and prioritized 34 variants with an immediate implication on lipid metabolism, body mass index (BMI), and cognitive performance, among other traits, revealed by PheWAS analysis in the UK Biobank. Given the highly complex and non-linear interactions between the genetic determinants of longevity, we reasoned that a composite polygenic score would approximate a substantial portion of the variance in lifespan and developed the integrated longevity genetic scores (iLGSs) for distinguishing exceptional survival. We showed that coefficients derived from our ensemble model could potentially reveal an interesting pattern of genomic pleiotropy specific to lifespan. We assessed the predictive performance of our model for distinguishing the enrichment of exceptional longevity among long-lived individuals in two replication cohorts (the Scripps Wellderly cohort and the Medical Genome Reference Bank (MRGB)) and showed that the median lifespan in the highest decile of our composite prognostic index is up to 4.8 years longer. Finally, using the proteomic correlates of iLGS, we identified protein markers associated with exceptional longevity irrespective of chronological age and prioritized drugs with repurposing potentials for gerotherapeutics. Together, our approach demonstrates a promising framework for polygenic modeling of additive liability conferred by ARTs in defining exceptional longevity and assisting the identification of individuals at a higher risk of mortality for targeted lifestyle modifications earlier in life. Furthermore, the proteomic signature associated with iLGS highlights the functional pathway upstream of the PI3K-Akt that can be effectively targeted to slow down aging and extend lifespan. |
| format | Article |
| id | doaj-art-e7089311efc14bf3834f43d096b8f9b4 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-e7089311efc14bf3834f43d096b8f9b42025-02-09T12:38:17ZengNature PortfolioScientific Reports2045-23222024-08-0114111910.1038/s41598-024-69069-0Polygenic prediction of human longevity on the supposition of pervasive pleiotropyM. Reza Jabalameli0Jhih-Rong Lin1Quanwei Zhang2Zhen Wang3Joydeep Mitra4Nha Nguyen5Tina Gao6Mark Khusidman7Sanish Sathyan8Gil Atzmon9Sofiya Milman10Jan Vijg11Nir Barzilai12Zhengdong D. Zhang13Department of Genetics, Albert Einstein College of MedicineDepartment of Genetics, Albert Einstein College of MedicineDepartment of Genetics, Albert Einstein College of MedicineDepartment of Genetics, Albert Einstein College of MedicineDepartment of Genetics, Albert Einstein College of MedicineDepartment of Genetics, Albert Einstein College of MedicineDepartment of Medicine, Albert Einstein College of MedicineDepartment of Genetics, Albert Einstein College of MedicineDepartment of Neurology, Albert Einstein College of MedicineDepartment of Genetics, Albert Einstein College of MedicineDepartment of Genetics, Albert Einstein College of MedicineDepartment of Genetics, Albert Einstein College of MedicineDepartment of Genetics, Albert Einstein College of MedicineDepartment of Genetics, Albert Einstein College of MedicineAbstract The highly polygenic nature of human longevity renders pleiotropy an indispensable feature of its genetic architecture. Leveraging the genetic correlation between aging-related traits (ARTs), we aimed to model the additive variance in lifespan as a function of the cumulative liability from pleiotropic segregating variants. We tracked allele frequency changes as a function of viability across different age bins and prioritized 34 variants with an immediate implication on lipid metabolism, body mass index (BMI), and cognitive performance, among other traits, revealed by PheWAS analysis in the UK Biobank. Given the highly complex and non-linear interactions between the genetic determinants of longevity, we reasoned that a composite polygenic score would approximate a substantial portion of the variance in lifespan and developed the integrated longevity genetic scores (iLGSs) for distinguishing exceptional survival. We showed that coefficients derived from our ensemble model could potentially reveal an interesting pattern of genomic pleiotropy specific to lifespan. We assessed the predictive performance of our model for distinguishing the enrichment of exceptional longevity among long-lived individuals in two replication cohorts (the Scripps Wellderly cohort and the Medical Genome Reference Bank (MRGB)) and showed that the median lifespan in the highest decile of our composite prognostic index is up to 4.8 years longer. Finally, using the proteomic correlates of iLGS, we identified protein markers associated with exceptional longevity irrespective of chronological age and prioritized drugs with repurposing potentials for gerotherapeutics. Together, our approach demonstrates a promising framework for polygenic modeling of additive liability conferred by ARTs in defining exceptional longevity and assisting the identification of individuals at a higher risk of mortality for targeted lifestyle modifications earlier in life. Furthermore, the proteomic signature associated with iLGS highlights the functional pathway upstream of the PI3K-Akt that can be effectively targeted to slow down aging and extend lifespan.https://doi.org/10.1038/s41598-024-69069-0PleiotropyPolygenic scoreCommon variantsAgingLifespanLongevity |
| spellingShingle | M. Reza Jabalameli Jhih-Rong Lin Quanwei Zhang Zhen Wang Joydeep Mitra Nha Nguyen Tina Gao Mark Khusidman Sanish Sathyan Gil Atzmon Sofiya Milman Jan Vijg Nir Barzilai Zhengdong D. Zhang Polygenic prediction of human longevity on the supposition of pervasive pleiotropy Scientific Reports Pleiotropy Polygenic score Common variants Aging Lifespan Longevity |
| title | Polygenic prediction of human longevity on the supposition of pervasive pleiotropy |
| title_full | Polygenic prediction of human longevity on the supposition of pervasive pleiotropy |
| title_fullStr | Polygenic prediction of human longevity on the supposition of pervasive pleiotropy |
| title_full_unstemmed | Polygenic prediction of human longevity on the supposition of pervasive pleiotropy |
| title_short | Polygenic prediction of human longevity on the supposition of pervasive pleiotropy |
| title_sort | polygenic prediction of human longevity on the supposition of pervasive pleiotropy |
| topic | Pleiotropy Polygenic score Common variants Aging Lifespan Longevity |
| url | https://doi.org/10.1038/s41598-024-69069-0 |
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