High polygenic risk score for exceptional longevity is associated with a healthy metabolic profile

Mary Revelas; Anbupalam Thalamuthu; Anna Zettergren; Christopher Oldmeadow; Jenna Najar; Nazib M Seidu; Nicola J Armstrong; Carlos Riveros; John B Kwok; Peter R Schofield; Julian N Trollor; Margda Waern; Margaret J Wright; Henrik Zetterberg; David Ames; Kaj Belnnow; Henry Brodaty; Rodney J Scott; Ingmar Skoog; John R Attia; Perminder S Sachdev; Karen A Mather

doi:10.1007/s11357-022-00643-y

High polygenic risk score for exceptional longevity is associated with a healthy metabolic profile

Geroscience. 2023 Feb;45(1):399-413. doi: 10.1007/s11357-022-00643-y. Epub 2022 Aug 16.

Authors

Mary Revelas^{1

2}, Anbupalam Thalamuthu^{3

4}, Anna Zettergren⁵, Christopher Oldmeadow⁶, Jenna Najar^{5

7}, Nazib M Seidu⁵, Nicola J Armstrong^{3

8}, Carlos Riveros^{6

9}, John B Kwok^{4

10}, Peter R Schofield^{4

10}, Julian N Trollor^{3

11}, Margda Waern^{5

12}, Margaret J Wright^{9

13}, Henrik Zetterberg^{14

15

16

17

18}, David Ames^{19

20}, Kaj Belnnow^{16

17}, Henry Brodaty^{3

21}, Rodney J Scott^{22

23}, Ingmar Skoog^{5

7}, John R Attia^{6

22

23}, Perminder S Sachdev^{3

24}, Karen A Mather^{3

4}

Affiliations

¹ Centre for Healthy Brain Ageing, School of Psychiatry, UNSW Medicine & Health, UNSW, Sydney, Australia. m.revelas@student.unsw.edu.au.
² Neuroscience Research Australia, Sydney, NSW, Australia. m.revelas@student.unsw.edu.au.
³ Centre for Healthy Brain Ageing, School of Psychiatry, UNSW Medicine & Health, UNSW, Sydney, Australia.
⁴ Neuroscience Research Australia, Sydney, NSW, Australia.
⁵ Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden.
⁶ Hunter Medical Research Institute, Newcastle, NSW, Australia.
⁷ Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden.
⁸ Mathematics and Statistics, Curtin University, Perth, Australia.
⁹ Queensland Brain Institute, University of Queensland, Brisbane, Australia.
¹⁰ School of Medical Sciences, UNSW, Sydney, Australia.
¹¹ Department of Developmental Disability Neuropsychiatry, School of Psychiatry, UNSW Medicine & Health, UNSW, Sydney, Australia.
¹² Region Västra Götaland, Sahlgrenska University Hospital, Psychosis Clinic, Gothenburg, Sweden.
¹³ Centre for Advanced Imaging, University of Queensland, Brisbane, Australia.
¹⁴ Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.
¹⁵ UK Dementia Research Institute at UCL, London, UK.
¹⁶ Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
¹⁷ Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.
¹⁸ Hong Kong Centre for Neurodegenerative Diseases, Hong Kong, China.
¹⁹ University of Melbourne Academic Unit for Psychiatry of Old Age, St George's Hospital, Kew, VIC, Australia.
²⁰ National Ageing Research Institute, Parkville Victoria, Australia.
²¹ Dementia Centre for Research Collaboration, UNSW, Sydney, Australia.
²² Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW, Australia.
²³ Pathology North, John Hunter Hospital, Newcastle, NSW, Australia.
²⁴ Neuropsychiatric Institute, Prince of Wales Hospital, Randwick, NSW, Australia.

Abstract

Healthy metabolic measures in humans are associated with longevity. Dysregulation leads to metabolic syndrome (MetS) and negative health outcomes. Recent exceptional longevity (EL) genome wide association studies have facilitated estimation of an individual's polygenic risk score (PRS) for EL. We tested the hypothesis that individuals with high ELPRS have a low prevalence of MetS. Participants were from five cohorts of middle-aged to older adults. The primary analyses were performed in the UK Biobank (UKBB) (n = 407,800, 40-69 years). Replication analyses were undertaken using three Australian studies: Hunter Community Study (n = 2122, 55-85 years), Older Australian Twins Study (n = 539, 65-90 years) and Sydney Memory and Ageing Study (n = 925, 70-90 years), as well as the Swedish Gothenburg H70 Birth Cohort Studies (n = 2273, 70-93 years). MetS was defined using established criteria. Regressions and meta-analyses were performed with the ELPRS and MetS and its components. Generally, MetS prevalence (22-30%) was higher in the older cohorts. In the UKBB, high EL polygenic risk was associated with lower MetS prevalence (OR = 0.94, p = 1.84 × 10^-42) and its components (p < 2.30 × 10^-8). Meta-analyses of the replication cohorts showed nominal associations with MetS (p = 0.028) and 3 MetS components (p < 0.05). This work suggests individuals with a high polygenic risk for EL have a healthy metabolic profile promoting longevity.

Keywords: Longevity; Metabolic syndrome; PRS.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Aged
Australia
Genome-Wide Association Study
Humans
Longevity* / genetics
Metabolic Syndrome* / epidemiology
Metabolic Syndrome* / genetics
Metabolome
Middle Aged
Risk Factors

Abstract

Publication types

MeSH terms

Grants and funding