Biological ages : correlations, genetic determinants, and health outcomes
Author: Li, Xia
Date: 2021-11-11
Location: Lecture hall Petrén, Nobels väg 12B, Karolinska Institutet, Solna
Time: 16.00
Department: Inst för medicinsk epidemiologi och biostatistik / Dept of Medical Epidemiology and Biostatistics
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Thesis (2.066Mb)
Abstract
Population aging is a global trend and requires better evidence-based guidance. This thesis studied population aging from a molecular epidemiological angle. The overall work is centered on the “biological age (BA)”, which, in a broad sense, is a quantification of any aging-related changes in the cellular, organ-, system-, and/or organismal features. Ideally, BA provides additional information in the assessment and prediction of aging risks independent of chronological age.
The first and second studies explored the correlations between BAs and mortality associations. Study 1 examined a frailty measure, the frailty index (FI), with all-cause and cause-specific mortality in 42,953 twins. Increased FI was associated with higher risks of death due to all-cause, cardiovascular diseases, and respiratory-related causes. Particularly, the effect was independent of familiar factors and declined with growing age. Study 2 focused on a list of established BAs, including telomere length (TL), DNA methylation-based age estimators (DNAmAges), a multiple biomarker-derived BA score, and functional BA measures in 846 adults. Correlations were generally stronger between BAs of the same type, with TL showing the weakest correlations to other BAs, and the remaining demonstrating moderate to high correlations across BAs. Individually, all BAs except for TL were associated with mortality risk; jointly, two DNAmAges and the FI were predictive of mortality risk independent of the other BAs.
The third and fourth studies incorporated genetic information to disentangle relationships between genetic factors, clinical biomarkers, and aging phenotypes. Study 3 investigated a set of clinical biomarkers in relation to healthspan, i.e., disease-free lifespan, and used genetically predicted biomarkers as instrumental variables in 12,098 participants. Glycemic, lipid-, and inflammatory biomarkers were associated with altered risks of healthspan. In addition, genetic predisposition to elevated fasting blood glucose was associated with a higher risk of encountering an end of healthspan during the follow-up. Study 4 interrogated rare and functional genetic determinants of C-reactive protein (CRP) and the clinical relevance of the discovered genetic mutations in 161,430 adults. Carrying a protein-altering or loss-of-function mutation in the CRP gene was significantly associated with decreased serum CRP concentration. Mutation carriers were less affected by obese status in terms of the magnitude of increased CRP level.
In conclusion, BAs can capture distinct aspects of aging-related information. Making use of a set of multi-dimensional BAs could provide complementary evidence for risk assessment and intervention/treatment effect evaluation in research as well as in clinical practices. Measurements of BA together with genetic assessments would facilitate the delivery of precision medicine.
The first and second studies explored the correlations between BAs and mortality associations. Study 1 examined a frailty measure, the frailty index (FI), with all-cause and cause-specific mortality in 42,953 twins. Increased FI was associated with higher risks of death due to all-cause, cardiovascular diseases, and respiratory-related causes. Particularly, the effect was independent of familiar factors and declined with growing age. Study 2 focused on a list of established BAs, including telomere length (TL), DNA methylation-based age estimators (DNAmAges), a multiple biomarker-derived BA score, and functional BA measures in 846 adults. Correlations were generally stronger between BAs of the same type, with TL showing the weakest correlations to other BAs, and the remaining demonstrating moderate to high correlations across BAs. Individually, all BAs except for TL were associated with mortality risk; jointly, two DNAmAges and the FI were predictive of mortality risk independent of the other BAs.
The third and fourth studies incorporated genetic information to disentangle relationships between genetic factors, clinical biomarkers, and aging phenotypes. Study 3 investigated a set of clinical biomarkers in relation to healthspan, i.e., disease-free lifespan, and used genetically predicted biomarkers as instrumental variables in 12,098 participants. Glycemic, lipid-, and inflammatory biomarkers were associated with altered risks of healthspan. In addition, genetic predisposition to elevated fasting blood glucose was associated with a higher risk of encountering an end of healthspan during the follow-up. Study 4 interrogated rare and functional genetic determinants of C-reactive protein (CRP) and the clinical relevance of the discovered genetic mutations in 161,430 adults. Carrying a protein-altering or loss-of-function mutation in the CRP gene was significantly associated with decreased serum CRP concentration. Mutation carriers were less affected by obese status in terms of the magnitude of increased CRP level.
In conclusion, BAs can capture distinct aspects of aging-related information. Making use of a set of multi-dimensional BAs could provide complementary evidence for risk assessment and intervention/treatment effect evaluation in research as well as in clinical practices. Measurements of BA together with genetic assessments would facilitate the delivery of precision medicine.
List of papers:
I. Li X, Ploner A, Karlsson IK, Liu X, Magnusson PK, Pedersen NL, Hägg S, Jylhävä J. The frailty index is a predictor of cause-specific mortality independent of familial effects from midlife onwards: a large cohort study. BMC Medicine. 2019 May 15;17(1):94.
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II. Li X, Ploner A, Wang Y, Magnusson PK, Reynolds C, Finkel D, Pedersen NL, Jylhävä J, Hägg S. Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up. eLife. 2020 Feb 11;9:e51507.
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III. Li X, Ploner A, Wang Y, Zhan Y, Pedersen NL, Magnusson PK, Jylhävä J, Hägg S. Clinical biomarkers and associations with healthspan and lifespan: evidence from observational and genetic data. EBioMedicine. 2021 Apr 1;66:103318.
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IV. Li X, Ploner A, Wang Y, Mak J, Lu Y, Magnusson PK, Jylhävä J, Hägg S. Associations of exome-wide rare genetic variants with serum C-reactive protein. [Manuscript]
I. Li X, Ploner A, Karlsson IK, Liu X, Magnusson PK, Pedersen NL, Hägg S, Jylhävä J. The frailty index is a predictor of cause-specific mortality independent of familial effects from midlife onwards: a large cohort study. BMC Medicine. 2019 May 15;17(1):94.
Fulltext (DOI)
Pubmed
View record in Web of Science®
II. Li X, Ploner A, Wang Y, Magnusson PK, Reynolds C, Finkel D, Pedersen NL, Jylhävä J, Hägg S. Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up. eLife. 2020 Feb 11;9:e51507.
Fulltext (DOI)
Pubmed
View record in Web of Science®
III. Li X, Ploner A, Wang Y, Zhan Y, Pedersen NL, Magnusson PK, Jylhävä J, Hägg S. Clinical biomarkers and associations with healthspan and lifespan: evidence from observational and genetic data. EBioMedicine. 2021 Apr 1;66:103318.
Fulltext (DOI)
Pubmed
View record in Web of Science®
IV. Li X, Ploner A, Wang Y, Mak J, Lu Y, Magnusson PK, Jylhävä J, Hägg S. Associations of exome-wide rare genetic variants with serum C-reactive protein. [Manuscript]
Institution: Karolinska Institutet
Supervisor: Hägg, Sara
Co-supervisor: Jylhävä, Juulia; Magnusson, Patrik; Ploner, Alexander
Issue date: 2021-10-08
Rights:
Publication year: 2021
ISBN: 978-91-8016-373-6
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