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Tissue-specific impacts of aging and genetics on gene expression patterns in humans

View ORCID ProfileRyo Yamamoto, View ORCID ProfileRyan Chung, View ORCID ProfileJuan Manuel Vazquez, View ORCID ProfileHuanjie Sheng, Philippa Steinberg, View ORCID ProfileNilah M Ioannidis, View ORCID ProfilePeter H Sudmant
doi: https://doi.org/10.1101/2021.11.16.468753
Ryo Yamamoto
1Department of Integrative Biology, University of California, Berkeley
2Bioinformatics Interdepartmental Program, University of California, Los Angeles
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Ryan Chung
3Center for Computational Biology, University of California, Berkeley
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Juan Manuel Vazquez
1Department of Integrative Biology, University of California, Berkeley
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Huanjie Sheng
1Department of Integrative Biology, University of California, Berkeley
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Philippa Steinberg
1Department of Integrative Biology, University of California, Berkeley
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Nilah M Ioannidis
3Center for Computational Biology, University of California, Berkeley
4Department of Electrical Engineering and Computer Sciences, University of California, Berkeley
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  • For correspondence: psudmant@berkeley.edu nilah@berkeley.edu
Peter H Sudmant
1Department of Integrative Biology, University of California, Berkeley
3Center for Computational Biology, University of California, Berkeley
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  • For correspondence: psudmant@berkeley.edu nilah@berkeley.edu
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Abstract

Age is the primary risk factor for many common human diseases including heart disease, Alzheimer’s dementias, cancers, and diabetes. Determining how and why tissues age differently is key to understanding the onset and progression of such pathologies. Here, we set out to quantify the relative contributions of genetics and aging to gene expression patterns from data collected across 27 tissues from 948 humans. We show that age impacts the predictive power of expression quantitative trait loci across several tissues. Jointly modelling the contributions of age and genetics to transcript level variation we find that the heritability (h2) of gene expression is largely consistent among tissues. In contrast, the average contribution of aging to gene expression variance varied by more than 20-fold among tissues with Embedded Image in 5 tissues. We find that the coordinated decline of mitochondrial and translation factors is a widespread signature of aging across tissues. Finally, we show that while in general the force of purifying selection is stronger on genes expressed early in life compared to late in life as predicted by Medawar’s hypothesis, a handful of highly proliferative tissues exhibit the opposite pattern. These non-Medawarian tissues exhibit high rates of cancer and age-of-expression associated somatic mutations in cancer. In contrast, gene expression variation that is under genetic control is strongly enriched for genes under relaxed constraint. Together we present a novel framework for predicting gene expression phenotypes from genetics and age and provide insights into the tissue-specific relative contributions of genes and the environment to phenotypes of aging.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/sudmantlab/gene_expression_aging

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted May 17, 2022.
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Tissue-specific impacts of aging and genetics on gene expression patterns in humans
Ryo Yamamoto, Ryan Chung, Juan Manuel Vazquez, Huanjie Sheng, Philippa Steinberg, Nilah M Ioannidis, Peter H Sudmant
bioRxiv 2021.11.16.468753; doi: https://doi.org/10.1101/2021.11.16.468753
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Tissue-specific impacts of aging and genetics on gene expression patterns in humans
Ryo Yamamoto, Ryan Chung, Juan Manuel Vazquez, Huanjie Sheng, Philippa Steinberg, Nilah M Ioannidis, Peter H Sudmant
bioRxiv 2021.11.16.468753; doi: https://doi.org/10.1101/2021.11.16.468753

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