Age-dependent changes in mean and variance of gene expression across tissues in a twin cohort
Ana Viñuela,Andrew A. Brown,Andrew A. Brown,Alfonso Buil,Alfonso Buil,Pei-Chien Tsai,Matthew N. Davies,Jordana T. Bell,Emmanouil T. Dermitzakis,Emmanouil T. Dermitzakis,Tim D. Spector,Kerrin S. Small +11 more
TL;DR: It is shown that additive genetic effects explain considerably more of the variance in gene expression than aging, but less that other environmental factors, potentially explaining why reliable expression-derived biomarkers for healthy-aging have proved elusive compared with those derived from methylation.
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Abstract: Changes in the mean and variance of gene expression with age have consequences for healthy aging and disease development. Age-dependent changes in phenotypic variance have been associated with a decline in regulatory functions leading to increase in disease risk. Here, we investigate age-related mean and variance changes in gene expression measured by RNA-seq of fat, skin, whole blood and derived lymphoblastoid cell lines (LCLs) expression from 855 adult female twins. We see evidence of up to 60% of age effects on transcription levels shared across tissues, and 47% of those on splicing. Using gene expression variance and discordance between genetically identical MZ twin pairs, we identify 137 genes with age-related changes in variance and 42 genes with age-related discordance between co-twins; implying the latter are driven by environmental effects. We identify four eQTLs whose effect on expression is age-dependent (FDR 5%). Combined, these results show a complicated mix of environmental and genetically driven changes in expression with age. Using the twin structure in our data, we show that additive genetic effects explain considerably more of the variance in gene expression than aging, but less that other environmental factors, potentially explaining why reliable expression-derived biomarkers for healthy-aging have proved elusive compared with those derived from methylation.
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Distinctive roles of age, sex, and genetics in shaping transcriptional variation of human immune responses to microbial challenges
Barbara Piasecka,Darragh Duffy,Alejandra Urrutia,Alejandra Urrutia,Hélène Quach,Etienne Patin,Celine Posseme,Jacob Bergstedt,Bruno Charbit,Vincent Rouilly,Cameron Ross MacPherson,Milena Hasan,Benoit Albaud,David Gentien,Jacques Fellay,Jacques Fellay,Matthew L. Albert,Matthew L. Albert,Lluis Quintana-Murci +18 more
TL;DR: The respective effects of age, sex, genetics, and cellular heterogeneity on the interindividual variability of immune responses are quantified and constitutes a valuable resource for further exploration in the context of different infection risks or disease outcomes.
210
Age-related DNA methylation changes are sex-specific: a comprehensive assessment.
I. I. Yusipov,Maria Giulia Bacalini,Alena I. Kalyakulina,Mikhail Krivonosov,Chiara Pirazzini,Noémie Gensous,Francesco Ravaioli,Maddalena Milazzo,Cristina Giuliani,Cristina Giuliani,Maria Vedunova,Giovanni Fiorito,Giovanni Fiorito,Amedeo Gagliardi,Silvia Polidoro,Paolo Garagnani,Mikhail Ivanchenko,Claudio Franceschi +17 more
- 03 Dec 2020
TL;DR: A meta-analysis of 4 large whole blood datasets comparing 4 aspects of epigenetic age-dependent remodeling between the two sexes found that a large fraction (43%) of sex-associated probes undergoes age-associated DNA methylation changes, and that a limited number of probes show age-by-sex interaction.
Gene expression variability: the other dimension in transcriptome analysis
TL;DR: An overview of recent findings on effects of external cues, such as diet and aging, on expression variability and on other biological phenomena that can be linked to it, and metrics and tools that were developed for quantification of expression variability are discussed.
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On the cross-population generalizability of gene expression prediction models.
Kevin L. Keys,Kevin L. Keys,Angel C.Y. Mak,Marquitta J. White,Walter L. Eckalbar,Andrew Dahl,Joel Mefford,Anna V. Mikhaylova,Maria G. Contreras,Maria G. Contreras,Jennifer R. Elhawary,Celeste Eng,Donglei Hu,Scott Huntsman,Sam S. Oh,Sandra Salazar,Michael A. LeNoir,Jimmie Ye,Timothy A. Thornton,Noah Zaitlen,Esteban G. Burchard,Christopher R. Gignoux +21 more
TL;DR: It is shown that accurate cross-population generalizability of transcriptome prediction only arises when eQTL architecture is substantially shared across populations, and that generating RNA-Seq data in diverse populations is a critical step towards multi-ethnic utility of gene expression prediction.
A transcriptome based aging clock near the theoretical limit of accuracy
David H. Meyer,Björn Schumacher +1 more
TL;DR: This work devised an approach that uses temporal scaling and binarization of C. elegans transcriptomes to define a gene set that predicts biological age with an accuracy that is close to the theoretical limit and shows that this transcriptome clock can also be applied to human age prediction with high accuracy.
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An integrated map of genetic variation from 1,092 human genomes
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DNA methylation age of human tissues and cell types
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