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Tanksley, P. T.

Publications and source records attributed to Tanksley, P. T..

2 recordsLinked to original sources

Stability of DNA-Methylation Profiles of Biological Aging in Children and Adolescents

Background and ObjectivesMethylation profile scores (MPSs) index biological aging and aging-related disease in adults and are cross-sectionally associated with social determinants of health in childhood. MPSs thus provide an opportunity to trace how aging-related biology responds to environmental changes in early life. Information regarding the stability of MPSs in early life is currently lacking. MethodWe use longitudinal data from children and adolescents ages 8-18 (N = 428, M age = 12.15 years) from the Texas Twin Project. Participants contributed two waves of salivary DNA-methylation data (mean lag = 3.94 years), which were used to construct four MPSs reflecting multi-system physiological decline and mortality risk (PhenoAgeAccel and GrimAgeAccel), pace of biological aging (DunedinPACE), and cognitive function (Epigenetic-g). Furthermore, we exploit variation among participants in whether they were exposed to the COVID-19 pandemic during the course of study participation, in order to test how a historical period characterized by environmental disruption might affect childrens aging-related MPSs. ResultsAll MPSs showed moderate longitudinal stability (test-retest rs = 0.42, 0.44, 0.46, 0.51 for PhenoAgeAccel, GrimAgeAccel, and Epigenetic-g, and DunedinPACE, respectively). No differences in the stability of MPSs were apparent between those whose second assessment took place after the onset of the COVID-19 pandemic vs. those for whom both assessments took place prior to the pandemic. ConclusionsAging-related DNA-methylation patterns are less stable in childhood than has been previously observed in adulthood. Further developmental research on the methylome is necessary to understand which environmental perturbations in childhood impact trajectories of biological aging and when children are most sensitive to those impacts. Article SummaryMethylation profiles of biological aging are less stable in childhood than has been previously observed in adulthood. Whats Known on This SubjectMethylation profile scores (MPSs) index biological aging in adults and are cross-sectionally associated with social determinants of health in childhood. Aging-related MPSs in adulthood show very high test-retest stability but data on longitudinal stability of MPSs in childhood is sparse. What This Study AddsChildrens methylation profiles of biological aging are moderately stable across an approximately four-year period. Methylation profiles are less stable in childhood than in adulthood, suggesting that aging-related biology in childhood might be more responsive to environmental changes than in adulthood.

developmental biology↗

Guidelines for Evaluating the Comparability of Down-Sampled GWAS Summary Statistics

Proprietary genetic datasets are valuable for boosting the statistical power of genome-wide association studies (GWASs), but their use can restrict investigators from publicly sharing the resulting summary statistics. Although researchers can resort to sharing down-sampled versions that exclude restricted data, down-sampling reduces power and might change the genetic etiology of the phenotype being studied. These problems are further complicated when using multivariate GWAS methods, such as genomic structural equation modeling (Genomic SEM), that model genetic correlations across multiple traits. Here, we propose a systematic approach to assess the comparability of GWAS summary statistics that include versus exclude restricted data. Illustrating this approach with a multivariate GWAS of an externalizing factor, we assessed the impact of down-sampling on (1) the strength of the genetic signal in univariate GWASs, (2) the factor loadings and model fit in multivariate Genomic SEM, (3) the strength of the genetic signal at the factor level, (4) insights from gene-property analyses, (5) the pattern of genetic correlations with other traits, and (6) polygenic score analyses in independent samples. For the externalizing GWAS, down-sampling resulted in a loss of genetic signal and fewer genome-wide significant loci, while the factor loadings and model fit, gene-property analyses, genetic correlations, and polygenic score analyses are robust. Given the importance of data sharing for the advancement of open science, we recommend that investigators who share down-sampled summary statistics report these analyses as accompanying documentation to support other researchers use of the summary statistics.

genetics↗