@article {9168, title = {Heterogeneity in polygenic scores for common human traits}, journal = {bioRxiv}, year = {Forthcoming}, abstract = {This study investigates the creation of polygenic scores (PGS)s for human population research. PGSs are a linear, usually weighted, combination of risk alleles that estimate the cumulative genetic risk of an individual for a particular trait. While conceptually simple, there are numerous ways to estimate PGSs, not all achieving the same end goals. In this paper, we systematically investigate the impact of four key decisions in the building of PGSs from published genome-wide association meta-analysis results: 1) whether to use single nucleotide polymorphisms (SNPs) assessed by imputation, 2) criteria for selecting which SNPs to include in the score, 3) whether to account for linkage disequilibrium (LD), and 4) if accounting for LD, which type of method best captures the correlation structure among SNPs (i.e. clumping vs. pruning). Using the Health and Retirement Study (HRS), a nationally representative, population-based longitudinal panel study of Americans over the age of 50, we examine the predictive ability as well as the variability and co-variability in PGSs arising from these different estimation approaches. We examine four traits with large published and replicated genome-wide association studies (height, body mass index, educational attainment, and depression). Our central finding demonstrates PGSs that include all available SNPs either explain the most amount of variation in an outcome or are not significantly different than the PGSs that does. Thus, for reproducibility through rigor and transparency, we recommend that researchers include a PGS with all available SNPs as a reference, and provide substantial justification for using alternative methods.}, keywords = {Genetics, Heterogeneity, PGS}, doi = {10.1101/106062}, author = {Erin B Ware and Lauren L Schmitz and Jessica Faul and Arianna M Gard and Colter Mitchell and Wei Zhao and David R Weir and Sharon L R Kardia} } @article {11828, title = {Trans-ethnic Meta-analysis of Interactions between Genetics and Early Life Socioeconomic Context on Memory Performance and Decline in Older Americans.}, journal = {The Journals of Gerontology, Series A}, volume = {77}, year = {2022}, pages = {2248-2256}, abstract = {

Later life cognitive function is influenced by genetics as well as early- and later-life socioeconomic context. However, few studies have examined the interaction between genetics and early childhood factors. Using gene-based tests (iSKAT/iSKAT-O), we examined whether common and/or rare exonic variants in 39 gene regions previously associated with cognitive performance, dementia, and related traits had an interaction with childhood socioeconomic context (parental education and financial strain) on memory performance or decline in European ancestry (EA, N=10,468) and African ancestry (AA, N=2,252) participants from the Health and Retirement Study. Of the 39 genes, 22 in EA and 19 in AA had nominally significant interactions with at least one childhood socioeconomic measure on memory performance and/or decline; however, all but one (father{\textquoteright}s education by SLC24A4 in AA) were not significant after multiple testing correction (FDR <0.05). In trans-ethnic meta-analysis, two genes interacted with childhood socioeconomic context (FDR <0.05): mother{\textquoteright}s education by MS4A4A on memory performance, and father{\textquoteright}s education by SLC24A4 on memory decline. Both interactions remained significant (p<0.05) after adjusting for respondent{\textquoteright}s own educational attainment, APOE ε4 status, lifestyle factors, BMI, and comorbidities. For both interactions in EA and AA, the genetic effect was stronger in participants with low parental education. Examination of common and rare variants in genes discovered through GWAS shows that childhood context may interact with key gene regions to jointly impact later life memory function and decline. Genetic effects may be more salient for those with lower childhood socioeconomic status.

}, keywords = {Childhood SES, Cognition, Education, Epidemiology, Gene-Environment Interaction, Genetics, Memory, Rare Variant}, issn = {1758-535X}, doi = {10.1093/gerona/glab255}, author = {Jessica Faul and Kho, Minjung and Zhao, Wei and Rumfelt, Kalee E and Yu, Miao and Colter Mitchell and Smith, Jennifer A} } @article {12054, title = {Association of GrimAge DNA methylation components and 2-year mortality in the Health and Retirement Study }, journal = {Innovation in Aging}, volume = {5}, year = {2021}, pages = {675}, abstract = {DNA methylation (DNAm) patterns related to age and aging phenotypes (i.e., epigenetic clocks) are of growing interest as indicators of biological age and risk of negative health outcomes. We investigated associations between the components of GrimAge, an epigenetic clock estimated from DNAm patterns for seven blood protein levels and smoking pack years, and 2-year mortality in the Health and Retirement Study (HRS) to determine if any of the DNAm subcomponents were driving observed associations. A representative subsample of individuals who participated in the HRS 2016 Venus Blood Study were included in this analysis (N=3430). DNAm was measured with the Infinium Methylation EPIC BeadChip. Deaths that occurred between 2016 and 2018 contributed to 2-year mortality estimates (N=159, 4.5\% of the sample). Weighted logistic regression estimated the association first between GrimAge and 2-year mortality and second between the DNAm subcomponents and 2-year mortality. All models were adjusted for age, sex, race/ethnicity, education, current smoking status, smoking pack years and cell composition of the biological sample. The average GrimAge for participants with and without 2-year mortality was 77 years 68 years respectively. A one-year increase in GrimAge was associated with 17\% higher odds of 2-year mortality (95\% CI: 1.16, 1.17). Two of the seven DNAm blood protein subcomponents of GrimAge (TIMP metallopeptidase inhibitor 1, adrenomedullin) and DNAm smoking pack years were associated with 2-year mortality and DNAm smoking pack years appeared to drive the overall GrimAge association with 2-year mortality. GrimAge was a better predictor of 2-year mortality than the DNAm subcomponents individually.}, keywords = {2-year mortality, DNA Methylation, GrimAge}, doi = {https://doi.org/10.1093/geroni/igab046.2525}, author = {Meier, Helen and Colter Mitchell and Eileen M. Crimmins and Bharat Thyagarajan and Jessica Faul} } @article {11490, title = {Cumulative Genetic Risk and APOE ε4 Are Independently Associated With Dementia Status in a Multiethnic, Population-Based Cohort}, journal = {Neurology Genetics}, volume = {7}, year = {2021}, pages = {e576}, abstract = {

Objective: Alzheimer disease (AD) is a common and costly neurodegenerative disorder. A large proportion of AD risk is heritable, and many genetic risk factors have been identified. The objective of this study was to test the hypothesis that cumulative genetic risk of known AD markers contributed to odds of dementia in a population-based sample.

Methods: In the US population-based Health and Retirement Study (waves 1995-2014), we evaluated the role of cumulative genetic risk of AD, with and without the alleles, on dementia status (dementia, cognitive impairment without dementia, borderline cognitive impairment without dementia, and cognitively normal). We used logistic regression, accounting for demographic covariates and genetic principal components, and analyses were stratified by European and African genetic ancestry.

Results: In the European ancestry sample (n = 8,399), both AD polygenic score excluding the genetic region (odds ratio [OR] = 1.10; 95\% confidence interval [CI]: 1.00-1.20) and the presence of any alleles (OR = 2.42; 95\% CI: 1.99-2.95) were associated with the odds of dementia relative to normal cognition in a mutually adjusted model. In the African ancestry sample (n = 1,605), the presence of any alleles was associated with 1.77 (95\% CI: 1.20-2.61) times higher odds of dementia, whereas the AD polygenic score excluding the genetic region was not significantly associated with the odds of dementia relative to normal cognition 1.06 (95\% CI: 0.97-1.30).

Conclusions: Cumulative genetic risk of AD and are both independent predictors of dementia in European ancestry. This study provides important insight into the polygenic nature of dementia and demonstrates the utility of polygenic scores in dementia research.

}, keywords = {Aging, Alzheimer disease, Cognition, genetic risk}, issn = {2376-7839}, doi = {10.1212/NXG.0000000000000576}, author = {Kelly M Bakulski and Vadari, Harita S and Jessica Faul and Steven G Heeringa and Sharon L R Kardia and Kenneth M. Langa and Jennifer A. Smith and Jennifer J Manly and Colter Mitchell and Benke, Kelly S and Erin B Ware} } @article {12053, title = {Epigenome Wide Associations of Smoking Behavior in the Health and Retirement Study}, journal = {Innovation in Aging}, volume = {5}, year = {2021}, pages = {668}, abstract = {DNA methylation (DNAm) is an increasingly popular biomarker of health and aging outcomes. Smoking behaviors have a significant and well documented correlation with methylation signatures within the epigenome and are important confounding variables to account for in epigenome-wide association studies (EWAS). However, the common classification of individuals as {\textquoteleft}current{\textquoteright}, {\textquoteleft}former{\textquoteright}, and {\textquoteleft}never{\textquoteright} smokers may miss crucial DNAm patterns associated with other smoking behaviors such as duration, intensity, and frequency of cigarette smoking, resulting in an underestimation of the contribution of smoking behaviors to DNAm and potentially biasing EWAS results. We investigated associations between multiple smoking behavioral phenotypes (smoking pack years, smoking duration, smoking start age, and smoking end age) and single site DNAm using linear regressions adjusting for age, sex, race/ethnicity, education, and cell-type proportions in a subsample of individuals who participated in the HRS 2016 Venous Blood Study (N=1,775). DNAm was measured using the Infinium Methylation EPIC BeadChip. All 4 phenotypes had significant associations (FDR < 0.05) with many methylation sites (packyears=6859, smoking duration=6572, start age=11374, quit age=773). There was not much overlap in DNAm sites between the full set of models with only 6 overlapping between all 4. However, the phenotypes packyears and smoking duration showed large overlap (N=3782). Results suggest additional smoking phenotypes beyond current/former/never smoker classification should be included in EWAS analyses to appropriately account for the influence of smoking behaviors on DNAm.}, keywords = {DNA Methylation, epigenome-wide association studies, Smoking}, doi = {https://doi.org/10.1093/geroni/igab046.2503}, author = {Fisher, Jonah and Meier, Helen and Jessica Faul and Colter Mitchell and Eileen M. Crimmins and Bharat Thyagarajan} } @article {9931, title = {Genetic effects and gene-by-education interactions on episodic memory performance and decline in an aging population.}, journal = {Social Science \& Medicine}, volume = {271}, year = {2021}, pages = {112039}, abstract = {Both social and genetic factors contribute to cognitive impairment and decline, yet genetic factors identified through genome-wide association studies (GWAS) explain only a small portion of trait variability. This "missing heritability" may be due to rare, potentially functional, genetic variants not assessed by GWAS, as well as gene-by-social factor interactions not explicitly modeled. Gene-by-social factor interactions may also operate differently across race/ethnic groups. We selected 39 genes that had significant, replicated associations with cognition, dementia, and related traits in published GWAS. Using gene-based analysis (SKAT/iSKAT), we tested whether common and/or rare variants were associated with episodic memory performance and decline either alone or through interaction with education in >10,000 European ancestry (EA) and >2200 African ancestry (AA) respondents from the Health and Retirement Study (HRS). Nine genes in EA and five genes in AA were associated with memory performance or decline (p < 0.05), and these effects did not attenuate after adjusting for education. Interaction between education and CLPTM1 on memory performance was significant in AA (p = 0.003; FDR-adjusted p = 0.038) and nominally significant in EA (p = 0.026). In both ethnicities, low memory performance was associated with CLPTM1 genotype (rs10416261) only for those with less than high school education, and effects persisted after adjusting for APOE ε4. For over 70\% of gene-by-education interactions across the genome that were at least nominally significant in either ethnic group (p < 0.05), genetic effects were only observed for those with less than high school education. These results suggest that genetic effects on memory identified in this study are not mediated by education, but there may be important gene-by-education interactions across the genome, including in the broader APOE genomic region, which operate independently of APOE ε4. This work illustrates the importance of developing theoretical frameworks and methodological approaches for integrating social and genomic data to study cognition across ethnic groups.}, keywords = {Education, Genetics, GWAS, Memory}, issn = {1873-5347}, doi = {10.1016/j.socscimed.2018.11.019}, author = {Jennifer A Smith and Kho, Minjung and Wei Zhao and Yu, Miao and Colter Mitchell and Jessica Faul} } @article {11589, title = {Phenotypic and genetic markers of psychopathology in a population-based sample of older adults.}, journal = {Translational Psychiatry}, volume = {11}, year = {2021}, pages = {239}, abstract = {

Although psychiatric phenotypes are hypothesized to organize into a two-factor internalizing-externalizing structure, few studies have evaluated the structure of psychopathology in older adults, nor explored whether genome-wide polygenic scores (PGSs) are associated with psychopathology in a domain-specific manner. We used data from 6003 individuals of European ancestry from the Health and Retirement Study, a large population-based sample of older adults in the United States. Confirmatory factor analyses were applied to validated measures of psychopathology and PGSs were derived from well-powered genome-wide association studies (GWAS). Genomic SEM was implemented to construct latent PGSs for internalizing, externalizing, and general psychopathology. Phenotypically, the data were best characterized by a single general factor of psychopathology, a factor structure that was replicated across genders and age groups. Although externalizing PGSs (cannabis use, antisocial behavior, alcohol dependence, attention deficit hyperactivity disorder) were not associated with any phenotypes, PGSs for major depressive disorder, neuroticism, and anxiety disorders were associated with both internalizing and externalizing phenotypes. Moreover, the variance explained in the general factor of psychopathology increased by twofold (from 1\% to 2\%) using the latent internalizing or latent one-factor PGSs, derived using weights from Genomic Structural Equation Modeling (SEM), compared with any of the individual PGSs. Collectively, results suggest that genetic risk factors for and phenotypic markers of psychiatric disorders are transdiagnostic in older adults of European ancestry. Alternative explanations are discussed, including methodological limitations of GWAS and phenotypic measurement of psychiatric outcome in large-scale population-based studies.

}, keywords = {Genetic Markers, Phenotypic markers, psychopathology}, issn = {2158-3188}, doi = {10.1038/s41398-021-01354-2}, author = {Arianna M Gard and Erin B Ware and Hyde, Luke W and Lauren L Schmitz and Jessica Faul and Colter Mitchell} } @article {11204, title = {Considering the APOE locus in Alzheimer{\textquoteright}s disease polygenic scores in the Health and Retirement Study: a longitudinal panel study.}, journal = {BMC Medical Genomics}, volume = {13}, year = {2020}, pages = {164}, abstract = {

BACKGROUND: Polygenic scores are a strategy to aggregate the small, additive effects of single nucleotide polymorphisms across the genome. With phenotypes like Alzheimer{\textquoteright}s disease, which have a strong and well-established genomic locus (APOE), the cumulative effect of genetic variants outside of this area has not been well established in a population-representative sample.

METHODS: Here we examine the association between polygenic scores for Alzheimer{\textquoteright}s disease both with and without the APOE region (chr19: 45,384,477 to 45,432,606, build 37/hg 19) at different P value thresholds and dementia. We also investigate the addition of APOE-ε4 carrier status and its effect on the polygenic score-dementia association in the Health and Retirement Study using generalized linear models accounting for repeated measures by individual and use a binomial distribution, logit link, and unstructured correlation structure.

RESULTS: In a large sample of European ancestry participants of the Health and Retirement Study (n = 9872) with an average of 5.2 (standard deviation 1.8) visit spaced two years apart, we found that including the APOE region through weighted variants in a polygenic score was insufficient to capture the large amount of risk attributed to this region. We also found that a polygenic score with a P value threshold of 0.01 had the strongest association with the odds of dementia in this sample (odds ratio = 1.10 95\%CI 1.0 to 1.2).

CONCLUSION: We recommend removing the APOE region from polygenic score calculation and treating the APOE locus as an independent covariate when modeling dementia. We also recommend using a moderately conservative P value threshold (e.g. 0.01) when creating polygenic scores for Alzheimer{\textquoteright}s disease on dementia. These recommendations may help elucidate relationships between polygenic scores and regions of strong significance for phenotypes similar to Alzheimer{\textquoteright}s disease.

}, keywords = {Alzheimer{\textquoteright}s disease, Apolipoprotein E, Dementia, P-value, polygenic score, Thresholding}, issn = {1755-8794}, doi = {10.1186/s12920-020-00815-9}, author = {Erin B Ware and Jessica Faul and Colter Mitchell and Kelly M Bakulski} } @article {9474, title = {Does Telomere Length Indicate Biological, Physical and Cognitive Health Among Older Adults? Evidence from the Health and Retirement Study.}, journal = {Journals of Gerontology Series A: Biological Sciences and Medical Sciences}, volume = {73}, year = {2018}, month = {07/2019}, pages = {905-905}, abstract = {Telomere length (TL) has been suggested as a biomarker that can indicate individual variability in the rate of aging. Yet, it remains unclear whether TL is related to recognized indicators of health in an aging, older nationally representative sample. We examine whether TL is associated with 15 biological, physical and cognitive markers of health among older adults ages 54+. TL was assayed from saliva using quantitative PCR (T/S ratio) in the 2008 Health and Retirement Study (n=4,074). We estimated probability of high risk levels across indictors of health by TL and age-singly and jointly. TL was associated with seven indicators of poor functioning: HDL and total cholesterol, cystatin C, pulse pressure, BMI, lung function, and walking speed. However, after adjusting for age, associations were substantially attenuated; only associations with cholesterol and lung function remained significant. Additionally, findings show TL did not add to the predictive power of chronological age in predicting poor functioning. While TL may not be a useful clinical marker of functional aging in an older adult population, it may still play an important role in longitudinal studies in young and middle aged populations that attempt to understand aging.}, keywords = {Biomarkers, Cognitive Ability, Health Conditions and Status, Telomeres}, issn = {1758-535X}, doi = {10.1093/gerona/gly001}, author = {Lauren L Brown and Yuan S Zhang and Colter Mitchell and Jennifer A Ailshire} } @article {8351, title = {Estimating Telomere Length Heritability in an Unrelated Sample of Adults: Is Heritability of Telomere Length Modified by Life Course Socioeconomic Status?}, journal = {Biodemography and Social Biology}, volume = {62}, year = {2016}, note = {Times Cited: 0 Si 0}, pages = {73-86}, publisher = {62}, abstract = {Telomere length (TL) is a widely used marker of biological aging and is associated with an increased risk of morbidity and mortality. Recently, there has been evidence for an association between TL and socioeconomic status (SES), particularly for measures of education and childhood SES. Individual differences in TL are also influenced by genetic factors, with heritability estimates from twin and sibling studies ranging from 34 to 82 percent. Yet the additive heritability of TL as a result of measured genetic variations and the extent to which heritability is modified by SES is still unknown. Data from the Health and Retirement Study, a nationally representative cohort of older adults (mean age 69years), were used to provide the first estimates of molecular-based heritability of TL using genome-wide complex trait analysis (GCTA). We found that additive genetic variance contributed 28 percent (p=.012) of total phenotypic variance of TL in the European American sample (n=3,290). Estimation using the GCTA and KING Robust relationship inference methods did not differ significantly in this sample. None of the variance from the gene-by-SES interactions examined contributed significantly to the total TL variance. Estimation of heritability and genetic interaction with SES in the African American sample (n=442) was too unstable to provide reliable estimates.}, keywords = {Genetics, Health Conditions and Status}, doi = {10.1080/19485565.2015.1120645}, author = {Jessica Faul and Colter Mitchell and Wei Zhao} }