@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 {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 {9172,
	title = {The complex genetics of gait speed: genome-wide meta-analysis approach.},
	journal = {Aging (Albany NY)},
	volume = {9},
	year = {2017},
	pages = {209-246},
	abstract = {Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging.},
	keywords = {Genetics, GWAS},
	issn = {1945-4589},
	doi = {10.18632/aging.101151},
	author = {Ben-Avraham, Dan and Karasik, David and Joe Verghese and Kathryn L Lunetta and John D Eicher and Vered, Rotem and Deelen, Joris and Alice M. Arnold and Aron S Buchman and Toshiko Tanaka and Jessica Faul and Nethander, Maria and Myriam Fornage and Hieab H Adams and Amy M Matteini and Michele L Callisaya and Albert Vernon Smith and Lei Yu and Philip L de Jager and Denis A Evans and Gudnason, Vilmundur and Hofman, Albert and Pattie, Alison and Corley, Janie and Lenore J Launer and David S Knopman and Parimi, Neeta and Stephen T Turner and Bandinelli, Stefania and Beekman, Marian and Gutman, Danielle and Sharvit, Lital and Simon P Mooijaart and David C Liewald and Jeanine J Houwing-Duistermaat and Ohlsson, Claes and Moed, Matthijs and Vincent J Verlinden and Mellstr{\"o}m, Dan and Jos N van der Geest and Karlsson, Magnus and Dena G Hernandez and McWhirter, Rebekah and Yongmei Liu and Thomson, Russell and Tranah, Gregory J and Andr{\'e} G Uitterlinden and David R Weir and Wei Zhao and John M Starr and Mohammed Arfan Ikram and David A Bennett and Steven R Cummings and Ian J Deary and Tamara B Harris and Sharon L R Kardia and Thomas H Mosley and Velandai K Srikanth and Beverly G Windham and Anne B Newman and Jeremy D Walston and Gail Davies and Daniel S Evans and Eline P Slagboom and Luigi Ferrucci and Douglas P Kiel and Joanne M Murabito and Atzmon, Gil}
}
@article {9429,
	title = {Gene-by-Psychosocial Factor Interactions Influence Diastolic Blood Pressure in European and African Ancestry Populations: Meta-Analysis of Four Cohort Studies.},
	journal = {Int J Environ Res Public Health},
	volume = {14},
	year = {2017},
	abstract = {Inter-individual variability in blood pressure (BP) is influenced by both genetic and non-genetic factors including socioeconomic and psychosocial stressors. A deeper understanding of the gene-by-socioeconomic/psychosocial factor interactions on BP may help to identify individuals that are genetically susceptible to high BP in specific social contexts. In this study, we used a genomic region-based method for longitudinal analysis, Longitudinal Gene-Environment-Wide Interaction Studies (LGEWIS), to evaluate the effects of interactions between known socioeconomic/psychosocial and genetic risk factors on systolic and diastolic BP in four large epidemiologic cohorts of European and/or African ancestry. After correction for multiple testing, two interactions were significantly associated with diastolic BP. In European ancestry participants, outward/trait anger score had a significant interaction with the C10orf107 genomic region (p = 0.0019). In African ancestry participants, depressive symptom score had a significant interaction with the HFE genomic region (p = 0.0048). This study provides a foundation for using genomic region-based longitudinal analysis to identify subgroups of the population that may be at greater risk of elevated BP due to the combined influence of genetic and socioeconomic/psychosocial risk factors.},
	keywords = {Blood pressure, Genetics, GWAS, Meta-analyses, Psychosocial, Socioeconomic factors},
	issn = {1660-4601},
	doi = {10.3390/ijerph14121596},
	author = {Wei Zhao and Yasutake, Kalyn and August, Carmella and Scott M Ratliff and Jessica Faul and Boerwinkle, Eric and Chakravarti, Aravinda and Ana V. Diez-Roux and Gao, Yan and Michael E Griswold and Gerardo Heiss and Sharon L R Kardia and Alanna C Morrison and Musani, Solomon K and Mwasongwe, Stanford and Kari E North and Rose, Kathryn M and Sims, Mario and Yan V Sun and David R Weir and Belinda L Needham}
}
@article {9313,
	title = {Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting},
	journal = {International Journal of Environmental Research and Public Health},
	volume = {14},
	year = {2017},
	month = {09/2017},
	pages = {1153},
	abstract = {Obesity, which develops over time, is one of the leading causes of chronic diseases such as cardiovascular disease. However, hundreds of BMI (body mass index)-associated genetic loci identified through large-scale genome-wide association studies (GWAS) only explain about 2.7\% of BMI variation. Most common human traits are believed to be influenced by both genetic and environmental factors. Past studies suggest a variety of environmental features that are associated with obesity, including socioeconomic status and psychosocial factors. This study combines both gene/regions and environmental factors to explore whether social/psychosocial factors (childhood and adult socioeconomic status, social support, anger, chronic burden, stressful life events, and depressive symptoms) modify the effect of sets of genetic variants on BMI in European American and African American participants in the Health and Retirement Study (HRS). In order to incorporate longitudinal phenotype data collected in the HRS and investigate entire sets of single nucleotide polymorphisms (SNPs) within gene/region simultaneously, we applied a novel set-based test for gene-environment interaction in longitudinal studies (LGEWIS). Childhood socioeconomic status (parental education) was found to modify the genetic effect in the gene/region around SNP rs9540493 on BMI in European Americans in the HRS. The most significant SNP (rs9540488) by childhood socioeconomic status interaction within the rs9540493 gene/region was suggestively replicated in the Multi-Ethnic Study of Atherosclerosis (MESA) (p = 0.07).},
	keywords = {BMI, Genetics, Obesity},
	doi = {10.3390/ijerph14101153},
	url = {http://www.mdpi.com/1660-4601/14/10/1153http://www.mdpi.com/1660-4601/14/10/1153/pdf},
	author = {Wei Zhao and Erin B Ware and He, Zihuai and Sharon L R Kardia and Jessica Faul}
}
@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}
}
@article {8876,
	title = {Personality Polygenes, Positive Affect, and Life Satisfaction.},
	journal = {Twin Res Hum Genet},
	volume = {19},
	year = {2016},
	month = {2016 Oct},
	pages = {407-17},
	abstract = {<p>Approximately half of the variation in wellbeing measures overlaps with variation in personality traits. Studies of non-human primate pedigrees and human twins suggest that this is due to common genetic influences. We tested whether personality polygenic scores for the NEO Five-Factor Inventory (NEO-FFI) domains and for item response theory (IRT) derived extraversion and neuroticism scores predict variance in wellbeing measures. Polygenic scores were based on published genome-wide association (GWA) results in over 17,000 individuals for the NEO-FFI and in over 63,000 for the IRT extraversion and neuroticism traits. The NEO-FFI polygenic scores were used to predict life satisfaction in 7 cohorts, positive affect in 12 cohorts, and general wellbeing in 1 cohort (maximal N = 46,508). Meta-analysis of these results showed no significant association between NEO-FFI personality polygenic scores and the wellbeing measures. IRT extraversion and neuroticism polygenic scores were used to predict life satisfaction and positive affect in almost 37,000 individuals from UK Biobank. Significant positive associations (effect sizes <0.05\%) were observed between the extraversion polygenic score and wellbeing measures, and a negative association was observed between the polygenic neuroticism score and life satisfaction. Furthermore, using GWA data, genetic correlations of -0.49 and -0.55 were estimated between neuroticism with life satisfaction and positive affect, respectively. The moderate genetic correlation between neuroticism and wellbeing is in line with twin research showing that genetic influences on wellbeing are also shared with other independent personality domains.</p>},
	keywords = {Genetics, Happiness, Polygenic Prediction, SSGAC, Well-being},
	issn = {1832-4274},
	doi = {10.1017/thg.2016.65},
	author = {Weiss, Alexander and Baselmans, Bart M L and Edith Hofer and Yang, Jingyun and Okbay, Aysu and Penelope A Lind and Michael B Miller and Ilja M Nolte and Wei Zhao and Hagenaars, Saskia P and Jouke-Jan Hottenga and Lindsay K Matteson and Snieder, Harold and Jessica Faul and Catharina A Hartman and Patricia A. Boyle and Henning Tiemeier and Mosing, Miriam A and Pattie, Alison and Gail Davies and David C Liewald and Schmidt, Reinhold and Philip L de Jager and Andrew C Heath and Markus Jokela and John M Starr and Oldehinkel, Albertine J and Johannesson, Magnus and Cesarini, David and Hofman, Albert and Sarah E Harris and Jennifer A Smith and Keltikangas-J{\"a}rvinen, Liisa and Pulkki-Raback, Laura and Schmidt, Helena and Jacqui Smith and Iacono, William G and McGue, Matt and David A Bennett and Nancy L Pedersen and Patrik K E Magnusson and Ian J Deary and Nicholas G Martin and Dorret I Boomsma and Bartels, Meike and Luciano, Michelle}
}
