Genetic diversity fuels gene discovery for tobacco and alcohol use

Nature · 2022 · 504 citations

• Biology
• Genetics
• Evolutionary biology

. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

Nature Genetics · 2022 · 673 citations

• Biology
• Genetics
• Evolutionary biology

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57.

Health in <scp>citizen‐state</scp> interactions: How physical and mental health problems shape experiences of administrative burden and reduce <scp>take‐up</scp>

Public Administration Review · 2022 · 80 citations

• Political Science
• Business
• Public relations

Abstract Public services represent a key means by which societies seek to reduce inequalities. However, some people may experience administrative procedures as more burdensome than others, creating inequality within programs intended to be equity‐enhancing. Prior work has found human capital (e.g., education and conditions like scarcity) to affect burden and take‐up. We build on this by examining the role of health in the form of attention disorders, pain, anxiety, and depression in the context of tax reporting in Denmark and college financial aid in Oklahoma, USA. Across cases, attention disorders and pain are associated with more burdensome experiences and in the financial aid case, they are associated with reduced take‐up as well. Individuals suffering from multiple health problems have the most negative experiences and lowest take‐up. The results suggest that extra support may be needed for people suffering from health problems in order to reduce inequities in experiences and outcomes.

Genome-wide meta-analysis of muscle weakness identifies 15 susceptibility loci in older men and women

Nature Communications · 2021 · 221 citations

• Biology
• Genetics
• Medicine

), cell cycle control and cancer protection, regulation of transcription, and others involved in the development and maintenance of the musculoskeletal system. Using Mendelian randomization we report possible overlapping causal pathways, including diabetes susceptibility, haematological parameters, and the immune system. We conclude that muscle weakness in older adults has distinct mechanisms from continuous strength, including several pathways considered to be hallmarks of ageing.

Reporting guidelines for human microbiome research: the STORMS checklist

Nature Medicine · 2021 · 452 citations

• Computer Science
• Medicine
• Data science

The particularly interdisciplinary nature of human microbiome research makes the organization and reporting of results spanning epidemiology, biology, bioinformatics, translational medicine and statistics a challenge. Commonly used reporting guidelines for observational or genetic epidemiology studies lack key features specific to microbiome studies. Therefore, a multidisciplinary group of microbiome epidemiology researchers adapted guidelines for observational and genetic studies to culture-independent human microbiome studies, and also developed new reporting elements for laboratory, bioinformatics and statistical analyses tailored to microbiome studies. The resulting tool, called 'Strengthening The Organization and Reporting of Microbiome Studies' (STORMS), is composed of a 17-item checklist organized into six sections that correspond to the typical sections of a scientific publication, presented as an editable table for inclusion in supplementary materials. The STORMS checklist provides guidance for concise and complete reporting of microbiome studies that will facilitate manuscript preparation, peer review, and reader comprehension of publications and comparative analysis of published results.

Resource profile and user guide of the Polygenic Index Repository

Nature Human Behaviour · 2021 · 178 citations

• Computer Science
• Information Retrieval
• Computer Science

Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is growing rapidly. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs' prediction accuracies, we constructed them using genome-wide association studies-some not previously published-from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the 'additive SNP factor'. Regressions in which the true regressor is this factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available.