In most complex diseases, much of the heritability remains unaccounted for by common variants. It has been postulated that lower-frequency variants contribute to the remaining heritability. Here, we describe a method to test for polygenic inheritance from lower-frequency variants by using GWAS summary association statistics. We explored scenarios with many causal low-frequency variants and showed that there is more power to detect risk variants than to detect protective variants, resulting in an increase in the ratio of detected risk to protective variants (R/P ratio). Such an excess can also occur if risk variants are present and kept at lower frequencies because of negative selection. The R/P ratio can be falsely elevated because of reasons unrelated to polygenic inheritance, such as uneven sample sizes or asymmetric population stratification, so precautions to correct for these confounders are essential. We tested our method on published GWAS results and observed a strong signal in some diseases (schizophrenia and type 2 diabetes) but not others. We also explored the shared genetic component in overlapping phenotypes related to inflammatory bowel disease (Crohn disease [CD] and ulcerative colitis [UC]) and diabetic nephropathy (macroalbuminuria and end-stage renal disease [ESRD]). Although the signal was still present when both CD and UC were jointly analyzed, the signal was lost when macroalbuminuria and ESRD were jointly analyzed, suggesting that these phenotypes should best be studied separately. Thus, our method may also help guide the design of future genetic studies of various traits and diseases.
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http://dx.doi.org/10.1016/j.ajhg.2014.02.006 | DOI Listing |
Elife
January 2025
Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States.
Apart from ancestry, personal or environmental covariates may contribute to differences in polygenic score (PGS) performance. We analyzed the effects of covariate stratification and interaction on body mass index (BMI) PGS (PGS) across four cohorts of European (N = 491,111) and African (N = 21,612) ancestry. Stratifying on binary covariates and quintiles for continuous covariates, 18/62 covariates had significant and replicable R differences among strata.
View Article and Find Full Text PDFTransl Psychiatry
January 2025
Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
Brain anatomy plays a key role in complex behaviors and mental disorders that are sexually divergent. While our understanding of the sex differences in the brain anatomy remains relatively limited, particularly of the underlying genetic and molecular mechanisms that contribute to these differences. We performed the largest study of sex differences in brain volumes (N = 33,208) by examining sex differences both in the raw brain volumes and after controlling the whole brain volumes.
View Article and Find Full Text PDFDiabetes Care
February 2025
Division of Blood Disorders and Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, GA.
Objective: The goal of this study was to assess the additive value of considering type 2 diabetes (T2D) polygenic risk score (PRS) in addition to family history for T2D prediction.
Research Design And Methods: Data were obtained from the All of Us (AoU) research database. First-degree T2D family history was self-reported on the personal family history health questionnaire.
Neurology
February 2025
Department of Pharmacology and Toxicology, University of Arizona, Tucson.
Background And Objectives: Alzheimer disease (AD) is a heterogeneous neurodegenerative disorder influenced by genetic and environmental factors. Conditions such as type 2 diabetes (T2D), cardiovascular disease, obesity, depression, and obstructive sleep apnea (OSA) increase AD risk and progression. This study aimed to examine the genetic predisposition to these conditions and their effect on AD pathophysiology, risk, and progression.
View Article and Find Full Text PDFGac Med Mex
January 2025
Universidad de Buenos Aires, Facultad de Farmacia y Bioquímica, Departamento de Bioquímica Clínica, Laboratorio de Lípidos y Aterosclerosis, Ciudad Autónoma de Buenos Aires.
Introduction: LDL-cholesterol greater than 190 mg/dL indicates severe hypercholesterolemia (HS) of monogenic and/or polygenic origin. Genetic risk scores (GRS) evaluate potential polygenic causes.
Objective: we applied a GRS of 6-SNP (GRS-6) in HS individuals.
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