Genetic Epidemiology

Wiley Online Library : Genetic Epidemiology

Latest articles

Chances and challenges of machine learning‐based disease classification in genetic association studies illustrated on age‐related macular degeneration

Abstract Imaging technology and machine learning algorithms for disease classification set the stage for high‐throughput phenotyping and promising new avenues for genome‐wide association studies (GWAS). Despite emerging algorithms, there has been no successful application in GWAS so far. We establish machine learning‐based phenotyping in genetic association...

Evaluating shared genetic influences on nonsyndromic cleft lip/palate and oropharyngeal neoplasms

Abstract It has been hypothesised that nonsyndromic cleft lip/palate (nsCL/P) and cancer may share aetiological risk factors. Population studies have found inconsistent evidence for increased incidence of cancer in nsCL/P cases, but several genes (e.g., CDH1 , AXIN2 ) have been implicated in the aetiologies of both phenotypes. We aimed to evaluate...

Penalized variance components for association of multiple genes with traits

Abstract Variance component models have gained popularity for genetic analyses, driven by their flexibility to simultaneously analyze multiple genetic variants in a gene by kernel statistics, and their ability to account for population stratification via genomic relationship matrices. For exploratory analyses with modest sample sizes and a potentially...

An enhanced machine learning tool for cis‐eQTL mapping with regularization and confounder adjustments

Abstract Many expression quantitative trait loci (eQTL) studies have been conducted to investigate the biological effects of variants in gene regulation. However, these eQTL studies may suffer from low or moderate statistical power and overly conservative false‐discovery rate. In practice, most algorithms for eQTL identification do not model the joint...

A general framework for integrative analysis of incomplete multiomics data

Abstract There is a tremendous current interest in measuring multiple types of omics features (e.g., DNA sequences, RNA expressions, methylation profiles, metabolic profiles, protein expressions) on a large number of subjects. Although genotypes are typically available for all study subjects, other data types may be measured only on a subset of subjects...

A principal component approach to improve association testing with polygenic risk scores

Abstract Polygenic risk scores (PRSs) have become an increasingly popular approach for demonstrating polygenic influences on complex traits and for establishing common polygenic signals between different traits. PRSs are typically constructed using pruning and thresholding (P+T), but the best choice of parameters is uncertain; thus multiple settings...

Statistical considerations for the analysis of massively parallel reporter assays data

Abstract Noncoding DNA contains gene regulatory elements that alter gene expression, and the function of these elements can be modified by genetic variation. Massively parallel reporter assays (MPRA) enable high‐throughput identification and characterization of functional genetic variants, but the statistical methods to identify allelic effects in...

SNP‐HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC‐centric analyses in genomics

Abstract Genome‐wide associations studies have repeatedly identified the major histocompatibility complex genomic region (6p21.3) as key in immune pathologies. Researchers have also aimed to extend the biological interpretation of associations by focusing directly on human leukocyte antigen (HLA ) polymorphisms and their combination as haplotypes....

Leveraging existing GWAS summary data of genetically correlated and uncorrelated traits to improve power for a new GWAS

Abstract In spite of the tremendous success of genome‐wide association studies (GWAS) in identifying genetic variants associated with complex traits and common diseases, many more are yet to be discovered. Hence, it is always desirable to improve the statistical power of GWAS. Paralleling with the intensive efforts of integrating GWAS with functional...

Colorectal cancer risk based on extended family history and body mass index

Abstract Family history and body mass index (BMI) are well‐known risk factors for colorectal cancer (CRC), however, their joint effects are not well described. Using linked data for genealogy, self‐reported height and weight from driver's licenses, and the Utah Surveillance, Epidemiology, and End‐Results cancer registry, we found that an increasing...

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