Computationally efficient whole-genome regression for quantitative and binary traits.

Genome-wide association analysis of cohorts with thousands of phenotypes is computationally expensive, particularly when accounting for sample relatedness or population structure. Here we present a novel machine-learning method called REGENIE for fitting a whole-genome regression model for quantitative and binary phenotypes that is substantially faster than alternatives in multi-trait analyses while maintaining statistical efficiency. The method naturally accommodates parallel analysis of multiple phenotypes and requires only local segments of the genotype matrix to be loaded in memory, in contrast to existing alternatives, which must load genome-wide matrices into memory.

Clustering of 770,000 genomes reveals post-colonial population structure of North America.

Despite strides in characterizing human history from genetic polymorphism data, progress in identifying genetic signatures of recent demography has been limited. Here we identify very recent fine-scale population structure in North America from a network of over 500 million genetic (identity-by-descent, IBD) connections among 770,000 genotyped individuals of US origin. We detect densely connected clusters within the network and annotate these clusters using a database of over 20 million genealogical records.

Discrepancies in the female pelvic medicine and reconstructive surgeon workforce.

Introduction: It is unclear whether the current distribution of surgeons practicing female pelvic medicine and reconstructive surgery in the United States is adequate to meet the needs of a growing and aging population. We assessed the geographic distribution of female pelvic surgeons as represented by members of the American Urogynecologic Society (AUGS) throughout the United States at the county, state, and American Congress of Obstetricians and Gynecologists district levels.

Materials And Methods: County-level data from the AUGS, American Congress of Obstetricians and Gynecologists, and the United States Census were analyzed in this observational study.

Genetic variants associated with idiopathic pulmonary fibrosis susceptibility and mortality: a genome-wide association study.

Background: Idiopathic pulmonary fibrosis (IPF) is a devastating disease that probably involves several genetic loci. Several rare genetic variants and one common single nucleotide polymorphism (SNP) of MUC5B have been associated with the disease. Our aim was to identify additional common variants associated with susceptibility and ultimately mortality in IPF.

Genome-wide association of lipid-lowering response to statins in combined study populations.

Background: Statins effectively lower total and plasma LDL-cholesterol, but the magnitude of decrease varies among individuals. To identify single nucleotide polymorphisms (SNPs) contributing to this variation, we performed a combined analysis of genome-wide association (GWA) results from three trials of statin efficacy.

Methods And Principal Findings: Bayesian and standard frequentist association analyses were performed on untreated and statin-mediated changes in LDL-cholesterol, total cholesterol, HDL-cholesterol, and triglyceride on a total of 3932 subjects using data from three studies: Cholesterol and Pharmacogenetics (40 mg/day simvastatin, 6 weeks), Pravastatin/Inflammation CRP Evaluation (40 mg/day pravastatin, 24 weeks), and Treating to New Targets (10 mg/day atorvastatin, 8 weeks).

Polymorphisms of the HNF1A gene encoding hepatocyte nuclear factor-1 alpha are associated with C-reactive protein.

Data from the Pharmacogenomics and Risk of Cardiovascular Disease (PARC) study and the Cardiovascular Health Study (CHS) provide independent and confirmatory evidence for association between common polymorphisms of the HNF1A gene encoding hepatocyte nuclear factor-1 alpha and plasma C-reactive protein (CRP) concentration. Analyses with the use of imputation-based methods to combine genotype data from both studies and to test untyped SNPs from the HapMap database identified several SNPs within a 5 kb region of HNF1A intron 1 with the strongest evidence of association with CRP phenotype.

Functional characterization of calcium sensing receptor polymorphisms and absence of association with indices of calcium homeostasis and bone mineral density.

Objectives: Associations between calcium-sensing receptor (CaSR) polymorphisms and serum calcium, PTH and bone mineral density (BMD) have been reported by six studies. However, three other studies have failed to detect such associations. We therefore further investigated three CaSR coding region polymorphisms (Ala986Ser, Arg990Gly and Gln1011Glu) for associations with indices of calcium homeostasis and BMD and for alterations in receptor function.

Linkage analysis of GAW14 simulated data: comparison of multimarker, multipoint, and conditional approaches.

The purposes of this study were 1) to examine the performance of a new multimarker regression approach for model-free linkage analysis in comparison to a conventional multipoint approach, and 2) to determine the whether a conditioning strategy would improve the performance of the conventional multipoint method when applied to data from two interacting loci. Linkage analysis of the Kofendrerd Personality Disorder phenotype to chromosomes 1 and 3 was performed in three populations for all 100 replicates of the Genetic Analysis Workshop 14 simulated data. Three approaches were used: a conventional multipoint analysis using the Zlr statistic as calculated in the program ALLEGRO; a conditioning approach in which the per-family contribution on one chromosome was weighted according to evidence for linkage on the other chromosome; and a novel multimarker regression approach.

A multimarker regression-based test of linkage for affected sib-pairs at two linked loci.

We address the analytical problem of evaluating the evidence for linkage at a test locus while taking into account the effect of a known linked disease locus. The method we propose is a multimarker regression approach that models the identity-by-descent states for affected sib-pairs at a series of linked markers in terms of the identity-by-descent state at the known disease locus. Our method allows analysis to be performed at a test location (or a series of locations) without the requirement that identity-by-descent be directly observed at either the test or the known conditioning locus.

Gamma regression improves Haseman-Elston and variance components linkage analysis for sib-pairs.

Existing standard methods of linkage analysis for quantitative phenotypes rest on the assumptions of either ordinary least squares (Haseman and Elston [1972] Behav. Genet. 2:3-19; Sham and Purcell [2001] Am.