Search

Variant-to-gene-to-program is a new approach to building maps of genome function to link risk variants to disease genes and to convergent signalling pathways in an unbiased manner; its strength is demonstrated in coronary artery disease.

Genome-wide analyses for 7,266 traits leveraging data from several genetic ancestry groups in UK Biobank identify new associations and enhance resources for interpreting risk variants across diverse populations.

Hilary Finucane, Brendan Bulik-Sullivan, Benjamin Neale, Alkes Price and colleagues introduce a new method, called stratified LD score regression, for partitioning heritability by functional category using genome-wide association study summary statistics. They observe a substantial enrichment of heritability in conserved regions and illustrate how this approach can provide insights into the biological basis of disease and direction for functional follow-up.

Similarities in cancers can be studied to interrogate their etiology. Here, the authors use genome-wide association study summary statistics from six cancer types based on 296,215 cases and 301,319 controls of European ancestry, showing that solid tumours arising from different tissues share a degree of common germline genetic basis.

Brendan Bulik-Sullivan, Benjamin Neale, Hilary Finucane, Alkes Price and colleagues introduce a new technique for estimating genetic correlation that requires only genome-wide association summary statistics and that is not biased by sample overlap. Using this method, they find genetic correlations between anorexia nervosa and schizophrenia, and between educational attainment and autism spectrum disorder.

Finding causal variants and genes from GWAS loci results remains a challenge. Here, the authors train a model to predict if a variant affects nearby gene expression, and apply the method to identify new possible causal eQTLs and mechanisms of GWAS loci.

A genome-wide-association meta-analysis of 18,381 austim spectrum disorder (ASD) cases and 27,969 controls identifies five risk loci. The authors find quantitative and qualitative polygenic heterogeneity across ASD subtypes.

A downsampling approach to assess causal variant fine-mapping, replication failure rate, finds that commonly used methods may be miscalibrated. Simulations suggest this is probably due to a nonsparse genetic architecture model misspecification. Incorporating infinitesimal effects in the SuSiE and FINEMAP frameworks improves performance.

John Perry and colleagues report the results of a large genome-wide association study meta-analysis to identify variants influencing age at natural menopause. They identify 54 independent signals and find enrichment near genes involved in delayed puberty and DNA damage response.

Polygenic Priority Score (PoPS) prioritizes candidate effector genes at complex trait loci by integrating genome-wide association summary statistics with other data types. Combining PoPS with methods that leverage local genetic signals further improves the performance.

A global network of researchers was formed to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity; this paper reports 13 genome-wide significant loci and potentially actionable mechanisms in response to infection.

Fine-mapping of blood cell traits in the UK Biobank identifies putative causal variants and enrichment of fine-mapped variants in accessible chromatin of hematopoietic progenitor cells. The study provides an analytical framework for single-variant and single-cell analyses of genetic associations.

HCR–FlowFISH is a new approach to characterize CRISPR-perturbed cis-regulatory elements (CREs) via accurate quantification of native transcripts, alongside CRISPR activity screen analysis (CASA), a hierarchical Bayesian model to quantify CRE activity.

A genome-wide association meta-analysis of individuals with clinically assessed or self-reported depression identifies 44 independent risk loci. Comparisons with other psychiatric disorders and candidate gene analyses provide new insights into major depressive disorder.

Genome-wide association studies of individuals from an isolated population (data from the Finnish biobank study FinnGen) and consequent meta-analyses facilitate the identification of previously unknown coding variant associations for both rare and common diseases.

A concerning trend in genetics is the common use of the term ‘trans-ethnic’ to describe analyses that combine or compare several ancestrally diverse populations. In this commentary, we discuss how this term is inaccurate and alienating. We propose that geneticists avoid using the term trans-ethnic entirely and that researchers across disciplines reach a new consensus about the best terms to use to describe the populations we study.

Negative selection removes deleterious genetic variation, and can influence genetic architectures and evolution of complex traits. Here, the authors analyze data from 25 UK Biobank diseases and complex traits, and quantify frequency-dependent genetic architectures which suggests actions of negative selection.

Genome-wide association analyses, functionally informed fine-mapping and complementary gene prioritization approaches identify new risk loci and candidate effector genes for CAD.

Whole-genome sequencing, transcriptome-wide association and fine-mapping analyses in over 7,000 individuals with critical COVID-19 are used to identify 16 independent variants that are associated with severe illness in COVID-19.

Steven Gazal, Alkes Price and colleagues extend stratified LD score regression to continuous annotations. They analyze summary statistics from 56 complex diseases and traits and find that SNPs with low levels of linkage disequilibrium have larger per-SNP heritability, consistent with the action of negative selection on deleterious variants that affect complex traits.

Roger Milne and colleagues conduct a genome-wide association study for estrogen receptor (ER)-negative breast cancer combined with BRCA1 mutation carriers in a large cohort. They identify ten new risk variants and find high genetic correlation between breast cancer risk for BRCA1 mutation carriers and risk of ER-negative breast cancer in the general population.

PolyFun is a computationally scalable framework for functionally informed fine-mapping that makes full use of genome-wide data. It prioritizes more variants than previous methods when applied to 49 complex traits from UK Biobank.

STAARpipeline is a comprehensive framework for flexible and scalable rare-variant association analysis using whole-genome sequencing data and annotation information.

Tractor is a statistical framework that facilitates the inclusion of admixed individuals in association studies by leveraging local ancestry. Tractor generates accurate ancestry-specific effect-size estimates and improves the resolution of association signals.

Alzheimer’s disease genetic risk is enriched in glial genes. Here, the authors derive cell-type-specific polygenic risk scores and link astrocytic genes with Aβ, and microglial genes with Aβ, tau, microglial activation, and cognitive decline.

John Perry, Ken Ong and colleagues analyze genotype data on ∼370,000 women and identify 389 independent signals that associate with age at menarche, implicating ∼250 genes. Their analyses suggest causal inverse associations, independent of BMI, between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men.

Mapping enhancer regulation across human cell types and tissues illuminates genome function and provides a resource to connect risk variants for common diseases to their molecular and cellular functions.

PolyPred and PolyPred⁺ methods that leverage fine-mapping and non-European training data significantly improve cross-population polygenic prediction accuracy when applied to diseases and complex traits in UK Biobank populations.

Past studies on genetics of puberty relied on rare disorders or age of menarche in women. Here, Dayet al. examine puberty timing in men by the age of voice breaking, and find some loci with sexually dimorphic effects and genetic architectures shared with other health conditions.

While genome-wide association studies have yielded thousands of trait-associated loci, identifying causal variants remains challenging. Here, the authors perform seven genomics assays in various cell types to prioritize genetic variants in the TNFAIP3 locus, and report high-priority variants within disease-associated haplotypes.

A new method tests whether disease heritability is enriched near genes with high tissue-specific expression. The authors use gene expression data together with GWAS summary statistics for 48 diseases and traits to identify disease-relevant tissues.

A transcriptome-wide association study integrating genome-wide association data with expression data from brain, blood and adipose tissues identifies new candidate susceptibility genes for schizophrenia, providing a step toward understanding the underlying biology.

Signed linkage disequilibrium profile regression is a new method for detecting directional effects of genomic annotations on disease risk. The results implicate new causal disease genes and can suggest mechanisms underlying the effects of causal genes on disease.

Association analysis identifies 65 new breast cancer risk loci, predicts target genes for known risk loci and demonstrates a strong overlap with somatic driver genes in breast tumours.

Environmental influences during prenatal development may have implications for health and disease later in life. Here, Czamara et al. assess DNA methylation in cord blood from new-born under various models including environmental and genetic effects individually and their additive or interaction effects.

Analysis of genotyping data for more than 150,000 individuals from the UK Biobank using long-range phase information sheds light on mechanisms of clonal haematopoiesis.

Po-Ru Loh, Alkes Price and colleagues present Eagle2, a reference-based phasing algorithm that allows for highly accurate and efficient phasing of genotypes across a broad range of cohort sizes. They demonstrate an approximately 10% improvement in accuracy and 20% improvement in speed compared to a competing method, SHAPEIT2.

The authors extend stratified linkage disequilibrium score regression to partition the heritability of both low-frequency and common variants in 40 heritable traits from the UK Biobank, providing insights into low-frequency and rare variant functional architectures.

A new set of functional annotations based on fine-mapped molecular quantitative trait loci from GTEx and BLUEPRINT consortium data are enriched for disease heritability across 41 diseases and complex traits.

Depression is correlated with many brain-related traits. Here, Shen et al. perform phenome-wide association studies of a depression polygenic risk score (PRS) and find associations with 51 behavioural and 26 neuroimaging traits which are further followed up on using Mendelian randomization and mediation analyses.

Benjamin Neale and colleagues report the LD Score regression method, used to distinguish the relative contributions of confounding bias and polygenicity to inflated test statistics in GWAS. They apply their method to summary statistics from GWAS for over 30 phenotypes, confirm that polygenicity accounts for the majority of inflation in test statistics and demonstrate use of this method as a correction factor.

Alkes Price, Po-Ru Loh and colleagues report the BOLT-LMM method for mixed-model association. They apply their method to 9 quantitative traits in 23,294 samples and demonstrate that it provides improvements in computational efficiency as well as gains in power that increase with the size of the cohort, making it useful for the analysis of large cohorts.

Po-Ru Loh, Alkes Price and colleagues developed a fast algorithm for multicomponent, multi-trait variance-components analysis and use it to analyze the genetic architectures of schizophrenia and nine complex diseases from the PGC and GERA cohorts. Their analyses support a largely polygenic architecture for schizophrenia and significant genetic correlations for several pairs of GERA diseases.