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Many published studies of the current SARS-CoV-2 pandemic have analysed data from non-representative samples from populations. Here, using UK BioBank samples, Gibran Hemani and colleagues discuss the potential for such studies to suffer from collider bias, and provide suggestions for optimising study design to account for this.

This study uncovered genetic associations with environmental sensitivity in psychiatric and neurodevelopmental traits in an international collaboration using data from more than 21,000 monozygotic twins—the largest genetic study of monozygotic twin differences to date.

Family-based study designs have been applied to resolve confounding by population stratification, dynastic effects and assortative mating in genetic association analyses. Here, Brumpton et al. describe theory and simulations for overcoming such biases in Mendelian randomization through within-family studies.

Within-sibship genome-wide association analyses using data from 178,076 siblings illustrate differences between population-based and within-sibship GWAS estimates for phenotypes influenced by demographic and indirect genetic effects.

Many genetic loci have been identified to be associated with kidney disease, but the molecular mechanisms are not well understood. Here, the authors perform epigenome-wide association studies on kidney function measures to identify epigenetic marks and pathways involved in kidney function.

Serum urate concentration can be studied in large datasets to find genetic and epigenetic loci that may be related to cardiometabolic traits. Here the authors identify and replicate 100 urate-associated CpGs, which provide insights into urate GWAS loci and shared CpGs of urate and cardiometabolic traits.

DNA methylation quantitative trait locus (mQTL) analyses on 32,851 participants identify genetic variants associated with DNA methylation at 420,509 sites in blood, resulting in a database of >270,000 independent mQTLs.

From observational studies, alcohol consumption behaviours are known to be correlated in spouses. Here, Howe et al. use partners’ genotypic information in a Mendelian randomization framework and show that a SNP in the ADH1B gene associates with partner’s alcohol consumption, suggesting that alcohol consumption affects mate choice.

Timothy Frayling, Joel Hirschhorn, Peter Visscher and colleagues report a meta-analysis of genome-wide association studies for adult height in 253,288 individuals. They identify 697 variants in 423 loci significantly associated with adult height and find that these variants cluster in pathways involved in growth and together explain one-fifth of the heritability for this trait.

Genome-wide association studies have been extensively used to uncover genetic variants that independently influence complex traits, including diseases. This Review describes advances in computational approaches to detect interactions (epistasis) between genetic variants underlying complex traits, including the different promises and pitfalls of the methods. Additionally, the authors summarize current empirical evidence on how pervasive epistasis is in complex traits and its wider biological implications.

In Mendelian randomization (MR) studies, one typically selects SNPs as instrumental variables that do not directly affect the outcome to avoid violation of MR assumptions. Here, Cho et al. present a framework, MR-TRYX, that leverages knowledge of such outliers of horizontal pleiotropy to identify putative causal relationships between exposure and outcome.

Mendelian Randomisation estimates causal effects between risk factors and complex outcomes using genetic variants as instrumental variables, however it can be affected by certain biases. To alleviate these biases the authors propose an approach based on clustering genetic instruments according to the types of trait they are associated with, and apply this method to revisit the surprisingly large apparent causal effect of body mass index on educational attainment.

An expanded GWAS of birth weight and subsequent analysis using structural equation modeling and Mendelian randomization decomposes maternal and fetal genetic contributions and causal links between birth weight, blood pressure and glycemic traits.

Genome-wide and epigenome-wide association studies both link genomic regions to human traits, but here the authors demonstrate that these study types are capturing different genes and biological aspects of complex traits.

Analyses of expression profiles from whole blood of 31,684 individuals identify cis-expression quantitative trait loci (eQTL) effects for 88% of genes and trans-eQTL effects for 37% of trait-associated variants.

Reopening of universities to students following COVID-19 restrictions risks increased transmission due to high numbers of social contacts and the potential for asymptomatic transmission. Here, the authors use a mathematical model with social contact data to estimate the impacts of reopening a typical non-campus based university in the UK.

Many genetic variants identified in genome-wide association studies are associated with gene expression. Here, Porcu et al. propose a transcriptome-wide summary statistics-based Mendelian randomization approach (TWMR) that, applied to 43 human traits, uncovers hundreds of previously unreported gene–trait associations.

Gene expression and how genetic variants can influence gene expression are tissue-specific processes with important implications for phenotypes. Here, Richardson et al. use eQTL data from GTEx and the eQTLGen project in a two-sample SMR + HEIDI framework for causal inference of gene expression associations with complex trait.

Population structure can bias the results of genetic and epidemiological analysis. Here, Haworth et al. report that fine-scale structure is detectable in apparently homogeneous samples such as ALSPAC when measured very precisely, and remains detectable in UK Biobank despite conventional approaches to account for it.

The mechanisms underlying how monozygotic (or identical) twins arise are yet to be determined. Here, the authors investigate this in an epigenome-wide association study, showing that monozygotic twinning has a characteristic DNA methylation signature in adult somatic tissues.

The authors conducted a genetic meta-analysis of depression and found 269 associated genes. These genes highlight several potential drug repositioning opportunities, and relationships with depression were found for neuroticism and smoking.

Linking epigenetic marks to clinical outcomes promises insight into the underlying processes. Here, the authors introduce a statistical approach to estimate associations between a phenotype and all epigenetic probes jointly, and to estimate the proportion of variation captured by epigenetic effects.

Estimated glomerular filtration rate (eGFR) is a measure of kidney function used to define chronic kidney disease. Here, Morris et al. perform trans-ethnic genome-wide meta-analyses for eGFR in 312,468 individuals and identify novel loci and downstream putative causal genes.

Epistasis has rarely been shown among natural polymorphisms in human traits; this research using advanced computation and gene expression data reveals many instances of epistasis between common single nucleotide polymorphisms in humans, with epistasis and the direction of its effect replicating in independent cohorts.

Covariance of gene expression pairs is due to a combination of shared genetic and environmental factors. Here the authors estimate the genetic correlation between highly heritable pairs and identify transcription factor control and chromatin interactions as possible mechanisms of correlation.

This Perspective discusses the strengths and limitations of future biobank sampling strategies based on oversampling close relatives as opposed to the current population-based approach.

Multi-ancestry genome-wide association analyses for birth weight in 153,781 individuals identified 60 genomic loci in which birth weight and fetal genotype were associated and found an inverse genetic correlation between birth weight and cardiometabolic risk.

An analysis of 16 health-related quantitative traits in approximately 350,000 individuals reveals statistically significant associations between genome-wide homozygosity and four complex traits (height, lung function, cognitive ability and educational attainment); in each case increased homozygosity associates with a decreased trait value, but no evidence was seen of an influence on blood pressure, cholesterol, or ten other cardio-metabolic traits.

A genetic study identifies hundreds of loci associated with risk tolerance and risky behaviors, finds evidence of substantial shared genetic influences across these phenotypes, and implicates genes involved in neurotransmission.

Mendelian randomization (MR) and colocalization analyses are used to estimate causal effects of 1,002 plasma proteins on 225 phenotypes. Evidence from drug developmental programs shows that target-indication pairs with MR and colocalization support were more likely to be approved, highlighting the value of this approach for prioritizing therapeutic targets.

Here, the authors present a TWAS framework OTTERS that adapts multiple polygenic risk score methods to estimate eQTL weights from summary-level eQTL data. Both simulation and real studies show OTTERS is powerful across a wide range of genetic architectures.

Genome-wide meta-analysis identifies >100 loci associated with hair color variation in humans of European ancestry. These loci explain a large portion of the heritability of this trait & provide insights into pathways regulating hair pigmentation.

Matthew Robinson and colleagues report an analysis of population genetic differences in human height and body mass index (BMI) across 14 European populations. They estimate the proportion of additive genetic variance attributable to population genetic differences and find evidence for selection increasing height while reducing BMI in European nations.

This genome-wide study of age at first sexual intercourse and first birth identifies 371 signals driven by reproductive biology, externalising behaviour and environmental effects, with later onset associated with lower incidence of some diseases.

Jian Yang and colleagues present a method, GREML-LDMS, to estimate heritability for complex human traits using whole-genome sequencing data or imputation with the 1000 Genomes Project reference panel. Using the heritability estimates from GREML-LDMS, they find that there is negligible missing heritability for human height and BMI.

To comprehend the genetic regulatory mechanisms underlying brain-related traits in humans, Qi et al. estimate the correlation of expression and DNA methylation QTL effects in cis between blood and brain and show that using blood eQTL/mQTL data of large sample size  can increase power in gene discovery for brain-related traits and diseases.

GWAS have so far identified 129 loci associated with type 2 diabetes (T2D). Here, the authors meta-analyse three large T2D GWA studies which uncovers 42 additional loci, further prioritize 33 functional genes using eQTL and mQTL data and propose regulatory mechanisms for three putative T2D genes.