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An analysis of 24,202 critical cases of COVID-19 identifies potentially druggable targets in inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).

Florez Ariza and Lue et al. use cryo-electron microscopy to investigate how the RECQL5 helicase regulates transcription. Their structural findings suggest that RECQL5 can modulate RNA polymerase II’s translocation state, potentially restarting stalled transcription.

Antscan is a publicly accessible database of synchrotron X-ray CT images of ants. The database covers almost 800 species from more than 200 genera and is coordinated with genome sequencing projects that will enable integrative analyses.

Jose Florez, Claudia Langenberg, Erik Ingelsson, Inga Prokopenko, Inês Barroso and colleagues perform large-scale association analyses using the Metabochip to gain further insights into the genetic architecture of glucose regulation. They identify 38 new loci influencing 1 or more glycemic traits and show that many of these loci also modify risk of type 2 diabetes.

Researchers studied the blood-based metabolome of over 23,000 people from ten ethnically diverse cohorts. They identified 235 metabolites associated with future risk of type 2 diabetes (T2D). By integrating genetic and modifiable lifestyle factors, their findings provide insights into T2D mechanisms and could improve risk prediction and inform precision prevention.

Human LINE-1 ORF2p relies on upstream single-stranded target DNA to position the adjacent duplex in the endonuclease active site for nicking of the longer DNA strand, with a single nick generating a staggered DNA break.

The CMS Collaboration reports the measurement of the spin, parity, and charge conjugation properties of all-charm tetraquarks, exotic fleeting particles formed in proton–proton collisions at the Large Hadron Collider.

Here the authors provide an explanation for 95% of examined predicted loss of function variants found in disease-associated haploinsufficient genes in the Genome Aggregation Database (gnomAD), underscoring the power of the presented analysis to minimize false assignments of disease risk.

Polygenic scores for body mass index and obesity constructed using data from 5 million people with different ancestries were associated with distinct weight gain trajectories from early childhood to adulthood.

Although previous studies unequivocally demonstrated that type 2 diabetes mellitus (T2DM) has a strong genetic component, the genes that contribute to the risk of this disease were largely unknown until recently, owing to the complexity of genetic and environmental interactions that are involved in T2DM. Genome-wide association studies, which provide global searches throughout the entire genome, have greatly improved our understanding of the genetic background of diabetes mellitus. Here, the authors discuss the currently available findings of diabetes-related genome-wide association studies and examine the utility of the genetic loci identified in these studies as predictors of T2DM.

Genetic and functional studies implicate allele-specific regulation of OAS1 splicing and nonsense-mediated decay in COVID-19 severity. The OAS1 risk haplotype is also associated with reduced SARS-CoV-2 clearance in a clinical trial with pegIFN-λ1.

A meta-analysis of genome-wide association studies of type 2 diabetes (T2D) identifies more than 600 T2D-associated loci; integrating physiological trait and single-cell chromatin accessibility data at these loci sheds light on heterogeneity within the T2D phenotype.

In a multivariate genetic analysis including 282,271 adults, Merino et al. identified 26 genomic regions associated with carbohydrate, protein and fat intake. The identified loci implicate brain regions and neuronal subtypes in influencing eating behaviour.

Both rare and common variants contribute to the aetiology of complex traits such as type 2 diabetes (T2D). Here, the authors examine the effect of coding variation on glycaemic traits and T2D, and identify low-frequency variation in GLP1Rsignificantly associated with these traits.

Most genome-wide association studies assume an additive model, exclude the X chromosome, and use one reference panel. Here, the authors implement a strategy including non-additive models and find that the number of loci for age-related traits increases as compared to the additive model alone.

This study presents a method for constructing complex trait polygenic scores from rare variants and shows that a polygenic score combining common and rare variants improves the accuracy of diagnosis for type 2 diabetes based on hemoglobin A1C levels.

A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.

The authors present a multiomics study of type 2 diabetes and quantitative blood lipid and lipoprotein traits in Hispanic/Latino populations. They demonstrate how integrating GWAS with omics characterization can advance precision medicine.

Genome-wide association and fine-mapping analyses in ancestrally diverse populations implicate candidate causal genes and mechanisms underlying type 2 diabetes. Trans-ancestry genetic risk scores enhance transferability across populations.

Here, the authors implement a genetic approach grouping fasting insulin-associated genetic variants based on their genetic and phenotypic similarities and highlight specific processes that decouple increased fasting insulin levels from T2D and cardiovascular risk, offering potential avenues for investigating process-specific pathways of disease risk.

Genome-wide association analyses of two oral glucose tolerance test-derived measures of postprandial insulin resistance discover ten new loci. Functional characterization identifies nine candidate genes implicated in the regulation of GLUT4.

A risk haplotype for type 2 diabetes is identified with four amino acid substitutions in SLC16A11, which is present at ∼50% frequency in Native American samples and ∼10% in east Asian samples, but is rare in European and African samples; SLC16A11 may alter hepatic lipid metabolism, causing an increase in triacylglycerol levels.

Genome-wide association analyses of blood glucose measurements under nonstandardized conditions provide insights into the biology of glucose regulation, diabetes complications and pathways for treatment stratification.

Penetrance of variants in monogenic disease and clinical utility of common polygenic variation has not been well explored on a large-scale. Here, the authors use exome sequencing data from 77,184 individuals to generate penetrance estimates and assess the utility of polygenic variation in risk prediction of monogenic variants.

Exome-sequencing analyses of a large cohort of patients with type 2 diabetes and control individuals without diabetes from five ancestries are used to identify gene-level associations of rare variants that are associated with type 2 diabetes.

Rare variant analyses identify a new type 2 diabetes risk allele near the LEP gene, which encodes leptin, and other risk alleles of intermediate penetrance in genes previously implicated in monogenic forms of diabetes.

Using plasma samples collected over several time points during pregnancy from three different cohorts, associations between circulating placental IGFBP1 levels, metabolic traits and birth anthropometric measurements were measured, with low IGFBP1 levels identified as a potential risk factor for gestational diabetes mellitus.

A multi-ancestry analysis in large cohorts of patients with type 2 diabetes (T2D) identified 12 disease genetic clusters with distinct cardiometabolic trait associations, including two lipodystrophy-related clusters that could provide insights on the increased T2D susceptibility in East Asian ancestries at a given body mass index level.

A transancestral exome-wide association study for body-fat distribution identifies protein-coding variants that are significantly associated with waist-to-hip ratio adjusted for body mass index.

Combining 32 genome-wide association studies with high-density imputation provides a comprehensive view of the genetic contribution to type 2 diabetes in individuals of European ancestry with respect to locus discovery, causal-variant resolution, and mechanistic insight.

Approximately 40 percent of people with type 1 diabetes develop kidney disease, but the risk factors are not well understood. Here, the authors identify DNA methylation signatures associated with diabetic kidney disease, of which 21 biomarkers predict the development of kidney failure.

Understanding how our genes interact with the environment is critical to improving health. Using a large-scale discovery pipeline, here the authors investigate synergies between genetic variants and a broad range of environmental factors impacting cardiometabolic health.

This study of 23,000 non-diabetic individuals highlights loci associated with fasting glucose and fasting insulin in diverse cohorts with whole genome sequence data.

Trans-ethnic analyses of exome array data identify new risk loci for type 2 diabetes. Fine-mapping analyses using genome-wide association data show that the index coding variants represent the likely causal variants at only a subset of these loci.

Sex differences in fasting glucose and insulin have been identified, but the genetic loci underlying these differences have not. Here, the authors perform a meta-analysis of genome-wide association studies to detect sex-specific and sex-dimorphic loci associated with fasting glucose and insulin.

A catalogue of predicted loss-of-function variants in 125,748 whole-exome and 15,708 whole-genome sequencing datasets from the Genome Aggregation Database (gnomAD) reveals the spectrum of mutational constraints that affect these human protein-coding genes.

Andrew Morris, Mark McCarthy, Michael Boehnke and colleagues report a meta-analysis of genome-wide association studies for type 2 diabetes, including 26,488 cases and 83,964 controls from populations of European, east Asian, south Asian and Mexican and Mexican American ancestry. They identify seven loci newly associated with type 2 diabetes and examine the genetic architecture of disease across populations.

A genomic constraint map for the human genome constructed using data from 76,156 human genomes from the Genome Aggregation Database shows that non-coding constrained regions are enriched for regulatory elements and variants associated with complex diseases and traits.

Gonçalo Abecasis and colleagues report associations with fasting plasma glucose levels in a collection of ten genome–wide association scans from the MAGIC consortium. They find variants in the gene encoding melatonin receptor 1B that are associated with fasting glucose levels and, in a meta-analysis of 13 case-control studies, also show association with increased risk of type 2 diabetes.

Genetic and Structural analysis of COVID patients cohort reveals a correlation between mitochondrial haplogroup and SARS-CoV-2 severity.

Data from over 700,000 individuals reveal the identity of 83 sequence variants that affect human height, implicating new candidate genes and pathways as being involved in growth.

A strategy for inferring phase for rare variant pairs is applied to exome sequencing data for 125,748 individuals from the Genome Aggregation Database (gnomAD). This resource will aid interpretation of rare co-occurring variants in the context of recessive disease.

Several GWAS have identified many common variants associated with blood metabolites. Here, the authors use an exome array to identify low frequency, potentially functional variants that impact human metabolism.

Claudia Langenberg, James Meigs and colleagues apply a joint meta-analysis approach that accounts for differences in body mass index to identify variants associated with glycemic traits. They report six new loci associated with fasting insulin levels and provide insights into the genetic basis of insulin resistance.

Kyle Gaulton, Mark McCarthy, Andrew Morris and colleagues report fine mapping and genomic annotation of 39 established type 2 diabetes susceptibility loci. They find that the set of potential causal variants is enriched for overlap with FOXA2 binding sites in human islet and liver cells, and they show that a likely causal variant near MTNR1B increases FOXA2-bound enhancer activity, providing a molecular mechanism to explain the effect of this locus on disease risk.

The choice of food intake is at least partially influenced by genetics, even though the effect sizes appear rather modest. Here, Cole et al. perform GWAS for food intake (85 individual food items and 85 derived dietary patterns) and test potential causal relationships with cardiometabolic traits using Mendelian randomization.

Exome-wide analysis identifies rare and low-frequency coding variants associated with body mass index. Gene-based meta-analysis and functional studies implicate 13 genes, eight of which are novel, and neuronal pathways as factors in human obesity.

Prediabetic states that involve impairments of insulin secretion and action can be identified. Medical therapy and lifestyle modifications can be used in people with these disorders to delay or prevent the onset of type 2 diabetes. In this Review, the data on development and evaluation of diabetes-prevention strategies are discussed and some recommendations for practice are provided.