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The recent developments in artificial intelligence (AI) have created both intrigue and apprehension in the world of research. In this Viewpoint, we asked 12 experts in the field of metabolism to share their — differing — opinions on the use of AI in pre-clinical and clinical metabolic research.

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.

Here the authors develop a novel statistical method for quantifying mutation burden from whole genome sequencing data and use it to discover the genetic, genomic, and phenotypic correlates of clonal hematopoiesis without known driver genetic lesions.

Ruth Loos and colleagues report results of a large genome-wide association study for body mass index. They identify 18 new loci associated with this trait, some of which map near key hypothalamic regulators of energy balance.

Genotype-phenotype data from over 450,000 individuals was analyzed to discover 205 genomic loci where an allele associated with increase adiposity was associated with a lower cardiometabolic disease risk to an individual.

Polygenic risk scores can help identify individuals at higher risk of type 2 diabetes. Here, the authors characterise a multi-ancestry score across nearly 900,000 people, showing that its predictive value depends on demographic and clinical context and extends to related traits and complications.

Ruth Loos and colleagues report a meta-analysis of genome-wide association studies in 181,171 individuals identifying 14 new loci associated with heart rate and test these for association with cardiac conduction, rhythm disorders and cardiovascular disease. Their experimental studies in Drosophila melanogaster and zebrafish models provide support for a role for 20 candidate genes at 11 of these loci in regulation of heart rate.

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.

Here, the authors leverage whole-genome sequencing from >88,000 diverse individuals to uncover 18 BMI-related genetic signals, including novel variants in participants of African genetic ancestry, highlighting the value of diversity in genetic discovery.

MultiSTAAR provides a general and flexible statistical framework for functionally informed multi-trait rare variant analysis of biobank-scale sequencing studies by jointly analyzing multiple traits and incorporating annotation information.

A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants.

A genome-wide association meta-analysis study of blood lipid levels in roughly 1.6 million individuals demonstrates the gain of power attained when diverse ancestries are included to improve fine-mapping and polygenic score generation, with gains in locus discovery related to sample size.

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.

Ruth Loos and colleagues use genome-wide association to identify common variants influencing body fat percentage. Unexpectedly, they show that a body-fat–decreasing allele near IRS1 is associated with an impaired metabolic profile, including increased risk of type 2 diabetes and coronary artery disease.

Using data from a single time point, passenger-approximated clonal expansion rate (PACER) estimates the fitness of common driver mutations that lead to clonal haematopoiesis and identifies TCL1A activation as a mediator of clonal expansion.

A genome-wide association study and Metabochip meta-analysis of body mass index (BMI) detects 97 BMI-associated loci, of which 56 were novel, and many loci have effects on other metabolic phenotypes; pathway analyses implicate the central nervous system in obesity susceptibility and new pathways such as those related to synaptic function, energy metabolism, lipid biology and adipogenesis.

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.

Reduced glomerular filtration rate (eGFR) is a hallmark of chronic kidney disease. Here, Pattaro et al. conduct a meta-analysis to discover several new loci associated with variation in eGFR and find that genes associated with eGFR loci often encode proteins potentially related to kidney development.

In this Viewpoint, experts in the fields of medical therapy, adipocyte biology, exercise and muscle, bariatric surgery, genetics, and public health give their perspectives on current and future progress in addressing the rising prevalence of obesity.

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.

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.

Inbreeding depression has been observed in many different species, but in humans a systematic analysis has been difficult so far. Here, analysing more than 1.3 million individuals, the authors show that a genomic inbreeding coefficient (FROH) is associated with disadvantageous outcomes in 32 out of 100 traits tested.

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.

Analyses of genome and exome sequencing data identify rare coding and structural variants associated with atrial fibrillation and highlight genetic links between atrial fibrillation and cardiomyopathies.

Past genome-wide associate studies have identified hundreds of genetic loci that influence body size and shape when examined one trait at a time. Here, Jeff and colleagues develop an aggregate score of various body traits, and use meta-analysis to find new loci linked to body shape.

GWAS have identified more than 500 genetic loci associated with blood lipid levels. Here, the authors report a genome-wide analysis of interactions between genetic markers and physical activity, and find that physical activity modifies the effects of four genetic loci on HDL or LDL cholesterol.

Not all individuals with obesity develop cardiometabolic complications. Huang et al. use genome-wide meta-analysis to identify genetic loci associated with lower cardiometabolic risk despite increased adiposity.

Genome-wide association meta-analyses of waist-to-hip ratio adjusted for body mass index in more than 224,000 individuals identify 49 loci, 33 of which are new and many showing significant sexual dimorphism with a stronger effect in women; pathway analyses implicate adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution.

Christopher Newton-Cheh and colleagues report a genome-wide association study for blood pressure traits as part of the Global BPgen consortium. They report eight loci with replicated association to systolic and/or diastolic blood pressure, with each also showing association to hypertension.

Erik Ingelsson and colleagues report a large-scale genome-wide meta-analysis for associations to the extremes of anthropometric traits, including body mass index, height, waist-to-hip ratio and clinical obesity. They identify four loci newly associated with height and seven loci newly associated with clinical obesity and find overlap in the genetic structure and distribution of variants identified for these extremes of the trait distributions and for the general population.

The authors found, after analyzing 10,960 individuals from 9 multiancestry biobanks across 6 countries, that genetic factors previously associated with BMI have limited impact on GLP-1 receptor agonist-induced weight loss.

John Chambers and colleagues identify common variants at four loci associated with serum creatinine levels, a marker of kidney function. Their findings provide insight into the pathways underlying susceptibility to chronic kidney disease.

Genome-wide association studies (GWAS) have become a key tool to discover genetic markers for complex traits; however, environmental factors that interact with genes are rarely considered. Here, the authors conduct a GWAS of obesity traits, and find that smoking may alter genetic susceptibilities.

Cecilia Lindgren and colleagues report results of a large-scale genome-wide association study for waist-to-hip ratio, a measure of body fat distribution. They identify 13 new loci associated with this trait, several of which show stronger effects in women than in men.

A new study from the eMERGE consortium provides insights on the development of a pipeline for the generation and reporting of polygenic risk scores for ten diseases to diverse populations in a clinical setting.

The QT interval is a heritable electrocardiographic measure associated with arrhythmia risk when prolonged. Here, the authors used a series of genetic analyses to identify genetic loci, pathways, therapeutic targets, and relationships with cardiovascular disease.

Elevated body mass index is heritable and associated with many health conditions that impact morbidity and mortality. Here, the authors identify greater than 900 genetic loci for body mass index (BMI) and find over 300 diagnoses associated with increasing BMI.

The MAGIC investigators report results of a large genome-wide association study meta-analysis to identify common variants influencing fasting glucose homeostasis. They further show that several of the newly discovered loci influencing glycemic traits are also associated with risk of type 2 diabetes.

The genetics and clinical consequences of resting heart rate (RHR) remain incompletely understood. Here, the authors discover new genetic variants associated with RHR and find that higher genetically predicted RHR decreases risk of atrial fibrillation and ischemic stroke.

This meta-analysis of genome-wide association studies identifies four genetic loci associated with circulating leptin levels independent of adiposity. Examination in mouse adipose tissue explants provides functional support for the leptin-associated loci.

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.

Meta-analyses in up to 1.3 million individuals identify 87 rare-variant associations with blood pressure traits. On average, rare variants exhibit effects ~8 times larger than the mean effects of common variants and implicate candidate causal genes at associated regions.

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.

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.

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.

A multi-ancestry genome-wide gene–smoking interaction study identifies 13 new loci associated with serum lipids.

Genome-wide association analysis in over one million individuals of European ancestry identifies 2,103 independent genetic signals (including 113 new loci) associated with blood pressure traits.

Lipid concentration in the serum is one of the most important risk factors for coronary artery disease and can be targeted for therapeutic intervention. A genome-wide association study in >100,000 individuals of European ancestry now finds 95 significantly associated loci that also affect lipid traits in non-European populations. Among associated loci are those involved in cholesterol metabolism, known targets of cholesterol-lowering drugs and those that contribute to normal variation in lipid traits and to extreme lipid phenotypes.