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The authors use artificial intelligence approaches to explore the predictive value of whole exome sequencing in forecasting clinical outcomes following surgery for congenital heart defects. Findings include that damaging genotypes in chromatin-modifying and cilia-related genes are associated with an increased risk of adverse post-operative outcomes such as mortality, cardiac arrest, and prolonged mechanical ventilation.

Basal cells, rather than neuroendocrine cells, have been identified as the probable origin of small cell lung cancer and other neuroendocrine–tuft cancers, explaining neuroendocrine–tuft heterogeneity and offering new perspectives for targeting lineage plasticity.

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.

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.

Two approaches using an adenine base editor and a Cas9 nuclease prevented the development of hypertrophic cardiomyopathy in mice carrying a pathogenic mutation on the Myh6 gene, highlighting the potential of single-dose genetic therapies for the treatment of cardiac disease.

Maatz, Lindberg et al. identify molecular alterations and immune response changes in endomyocardial biopsies from patients with myocarditis after COVID-19 infection, after anti-COVID-19 vaccination or from non-COVID-related causes.

The goals, resources and design of the NHLBI Trans-Omics for Precision Medicine (TOPMed) programme are described, and analyses of rare variants detected in the first 53,831 samples provide insights into mutational processes and recent human evolutionary history.

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.

Single-cell and single-nucleus RNA sequencing are used to construct a cellular atlas of the human heart that will aid further research into cardiac physiology and disease.

Most studies of the genetics of the metabolome have been done in individuals of European descent. Here, the authors integrate genomics and metabolomics in Black individuals, highlighting the value of whole genome sequencing in diverse populations and linking circulating metabolites to human disease.

Identifying complex patterns through deep learning often comes at the cost of interpretability. Focusing on the interpretation of classification of in vitro fertilization embryos, the authors present DISCOVER, an approach that enables visual interpretability of image-based classification models.

Analysis of whole-genome sequences of 25,465 individuals of European ancestry shows that rare variants contribute substantially to the heritability of height and body mass index.

A study shows that clonal haematopoiesis of indeterminate potential is associated with an increased risk of chronic liver disease specifically through the promotion of liver inflammation and injury.

Although the common genetic variants contributing to blood lipid levels have been studied, the contribution of rare variants is less understood. Here, the authors perform a rare coding and noncoding variant association study of blood lipid levels using whole genome sequencing data.

Using engineered cardiac tissues, Fleischer, Nash et al. found that patients with lupus-mediated cardiac damage have unique autoantibodies that can independently alter tissue function. They also identified autoantibodies associated with heart injury.

Analysis of 97,691 high-coverage human blood DNA-derived whole-genome sequences enabled simultaneous identification of germline and somatic mutations that predispose individuals to clonal expansion of haematopoietic stem cells, indicating that both inherited and acquired mutations are linked to age-related cancers and coronary heart disease.

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

Computational analyses integrating whole-genome sequencing, cardiac epigenomic data and RNA-binding-protein data identify a role for noncoding de novo mutations in congenital heart disease.

Advanced paternal age associates with increased risk for psychiatric and developmental disorders in offspring. Here, Taylor et al. utilize parent-child trio exome sequencing data sets to estimate the contribution of paternal age-related de novo mutations to multiple disorders, including heart disease and schizophrenia.

A genome-wide association study including over 76,000 individuals with schizophrenia and over 243,000 control individuals identifies common variant associations at 287 genomic loci, and further fine-mapping analyses highlight the importance of genes involved in synaptic processes.

Pooling participant-level genetic data into a single analysis can result in variance stratification, reducing statistical performance. Here, the authors develop variant-specific inflation factors to assess variance stratification and apply this to pooled individual-level data from whole genome sequencing.

Platelet aggregation is associated with myocardial infarction and stroke. Here, the authors have conducted a whole genome sequencing association study on platelet aggregation, discovering a locus in RGS18, where enhancer assays suggest an effect on activity of haematopoeitic lineage transcription factors.

Concatenated PCR products serve as subgenomic traps in this targeted genome capture technique; subsequent high-throughput sequencing allows the detection of nucleotide and structural variations in the captured genomic regions.

The influence of X chromosome genetic variation on blood lipids and coronary heart disease (CHD) is not well understood. Here, the authors analyse X chromosome sequencing data across 65,322 multi-ancestry individuals, identifying associations of the Xq23 locus with lipid changes and reduced risk of CHD and diabetes mellitus.

Stuart Cook and colleagues study the role of TTN (titin)-truncating variants using a combination of heart physiology experiments in rats and genomic analysis in humans. Their data show that TTN variants are associated with a range of cardiac phenotypes in healthy individuals and in patients with dilated cardiomyopathy.

Sexual dimorphism in genetic vulnerability to schizophrenia, systemic lupus erythematosus and Sjögren’s syndrome is linked to differential protein abundance from alleles of complement component 4.

A meta-analysis of genome-wide association studies across different populations highlights new risk loci and provides a genetic risk score that can stratify prostate cancer risk across ancestries.

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.

Prostate cancer (PrCa) involves a large heritable genetic component. Here, the authors perform multivariate fine-mapping of known PrCa GWAS loci, identifying variants enriched for biological function, explaining more familial relative risk, and with potential application in clinical risk profiling.

STAAR is a powerful rare variant association test that incorporates variant functional categories and complementary functional annotations using a dynamic weighting scheme based on annotation principal components. STAAR accounts for population structure and relatedness and is scalable for analyzing large whole-genome sequencing studies.

MetaSTAAR enables functionally informed rare variant association analysis in biobank-scale cohorts using an efficient, sparse matrix approach for summary statistic storage.

The CNV analysis group of the Psychiatric Genomic Consortium analyzes a large schizophrenia cohort to examine genomic copy number variants (CNVs) and disease risk. They find an enrichment of CNV burden in cases versus controls and identify 8 genome-wide significant loci as well as novel suggestive loci conferring either risk or protection to schizophrenia.

In this Review, Seidman and colleagues summarize the progress over the past 10 years with regard to genomic discoveries and strategies at the forefront of research on congenital heart disease (CHD), highlighting definitive and candidate genes associated with CHD in humans and the potential of integrating technological advances to gain new insights into the genetic architecture of CHD.

Stratified medicine promises to tailor treatment for individual patients, however it remains a major challenge to leverage genetic risk data to aid patient stratification. Here the authors introduce an approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue-specific gene expression levels, and highlight its ability to identify biologically meaningful and clinically actionable patient subgroups, supporting the notion of different patient ‘biotypes’ characterized by partially distinct disease mechanisms.

Large whole-exome sequencing studies have suggested that the genetic architecture of syndromic congenital heart disease (CHD) is different from sporadic forms. Here, Watkins et al. estimate the relative contribution of damaging recessive and de novo genotypes to CHD in 2391 trios and find them to be associated with different gene functions.