Phenome-wide identification of therapeutic genetic targets, leveraging knowledge graphs, graph neural networks, and UK Biobank data.

The ongoing expansion of human genomic datasets propels therapeutic target identification; however, extracting gene-disease associations from gene annotations remains challenging. Here, we introduce Mantis-ML 2.0, a framework integrating AstraZeneca's Biological Insights Knowledge Graph and numerous tabular datasets, to assess gene-disease probabilities throughout the phenome. We use graph neural networks, capturing the graph's holistic structure, and train them on hundreds of balanced datasets via a robust semi-supervised learning framework to provide gene-disease probabilities across the human exome. Mantis-ML 2.0 incorporates natural language processing to automate disease-relevant feature selection for thousands of diseases. The enhanced models demonstrate a 6.9% average classification power boost, achieving a median receiver operating characteristic (ROC) area under curve (AUC) score of 0.90 across 5220 diseases from Human Phenotype Ontology, OpenTargets, and Genomics England. Notably, Mantis-ML 2.0 prioritizes associations from an independent UK Biobank phenome-wide association study (PheWAS), providing a stronger form of triaging and mitigating against underpowered PheWAS associations. Results are exposed through an interactive web resource.

Characterising the contribution of rare protein-coding germline variants to prostate cancer risk and severity in 37,184 cases.

The etiology of prostate cancer, the second most common cancer in men globally, has a strong heritable component. While rare coding germline variants in several genes have been identified as risk factors from candidate gene and linkage studies, the exome-wide spectrum of causal rare variants remains to be fully explored. To more comprehensively address their contribution, we analysed data from 37,184 prostate cancer cases and 331,329 male controls from five cohorts with germline exome/genome sequencing and one cohort with imputed array data from a population enriched in low-frequency deleterious variants. Our gene-level collapsing analysis revealed that rare damaging variants in SAMHD1 as well as genes in the DNA damage response pathway ( BRCA2 , ATM and CHEK2 ) are associated with the risk of overall prostate cancer. We also found that rare damaging variants in AOX1 and BRCA2 were associated with increased severity of prostate cancer in a case-only analysis of aggressive versus non-aggressive prostate cancer. At the single-variant level, we found rare non-synonymous variants in three genes ( HOXB13 , CHEK2 , BIK ) significantly associated with increased risk of overall prostate cancer and in four genes ( ANO7 , SPDL1 , AR , TERT ) with decreased risk. Altogether, this study provides deeper insights into the genetic architecture and biological basis of prostate cancer risk and severity.

Meta-analysis indicates better climate adaptation and mitigation performance of hybrid engineering-natural coastal defence measures.

Traditional approaches to coastal defence often struggle to reduce the risks of accelerated climate change. Incorporating nature-based components into coastal defences may enhance adaptation to climate change with added benefits, but we need to compare their performance against conventional hard measures. We conduct a meta-analysis that compares the performances of hard, hybrid, soft and natural measures for coastal defence across different functions of risk reduction, climate change mitigation, and cost-effectiveness. Hybrid and soft measures offer higher risk reduction and climate change mitigation benefits than unvegetated natural systems, while performing on par with natural measures. Soft and hybrid measures are more cost-effective than hard measures, while hybrid measures provide the highest hazard reduction among all measures. All coastal defence measures have a positive economic return over a 20-year period. Mindful of risk context, our results provide strong an evidence-base for integrating and upscaling nature-based components into coastal defences in lower risk areas.

Protein-truncating variants in BSN are associated with severe adult-onset obesity, type 2 diabetes and fatty liver disease.

Obesity is a major risk factor for many common diseases and has a substantial heritable component. To identify new genetic determinants, we performed exome-sequence analyses for adult body mass index (BMI) in up to 587,027 individuals. We identified rare loss-of-function variants in two genes (BSN and APBA1) with effects substantially larger than those of well-established obesity genes such as MC4R. In contrast to most other obesity-related genes, rare variants in BSN and APBA1 were not associated with normal variation in childhood adiposity. Furthermore, BSN protein-truncating variants (PTVs) magnified the influence of common genetic variants associated with BMI, with a common variant polygenic score exhibiting an effect twice as large in BSN PTV carriers than in noncarriers. Finally, we explored the plasma proteomic signatures of BSN PTV carriers as well as the functional consequences of BSN deletion in human induced pluripotent stem cell-derived hypothalamic neurons. Collectively, our findings implicate degenerative processes in synaptic function in the etiology of adult-onset obesity.

Rare variant associations with plasma protein levels in the UK Biobank.

Integrating human genomics and proteomics can help elucidate disease mechanisms, identify clinical biomarkers and discover drug targets1-4. Because previous proteogenomic studies have focused on common variation via genome-wide association studies, the contribution of rare variants to the plasma proteome remains largely unknown. Here we identify associations between rare protein-coding variants and 2,923 plasma protein abundances measured in 49,736 UK Biobank individuals. Our variant-level exome-wide association study identified 5,433 rare genotype-protein associations, of which 81% were undetected in a previous genome-wide association study of the same cohort5. We then looked at aggregate signals using gene-level collapsing analysis, which revealed 1,962 gene-protein associations. Of the 691 gene-level signals from protein-truncating variants, 99.4% were associated with decreased protein levels. STAB1 and STAB2, encoding scavenger receptors involved in plasma protein clearance, emerged as pleiotropic loci, with 77 and 41 protein associations, respectively. We demonstrate the utility of our publicly accessible resource through several applications. These include detailing an allelic series in NLRC4, identifying potential biomarkers for a fatty liver disease-associated variant in HSD17B13 and bolstering phenome-wide association studies by integrating protein quantitative trait loci with protein-truncating variants in collapsing analyses. Finally, we uncover distinct proteomic consequences of clonal haematopoiesis (CH), including an association between TET2-CH and increased FLT3 levels. Our results highlight a considerable role for rare variation in plasma protein abundance and the value of proteogenomics in therapeutic discovery.

The effects of pathogenic and likely pathogenic variants for inherited hemostasis disorders in 140 214 UK Biobank participants.

Rare genetic diseases affect millions, and identifying causal DNA variants is essential for patient care. Therefore, it is imperative to estimate the effect of each independent variant and improve their pathogenicity classification. Our study of 140 214 unrelated UK Biobank (UKB) participants found that each of them carries a median of 7 variants previously reported as pathogenic or likely pathogenic. We focused on 967 diagnostic-grade gene (DGG) variants for rare bleeding, thrombotic, and platelet disorders (BTPDs) observed in 12 367 UKB participants. By association analysis, for a subset of these variants, we estimated effect sizes for platelet count and volume, and odds ratios for bleeding and thrombosis. Variants causal of some autosomal recessive platelet disorders revealed phenotypic consequences in carriers. Loss-of-function variants in MPL, which cause chronic amegakaryocytic thrombocytopenia if biallelic, were unexpectedly associated with increased platelet counts in carriers. We also demonstrated that common variants identified by genome-wide association studies (GWAS) for platelet count or thrombosis risk may influence the penetrance of rare variants in BTPD DGGs on their associated hemostasis disorders. Network-propagation analysis applied to an interactome of 18 410 nodes and 571 917 edges showed that GWAS variants with large effect sizes are enriched in DGGs and their first-order interactors. Finally, we illustrate the modifying effect of polygenic scores for platelet count and thrombosis risk on disease severity in participants carrying rare variants in TUBB1 or PROC and PROS1, respectively. Our findings demonstrate the power of association analyses using large population datasets in improving pathogenicity classifications of rare variants.

Effects of protein-coding variants on blood metabolite measurements and clinical biomarkers in the UK Biobank.

Genome-wide association studies (GWASs) have established the contribution of common and low-frequency variants to metabolic blood measurements in the UK Biobank (UKB). To complement existing GWAS findings, we assessed the contribution of rare protein-coding variants in relation to 355 metabolic blood measurements-including 325 predominantly lipid-related nuclear magnetic resonance (NMR)-derived blood metabolite measurements (Nightingale Health Plc) and 30 clinical blood biomarkers-using 412,393 exome sequences from four genetically diverse ancestries in the UKB. Gene-level collapsing analyses were conducted to evaluate a diverse range of rare-variant architectures for the metabolic blood measurements. Altogether, we identified significant associations (p < 1 × 10-8) for 205 distinct genes that involved 1,968 significant relationships for the Nightingale blood metabolite measurements and 331 for the clinical blood biomarkers. These include associations for rare non-synonymous variants in PLIN1 and CREB3L3 with lipid metabolite measurements and SYT7 with creatinine, among others, which may not only provide insights into novel biology but also deepen our understanding of established disease mechanisms. Of the study-wide significant clinical biomarker associations, 40% were not previously detected on analyzing coding variants in a GWAS in the same cohort, reinforcing the importance of studying rare variation to fully understand the genetic architecture of metabolic blood measurements.

A minimal role for synonymous variation in human disease.

Synonymous mutations change the DNA sequence of a gene without affecting the amino acid sequence of the encoded protein. Although some synonymous mutations can affect RNA splicing, translational efficiency, and mRNA stability, studies in human genetics, mutagenesis screens, and other experiments and evolutionary analyses have repeatedly shown that most synonymous variants are neutral or only weakly deleterious, with some notable exceptions. Based on a recent study in yeast, there have been claims that synonymous mutations could be as important as nonsynonymous mutations in causing disease, assuming the yeast findings hold up and translate to humans. Here, we argue that there is insufficient evidence to overturn the large, coherent body of knowledge establishing the predominant neutrality of synonymous variants in the human genome.

Human genetics uncovers MAP3K15 as an obesity-independent therapeutic target for diabetes.

We performed collapsing analyses on 454,796 UK Biobank (UKB) exomes to detect gene-level associations with diabetes. Recessive carriers of nonsynonymous variants in MAP3K15 were 30% less likely to develop diabetes (P = 5.7 × 10-10) and had lower glycosylated hemoglobin (ß = -0.14 SD units, P = 1.1 × 10-24). These associations were independent of body mass index, suggesting protection against insulin resistance even in the setting of obesity. We replicated these findings in 96,811 Admixed Americans in the Mexico City Prospective Study (P < 0.05)Moreover, the protective effect of MAP3K15 variants was stronger in individuals who did not carry the Latino-enriched SLC16A11 risk haplotype (P = 6.0 × 10-4). Separately, we identified a Finnish-enriched MAP3K15 protein-truncating variant associated with decreased odds of both type 1 and type 2 diabetes (P < 0.05) in FinnGen. No adverse phenotypes were associated with protein-truncating MAP3K15 variants in the UKB, supporting this gene as a therapeutic target for diabetes.

Cancer-driving mutations are enriched in genic regions intolerant to germline variation.

Large reference datasets of protein-coding variation in human populations have allowed us to determine which genes and genic subregions are intolerant to germline genetic variation. There is also a growing number of genes implicated in severe Mendelian diseases that overlap with genes implicated in cancer. We hypothesized that cancer-driving mutations might be enriched in genic subregions that are depleted of germline variation relative to somatic variation. We introduce a new metric, OncMTR (oncology missense tolerance ratio), which uses 125,748 exomes in the Genome Aggregation Database (gnomAD) to identify these genic subregions. We demonstrate that OncMTR can significantly predict driver mutations implicated in hematologic malignancies. Divergent OncMTR regions were enriched for cancer-relevant protein domains, and overlaying OncMTR scores on protein structures identified functionally important protein residues. Last, we performed a rare variant, gene-based collapsing analysis on an independent set of 394,694 exomes from the UK Biobank and find that OncMTR markedly improves genetic signals for hematologic malignancies.

Pharmacogenomic study of heart failure and candesartan response from the CHARM programme.

AIMS: The Candesartan in Heart failure Assessment of Reduction in Mortality and morbidity (CHARM) programme consisted of three parallel, randomized, double-blind clinical trials comparing candesartan with placebo in patients with heart failure (HF) categorized according to left ventricular ejection fraction and tolerability to an angiotensin-converting enzyme inhibitor. We conducted a pharmacogenomic study of the CHARM trials with the objective of identifying genetic predictors of HF progression and of the efficacy and safety of treatment with candesartan. METHODS: We performed genome-wide association studies in 2727 patients of European ancestry from CHARM-Overall and stratified by CHARM study according to preserved and reduced ejection fraction and according to assignment to the interventional treatment with candesartan. We tested genetic association with the composite endpoint of cardiovascular death or hospitalization for heart failure for drug efficacy in candesartan-treated patients and for HF progression using patients from both candesartan and placebo arms. The safety endpoints for response to candesartan were hyperkalaemia, renal dysfunction, hypotension, and change in systolic blood pressure between baseline and 6 weeks of treatment. To support our observations, we conducted a genome-wide gene-level collapsing analysis from whole-exome sequencing data with the composite cardiovascular endpoint. RESULTS: We found that the A allele (14% allele frequency) of the genetic variant rs66886237 at 8p21.3 near the gene GFRA2 was associated with the composite cardiovascular endpoint in 1029 HF patients with preserved ejection fraction from the CHARM-Preserved study (hazard ratio: 1.91, 95% confidence interval: 1.55-2.35; P = 1.7 × 10-9 ). The association was independent of candesartan treatment, and the genetic variant was not associated with the cardiovascular endpoint in patients with reduced ejection fraction. None of the genome-wide association studies for candesartan safety or efficacy conducted in patients treated with candesartan passed the significance threshold. We found no significant association from the gene-level collapsing analysis. CONCLUSIONS: We have identified a candidate genetic variant potentially predictive of the progression of heart failure in patients with preserved ejection fraction. The findings require further replication, and we cannot exclude the possibility that the results may be chance findings.

Uncovering variable neoplasms between ATM protein-truncating and common missense variants using 394 694 UK Biobank exomes.

As an essential regulator of DNA damage, ataxia-telangiectasia mutated (ATM) gene has been widely studied in oncology. However, the independent effects of ATM missense variants and protein-truncating variants (PTVs) on neoplasms have not been heavily studied. Whole-exome sequencing data and the clinical health records of 394,694 UK Biobank European participants were used in this analysis. We mined genetic associations from gene-level and variant-level phenome-wide association studies, and conducted a variant-level conditional association study to test whether the effects of ATM missense variants on neoplasms were independent of ATM PTV carrier status. The gene-level PTV collapsing analysis was consistent with established ATM PTV literature showing that the aggregated impact of 286 ATM PTVs significantly (p < 2 × 10-9 ) associated with 31 malignant neoplasm phenotypes. Of 773 distinct protein-coding variants in ATM, three individual missense variants significantly (p < 2 × 10-9 ) associated with nine phenotypes. Remarkably, although the nine phenotypes were tumor-related, none overlapped the established ATM PTV-linked malignancies. A subsequent conditional analysis identified that the missense signals were acting independently of the known clinically relevant ATM PTVs.

Gene-SCOUT: identifying genes with similar continuous trait fingerprints from phenome-wide association analyses.

Large-scale phenome-wide association studies performed using densely-phenotyped cohorts such as the UK Biobank (UKB), reveal many statistically robust gene-phenotype relationships for both clinical and continuous traits. Here, we present Gene-SCOUT, a tool used to identify genes with similar continuous trait fingerprints to a gene of interest. A fingerprint reflects the continuous traits identified to be statistically associated with a gene of interest based on multiple underlying rare variant genetic architectures. Similarities between genes are evaluated by the cosine similarity measure, to capture concordant effect directionality, elucidating clusters of genes in a high dimensional space. The underlying gene-biomarker population-scale association statistics were obtained from a gene-level rare variant collapsing analysis performed on over 1500 continuous traits using 394 692 UKB participant exomes, with additional metabolomic trait associations provided through Nightingale Health's recent study of 121 394 of these participants. We demonstrate that gene similarity estimates from Gene-SCOUT provide stronger enrichments for clinical traits compared to existing methods. Furthermore, we provide a fully interactive web-resource (http://genescout.public.cgr.astrazeneca.com) to explore the pre-calculated exome-wide similarities. This resource enables a user to examine the biological relevance of the most similar genes for Gene Ontology (GO) enrichment and UKB clinical trait enrichment statistics, as well as a detailed breakdown of the traits underpinning a given fingerprint.

Rare variant contribution to human disease in 281,104 UK Biobank exomes.

Genome-wide association studies have uncovered thousands of common variants associated with human disease, but the contribution of rare variants to common disease remains relatively unexplored. The UK Biobank contains detailed phenotypic data linked to medical records for approximately 500,000 participants, offering an unprecedented opportunity to evaluate the effect of rare variation on a broad collection of traits1,2. Here we study the relationships between rare protein-coding variants and 17,361 binary and 1,419 quantitative phenotypes using exome sequencing data from 269,171 UK Biobank participants of European ancestry. Gene-based collapsing analyses revealed 1,703 statistically significant gene-phenotype associations for binary traits, with a median odds ratio of 12.4. Furthermore, 83% of these associations were undetectable via single-variant association tests, emphasizing the power of gene-based collapsing analysis in the setting of high allelic heterogeneity. Gene-phenotype associations were also significantly enriched for loss-of-function-mediated traits and approved drug targets. Finally, we performed ancestry-specific and pan-ancestry collapsing analyses using exome sequencing data from 11,933 UK Biobank participants of African, East Asian or South Asian ancestry. Our results highlight a significant contribution of rare variants to common disease. Summary statistics are publicly available through an interactive portal ( http://azphewas.com/ ).

Pan-ancestry exome-wide association analyses of COVID-19 outcomes in 586,157 individuals.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, and results are publicly available through the Regeneron Genetics Center COVID-19 Results Browser.

Identification of a missense variant in SPDL1 associated with idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a fatal disorder characterised by progressive, destructive lung scarring. Despite substantial progress, the genetic determinants of this disease remain incompletely defined. Using whole genome and whole exome sequencing data from 752 individuals with sporadic IPF and 119,055 UK Biobank controls, we performed a variant-level exome-wide association study (ExWAS) and gene-level collapsing analyses. Our variant-level analysis revealed a novel association between a rare missense variant in SPDL1 and IPF (NM_017785.5:g.169588475 G > A p.Arg20Gln; p = 2.4 × 10-7, odds ratio = 2.87, 95% confidence interval: 2.03-4.07). This signal was independently replicated in the FinnGen cohort, which contains 1028 cases and 196,986 controls (combined p = 2.2 × 10-20), firmly associating this variant as an IPF risk allele. SPDL1 encodes Spindly, a protein involved in mitotic checkpoint signalling during cell division that has not been previously described in fibrosis. To the best of our knowledge, these results highlight a novel mechanism underlying IPF, providing the potential for new therapeutic discoveries in a disease of great unmet need.

Assessing the Role of Rare Genetic Variation in Patients With Heart Failure.

Importance: Sequencing studies have identified causal genetic variants for distinct subtypes of heart failure (HF) such as hypertrophic or dilated cardiomyopathy. However, the role of rare, high-impact variants in HF, for which ischemic heart disease is the leading cause, has not been systematically investigated. Objective: To assess the contribution of rare variants to all-cause HF with and without reduced left ventricular ejection fraction. Design, Setting, and Participants: This was a retrospective analysis of clinical trials and a prospective epidemiological resource (UK Biobank). Whole-exome sequencing of patients with HF was conducted from the Candesartan in Heart Failure-Assessment of Reduction in Mortality and Morbidity (CHARM) and Controlled Rosuvastatin Multinational Trial in Heart Failure (CORONA) clinical trials. Data were collected from March 1999 to May 2003 for the CHARM studies and September 2003 to July 2007 for the CORONA study. Using a gene-based collapsing approach, the proportion of patients with HF and controls carrying rare and presumed deleterious variants was compared. The burden of pathogenic variants in known cardiomyopathy genes was also investigated to assess the diagnostic yield. Exome sequencing data were generated between January 2018 and October 2018, and analysis began October 2018 and ended April 2020. Main Outcomes and Measures: Odds ratios and P values for genes enriched for rare and presumed deleterious variants in either patients with HF or controls and diagnostic yield of pathogenic variants in known cardiomyopathy genes. Results: This study included 5942 patients with HF and 13 156 controls. The mean (SD) age was 68.9 (9.9) years and 4213 (70.9%) were male. A significant enrichment of protein-truncating variants in the TTN gene (P = 3.35 × 10-13; odds ratio, 2.54; 95% CI, 1.96-3.31) that was further increased after restriction to variants in exons constitutively expressed in the heart (odds ratio, 4.52; 95% CI, 3.10-6.68). Validation using UK Biobank data showed a similar enrichment (odds ratio, 4.97; 95% CI, 3.94-6.19 after restriction). In the clinical trials, 201 of 5916 patients with HF (3.4%) had a pathogenic or likely pathogenic cardiomyopathy variant implicating 21 different genes. Notably, 121 of 201 individuals (60.2%) had ischemic heart disease as the clinically identified etiology for the HF. Individuals with HF and preserved ejection fraction had only a slightly lower yield than individuals with midrange or reduced ejection fraction (20 of 767 [2.6%] vs 15 of 392 [3.8%] vs 166 of 4757 [3.5%]). Conclusions and Relevance: An increased burden of diagnostic mendelian cardiomyopathy variants in a broad group of patients with HF of mostly ischemic etiology compared with controls was observed. This work provides further evidence that mendelian genetic conditions may represent an important subset of complex late-onset diseases such as HF, irrespective of the clinical presentation.

Spontaneous Coronary Artery Dissection: Insights on Rare Genetic Variation From Genome Sequencing.

BACKGROUND: Spontaneous coronary artery dissection (SCAD) occurs when an epicardial coronary artery is narrowed or occluded by an intramural hematoma. SCAD mainly affects women and is associated with pregnancy and systemic arteriopathies, particularly fibromuscular dysplasia. Variants in several genes, such as those causing connective tissue disorders, have been implicated; however, the genetic architecture is poorly understood. Here, we aim to better understand the diagnostic yield of rare variant genetic testing among a cohort of SCAD survivors and to identify genes or gene sets that have a significant enrichment of rare variants. METHODS: We sequenced a cohort of 384 SCAD survivors from the United Kingdom, alongside 13 722 UK Biobank controls and a validation cohort of 92 SCAD survivors. We performed a research diagnostic screen for pathogenic variants and exome-wide and gene-set rare variant collapsing analyses. RESULTS: The majority of patients within both cohorts are female, 29% of the study cohort and 14% validation cohort have a remote arteriopathy. Four cases across the 2 cohorts had a diagnosed connective tissue disorder. We identified pathogenic or likely pathogenic variants in 7 genes (PKD1, COL3A1, SMAD3, TGFB2, LOX, MYLK, and YY1AP1) in 14/384 cases in the study cohort and in 1/92 cases in the validation cohort. In our rare variant collapsing analysis, PKD1 was the highest-ranked gene, and several functionally plausible genes were enriched for rare variants, although no gene achieved study-wide statistical significance. Gene-set enrichment analysis suggested a role for additional genes involved in renal function. CONCLUSIONS: By studying the largest sequenced cohort of SCAD survivors, we demonstrate that, based on current knowledge, only a small proportion have a pathogenic variant that could explain their disease. Our findings strengthen the overlap between SCAD and renal and connective tissue disorders, and we highlight several new genes for future validation.

Numerical study of critical re-entrainment velocity of fire smoke within the street canyons with different building height ratios.

Traffic accident may bring vehicle fire in the street canyons. With its high temperature and numerous hazardous materials, the smoke produced by the vehicle fire may cause serious damage to the human body and the properties nearby, such as the glass curtain walls of buildings. The influence of the ambient air flow speed and street aspect ratio on the dispersion of fire smoke in street canyon has been analyzed by FDS software and theoretical analysis in this study. The impact of different windward building heights and different ambient air flow speeds u0 on the fire smoke were investigated. The results show that the fire smoke tilts towards the opposing direction of the ambient air flow within the street canyon, while the ambient air flow is perpendicular to the windward building. The results indicate that the critical re-entrainment velocity decreases at first, and then increases until it attains a constant with the building height ratio H1/H2. Finally, a predictive model of the critical re-entrainment velocity was developed under different building height ratios H1/H2.

Whole-exome sequencing in the evaluation of fetal structural anomalies: a prospective cohort study.

BACKGROUND: Identification of chromosomal aneuploidies and copy number variants that are associated with fetal structural anomalies has substantial value. Although whole-exome sequencing (WES) has been applied to case series of a few selected prenatal cases, its value in routine clinical settings has not been prospectively assessed in a large unselected cohort of fetuses with structural anomalies. We therefore aimed to determine the incremental diagnostic yield (ie, the added value) of WES following uninformative results of standard investigations with karyotype testing and chromosomal microarray in an unselected cohort of sequential pregnancies showing fetal structural anomalies. METHODS: In this prospective cohort study, the parents of fetuses who were found to have a structural anomaly in a prenatal ultrasound were screened for possible participation in the study. These participants were predominantly identified in or were referred to the Columbia University Carmen and John Thain Center for Prenatal Pediatrics (New York, NY, USA). Fetuses with confirmed aneuploidy or a causal pathogenic copy number variant were excluded from WES analyses. By use of WES of the fetuses and parents (parent-fetus trios), we identified genetic variants that indicated an underlying cause (diagnostic genetic variants) and genetic variants that met the criteria of bioinformatic signatures that had previously been described to be significantly enriched among diagnostic genetic variants. FINDINGS: Between April 24, 2015, and April 19, 2017, 517 sequentially identified pregnant women found to have fetuses with a structural anomaly were screened for their eligibility for inclusion in our study. 71 (14%) couples declined testing, 87 (17%) trios were missing at least one DNA sample (from either parent or the fetus), 69 (13%) trios had a clinically relevant abnormal karyotype or chromosomal microarray finding, 51 (10%) couples did not consent to WES or withdrew consent, and five (1%) samples were not of good enough quality for analysis. DNA samples from 234 (45%) eligible trios were therefore used for analysis of the primary outcome. By use of trio sequence data, we identified diagnostic genetic variants in 24 (10%) families. Mutations with bioinformatic signatures that were indicative of pathogenicity but with insufficient evidence to be considered diagnostic were also evaluated; 46 (20%) of the 234 fetuses assessed were found to have such signatures. INTERPRETATION: Our analysis of WES data in a prospective cohort of unselected fetuses with structural anomalies shows the value added by WES following the use of routine genetic tests. Our findings suggest that, in cases of fetal anomalies in which assessment with karyotype testing and chromosomal microarray fail to determine the underlying cause of a structural anomaly, WES can add clinically relevant information that could assist current management of a pregnancy. The unique challenges of WES-based prenatal diagnostics require analysis by a multidisciplinary team of perinatal practitioners and laboratory specialists. FUNDING: Institute for Genomic Medicine (Columbia University Irving Medical Center).