Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism.

We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n = 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.

Oncogenic Signaling Pathways in The Cancer Genome Atlas.

Genetic alterations in signaling pathways that control cell-cycle progression, apoptosis, and cell growth are common hallmarks of cancer, but the extent, mechanisms, and co-occurrence of alterations in these pathways differ between individual tumors and tumor types. Using mutations, copy-number changes, mRNA expression, gene fusions and DNA methylation in 9,125 tumors profiled by The Cancer Genome Atlas (TCGA), we analyzed the mechanisms and patterns of somatic alterations in ten canonical pathways: cell cycle, Hippo, Myc, Notch, Nrf2, PI-3-Kinase/Akt, RTK-RAS, TGFß signaling, p53 and ß-catenin/Wnt. We charted the detailed landscape of pathway alterations in 33 cancer types, stratified into 64 subtypes, and identified patterns of co-occurrence and mutual exclusivity. Eighty-nine percent of tumors had at least one driver alteration in these pathways, and 57% percent of tumors had at least one alteration potentially targetable by currently available drugs. Thirty percent of tumors had multiple targetable alterations, indicating opportunities for combination therapy.

Genetic and Functional Drivers of Diffuse Large B Cell Lymphoma.

Diffuse large B cell lymphoma (DLBCL) is the most common form of blood cancer and is characterized by a striking degree of genetic and clinical heterogeneity. This heterogeneity poses a major barrier to understanding the genetic basis of the disease and its response to therapy. Here, we performed an integrative analysis of whole-exome sequencing and transcriptome sequencing in a cohort of 1,001 DLBCL patients to comprehensively define the landscape of 150 genetic drivers of the disease. We characterized the functional impact of these genes using an unbiased CRISPR screen of DLBCL cell lines to define oncogenes that promote cell growth. A prognostic model comprising these genetic alterations outperformed current established methods: cell of origin, the International Prognostic Index comprising clinical variables, and dual MYC and BCL2 expression. These results comprehensively define the genetic drivers and their functional roles in DLBCL to identify new therapeutic opportunities in the disease.

Rare variants and handedness: spotlight on TUBB4B.

Twin studies suggest that additive genetic effects account for about a quarter of the variance in handedness. Recently, Schijven et al. used exome-wide sequencing to provide evidence for a role of rare protein-coding variants in handedness. These included the gene encoding beta-tubulin, TUBB4B, suggesting that microtubules are relevant for handedness ontogenesis.

De novo missense variants in exon 9 of SEPHS1 cause a neurodevelopmental condition with developmental delay, poor growth, hypotonia, and dysmorphic features.

Selenophosphate synthetase (SEPHS) plays an essential role in selenium metabolism. Two mammalian SEPHS paralogues, SEPHS1 and SEPHS2, share high sequence identity and structural homology with SEPHS. Here, we report nine individuals from eight families with developmental delay, growth and feeding problems, hypotonia, and dysmorphic features, all with heterozygous missense variants in SEPHS1. Eight of these individuals had a recurrent variant at amino acid position 371 of SEPHS1 (p.Arg371Trp, p.Arg371Gln, and p.Arg371Gly); seven of these variants were known to be de novo. Structural modeling and biochemical assays were used to understand the effect of these variants on SEPHS1 function. We found that a variant at residue Trp352 results in local structural changes of the C-terminal region of SEPHS1 that decrease the overall thermal stability of the enzyme. In contrast, variants of a solvent-exposed residue Arg371 do not impact enzyme stability and folding but could modulate direct protein-protein interactions of SEPSH1 with cellular factors in promoting cell proliferation and development. In neuronal SH-SY5Y cells, we assessed the impact of SEPHS1 variants on cell proliferation and ROS production and investigated the mRNA expression levels of genes encoding stress-related selenoproteins. Our findings provided evidence that the identified SEPHS1 variants enhance cell proliferation by modulating ROS homeostasis. Our study supports the hypothesis that SEPHS1 plays a critical role during human development and provides a basis for further investigation into the molecular mechanisms employed by SEPHS1. Furthermore, our data suggest that variants in SEPHS1 are associated with a neurodevelopmental disorder.

Toward clinical exomes in diagnostics and management of male infertility.

Infertility, affecting ∼10% of men, is predominantly caused by primary spermatogenic failure (SPGF). We screened likely pathogenic and pathogenic (LP/P) variants in 638 candidate genes for male infertility in 521 individuals presenting idiopathic SPGF and 323 normozoospermic men in the ESTAND cohort. Molecular diagnosis was reached for 64 men with SPGF (12%), with findings in 39 genes (6%). The yield did not differ significantly between the subgroups with azoospermia (20/185, 11%), oligozoospermia (18/181, 10%), and primary cryptorchidism with SPGF (26/155, 17%). Notably, 19 of 64 LP/P variants (30%) identified in 28 subjects represented recurrent findings in this study and/or with other male infertility cohorts. NR5A1 was the most frequently affected gene, with seven LP/P variants in six SPGF-affected men and two normozoospermic men. The link to SPGF was validated for recently proposed candidate genes ACTRT1, ASZ1, GLUD2, GREB1L, LEO1, RBM5, ROS1, and TGIF2LY. Heterozygous truncating variants in BNC1, reported in female infertility, emerged as plausible causes of severe oligozoospermia. Data suggested that several infertile men may present congenital conditions with less pronounced or pleiotropic phenotypes affecting the development and function of the reproductive system. Genes regulating the hypothalamic-pituitary-gonadal axis were affected in >30% of subjects with LP/P variants. Six individuals had more than one LP/P variant, including five with two findings from the gene panel. A 4-fold increased prevalence of cancer was observed in men with genetic infertility compared to the general male population (8% vs. 2%; p = 4.4 × 10-3). Expanding genetic testing in andrology will contribute to the multidisciplinary management of SPGF.

Pathogenic variants in HGF give rise to childhood-to-late onset primary lymphoedema by loss of function.

Developmental and functional defects in the lymphatic system are responsible for primary lymphoedema (PL). PL is a chronic debilitating disease caused by increased accumulation of interstitial fluid, predisposing to inflammation, infections and fibrosis. There is no cure, only symptomatic treatment is available. Thirty-two genes or loci have been linked to PL, and another 22 are suggested, including Hepatocyte Growth Factor (HGF). We searched for HGF variants in 770 index patients from the Brussels PL cohort. We identified ten variants predicted to cause HGF loss-of-function (six nonsense, two frameshifts, and two splice-site changes; 1.3% of our cohort), and 14 missense variants predicted to be pathogenic in 17 families (2.21%). We studied co-segregation within families, mRNA stability for non-sense variants, and in vitro functional effects of the missense variants. Analyses of the mRNA of patient cells revealed degradation of the nonsense mutant allele. Reduced protein secretion was detected for nine of the 14 missense variants expressed in COS-7 cells. Stimulation of lymphatic endothelial cells with these 14 HGF variant proteins resulted in decreased activation of the downstream targets AKT and ERK1/2 for three of them. Clinically, HGF-associated PL was diverse, but predominantly bilateral in the lower limbs with onset varying from early childhood to adulthood. Finally, aggregation study in a second independent cohort underscored that rare likely pathogenic variants in HGF explain about 2% of PL. Therefore, HGF signalling seems crucial for lymphatic development and/or maintenance in human beings and HGF should be included in diagnostic genetic screens for PL.

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.

An allelic-series rare-variant association test for candidate-gene discovery.

Allelic series are of candidate therapeutic interest because of the existence of a dose-response relationship between the functionality of a gene and the degree or severity of a phenotype. We define an allelic series as a collection of variants in which increasingly deleterious mutations lead to increasingly large phenotypic effects, and we have developed a gene-based rare-variant association test specifically targeted to identifying genes containing allelic series. Building on the well-known burden test and sequence kernel association test (SKAT), we specify a variety of association models covering different genetic architectures and integrate these into a Coding-Variant Allelic-Series Test (COAST). Through extensive simulations, we confirm that COAST maintains the type I error and improves the power when the pattern of coding-variant effect sizes increases monotonically with mutational severity. We applied COAST to identify allelic-series genes for four circulating-lipid traits and five cell-count traits among 145,735 subjects with available whole-exome sequencing data from the UK Biobank. Compared with optimal SKAT (SKAT-O), COAST identified 29% more Bonferroni-significant associations with circulating-lipid traits, on average, and 82% more with cell-count traits. All of the gene-trait associations identified by COAST have corroborating evidence either from rare-variant associations in the full cohort (Genebass, n = 400,000) or from common-variant associations in the GWAS Catalog. In addition to detecting many gene-trait associations present in Genebass by using only a fraction (36.9%) of the sample, COAST detects associations, such as that between ANGPTL4 and triglycerides, that are absent from Genebass but that have clear common-variant support.

Systematic evaluation of genome sequencing for the diagnostic assessment of autism spectrum disorder and fetal structural anomalies.

Short-read genome sequencing (GS) holds the promise of becoming the primary diagnostic approach for the assessment of autism spectrum disorder (ASD) and fetal structural anomalies (FSAs). However, few studies have comprehensively evaluated its performance against current standard-of-care diagnostic tests: karyotype, chromosomal microarray (CMA), and exome sequencing (ES). To assess the clinical utility of GS, we compared its diagnostic yield against these three tests in 1,612 quartet families including an individual with ASD and in 295 prenatal families. Our GS analytic framework identified a diagnostic variant in 7.8% of ASD probands, almost 2-fold more than CMA (4.3%) and 3-fold more than ES (2.7%). However, when we systematically captured copy-number variants (CNVs) from the exome data, the diagnostic yield of ES (7.4%) was brought much closer to, but did not surpass, GS. Similarly, we estimated that GS could achieve an overall diagnostic yield of 46.1% in unselected FSAs, representing a 17.2% increased yield over karyotype, 14.1% over CMA, and 4.1% over ES with CNV calling or 36.1% increase without CNV discovery. Overall, GS provided an added diagnostic yield of 0.4% and 0.8% beyond the combination of all three standard-of-care tests in ASD and FSAs, respectively. This corresponded to nine GS unique diagnostic variants, including sequence variants in exons not captured by ES, structural variants (SVs) inaccessible to existing standard-of-care tests, and SVs where the resolution of GS changed variant classification. Overall, this large-scale evaluation demonstrated that GS significantly outperforms each individual standard-of-care test while also outperforming the combination of all three tests, thus warranting consideration as the first-tier diagnostic approach for the assessment of ASD and FSAs.

Bi-allelic variants in the ESAM tight-junction gene cause a neurodevelopmental disorder associated with fetal intracranial hemorrhage.

The blood-brain barrier (BBB) is an essential gatekeeper for the central nervous system and incidence of neurodevelopmental disorders (NDDs) is higher in infants with a history of intracerebral hemorrhage (ICH). We discovered a rare disease trait in thirteen individuals, including four fetuses, from eight unrelated families associated with homozygous loss-of-function variant alleles of ESAM which encodes an endothelial cell adhesion molecule. The c.115del (p.Arg39Glyfs∗33) variant, identified in six individuals from four independent families of Southeastern Anatolia, severely impaired the in vitro tubulogenic process of endothelial colony-forming cells, recapitulating previous evidence in null mice, and caused lack of ESAM expression in the capillary endothelial cells of damaged brain. Affected individuals with bi-allelic ESAM variants showed profound global developmental delay/unspecified intellectual disability, epilepsy, absent or severely delayed speech, varying degrees of spasticity, ventriculomegaly, and ICH/cerebral calcifications, the latter being also observed in the fetuses. Phenotypic traits observed in individuals with bi-allelic ESAM variants overlap very closely with other known conditions characterized by endothelial dysfunction due to mutation of genes encoding tight junction molecules. Our findings emphasize the role of brain endothelial dysfunction in NDDs and contribute to the expansion of an emerging group of diseases that we propose to rename as "tightjunctionopathies."

Scalable mixed model methods for set-based association studies on large-scale categorical data analysis and its application to exome-sequencing data in UK Biobank.

The ongoing release of large-scale sequencing data in the UK Biobank allows for the identification of associations between rare variants and complex traits. SAIGE-GENE+ is a valid approach to conducting set-based association tests for quantitative and binary traits. However, for ordinal categorical phenotypes, applying SAIGE-GENE+ with treating the trait as quantitative or binarizing the trait can cause inflated type I error rates or power loss. In this study, we propose a scalable and accurate method for rare-variant association tests, POLMM-GENE, in which we used a proportional odds logistic mixed model to characterize ordinal categorical phenotypes while adjusting for sample relatedness. POLMM-GENE fully utilizes the categorical nature of phenotypes and thus can well control type I error rates while remaining powerful. In the analyses of UK Biobank 450k whole-exome-sequencing data for five ordinal categorical traits, POLMM-GENE identified 54 gene-phenotype associations.

Loss of PTEN Is Associated with Resistance to Anti-PD-1 Checkpoint Blockade Therapy in Metastatic Uterine Leiomyosarcoma.

Response to immune checkpoint blockade in mesenchymal tumors is poorly characterized, but immunogenomic dissection of these cancers could inform immunotherapy mediators. We identified a treatment-naive patient who has metastatic uterine leiomyosarcoma and has experienced complete tumor remission for >2 years on anti-PD-1 (pembrolizumab) monotherapy. We analyzed the primary tumor, the sole treatment-resistant metastasis, and germline tissue to explore mechanisms of immunotherapy sensitivity and resistance. Both tumors stained diffusely for PD-L2 and showed sparse PD-L1 staining. PD-1+ cell infiltration significantly decreased in the resistant tumor (p = 0.039). Genomically, the treatment-resistant tumor uniquely harbored biallelic PTEN loss and had reduced expression of two neoantigens that demonstrated strong immunoreactivity with patient T cells in vitro, suggesting long-lasting immunological memory. In this near-complete response to PD-1 blockade in a mesenchymal tumor, we identified PTEN mutations and reduced expression of genes encoding neoantigens as potential mediators of resistance to immune checkpoint therapy.

A role for mutations in AK9 and other genes affecting ependymal cells in idiopathic normal pressure hydrocephalus.

Idiopathic normal pressure hydrocephalus (iNPH) is an enigmatic neurological disorder that develops after age 60 and is characterized by gait difficulty, dementia, and incontinence. Recently, we reported that heterozygous CWH43 deletions may cause iNPH. Here, we identify mutations affecting nine additional genes (AK9, RXFP2, PRKD1, HAVCR1, OTOG, MYO7A, NOTCH1, SPG11, and MYH13) that are statistically enriched among iNPH patients. The encoded proteins are all highly expressed in choroid plexus and ependymal cells, and most have been associated with cilia. Damaging mutations in AK9, which encodes an adenylate kinase, were detected in 9.6% of iNPH patients. Mice homozygous for an iNPH-associated AK9 mutation displayed normal cilia structure and number, but decreased cilia motility and beat frequency, communicating hydrocephalus, and balance impairment. AK9+/- mice displayed normal brain development and behavior until early adulthood, but subsequently developed communicating hydrocephalus. Together, our findings suggest that heterozygous mutations that impair ventricular epithelial function may contribute to iNPH.

Are trait-associated genes clustered together in a gene network?

Genome-wide association studies (GWAS) have provided an abundance of information about the genetic variants and their loci that are associated to complex traits and diseases. However, due to linkage disequilibrium (LD) and noncoding regions of loci, it remains a challenge to pinpoint the causal genes. Gene network-based approaches, paired with network diffusion methods, have been proposed to prioritize causal genes and to boost statistical power in GWAS based on the assumption that trait-associated genes are clustered in a gene network. Due to the difficulty in mapping trait-associated variants to genes in GWAS, this assumption has never been directly or rigorously tested empirically. On the other hand, whole exome sequencing (WES) data focuses on the protein-coding regions, directly identifying trait-associated genes. In this study, we tested the assumption by leveraging the recently available exome-based association statistics from the UK Biobank WES data along with two types of networks. We found that almost all trait-associated genes were significantly more proximal to each other than randomly selected genes within both networks. These results support the assumption that trait-associated genes are clustered in gene networks, which can be further leveraged to boost the power of GWAS such as by introducing less stringent p value thresholds.

Exome/Genome Sequencing in Undiagnosed Syndromes.

Exome sequencing (ES) and genome sequencing (GS) have radically transformed the diagnostic approach to undiagnosed rare/ultrarare Mendelian diseases. Next-generation sequencing (NGS), the technology integral for ES, GS, and most large (100+) gene panels, has enabled previously unimaginable diagnoses, changes in medical management, new treatments, and accurate reproductive risk assessments for patients, as well as new disease gene discoveries. Yet, challenges remain, as most individuals remain undiagnosed with current NGS. Improved NGS technology has resulted in long-read sequencing, which may resolve diagnoses in some patients who do not obtain a diagnosis with current short-read ES and GS, but its effectiveness is unclear, and it is expensive. Other challenges that persist include the resolution of variants of uncertain significance, the urgent need for patients with ultrarare disorders to have access to therapeutics, the need for equity in patient access to NGS-based testing, and the study of ethical concerns. However, the outlook for undiagnosed disease resolution is bright, due to continual advancements in the field.

Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes.

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.

PhenoApt leverages clinical expertise to prioritize candidate genes via machine learning.

In recent years, exome sequencing (ES) has shown great utility in the diagnoses of Mendelian disorders. However, after rigorous filtering, a typical ES analysis still involves the interpretation of hundreds of variants, which greatly hinders the rapid identification of causative genes. Since the interpretations of ES data require comprehensive clinical analyses, taking clinical expertise into consideration can speed the molecular diagnoses of Mendelian disorders. To leverage clinical expertise to prioritize candidate genes, we developed PhenoApt, a phenotype-driven gene prioritization tool that allows users to assign a customized weight to each phenotype, via a machine-learning algorithm. Using the ability to rank causative genes in top-10 lists as an evaluation metric, baseline analysis demonstrated that PhenoApt outperformed previous phenotype-driven gene prioritization tools by a relative increase of 22.7%-140.0% in three independent, real-world, multi-center cohorts (cohort 1, n = 185; cohort 2, n = 784; and cohort 3, n = 208). Additional trials showed that, by adding weights to clinical indications, which should be explained by the causative gene, PhenoApt performance was improved by a relative increase of 37.3% in cohort 2 (n = 471) and 21.4% in cohort 3 (n = 208). Moreover, PhenoApt could assign an intrinsic weight to each phenotype based on the likelihood of its being a Mendelian trait using term frequency-inverse document frequency techniques. When clinical indications were assigned with intrinsic weights, PhenoApt performance was improved by a relative increase of 23.7% in cohort 2 and 15.5% in cohort 3. For the integration of PhenoApt into clinical practice, we developed a user-friendly website and a command-line tool.

Whole-exome sequencing improves the diagnosis and care of men with non-obstructive azoospermia.

Non-obstructive azoospermia (NOA) is a severe and frequent cause of male infertility, often treated by testicular sperm extraction followed by intracytoplasmic sperm injection. The aim of this study is to improve the genetic diagnosis of NOA, by identifying new genes involved in human NOA and to better assess the chances of successful sperm extraction according to the individual's genotype. Exome sequencing was performed on 96 NOA-affected individuals negative for routine genetic tests. Bioinformatics analysis was limited to a panel of 151 genes selected as known causal or candidate genes for NOA. Only highly deleterious homozygous or hemizygous variants were retained as candidates. A likely causal defect was identified in 16 genes in a total of 22 individuals (23%). Six genes had not been described in man (DDX25, HENMT1, MCMDC2, MSH5, REC8, TDRKH) and 10 were previously reported (C14orf39, DMC1, FANCM, GCNA, HFM1, MCM8, MEIOB, PDHA2, TDRD9, TERB1). Seven individuals had defects in genes from piwi or DNA repair pathways, three in genes involved in post-meiotic maturation, and 12 in meiotic processes. Interestingly, all individuals with defects in meiotic genes had an unsuccessful sperm retrieval, indicating that genetic diagnosis prior to TESE could help identify individuals with low or null chances of successful sperm retrieval and thus avoid unsuccessful surgeries.