Exome-wide analysis implicates rare protein-altering variants in human handedness.

Handedness is a manifestation of brain hemispheric specialization. Left-handedness occurs at increased rates in neurodevelopmental disorders. Genome-wide association studies have identified common genetic effects on handedness or brain asymmetry, which mostly involve variants outside protein-coding regions and may affect gene expression. Implicated genes include several that encode tubulins (microtubule components) or microtubule-associated proteins. Here we examine whether left-handedness is also influenced by rare coding variants (frequencies ≤ 1%), using exome data from 38,043 left-handed and 313,271 right-handed individuals from the UK Biobank. The beta-tubulin gene TUBB4B shows exome-wide significant association, with a rate of rare coding variants 2.7 times higher in left-handers than right-handers. The TUBB4B variants are mostly heterozygous missense changes, but include two frameshifts found only in left-handers. Other TUBB4B variants have been linked to sensorineural and/or ciliopathic disorders, but not the variants found here. Among genes previously implicated in autism or schizophrenia by exome screening, DSCAM and FOXP1 show evidence for rare coding variant association with left-handedness. The exome-wide heritability of left-handedness due to rare coding variants was 0.91%. This study reveals a role for rare, protein-altering variants in left-handedness, providing further evidence for the involvement of microtubules and disorder-relevant genes.

Genetic associations of protein-coding variants in venous thromboembolism.

Previous genetic studies of venous thromboembolism (VTE) have been largely limited to common variants, leaving the genetic determinants relatively incomplete. We performed an exome-wide association study of VTE among 14,723 cases and 334,315 controls. Fourteen known and four novel genes (SRSF6, PHPT1, CGN, and MAP3K2) were identified through protein-coding variants, with broad replication in the FinnGen cohort. Most genes we discovered exhibited the potential to predict future VTE events in longitudinal analysis. Notably, we provide evidence for the additive contribution of rare coding variants to known genome-wide polygenic risk in shaping VTE risk. The identified genes were enriched in pathways affecting coagulation and platelet activation, along with liver-specific expression. The pleiotropic effects of these genes indicated the potential involvement of coagulation factors, blood cell traits, liver function, and immunometabolic processes in VTE pathogenesis. In conclusion, our study unveils the valuable contribution of protein-coding variants in VTE etiology and sheds new light on its risk stratification.

Comprehensive Molecular Profiling of NPM1-Mutated Acute Myeloid Leukemia Using RNAseq Approach.

Acute myeloid leukemia (AML) is a complex hematologic malignancy with high morbidity and mortality. Nucleophosmin 1 (NPM1) mutations occur in approximately 30% of AML cases, and NPM1-mutated AML is classified as a distinct entity. NPM1-mutated AML patients without additional genetic abnormalities have a favorable prognosis. Despite this, 30-50% of them experience relapse. This study aimed to investigate the potential of total RNAseq in improving the characterization of NPM1-mutated AML patients. We explored genetic variations independently of myeloid stratification, revealing a complex molecular scenario. We showed that total RNAseq enables the uncovering of different genetic alterations and clonal subtypes, allowing for a comprehensive evaluation of the real expression of exome transcripts in leukemic clones and the identification of aberrant fusion transcripts. This characterization may enhance understanding and guide improved treatment strategies for NPM1mut AML patients, contributing to better outcomes. Our findings underscore the complexity of NPM1-mutated AML, supporting the incorporation of advanced technologies for precise risk stratification and personalized therapeutic strategies. The study provides a foundation for future investigations into the clinical implications of identified genetic variations and highlights the importance of evolving diagnostic approaches in leukemia management.

Prioritization of oligogenic variant combinations in whole exomes.

MOTIVATION: Whole exome sequencing (WES) has emerged as a powerful tool for genetic research, enabling the collection of a tremendous amount of data about human genetic variation. However, properly identifying which variants are causative of a genetic disease remains an important challenge, often due to the number of variants that need to be screened. Expanding the screening to combinations of variants in two or more genes, as would be required under the oligogenic inheritance model, simply blows this problem out of proportion. RESULTS: We present here the High-throughput oligogenic prioritizer (Hop), a novel prioritization method that uses direct oligogenic information at the variant, gene and gene pair level to detect digenic variant combinations in WES data. This method leverages information from a knowledge graph, together with specialized pathogenicity predictions in order to effectively rank variant combinations based on how likely they are to explain the patient's phenotype. The performance of Hop is evaluated in cross-validation on 36 120 synthetic exomes for training and 14 280 additional synthetic exomes for independent testing. Whereas the known pathogenic variant combinations are found in the top 20 in approximately 60% of the cross-validation exomes, 71% are found in the same ranking range when considering the independent set. These results provide a significant improvement over alternative approaches that depend simply on a monogenic assessment of pathogenicity, including early attempts for digenic ranking using monogenic pathogenicity scores. AVAILABILITY AND IMPLEMENTATION: Hop is available at https://github.com/oligogenic/HOP.

Identification of skewed X chromosome inactivation using exome and transcriptome sequencing in patients with suspected rare genetic disease.

BACKGROUND: X-chromosome inactivation (XCI) is an epigenetic process that occurs during early development in mammalian females by randomly silencing one of two copies of the X chromosome in each cell. The preferential inactivation of either the maternal or paternal copy of the X chromosome in a majority of cells results in a skewed or non-random pattern of X inactivation and is observed in over 25% of adult females. Identifying skewed X inactivation is of clinical significance in patients with suspected rare genetic diseases due to the possibility of biased expression of disease-causing genes present on the active X chromosome. The current clinical test for the detection of skewed XCI relies on the methylation status of the methylation-sensitive restriction enzyme (Hpall) binding site present in proximity of short tandem polymorphic repeats on the androgen receptor (AR) gene. This approach using one locus results in uninformative or inconclusive data for 10-20% of tests. Further, recent studies have shown inconsistency between methylation of the AR locus and the state of inactivation of the X chromosome. Herein, we develop a method for estimating X inactivation status, using exome and transcriptome sequencing data derived from blood in 227 female samples. We built a reference model for evaluation of XCI in 135 females from the GTEx consortium. We tested and validated the model on 11 female individuals with different types of undiagnosed rare genetic disorders who were clinically tested for X-skew using the AR gene assay and compared results to our outlier-based analysis technique. RESULTS: In comparison to the AR clinical test for identification of X inactivation, our method was concordant with the AR method in 9 samples, discordant in 1, and provided a measure of X inactivation in 1 sample with uninformative clinical results. We applied this method on an additional 81 females presenting to the clinic with phenotypes consistent with different hereditary disorders without a known genetic diagnosis. CONCLUSIONS: This study presents the use of transcriptome and exome sequencing data to provide an accurate and complete estimation of X-inactivation and skew status in a cohort of female patients with different types of suspected rare genetic disease.

Decoding triancestral origins, archaic introgression, and natural selection in the Japanese population by whole-genome sequencing.

We generated Japanese Encyclopedia of Whole-Genome/Exome Sequencing Library (JEWEL), a high-depth whole-genome sequencing dataset comprising 3256 individuals from across Japan. Analysis of JEWEL revealed genetic characteristics of the Japanese population that were not discernible using microarray data. First, rare variant-based analysis revealed an unprecedented fine-scale genetic structure. Together with population genetics analysis, the present-day Japanese can be decomposed into three ancestral components. Second, we identified unreported loss-of-function (LoF) variants and observed that for specific genes, LoF variants appeared to be restricted to a more limited set of transcripts than would be expected by chance, with PTPRD as a notable example. Third, we identified 44 archaic segments linked to complex traits, including a Denisovan-derived segment at NKX6-1 associated with type 2 diabetes. Most of these segments are specific to East Asians. Fourth, we identified candidate genetic loci under recent natural selection. Overall, our work provided insights into genetic characteristics of the Japanese population.

Added value of whole-exome and RNA sequencing in advanced and refractory cancer patients with no molecular-based treatment recommendation based on a 90-gene panel.

INTRODUCTION: The objective was to determine the added value of comprehensive molecular profile by whole-exome and RNA sequencing (WES/RNA-Seq) in advanced and refractory cancer patients who had no molecular-based treatment recommendation (MBTR) based on a more limited targeted gene panel (TGP) plus array-based comparative genomic hybridization (aCGH). MATERIALS AND METHODS: In this retrospective analysis, we selected 50 patients previously included in the PROFILER trial (NCT01774409) for which no MBT could be recommended based on a targeted 90-gene panel and aCGH. For each patient, the frozen tumor sample mirroring the FFPE sample used for TGP/aCGH analysis were processed for WES and RNA-Seq. Data from TGP/aCGH were reanalyzed, and together with WES/RNA-Seq, findings were simultaneously discussed at a new molecular tumor board (MTB). RESULTS: After exclusion of variants of unknown significance, a total of 167 somatic molecular alterations were identified in 50 patients (median: 3 [1-10]). Out of these 167 relevant molecular alterations, 51 (31%) were common to both TGP/aCGH and WES/RNA-Seq, 19 (11%) were identified by the TGP/aCGH only and 97 (58%) were identified by WES/RNA-Seq only, including two fusion transcripts in two patients. A MBTR was provided in 4/50 (8%) patients using the information from TGP/aCGH versus 9/50 (18%) patients using WES/RNA-Seq findings. Three patients had similar recommendations based on TGP/aCGH and WES/RNA-Seq. CONCLUSIONS: In advanced and refractory cancer patients in whom no MBTR was recommended from TGP/aCGH, WES/RNA-Seq allowed to identify more alterations which may in turn, in a limited fraction of patients, lead to new MBTR.

Exome-Based Amino Acid Optimization: A Dietary Strategy to Satisfy Human Nutritional Demands and Enhance Muscle Strength in Breast Tumor Mice Undergoing Chemotherapy.

Breast cancer patients undergoing chemotherapy often experience muscle wasting and weakness, which impact their quality of life. A potential solution lies in customizing amino acid compositions based on exome-derived formulations (ExAAs). The study hypothesized that tailoring dietary amino acids using ExAAs could enhance muscle health. Theoretical amino acid requirements were calculated from the genome's exome region, and a breast cancer mouse model undergoing paclitaxel treatment was established. The mice were supplemented with a cancer-specific nutritional formula (QJS), and the effects of QJS and amino acid-adjusted QJS (adjQJS) were compared. Both formulations improved the nutritional status without compromising tumor growth. Notably, adjQJS significantly enhanced muscle strength compared to QJS (1.51 ± 0.25 vs. 1.30 ± 0.08 fold change, p < 0.05). Transcriptome analysis revealed alterations in complement and coagulation cascades, with an observed upregulation of C3 gene expression in adjQJS. Immune regulation also changed, showing a decrease in B cells and an increase in monocytes in skeletal muscle with adjQJS. Importantly, adjQJS resulted in a notable increase in Alistipes abundance compared to QJS (10.19 ± 0.04% vs. 5.03 ± 1.75%). This study highlights the potential of ExAAs as valuable guide for optimizing amino acid composition in diets for breast cancer patients undergoing chemotherapy.

Diversity of CFTR variants across ancestries characterized using 454,727 UK biobank whole exome sequences.

BACKGROUND: Limited understanding of the diversity of variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene across ancestries hampers efforts to advance molecular diagnosis of cystic fibrosis (CF). The consequences pose a risk of delayed diagnoses and subsequently worsened health outcomes for patients. Therefore, characterizing the spectrum of CFTR variants across ancestries is critical for revolutionizing molecular diagnoses of CF. METHODS: We analyzed 454,727 UK Biobank (UKBB) whole-exome sequences to characterize the diversity of CFTR variants across ancestries. Using the PanUKBB classification, the participants were assigned into six major groups: African (AFR), American/American Admixed (AMR), Central South Asia (CSA), East Asian (EAS), European (EUR), and Middle East (MID). We segregated ancestry-specific CFTR variants, including those that are CF-causing or clinically relevant. The ages of certain CF-causing variants were determined and analyzed for selective pressure effects, and curated phenotype analysis was performed for participants with clinically relevant CFTR genotypes. RESULTS: We detected over 4000 CFTR variants, including novel ancestry-specific variants, across six ancestries. Europeans had the most unique CFTR variants [n = 2212], while the American group had the least unique variants [n = 23]. F508del was the most prevalent CF-causing variant found in all ancestries, except in EAS, where V520F was the most prevalent. Common EAS variants such as 3600G > A, V456A, and V520, which appeared approximately 270, 215, and 338 generations ago, respectively, did not show evidence of selective pressure. Sixteen participants had two CF-causing variants, with two being diagnosed with CF. We found 154 participants harboring a CF-causing and varying clinical consequences (VCC) variant. Phenotype analysis performed for participants with multiple clinically relevant variants returned significant associations with CF and its pulmonary phenotypes [Bonferroni-adjusted p < 0.05]. CONCLUSIONS: We leveraged the UKBB database to comprehensively characterize the broad spectrum of CFTR variants across ancestries. The detection of over 4000 CFTR variants, including several ancestry-specific and uncharacterized CFTR variants, warrants the need for further characterization of their functional and clinical relevance. Overall, the presentation of classical CF phenotypes seen in non-CF diagnosed participants with more than one CF-causing variant indicates that they may benefit from current CFTR modulator therapies.

Genetics Visit Uptake Among Individuals Receiving Clinically Actionable Genomic Screening Results.

Importance: Screening unselected populations for clinically actionable genetic disease risk can improve ascertainment and facilitate risk management. Genetics visits may encourage at-risk individuals to perform recommended management, but little has been reported on genetics visit completion or factors associated with completion in genomic screening programs. Objective: To identify factors associated with postdisclosure genetics visits in a genomic screening cohort. Design, Setting, and Participants: This was a cohort study of biobank data in a health care system in central Pennsylvania. Participants' exome sequence data were reviewed for pathogenic or likely pathogenic (P/LP) results in all genes on the American College of Medical Genetics and Genomics Secondary Findings list. Clinically confirmed results were disclosed by phone and letter. Participants included adult MyCode biobank participants who received P/LP results between July 2015 and November 2019. Data were analyzed from May 2021 to March 2022. Exposure: Clinically confirmed P/LP result disclosed by phone or letter. Main Outcomes and Measures: Completion of genetics visit in which the result was discussed and variables associated with completion were assessed by electronic health record (EHR) review. Results: Among a total of 1160 participants (703 [60.6%] female; median [IQR] age, 57.0 [42.1-68.5] years), fewer than half of participants (551 of 1160 [47.5%]) completed a genetics visit. Younger age (odds ratio [OR] for age 18-40 years, 2.98; 95% CI, 1.40-6.53; OR for age 41-65 years, 2.36; 95% CI, 1.22-4.74; OR for age 66-80 years, 2.60; 95% CI, 1.41-4.98 vs age ≥81 years); female sex (OR, 1.49; 95% CI, 1.14-1.96); being married (OR, 1.74; 95% CI, 1.23-2.47) or divorced (OR, 1.80; 95% CI, 1.11-2.91); lower Charlson comorbidity index (OR for score of 0-2, 1.76; 95% CI, 1.16-2.68; OR for score of 3-4, 1.73; 95% CI, 1.18-2.54 vs score of ≥5); EHR patient portal use (OR, 1.42; 95% CI, 1.06-1.89); living closer to a genetics clinic (OR, 1.64; 95% CI, 1.14-2.36 for <8.9 miles vs >20.1 miles); successful results disclosure (OR for disclosure by genetic counselor, 16.32; 95% CI, 8.16-37.45; OR for disclosure by research assistant, 20.30; 95% CI, 10.25-46.31 vs unsuccessful phone disclosure); and having a hereditary cancer result (OR, 2.13; 95% CI, 1.28-3.58 vs other disease risk) were significantly associated with higher rates of genetics visit completion. Preference to follow up with primary care was the most common reported reason for declining a genetics visit (68 of 152 patients [44.7%]). Conclusions and Relevance: This cohort study of a biobank-based population genomic screening program suggests that targeted patient engagement, improving multidisciplinary coordination, and reducing barriers to follow-up care may be necessary for enhancing genetics visit uptake.

Implementation of whole-exome sequencing for pharmacogenomics profiling and exploring its potential clinical utilities.

Whole-exome sequencing (WES) is widely used in clinical settings; however, the exploration of its use in pharmacogenomic analysis remains limited. Our study compared the variant callings for 28 core absorption, distribution, metabolism and elimination genes by WES and array-based technology using clinical trials samples. The results revealed that WES had a positive predictive value of 0.71-0.92 and a sensitivity of single-nucleotide variants between 0.68 and 0.95, compared with array-based technology, for the variants in the commonly targeted regions of the WES and PhamacoScan™ assay. Besides the common variants detected by both assays, WES identified 200-300 exclusive variants per sample, totalling 55 annotated exclusive variants, including important modulators of metabolism such as rs2032582 (ABCB1) and rs72547527 (SULT1A1). This study highlights the potential clinical advantages of using WES to identify a wider range of genetic variations and enabling precision medicine.

Detection of elusive DNA copy-number variations in hereditary disease and cancer through the use of noncoding and off-target sequencing reads.

Copy-number variants (CNVs) play a substantial role in the molecular pathogenesis of hereditary disease and cancer, as well as in normal human interindividual variation. However, they are still rather difficult to identify in mainstream sequencing projects, especially involving exome sequencing, because they often occur in DNA regions that are not targeted for analysis. To overcome this problem, we developed OFF-PEAK, a user-friendly CNV detection tool that builds on a denoising approach and the use of "off-target" DNA reads, which are usually discarded by sequencing pipelines. We benchmarked OFF-PEAK on data from targeted sequencing of 96 cancer samples, as well as 130 exomes of individuals with inherited retinal disease from three different populations. For both sets of data, OFF-PEAK demonstrated excellent performance (>95% sensitivity and >80% specificity vs. experimental validation) in detecting CNVs from in silico data alone, indicating its immediate applicability to molecular diagnosis and genetic research.

[The foetal exome revealed]. / L'ADN fœtal révélé.

New developments in the analysis of maternal cell-free DNA now allow complete analysis of the foetal exome. This makes possible an important extension of the breadth of prenatal diagnostics but raises significant ethical questions.

TG468: a text graph convolutional network for predicting clinical response to immune checkpoint inhibitor therapy.

Enhancing cancer treatment efficacy remains a significant challenge in human health. Immunotherapy has witnessed considerable success in recent years as a treatment for tumors. However, due to the heterogeneity of diseases, only a fraction of patients exhibit a positive response to immune checkpoint inhibitor (ICI) therapy. Various single-gene-based biomarkers and tumor mutational burden (TMB) have been proposed for predicting clinical responses to ICI; however, their predictive ability is limited. We propose the utilization of the Text Graph Convolutional Network (GCN) method to comprehensively assess the impact of multiple genes, aiming to improve the predictive capability for ICI response. We developed TG468, a Text GCN model framing drug response prediction as a text classification task. By combining natural language processing (NLP) and graph neural network techniques, TG468 effectively handles sparse and high-dimensional exome sequencing data. As a result, TG468 can distinguish survival time for patients who received ICI therapy and outperforms single gene biomarkers, TMB and some classical machine learning models. Additionally, TG468's prediction results facilitate the identification of immune status differences among specific patient types in the Cancer Genome Atlas dataset, providing a rationale for the model's predictions. Our approach represents a pioneering use of a GCN model to analyze exome data in patients undergoing ICI therapy and offers inspiration for future research using NLP technology to analyze exome sequencing data.

A Rare Inherited Bone Marrow Failure Syndrome Disclosed by Reanalysis of the Exome Data of a Patient Evaluated for Cytopenia and Dysmorphic Features.

BACKGROUND: Multisystemic findings of inherited bone marrow failure syndromes may cause difficulty in diagnosis. Exome sequencing (ES) helps to define the etiology of rare diseases and reanalysis offers a valuable new diagnostic approach. Herein, we present the clinical and molecular characteristics of a girl who was referred for cytopenia and frequent infections. CASE REPORT: A 5-year-old girl with cytopenia, dysmorphism, short stature, developmental delay, and myopia was referred for genetic counseling. Reanalysis of the ES data revealed a homozygous splice-site variant in the DNAJC21 (NM_001012339.3:c.983+1G>A), causing Shwachman-Diamond Syndrome (SDS). It was shown by the RNA sequencing that exon 7 was skipped, causing an 88-nucleotide deletion. CONCLUSIONS: Precise genetic diagnosis enables genetic counseling and improves patient management by avoiding inappropriate treatment and unnecessary testing. This report would contribute to the clinical and molecular understanding of this rare type of SDS caused by DNAJC21 variants and expand the phenotypic features of this condition.

Rapid exome sequencing for children with severe acute encephalopathy - A case series.

Increasingly, next-generation sequencing (NGS) is becoming an invaluable tool in the diagnosis of unexplained acute neurological disorders, such as acute encephalopathy/encephalitis. Here, we describe a brief series of pediatric patients who presented at the pediatric intensive care unit with severe acute encephalopathy, initially suspected as infectious or inflammatory but subsequently diagnosed with a monogenic disorder. Rapid exome sequencing was performed during the initial hospitalization of three unrelated patients, and results were delivered within 7-21 days. All patients were previously healthy, 1.5-3 years old, of Muslim Arab descent, with consanguineous parents. One patient presenting with acute necrotizing encephalopathy (ANEC). Her sister presented with ANEC one year prior. Exome sequencing was diagnostic in all three patients. All were homozygous for pathogenic and likely-pathogenic variants associated with recessive disorders; MOCS2, NDUFS8 and DBR1. Surprisingly, the initial workup was not suggestive of the final diagnosis. This case series demonstrates that the use of rapid exome sequencing is shifting the paradigm of diagnostics even in critical care situations and should be considered early on in children with acute encephalopathy. A timely diagnosis can direct initial treatment as well as inform decisions regarding long-term care.

In-Depth Genomic Analysis: The New Challenge in Congenital Heart Disease.

The use of next-generation sequencing has provided new insights into the causes and mechanisms of congenital heart disease (CHD). Examinations of the whole exome sequence have detected detrimental gene variations modifying single or contiguous nucleotides, which are characterised as pathogenic based on statistical assessments of families and correlations with congenital heart disease, elevated expression during heart development, and reductions in harmful protein-coding mutations in the general population. Patients with CHD and extracardiac abnormalities are enriched for gene classes meeting these criteria, supporting a common set of pathways in the organogenesis of CHDs. Single-cell transcriptomics data have revealed the expression of genes associated with CHD in specific cell types, and emerging evidence suggests that genetic mutations disrupt multicellular genes essential for cardiogenesis. Metrics and units are being tracked in whole-genome sequencing studies.

Investigation of Recessive Effects of Coding Variants on Common Clinical Phenotypes in Exome-Sequenced UK Biobank Participants.

INTRODUCTION: Previous studies have demonstrated effects of rare coding variants on common, clinically relevant phenotypes although the additive burden of these variants makes only a small contribution to overall trait variance. Although recessive effects of individual homozygous variants have been studied, little work has been done to elucidate the impact of rare coding variants occurring together as compound heterozygotes. METHODS: In this study, attempts were made to identify pairs of variants likely to be occurring as compound heterozygotes using 200,000 exome-sequenced subjects from the UK Biobank. Pairs of variants, which were seen together in the same subject more often than would be expected by chance, were excluded as it was assumed that these might be present in the same haplotype. Attention was restricted to variants with minor allele frequency ≤0.05 and to those predicted to alter amino acid sequence or prevent normal gene expression. For each gene, compound heterozygotes were assigned scores based on the rarity and predicted functional consequences of the constituent variants and the scores were used in a logistic regression analysis to test for association with hypertension, hyperlipidaemia, and type 2 diabetes. RESULTS: No statistically significant associations were observed and the results conformed to the distribution, which would be expected under the null hypothesis. The average number of apparently compound heterozygous subjects for each gene was only 282.2. CONCLUSION: It seems difficult to detect an effect of compound heterozygotes on the risk of these phenotypes. Even if recessive effects from compound heterozygotes do occur, they would only affect a small number of people and overall would not make a substantial contribution to phenotypic variance. This research has been conducted using the UK Biobank Resource.