Rare variant analyses validate known ALS genes in a multi-ethnic population and identifies ANTXR2 as a candidate in PLS.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease affecting over 300,000 people worldwide. It is characterized by the progressive decline of the nervous system that leads to the weakening of muscles which impacts physical function. Approximately, 15% of individuals diagnosed with ALS have a known genetic variant that contributes to their disease. As therapies that slow or prevent symptoms continue to develop, such as antisense oligonucleotides, it is important to discover novel genes that could be targets for treatment. Additionally, as cohorts continue to grow, performing analyses in ALS subtypes, such as primary lateral sclerosis (PLS), becomes possible due to an increase in power. These analyses could highlight novel pathways in disease manifestation. METHODS: Building on our previous discoveries using rare variant association analyses, we conducted rare variant burden testing on a substantially larger multi-ethnic cohort of 6,970 ALS patients, 166 PLS patients, and 22,524 controls. We used intolerant domain percentiles based on sub-region Residual Variation Intolerance Score (subRVIS) that have been described previously in conjunction with gene based collapsing approaches to conduct burden testing to identify genes that associate with ALS and PLS. RESULTS: A gene based collapsing model showed significant associations with SOD1, TARDBP, and TBK1 (OR = 19.18, p = 3.67 × 10-39; OR = 4.73, p = 2 × 10-10; OR = 2.3, p = 7.49 × 10-9, respectively). These genes have been previously associated with ALS. Additionally, a significant novel control enriched gene, ALKBH3 (p = 4.88 × 10-7), was protective for ALS in this model. An intolerant domain-based collapsing model showed a significant improvement in identifying regions in TARDBP that associated with ALS (OR = 10.08, p = 3.62 × 10-16). Our PLS protein truncating variant collapsing analysis demonstrated significant case enrichment in ANTXR2 (p = 8.38 × 10-6). CONCLUSIONS: In a large multi-ethnic cohort of 6,970 ALS patients, collapsing analyses validated known ALS genes and identified a novel potentially protective gene, ALKBH3. A first-ever analysis in 166 patients with PLS found a candidate association with loss-of-function mutations in ANTXR2.

Rare variant analyses validate known ALS genes in a multi-ethnic population and identifies ANTXR2 as a candidate in PLS.

Background: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease affecting over 30,000 people in the United States. It is characterized by the progressive decline of the nervous system that leads to the weakening of muscles which impacts physical function. Approximately, 15% of individuals diagnosed with ALS have a known genetic variant that contributes to their disease. As therapies that slow or prevent symptoms, such as antisense oligonucleotides, continue to develop, it is important to discover novel genes that could be targets for treatment. Additionally, as cohorts continue to grow, performing analyses in ALS subtypes, such as primary lateral sclerosis (PLS), becomes possible due to an increase in power. These analyses could highlight novel pathways in disease manifestation. Methods: Building on our previous discoveries using rare variant association analyses, we conducted rare variant burden testing on a substantially larger cohort of 6,970 ALS patients from a large multi-ethnic cohort as well as 166 PLS patients, and 22,524 controls. We used intolerant domain percentiles based on sub-region Residual Variation Intolerance Score (subRVIS) that have been described previously in conjunction with gene based collapsing approaches to conduct burden testing to identify genes that associate with ALS and PLS. Results: A gene based collapsing model showed significant associations with SOD1, TARDBP, and TBK1 (OR=19.18, p = 3.67 × 10-39; OR=4.73, p = 2 × 10-10; OR=2.3, p = 7.49 × 10-9, respectively). These genes have been previously associated with ALS. Additionally, a significant novel control enriched gene, ALKBH3 (p = 4.88 × 10-7), was protective for ALS in this model. An intolerant domain based collapsing model showed a significant improvement in identifying regions in TARDBP that associated with ALS (OR=10.08, p = 3.62 × 10-16). Our PLS protein truncating variant collapsing analysis demonstrated significant case enrichment in ANTXR2 (p=8.38 × 10-6). Conclusions: In a large multi-ethnic cohort of 6,970 ALS patients, rare variant burden testing validated known ALS genes and identified a novel potentially protective gene, ALKBH3. A first-ever analysis in 166 patients with PLS found a candidate association with loss-of-function mutations in ANTXR2.

Prevalence and significance of clonal hematopoiesis of indeterminate potential in lung transplant recipients.

BACKGROUND: Clonal hematopoiesis of indeterminate potential (CHIP), the age-related acquisition of somatic mutations that leads to an expanded blood cell clone, has been associated with development of a pro-inflammatory state. An enhanced or dysregulated inflammatory response may contribute to rejection after lung transplantation, however the prevalence of CHIP in lung recipients and influence of CHIP on allograft outcomes is unknown. METHODS: We analyzed whole-exome sequencing data in 279 lung recipients to detect CHIP, defined by pre-specified somatic mutations in 74 genes known to promote clonal expansion of hematopoietic stem cells. We compared the burden of acute rejection (AR) over the first post-transplant year in lung recipients with vs. without CHIP using multivariable ordinal regression. Multivariate Cox proportional hazards models were used to assess the association between CHIP and CLAD-free survival. An exploratory analysis evaluated the association between the number of CHIP-associated variants and chronic lung allograft dysfunction (CLAD)-free survival. RESULTS: We detected 64 CHIP-associated mutations in 45 individuals (15.7%), most commonly in TET2 (10.8%), DNMT3A (9.2%), and U2AF1 (9.2%). Patients with CHIP tended to be older but did not significantly differ from patients without CHIP in terms of race or native lung disease. Patients with CHIP did not have a higher incidence of AR over the first post-transplant year (p = 0.45) or a significantly increased risk of death or CLAD (adjusted HR 1.25, 95% CI 0.88-1.78). We did observe a significant association between the number of CHIP variants and CLAD-free survival, specifically patients with 2 or more CHIP-associated variants had an increased risk for death or CLAD (adjusted HR 3.79, 95% CI 1.98-7.27). CONCLUSIONS: Lung recipients have a higher prevalence of CHIP and a larger variety of genes with CHIP-associated mutations compared with previous reports for the general population. CHIP did not increase the risk of AR, CLAD, or death in lung recipients.

Clinical and Genetic Characteristics of CKD Patients with High-Risk APOL1 Genotypes.

SIGNIFICANCE STATEMENT: APOL1 high-risk genotypes confer a significant risk of kidney disease, but variability in patient outcomes suggests the presence of modifiers of the APOL1 effect. We show that a diverse population of CKD patients with high-risk APOL1 genotypes have an increased lifetime risk of kidney failure and higher eGFR decline rates, with a graded risk among specific high-risk genotypes. CKD patients with high-risk APOL1 genotypes have a lower diagnostic yield for monogenic kidney disease. Exome sequencing revealed enrichment of rare missense variants within the inflammasome pathway modifying the effect of APOL1 risk genotypes, which may explain some clinical heterogeneity. BACKGROUND: APOL1 genotype has significant effects on kidney disease development and progression that vary among specific causes of kidney disease, suggesting the presence of effect modifiers. METHODS: We assessed the risk of kidney failure and the eGFR decline rate in patients with CKD carrying high-risk ( N =239) and genetically matched low-risk ( N =1187) APOL1 genotypes. Exome sequencing revealed monogenic kidney diseases. Exome-wide association studies and gene-based and gene set-based collapsing analyses evaluated genetic modifiers of the effect of APOL1 genotype on CKD. RESULTS: Compared with genetic ancestry-matched patients with CKD with low-risk APOL1 genotypes, those with high-risk APOL1 genotypes had a higher risk of kidney failure (Hazard Ratio [HR]=1.58), a higher decline in eGFR (6.55 versus 3.63 ml/min/1.73 m 2 /yr), and were younger at time of kidney failure (45.1 versus 53.6 years), with the G1/G1 genotype demonstrating the highest risk. The rate for monogenic kidney disorders was lower among patients with CKD with high-risk APOL1 genotypes (2.5%) compared with those with low-risk genotypes (6.7%). Gene set analysis identified an enrichment of rare missense variants in the inflammasome pathway in individuals with high-risk APOL1 genotypes and CKD (odds ratio=1.90). CONCLUSIONS: In this genetically matched cohort, high-risk APOL1 genotypes were associated with an increased risk of kidney failure and eGFR decline rate, with a graded risk between specific high-risk genotypes and a lower rate of monogenic kidney disease. Rare missense variants in the inflammasome pathway may act as genetic modifiers of APOL1 effect on kidney disease.

Genetic insights into childhood-onset schizophrenia: The yield of clinical exome sequencing.

Childhood-onset schizophrenia (COS) is a rare form of schizophrenia with an onset prior to 13 years of age. Although genetic factors play a role in COS etiology, only a few causal variants have been reported to date. This study presents a diagnostic exome sequencing (ES) in 37 Israeli Jewish families with a proband diagnosed with COS. By implementing a trio/duo ES approach and applying a well-established diagnostic pipeline, we detected clinically significant variants in 7 probands (19 %). These single nucleotide variants and indels were mostly inherited. The implicated genes were ANKRD11, GRIA2, CHD2, CLCN3, CLTC, IGF1R and MICU1. In a secondary analysis that compared COS patients to 4721 healthy controls, we observed that patients had a significant enrichment of rare loss of function (LoF) variants in LoF intolerant genes associated with developmental diseases. Taken together, ES could be considered as a valuable tool in the genetic workup for COS patients.

Rare variant analyses validate known ALS genes in a multi-ethnic population and identifies ANTXR2 as a candidate in PLS.

Background: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease affecting over 30,000 people in the United States. It is characterized by the progressive decline of the nervous system that leads to the weakening of muscles which impacts physical function. Approximately, 15% of individuals diagnosed with ALS have a known genetic variant that contributes to their disease. As therapies that slow or prevent symptoms, such as antisense oligonucleotides, continue to develop, it is important to discover novel genes that could be targets for treatment. Additionally, as cohorts continue to grow, performing analyses in ALS subtypes, such as primary lateral sclerosis (PLS), becomes possible due to an increase in power. These analyses could highlight novel pathways in disease manifestation. Methods: Building on our previous discoveries using rare variant association analyses, we conducted rare variant burden testing on a substantially larger cohort of 6,970 ALS patients from a large multi-ethnic cohort as well as 166 PLS patients, and 22,524 controls. We used intolerant domain percentiles based on sub-region Residual Variation Intolerance Score (subRVIS) that have been described previously in conjunction with gene based collapsing approaches to conduct burden testing to identify genes that associate with ALS and PLS. Results: A gene based collapsing model showed significant associations with SOD1, TARDBP, and TBK1 (OR=19.18, p = 3.67 × 10-39; OR=4.73, p = 2 × 10-10; OR=2.3, p = 7.49 × 10-9, respectively). These genes have been previously associated with ALS. Additionally, a significant novel control enriched gene, ALKBH3 (p = 4.88 × 10-7), was protective for ALS in this model. An intolerant domain based collapsing model showed a significant improvement in identifying regions in TARDBP that associated with ALS (OR=10.08, p = 3.62 × 10-16). Our PLS protein truncating variant collapsing analysis demonstrated significant case enrichment in ANTXR2 (p=8.38 × 10-6). Conclusions: In a large multi-ethnic cohort of 6,970 ALS patients, rare variant burden testing validated known ALS genes and identified a novel potentially protective gene, ALKBH3. A first-ever analysis in 166 patients with PLS found a candidate association with loss-of-function mutations in ANTXR2.

Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative.

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

Utility of whole genome sequencing in assessing risk and clinically relevant outcomes for pulmonary fibrosis.

BACKGROUND: Whole genome sequencing (WGS) can detect variants and estimate telomere length. The clinical utility of WGS in estimating risk, progression and survival of pulmonary fibrosis patients is unknown. METHODS: In this observational cohort study, we performed WGS on 949 patients with idiopathic pulmonary fibrosis or familial pulmonary fibrosis to determine rare and common variant genotypes, estimate telomere length and assess the association of genomic factors with clinical outcomes. RESULTS: WGS estimates of telomere length correlated with quantitative PCR (R=0.65) and Southern blot (R=0.71) measurements. Rare deleterious qualifying variants were found in 14% of the total cohort, with a five-fold increase in those with a family history of disease versus those without (25% versus 5%). Most rare qualifying variants (85%) were found in telomere-related genes and were associated with shorter telomere lengths. Rare qualifying variants had a greater effect on telomere length than a polygenic risk score calculated using 20 common variants previously associated with telomere length. The common variant polygenic risk score predicted telomere length only in sporadic disease. Reduced transplant-free survival was associated with rare qualifying variants, shorter quantitative PCR-measured telomere lengths and absence of the MUC5B promoter (rs35705950) single nucleotide polymorphism, but not with WGS-estimated telomere length or the common variant polygenic risk score. Disease progression was associated with both measures of telomere length (quantitative PCR measured and WGS estimated), rare qualifying variants and the common variant polygenic risk score. CONCLUSION: As a single test, WGS can inform pulmonary fibrosis genetic-mediated risk, evaluate the functional effect of telomere-related variants by estimating telomere length, and prognosticate clinically relevant disease outcomes.

Rare and Common Variants in KIF15 Contribute to Genetic Risk of Idiopathic Pulmonary Fibrosis.

Rationale: Genetic studies of idiopathic pulmonary fibrosis (IPF) have improved our understanding of this disease, but not all causal loci have been identified. Objectives: To identify genes enriched with rare deleterious variants in IPF and familial pulmonary fibrosis. Methods: We performed gene burden analysis of whole-exome data, tested single variants for disease association, conducted KIF15 (kinesin family member 15) functional studies, and examined human lung single-cell RNA sequencing data. Measurements and Main Results: Gene burden analysis of 1,725 cases and 23,509 control subjects identified heterozygous rare deleterious variants in KIF15, a kinesin involved in spindle separation during mitosis, and three telomere-related genes (TERT [telomerase reverse transcriptase], RTEL1 [regulator of telomere elongation helicase 1], and PARN [poly(A)-specific ribonuclease]). KIF15 was implicated in autosomal-dominant models of rare deleterious variants (odds ratio [OR], 4.9; 95% confidence interval [CI], 2.7-8.8; P = 2.55 × 10-7) and rare protein-truncating variants (OR, 7.6; 95% CI, 3.3-17.1; P = 8.12 × 10-7). Meta-analyses of the discovery and replication cohorts, including 2,966 cases and 29,817 control subjects, confirm the involvement of KIF15 plus the three telomere-related genes. A common variant within a KIF15 intron (rs74341405; OR, 1.6; 95% CI, 1.4-1.9; P = 5.63 × 10-10) is associated with IPF risk, confirming a prior report. Lymphoblastoid cells from individuals heterozygous for the common variant have decreased KIF15 and reduced rates of cell growth. Cell proliferation is dependent on KIF15 in the presence of an inhibitor of Eg5/KIF11, which has partially redundant function. KIF15 is expressed specifically in replicating human lung cells and shows diminished expression in replicating epithelial cells of patients with IPF. Conclusions: Both rare deleterious variants and common variants in KIF15 link a nontelomerase pathway of cell proliferation with IPF susceptibility.

The benefit of diagnostic whole genome sequencing in schizophrenia and other psychotic disorders.

Schizophrenia has a multifactorial etiology, involving a polygenic architecture. The potential benefit of whole genome sequencing (WGS) in schizophrenia and other psychotic disorders is not well studied. We investigated the yield of clinical WGS analysis in 251 families with a proband diagnosed with schizophrenia (N = 190), schizoaffective disorder (N = 49), or other conditions involving psychosis (N = 48). Participants were recruited in Israel and USA, mainly of Jewish, Arab, and other European ancestries. Trio (parents and proband) WGS was performed for 228 families (90.8%); in the other families, WGS included parents and at least two affected siblings. In the secondary analyses, we evaluated the contribution of rare variant enrichment in particular gene sets, and calculated polygenic risk score (PRS) for schizophrenia. For the primary outcome, diagnostic rate was 6.4%; we found clinically significant, single nucleotide variants (SNVs) or small insertions or deletions (indels) in 14 probands (5.6%), and copy number variants (CNVs) in 2 (0.8%). Significant enrichment of rare loss-of-function variants was observed in a gene set of top schizophrenia candidate genes in affected individuals, compared with population controls (N = 6,840). The PRS for schizophrenia was significantly increased in the affected individuals group, compared to their unaffected relatives. Last, we were also able to provide pharmacogenomics information based on CYP2D6 genotype data for most participants, and determine their antipsychotic metabolizer status. In conclusion, our findings suggest that WGS may have a role in the setting of both research and genetic counseling for individuals with schizophrenia and other psychotic disorders and their families.

Rare loss-of-function variants in type I IFN immunity genes are not associated with severe COVID-19.

A recent report found that rare predicted loss-of-function (pLOF) variants across 13 candidate genes in TLR3- and IRF7-dependent type I IFN pathways explain up to 3.5% of severe COVID-19 cases. We performed whole-exome or whole-genome sequencing of 1,864 COVID-19 cases (713 with severe and 1,151 with mild disease) and 15,033 ancestry-matched population controls across 4 independent COVID-19 biobanks. We tested whether rare pLOF variants in these 13 genes were associated with severe COVID-19. We identified only 1 rare pLOF mutation across these genes among 713 cases with severe COVID-19 and observed no enrichment of pLOFs in severe cases compared to population controls or mild COVID-19 cases. We found no evidence of association of rare LOF variants in the 13 candidate genes with severe COVID-19 outcomes.

ATAV: a comprehensive platform for population-scale genomic analyses.

BACKGROUND: A common approach for sequencing studies is to do joint-calling and store variants of all samples in a single file. If new samples are continually added or controls are re-used for several studies, the cost and time required to perform joint-calling for each analysis can become prohibitive. RESULTS: We present ATAV, an analysis platform for large-scale whole-exome and whole-genome sequencing projects. ATAV stores variant and per site coverage data for all samples in a centralized database, which is efficiently queried by ATAV to support diagnostic analyses for trios and singletons, as well as rare-variant collapsing analyses for finding disease associations in complex diseases. Runtime logs ensure full reproducibility and the modularized ATAV framework makes it extensible to continuous development. Besides helping with the identification of disease-causing variants for a range of diseases, ATAV has also enabled the discovery of disease-genes by rare-variant collapsing on datasets containing more than 20,000 samples. Analyses to date have been performed on data of more than 110,000 individuals demonstrating the scalability of the framework. To allow users to easily access variant-level data directly from the database, we provide a web-based interface, the ATAV data browser ( http://atavdb.org/ ). Through this browser, summary-level data for more than 40,000 samples can be queried by the general public representing a mix of cases and controls of diverse ancestries. Users have access to phenotype categories of variant carriers, as well as predicted ancestry, gender, and quality metrics. In contrast to many other platforms, the data browser is able to show data of newly-added samples in real-time and therefore evolves rapidly as more and more samples are sequenced. CONCLUSIONS: Through ATAV, users have public access to one of the largest variant databases for patients sequenced at a tertiary care center and can look up any genes or variants of interest. Additionally, since the entire code is freely available on GitHub, ATAV can easily be deployed by other groups that wish to build their own platform, database, and user interface.

Erratum: Increased yields of duplex sequencing data by a series of quality control tools.

[This corrects the article DOI: 10.1093/nargab/lqab002.].

Increased yields of duplex sequencing data by a series of quality control tools.

Duplex sequencing is currently the most reliable method to identify ultra-low frequency DNA variants by grouping sequence reads derived from the same DNA molecule into families with information on the forward and reverse strand. However, only a small proportion of reads are assembled into duplex consensus sequences (DCS), and reads with potentially valuable information are discarded at different steps of the bioinformatics pipeline, especially reads without a family. We developed a bioinformatics toolset that analyses the tag and family composition with the purpose to understand data loss and implement modifications to maximize the data output for the variant calling. Specifically, our tools show that tags contain polymerase chain reaction and sequencing errors that contribute to data loss and lower DCS yields. Our tools also identified chimeras, which likely reflect barcode collisions. Finally, we also developed a tool that re-examines variant calls from raw reads and provides different summary data that categorizes the confidence level of a variant call by a tier-based system. With this tool, we can include reads without a family and check the reliability of the call, that increases substantially the sequencing depth for variant calling, a particular important advantage for low-input samples or low-coverage regions.

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.

Causal Genetic Variants in Stillbirth.

BACKGROUND: In the majority of cases, the cause of stillbirth remains unknown despite detailed clinical and laboratory evaluation. Approximately 10 to 20% of stillbirths are attributed to chromosomal abnormalities. However, the causal nature of single-nucleotide variants and small insertions and deletions in exomes has been understudied. METHODS: We generated exome sequencing data for 246 stillborn cases and followed established guidelines to identify causal variants in disease-associated genes. These genes included those that have been associated with stillbirth and strong candidate genes. We also evaluated the contribution of 18,653 genes in case-control analyses stratified according to the degree of depletion of functional variation (described here as "intolerance" to variation). RESULTS: We identified molecular diagnoses in 15 of 246 cases of stillbirth (6.1%) involving seven genes that have been implicated in stillbirth and six disease genes that are good candidates for phenotypic expansion. Among the cases we evaluated, we also found an enrichment of loss-of-function variants in genes that are intolerant to such variation in the human population (odds ratio, 2.15; 95% confidence interval [CI], 1.46 to 3.06). Loss-of-function variants in intolerant genes were concentrated in genes that have not been associated with human disease (odds ratio, 2.22; 95% CI, 1.41 to 3.34), findings that differ from those in two postnatal clinical populations that were also evaluated in this study. CONCLUSIONS: Our findings establish the diagnostic utility of clinical exome sequencing to evaluate the role of small genomic changes in stillbirth. The strength of the novel risk signal (as generated through the stratified analysis) was similar to that in known disease genes, which indicates that the genetic cause of stillbirth remains largely unknown. (Funded by the Institute for Genomic Medicine.).

Rare genetic causes of complex kidney and urological diseases.

Although often considered a single-entity, chronic kidney disease (CKD) comprises many pathophysiologically distinct disorders that result in persistently abnormal kidney structure and/or function, and encompass both monogenic and polygenic aetiologies. Rare inherited forms of CKD frequently span diverse phenotypes, reflecting genetic phenomena including pleiotropy, incomplete penetrance and variable expressivity. Use of chromosomal microarray and massively parallel sequencing technologies has revealed that genomic disorders and monogenic aetiologies contribute meaningfully to seemingly complex forms of CKD across different clinically defined subgroups and are characterized by high genetic and phenotypic heterogeneity. Investigations of prevalent genomic disorders in CKD have integrated genetic, bioinformatic and functional studies to pinpoint the genetic drivers underlying their renal and extra-renal manifestations, revealing both monogenic and polygenic mechanisms. Similarly, massively parallel sequencing-based analyses have identified gene- and allele-level variation that contribute to the clinically diverse phenotypes observed for many monogenic forms of nephropathy. Genome-wide sequencing studies suggest that dual genetic diagnoses are found in at least 5% of patients in whom a genetic cause of disease is identified, highlighting the fact that complex phenotypes can also arise from multilocus variation. A multifaceted approach that incorporates genetic and phenotypic data from large, diverse cohorts will help to elucidate the complex relationships between genotype and phenotype for different forms of CKD, supporting personalized medicine for individuals with kidney disease.

Family reunion via error correction: an efficient analysis of duplex sequencing data.

BACKGROUND: Duplex sequencing is the most accurate approach for identification of sequence variants present at very low frequencies. Its power comes from pooling together multiple descendants of both strands of original DNA molecules, which allows distinguishing true nucleotide substitutions from PCR amplification and sequencing artifacts. This strategy comes at a cost-sequencing the same molecule multiple times increases dynamic range but significantly diminishes coverage, making whole genome duplex sequencing prohibitively expensive. Furthermore, every duplex experiment produces a substantial proportion of singleton reads that cannot be used in the analysis and are thrown away. RESULTS: In this paper we demonstrate that a significant fraction of these reads contains PCR or sequencing errors within duplex tags. Correction of such errors allows "reuniting" these reads with their respective families increasing the output of the method and making it more cost effective. CONCLUSIONS: We combine an error correction strategy with a number of algorithmic improvements in a new version of the duplex analysis software, Du Novo 2.0. It is written in Python, C, AWK, and Bash. It is open source and readily available through Galaxy, Bioconda, and Github: https://github.com/galaxyproject/dunovo.