Identification of deleterious mutations within three human genomes

Machine-learning of complex evolutionary signals improves classification of SNVs

Conservation is a strong predictor for the pathogenicity of single-nucleotide variants (SNVs). However, some positions that present complex conservation patterns across vertebrates stray from this paradigm. Here, we analyzed the association between complex conservation patterns and the pathogenicity of SNVs in the 115 disease-genes that had sufficient variant data. We show that conservation is not a one-rule-fits-all solution since its accuracy highly depends on the analyzed set of species and genes. For example, pairwise comparisons between the human and 99 vertebrate species showed that species differ in their ability to predict the clinical outcomes of variants among different genes using conservation. Furthermore, certain genes were less amenable for conservation-based variant prediction, while others demonstrated species that optimize prediction. These insights led to developing EvoDiagnostics, which uses the conservation against each species as a feature within a random-forest machine-learning classification algorithm. EvoDiagnostics outperformed traditional conservation algorithms, deep-learning based methods and most ensemble tools in every prediction-task, highlighting the strength of optimizing conservation analysis per-species and per-gene. Overall, we suggest a new and a more biologically relevant approach for analyzing conservation, which improves prediction of variant pathogenicity.

A rare genetic variant in the cleavage site of prepro-orexin is associated with idiopathic hypersomnia

Idiopathic hypersomnia (IH) is a rare, heterogeneous sleep disorder characterized by excessive daytime sleepiness. In contrast to narcolepsy type 1, which is a well-defined type of central disorders of hypersomnolence, the etiology of IH is poorly understood. No susceptibility loci associated with IH have been clearly identified, despite the tendency for familial aggregation of IH. We performed a variation screening of the prepro-orexin/hypocretin and orexin receptors genes and an association study for IH in a Japanese population, with replication (598 patients and 9826 controls). We identified a rare missense variant (g.42184347T>C; p.Lys68Arg; rs537376938) in the cleavage site of prepro-orexin that was associated with IH (minor allele frequency of 1.67% in cases versus 0.32% in controls, P = 2.7 × 10-8, odds ratio = 5.36). Two forms of orexin (orexin-A and -B) are generated from cleavage of one precursor peptide, prepro-orexin. The difference in cleavage efficiency between wild-type (Gly-Lys-Arg; GKR) and mutant (Gly-Arg-Arg; GRR) peptides was examined by assays using proprotein convertase subtilisin/kexin (PCSK) type 1 and PCSK type 2. In both PCSK1 and PCSK2 assays, the cleavage efficiency of the mutant peptide was lower than that of the wild-type peptide. We also confirmed that the prepro-orexin peptides themselves transmitted less signaling through orexin receptors than mature orexin-A and orexin-B peptides. These results indicate that a subgroup of IH is associated with decreased orexin signaling, which is believed to be a hallmark of narcolepsy type 1.

The genomic landscape of blood groups in Indigenous Australians in remote communities

Background

Methods and materials

Results

Conclusion

GENESIS: Gene-Specific Machine Learning Models for Variants of Uncertain Significance Found in Catecholaminergic Polymorphic Ventricular Tachycardia and Long QT Syndrome-Associated Genes

BACKGROUND

Cardiac channelopathies such as catecholaminergic polymorphic tachycardia and long QT syndrome predispose patients to fatal arrhythmias and sudden cardiac death. As genetic testing has become common in clinical practice, variants of uncertain significance (VUS) in genes associated with catecholaminergic polymorphic ventricular tachycardia and long QT syndrome are frequently found. The objective of this study was to predict pathogenicity of catecholaminergic polymorphic ventricular tachycardia-associated RYR2 VUS and long QT syndrome-associated VUS in KCNQ1, KCNH2, and SCN5A by developing gene-specific machine learning models and assessing them using cross-validation, cellular electrophysiological data, and clinical correlation.

METHODS

The GENe-specific EnSemble grId Search framework was developed to identify high-performing machine learning models for RYR2, KCNQ1, KCNH2, and SCN5A using variant- and protein-specific inputs. Final models were applied to datasets of VUS identified from ClinVar and exome sequencing. Whole cell patch clamp and clinical correlation of selected VUS was performed.

RESULTS

The GENe-specific EnSemble grId Search models outperformed alternative methods, with area under the receiver operating characteristics up to 0.87, average precisions up to 0.83, and calibration slopes as close to 1.0 (perfect) as 1.04. Blinded voltage-clamp analysis of HEK293T cells expressing 2 predicted pathogenic variants in KCNQ1 each revealed an ≈80% reduction of peak Kv7.1 current compared with WT. Normal Kv7.1 function was observed in KCNQ1-V241I HEK cells as predicted. Though predicted benign, loss of Kv7.1 function was observed for KCNQ1-V106D HEK cells. Clinical correlation of 9/10 variants supported model predictions.

CONCLUSIONS

Gene-specific machine learning models may have a role in post-genetic testing diagnostic analyses by providing high performance prediction of variant pathogenicity.

Update on CD164 and LMX1A genes to strengthen their causative role in autosomal dominant hearing loss

Novel hearing loss (HL) genes are constantly being discovered, and evidence from independent studies is essential to strengthen their position as causes of hereditary HL. To address this issue, we searched our genetic data of families with autosomal dominant HL (ADHL) who had been tested with high-throughput DNA sequencing methods. For CD164, only one pathogenic variant in one family has so far been reported. For LMX1A, just two previous studies have revealed its involvement in ADHL. In this study we found two families with the same pathogenic variant in CD164 and one family with a novel variant in LMX1A (c.686C>A; p.(Ala229Asp)) that impairs its transcriptional activity. Our data show recurrence of the same CD164 variant in two HL families of different geographic origin, which strongly suggests it is a mutational hotspot. We also provide further evidence for haploinsufficiency as the pathogenic mechanism underlying LMX1A-related ADHL.

PirePred: An Accurate Online Consensus Tool to Interpret Newborn Screening-Related Genetic Variants in Structural Context

PirePred is a genetic interpretation tool used for a variety of medical conditions investigated in newborn screening programs. The PirePred server retrieves, analyzes, and displays in real time genetic and structural data on 58 genes/proteins associated with medical conditions frequently investigated in the newborn. PirePred analyzes the predictions generated by 15 pathogenicity predictors and applies an optimized majority vote algorithm to classify any possible nonsynonymous single-nucleotide variant as pathogenic, benign, or of uncertain significance. PirePred predictions for variants of clear clinical significance are better than those of any of the individual predictors considered (based on accuracy, sensitivity, and negative predictive value) or are among the best ones (for positive predictive value and Matthews correlation coefficient). PirePred predictions also outperform the comparable in silico predictions offered as supporting evidence, according to American College of Medical Genetics and Genomics guidelines, by VarSome and Franklin. Also, PirePred has very high prediction coverage. To facilitate the molecular interpretation of the missense, nonsense, and frameshift variants in ClinVar, the changing amino acid residue is displayed in its structural context, which is analyzed to provide functional clues. PirePred is an accurate, robust, and easy-to-use tool for clinicians involved in neonatal screening programs and for researchers of related diseases. The server is freely accessible and provides a user-friendly gateway into the structural/functional consequences of genetic variants at the protein level.

AmazonForest: In Silico Metaprediction of Pathogenic Variants

Simple Summary

ClinVar is a valuable platform that stores a large set of relevant genetic associations with complex phenotypes. However, the functional impact of a partial set of such associations remains misinterpreted, due to the presence of variants with uncertain significance or with conflicting pathogenicity interpretations. To fill this gap, we present AmazonForest: a metaprediction model based on Random Forest for pathogenicity prediction. AmazonForest was used to reclassify a set of ∼101,000 variants that were predicted as having high pathogenic probability. AmazonForest is available as a web tool with a simple web interface, and also as an R object for pathogenicity predictions.

Abstract

ClinVar is a web platform that stores ∼789,000 genetic associations with complex diseases. A partial set of these cataloged genetic associations has challenged clinicians and geneticists, often leading to conflicting interpretations or uncertain clinical impact significance. In this study, we addressed the (re)classification of genetic variants by AmazonForest, which is a random-forest-based pathogenicity metaprediction model that works by combining functional impact data from eight prediction tools. We evaluated the performance of representation learning algorithms such as autoencoders to propose a better strategy. All metaprediction models were trained with ClinVar data, and genetic variants were annotated with eight functional impact predictors cataloged with SnpEff/SnpSift. AmazonForest implements the best random forest model with a one hot data-encoding strategy, which shows an Area Under ROC Curve of ≥0.93. AmazonForest was employed for pathogenicity prediction of a set of ∼101,000 genetic variants of uncertain significance or conflict of interpretation. Our findings revealed ∼24,000 variants with high pathogenic probability (RFprob≥0.9). In addition, we show results for Alzheimer’s Disease as a demonstration of its application in clinical interpretation of genetic variants in complex diseases. Lastly, AmazonForest is available as a web tool and R object that can be loaded to perform pathogenicity predictions.

Genome-wide association studies of metabolites in Finnish men identify disease-relevant loci

Few studies have explored the impact of rare variants (minor allele frequency < 1%) on highly heritable plasma metabolites identified in metabolomic screens. The Finnish population provides an ideal opportunity for such explorations, given the multiple bottlenecks and expansions that have shaped its history, and the enrichment for many otherwise rare alleles that has resulted. Here, we report genetic associations for 1391 plasma metabolites in 6136 men from the late-settlement region of Finland. We identify 303 novel association signals, more than one third at variants rare or enriched in Finns. Many of these signals identify genes not previously implicated in metabolite genome-wide association studies and suggest mechanisms for diseases and disease-related traits.

KNa1.1 gain-of-function preferentially dampens excitability of murine parvalbumin-positive interneurons

KCNT1 encodes the sodium-activated potassium channel K_Na1.1, expressed preferentially in the frontal cortex, hippocampus, cerebellum, and brainstem. Pathogenic missense variants in KCNT1 are associated with intractable epilepsy, namely epilepsy of infancy with migrating focal seizures (EIMFS), and sleep-related hypermotor epilepsy (SHE). In vitro studies of pathogenic KCNT1 variants support predominantly a gain-of-function molecular mechanism, yet how these variants behave in a neuron or ultimately drive formation of an epileptogenic circuit is an important and timely question. Using CRISPR/Cas9 gene editing, we introduced a gain-of-function variant into the endogenous mouse Kcnt1 gene. Compared to wild-type (WT) littermates, heterozygous and homozygous knock-in mice displayed greater seizure susceptibility to the chemoconvulsants kainate and pentylenetetrazole (PTZ), but not to flurothyl. Using acute slice electrophysiology in heterozygous and homozygous Kcnt1 knock-in and WT littermates, we demonstrated that CA1 hippocampal pyramidal neurons exhibit greater amplitude of miniature inhibitory postsynaptic currents in mutant mice with no difference in frequency, suggesting greater inhibitory tone associated with the Kcnt1 mutation. To address alterations in GABAergic signaling, we bred Kcnt1 knock-in mice to a parvalbumin-tdTomato reporter line, and found that parvalbumin-expressing (PV+) interneurons failed to fire repetitively with large amplitude current injections and were more prone to depolarization block. These alterations in firing can be recapitulated by direct application of the K_Na1.1 channel activator loxapine in WT but are occluded in knock-in littermates, supporting a direct channel gain-of-function mechanism. Taken together, these results suggest that K_Na1.1 gain-of-function dampens interneuron excitability to a greater extent than it impacts pyramidal neuron excitability, driving seizure susceptibility in a mouse model of KCNT1-associated epilepsy.

A CTNNB1-altered medulloblastoma shows the immunophenotypic, DNA methylation, and transcriptomic profiles of SHH-activated, and not WNT-activated, medulloblastoma

Recent advancement in molecular characterisation has identified four principal molecular groups of medulloblastoma (MB), namely WNT, SHH, group 3, and group 4, and each has its characteristic clinical features, predilection for specific anatomic sites, signature genetic alterations, and distinct DNA methylome profiles [1]. Immunophenotypically, MB can be divided into WNT, SHH, and non-WNT/non-SHH groups by their expression of YAP1 and GAB1-WNT MB expresses YAP1, in addition to its characteristic nuclear b-catenin positivity, and SHH MB expresses both. In contrast, non-WNT/non-SHH MB is negative for both [2]. Thus far, CTNNB1 mutations have been considered pathognomonic of WNT MB. Furthermore, it has been shown that CTNNB1 mutations dominantly drive the WNT-activated phenotype in MB, even in the presence of alterations in the SHH pathway [3, 4].

Machine learning methods for prediction of cancer driver genes: a survey paper

Identifying the genes and mutations that drive the emergence of tumors is a critical step to improving our understanding of cancer and identifying new directions for disease diagnosis and treatment. Despite the large volume of genomics data, the precise detection of driver mutations and their carrying genes, known as cancer driver genes, from the millions of possible somatic mutations remains a challenge. Computational methods play an increasingly important role in discovering genomic patterns associated with cancer drivers and developing predictive models to identify these elements. Machine learning (ML), including deep learning, has been the engine behind many of these efforts and provides excellent opportunities for tackling remaining gaps in the field. Thus, this survey aims to perform a comprehensive analysis of ML-based computational approaches to identify cancer driver mutations and genes, providing an integrated, panoramic view of the broad data and algorithmic landscape within this scientific problem. We discuss how the interactions among data types and ML algorithms have been explored in previous solutions and outline current analytical limitations that deserve further attention from the scientific community. We hope that by helping readers become more familiar with significant developments in the field brought by ML, we may inspire new researchers to address open problems and advance our knowledge towards cancer driver discovery.

Filamin A Is a Potential Driver of Breast Cancer Metastasis via Regulation of MMP-1

Recurrent metastasis is a major fatal cause of breast cancer. Regretfully, the driving force and the molecular beneath have not been fully illustrated yet. In this study, a cohort of breast cancer patients with locoregional metastasis was recruited. For them, we collected the matched samples of the primary tumor and metastatic tumor, and then we determined the mutation profiles with whole-exome sequencing (WES). On basis of the profiles, we identified a list of deleterious variants in eight susceptible genes. Of them, filamin A (FLNA) was considered a potential driver gene of metastasis, and its low expression could enhance 5 years’ relapse survival rate by 15%. To prove the finding, we constructed a stable FLNA knockout tumor cell line, which manifested that the cell abilities of proliferation, migration, and invasion were significantly weakened in response to the gene knockout. Subsequently, xenograft mouse experiments further proved that FLNA knockout could inhibit local or distal metastasis. Putting all the results together, we consolidated that FLNA could be a potential driver gene to metastasis of breast cancer, in particular triple-negative breast cancer. Additional experiments also suggested that FLNA might intervene in metastasis via the regulation of MMP-1 expression. In summary, this study demonstrates that FLNA may play as a positive regulator in cancer proliferation and recurrence. It provides new insight into breast cancer metastasis and suggests a potential new therapeutic target for breast cancer therapy.

Case Report: Next-Generation Sequencing Identified a Novel Pair of Compound-Heterozygous Mutations of LPL Gene Causing Lipoprotein Lipase Deficiency

Lipoprotein lipase deficiency (LPLD) is a rare disease characterized by the accumulation of chylomicronemia with early-onset. Common symptoms are abdominal pain, hepatosplenomegaly, eruptive xanthomas and lipemia retinalis. Serious complications include acute pancreatitis. Gene LPL is one of causative factors of LPLD. Here, we report our experience on an asymptomatic 3.5-month-old Chinese girl with only milky blood. Whole-exome sequencing was performed and identified a pair of compound-heterozygous mutations in LPL gene, c.862G&gt;A (p.A288T) and c.461A&gt;G (p.H154R). Both variants are predicted “deleterious” and classified as “likely pathogenic”. This study expanded the LPL mutation spectrum of disease LPLD, thereby offering exhaustive and valuable experience on early diagnosis and proper medication of LPLD.

Analysis of missense variants in the human genome reveals widespread gene-specific clustering and improves prediction of pathogenicity

We used a machine learning approach to analyze the within-gene distribution of missense variants observed in hereditary conditions and cancer. When applied to 840 genes from the ClinVar database, this approach detected a significant non-random distribution of pathogenic and benign variants in 387 (46%) and 172 (20%) genes, respectively, revealing that variant clustering is widespread across the human exome. This clustering likely occurs as a consequence of mechanisms shaping pathogenicity at the protein level, as illustrated by the overlap of some clusters with known functional domains. We then took advantage of these findings to develop a pathogenicity predictor, MutScore, that integrates qualitative features of DNA substitutions with the new additional information derived from this positional clustering. Using a random forest approach, MutScore was able to identify pathogenic missense mutations with very high accuracy, outperforming existing predictive tools, especially for variants associated with autosomal-dominant disease and cancer. Thus, the within-gene clustering of pathogenic and benign DNA changes is an important and previously underappreciated feature of the human exome, which can be harnessed to improve the prediction of pathogenicity and disambiguation of DNA variants of uncertain significance.

An expanded phenotype centric benchmark of variant prioritisation tools

Identifying the causal variant for diagnosis of genetic diseases is challenging when using next‐generation sequencing approaches and variant prioritization tools can assist in this task. These tools provide in silico predictions of variant pathogenicity, however they are agnostic to the disease under study. We previously performed a disease‐specific benchmark of 24 such tools to assess how they perform in different disease contexts. We found that the tools themselves show large differences in performance, but more importantly that the best tools for variant prioritization are dependent on the disease phenotypes being considered. Here we expand the assessment to 37 tools and refine our assessment by separating performance for nonsynonymous single nucleotide variants (nsSNVs) and missense variants (i.e., excluding nonsense variants). We found differences in performance for missense variants compared to nsSNVs and recommend three tools that stand out in terms of their performance (BayesDel, CADD, and ClinPred).

Identification of ultra-rare disruptive variants in voltage-gated calcium channel-encoding genes in Japanese samples of schizophrenia and autism spectrum disorder

Several large-scale whole-exome sequencing studies in patients with schizophrenia (SCZ) and autism spectrum disorder (ASD) have identified rare variants with modest or strong effect size as genetic risk factors. Dysregulation of cellular calcium homeostasis might be involved in SCZ/ASD pathogenesis, and genes encoding L-type voltage-gated calcium channel (VGCC) subunits Ca_v1.1 (CACNA1S), Ca_v1.2 (CACNA1C), Ca_v1.3 (CACNA1D), and T-type VGCC subunit Ca_v3.3 (CACNA1I) recently were identified as risk loci for psychiatric disorders. We performed a screening study, using the Ion Torrent Personal Genome Machine (PGM), of exon regions of these four candidate genes (CACNA1C, CACNA1D, CACNA1S, CACNA1I) in 370 Japanese patients with SCZ and 192 with ASD. Variant filtering was applied to identify biologically relevant mutations that were not registered in the dbSNP database or that have a minor allele frequency of less than 1% in East-Asian samples from databases; and are potentially disruptive, including nonsense, frameshift, canonical splicing site single nucleotide variants (SNVs), and non-synonymous SNVs predicted as damaging by five different in silico analyses. Each of these filtered mutations were confirmed by Sanger sequencing. If parental samples were available, segregation analysis was employed for measuring the inheritance pattern. Using our filter, we discovered one nonsense SNV (p.C1451* in CACNA1D), one de novo SNV (p.A36V in CACNA1C), one rare short deletion (p.E1675del in CACNA1D), and 14 NSstrict SNVs (non-synonymous SNV predicted as damaging by all of five in silico analyses). Neither p.A36V in CACNA1C nor p.C1451* in CACNA1D were found in 1871 SCZ cases, 380 ASD cases, or 1916 healthy controls in the independent sample set, suggesting that these SNVs might be ultra-rare SNVs in the Japanese population. The neuronal splicing isoform of Ca_v1.2 with the p.A36V mutation, discovered in the present study, showed reduced Ca²⁺-dependent inhibition, resulting in excessive Ca²⁺ entry through the mutant channel. These results suggested that this de novo SNV in CACNA1C might predispose to SCZ by affecting Ca²⁺ homeostasis. Thus, our analysis successfully identified several ultra-rare and potentially disruptive gene variants, lending partial support to the hypothesis that VGCC-encoding genes may contribute to the risk of SCZ/ASD.

Two rare variants reveal the significance of Grainyhead‐like 3 Arginine 391 underlying non‐syndromic cleft palate only

OBJECTIVES

Non-syndromic cleft palate only (NSCPO) is one of the most common craniofacial birth defects with largely undetermined genetic etiology. It has been established that Grainyhead-like 3 (GRHL3) plays an essential role in the pathogenesis of NSCPO. This study aimed to identify and verify the first-reported GRHL3 variant underlying NSCPO among the Chinese cohort.

METHODS

We performed whole-exome sequencing (WES) on a Chinese NSCPO patient and identified a rare variant of GRHL3 (p.Arg391His). A validated deleterious variant p.Arg391Cys was introduced as a positive control. Zebrafish embryos injection, reporter assays, live-cell imaging, and RNA sequencing were conducted to test the pathogenicity of the variants.

RESULTS

Zebrafish embryos microinjection demonstrated that overexpression of the variants could disrupt the normal development of zebrafish embryos. Reporter assays showed that Arg391His disturbed transcriptional activity of GRHL3 and exerted a dominant-negative effect. Interestingly, Arg391His and Arg391Cys displayed distinct nuclear localization patterns from that of wild-type GRHL3 in live-cell imaging. Bulk RNA sequencing suggested that the two variants changed the pattern of gene expression.

CONCLUSIONS

In aggregate, this study identified and characterized a rare GRHL3 variant in NSCPO, revealing the critical role of Arginine 391 in GRHL3. Our findings will help facilitate understanding and genetic counseling of NSCPO.

Comparative genomics and signatures of selection in North Atlantic eels

Comparative genomic approaches can identify putative private and shared signatures of selection. We performed a comparative genomic study of North Atlantic eels, European eel (Anguilla Anguilla) and American eel (A. rostrata). The two sister species are nearly undistinguishable at the phenotypic level and despite a wide non-overlapping continental distribution, they spawn in partial sympatry in the Sargasso Sea. Taking advantage of the newly assembled and annotated genome, we used genome wide RAD sequencing data of 359 individuals retrieved from Sequence Nucleotide Archive and state-of-the-art statistic tests to identify putative genomic signatures of selection in North Atlantic eels. First, using the F_ST and XP-EHH methods, we detected apparent islands of divergence on a total of 7 chromosomes, particularly on chromosomes 6 and 10. Gene ontology analyses suggested candidate genes mainly related to energy production, development and regulation, which could reflect strong selection on traits related to eel migration and larval duration time. Gene effect prediction using SNPeff showed a high number of SNPs in noncoding regions, pointing to a possible regulatory role. Second, using the iHS method we detected shared regions under selection on a total of 11 chromosomes. Several hypotheses might account for the detection of shared islands of selection in North Atlantic eels, including parallel evolution due to adaptation to similar environments and introgression. Future comparative genomic studies will be needed to further clarify the causes and consequences of introgression, including the directionality of these introgression events.

Identifying Actionable Variants Using Capture-Based Targeted Sequencing in 563 Patients With Non-Small Cell Lung Carcinoma

Although the NSCLC diagnostic standards recommend the detection of driver gene mutation, comprehensive genomic profiling has not been used widely in clinical practice. As to the different mutation spectrum characteristics between populations, the research based on Chinese NSCLC cohort is very important for clinical practice. Therefore, we collected 563 surgical specimens from patients with non-small cell lung carcinoma and applied capture-based sequencing using eight-gene panel. We identified 556 variants, with 416 potentially actionable variants in 54.88% (309/563) patients. These single nucleotide variants, insertions and deletions were most commonly found in EGFR (55%), followed by ERBB2 (12%), KRAS (11%), PIK3CA (9%), MET (8%), BRAF (7%), DDR2 (2%), NRAS (0.3%). By using ten protein function prediction algorithms, we also identified 30 novel potentially pathogenic variants. Ninety-eight patients harbored EFGR exon 21 p.L858R mutation and the catalytic domain of the protein tyrosine kinase (PTKc) in EGFR is largely mutated. In addition, there were nine frequent pathogenic variants found in five or more patients. This data provides the potential molecular basis for directing the treatment of lung cancer.

Whole genome sequence analysis of platelet traits in the NHLBI Trans-Omics for Precision Medicine (TOPMed) initiative

Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing (WGS) from NHLBI's Trans-Omics for Precision Medicine initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet-related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several genome-wide association study identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of WGS in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits.

Answer ALS, a large-scale resource for sporadic and familial ALS combining clinical and multi-omics data from induced pluripotent cell lines

Answer ALS is a biological and clinical resource of patient-derived, induced pluripotent stem (iPS) cell lines, multi-omic data derived from iPS neurons and longitudinal clinical and smartphone data from over 1,000 patients with ALS. This resource provides population-level biological and clinical data that may be employed to identify clinical-molecular-biochemical subtypes of amyotrophic lateral sclerosis (ALS). A unique smartphone-based system was employed to collect deep clinical data, including fine motor activity, speech, breathing and linguistics/cognition. The iPS spinal neurons were blood derived from each patient and these cells underwent multi-omic analytics including whole-genome sequencing, RNA transcriptomics, ATAC-sequencing and proteomics. The intent of these data is for the generation of integrated clinical and biological signatures using bioinformatics, statistics and computational biology to establish patterns that may lead to a better understanding of the underlying mechanisms of disease, including subgroup identification. A web portal for open-source sharing of all data was developed for widespread community-based data analytics.

Deleterious Mutations Accumulate Faster in Allopolyploid than Diploid Cotton (Gossypium) and Unequally between Subgenomes

Whole genome duplication (polyploidization) is among the most dramatic mutational processes in nature, so understanding how natural selection differs in polyploids relative to diploids is an important goal. Population genetics theory predicts that recessive deleterious mutations accumulate faster in allopolyploids than diploids due to the masking effect of redundant gene copies, but this prediction is hitherto unconfirmed. Here, we use the cotton genus (Gossypium), which contains seven allopolyploids derived from a single polyploidization event 1-2 million years ago, to investigate deleterious mutation accumulation. We use two methods of identifying deleterious mutations at the nucleotide and amino acid level, along with whole-genome resequencing of 43 individuals spanning six allopolyploid species and their two diploid progenitors, to demonstrate that deleterious mutations accumulate faster in allopolyploids than in their diploid progenitors. We find that, unlike what would be expected under models of demographic changes alone, strongly deleterious mutations show the biggest difference between ploidy levels, and this effect diminishes for moderately and mildly deleterious mutations. We further show that the proportion of nonsynonymous mutations that are deleterious differs between the two co-resident subgenomes in the allopolyploids, suggesting that homoeologous masking acts unequally between subgenomes. Our results provide a genome-wide perspective on classic notions of the significance of gene duplication that likely are broadly applicable to allopolyploids, with implications for our understanding of the evolutionary fate of deleterious mutations. Finally, we note that some measures of selection (e.g. dN/dS, πN/πS) may be biased when species of different ploidy levels are compared.

Potential Involvement of NSD1, KRT24 and ACACA in the Genetic Predisposition to Colorectal Cancer

Simple Summary

Methods used for the identification of hereditary cancer genes have evolved in parallel to technological progress; however, much of the genetic predisposition to cancer remains unexplained. A new in silico method based on Knudson’s two-hit hypothesis recently identified ~50 putative cancer predisposing genes, but their actual association with cancer has not yet been validated. In our study, we aimed to assess the involvement of these genes in familial/early-onset colorectal cancer (CRC) using different lines of evidence. Our results indicated that most of those genes were not associated with a genetic predisposition to CRC, but suggested a possible association for NSD1, KRT24 and ACACA.

Abstract

The ALFRED (Allelic Loss Featuring Rare Damaging) in silico method was developed to identify cancer predisposition genes through the identification of somatic second hits. By applying ALFRED to ~10,000 tumor exomes, 49 candidate genes were identified. We aimed to assess the causal association of the identified genes with colorectal cancer (CRC) predisposition. Of the 49 genes, NSD1, HDAC10, KRT24, ACACA and TP63 were selected based on specific criteria relevant for hereditary CRC genes. Gene sequencing was performed in 736 patients with familial/early onset CRC or polyposis without germline pathogenic variants in known genes. Twelve (predicted) damaging variants in 18 patients were identified. A gene-based burden test in 1596 familial/early-onset CRC patients, 271 polyposis patients, 543 TCGA CRC patients and >134,000 controls (gnomAD, non-cancer), revealed no clear association with CRC for any of the studied genes. Nevertheless, (non-significant) over-representation of disruptive variants in NSD1, KRT24 and ACACA in CRC patients compared to controls was observed. A somatic second hit was identified in one of 20 tumors tested, corresponding to an NSD1 carrier. In conclusion, most genes identified through the ALFRED in silico method were not relevant for CRC predisposition, although a possible association was detected for NSD1, KRT24 and ACACA.

Comparative assessment of genes driving cancer and somatic evolution in non-cancer tissues: an update of the Network of Cancer Genes (NCG) resource

Background

Genetic alterations of somatic cells can drive non-malignant clone formation and promote cancer initiation. However, the link between these processes remains unclear and hampers our understanding of tissue homeostasis and cancer development.

Results

Here, we collect a literature-based repertoire of 3355 well-known or predicted drivers of cancer and non-cancer somatic evolution in 122 cancer types and 12 non-cancer tissues. Mapping the alterations of these genes in 7953 pan-cancer samples reveals that, despite the large size, the known compendium of drivers is still incomplete and biased towards frequently occurring coding mutations. High overlap exists between drivers of cancer and non-cancer somatic evolution, although significant differences emerge in their recurrence. We confirm and expand the unique properties of drivers and identify a core of evolutionarily conserved and essential genes whose germline variation is strongly counter-selected. Somatic alteration in even one of these genes is sufficient to drive clonal expansion but not malignant transformation.

Conclusions

Our study offers a comprehensive overview of our current understanding of the genetic events initiating clone expansion and cancer revealing significant gaps and biases that still need to be addressed. The compendium of cancer and non-cancer somatic drivers, their literature support, and properties are accessible in the Network of Cancer Genes and Healthy Drivers resource at http://www.network-cancer-genes.org/.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02607-z.

Coding and regulatory variants are associated with serum protein levels and disease

Circulating proteins can be used to diagnose and predict disease-related outcomes. A deep serum proteome survey recently revealed close associations between serum protein networks and common disease. In the current study, 54,469 low-frequency and common exome-array variants were compared to 4782 protein measurements in the serum of 5343 individuals from the AGES Reykjavik cohort. This analysis identifies a large number of serum proteins with genetic signatures overlapping those of many diseases. More specifically, using a study-wide significance threshold, we find that 2021 independent exome array variants are associated with serum levels of 1942 proteins. These variants reside in genetic loci shared by hundreds of complex disease traits, highlighting serum proteins' emerging role as biomarkers and potential causative agents of a wide range of diseases.

Preneoplastic somatic mutations including MYD88L265P in lymphoplasmacytic lymphoma

Normal cell counterparts of solid and myeloid tumors accumulate mutations years before disease onset; whether this occurs in B lymphocytes before lymphoma remains uncertain. We sequenced multiple stages of the B lineage in elderly individuals and patients with lymphoplasmacytic lymphoma, a singular disease for studying lymphomagenesis because of the high prevalence of mutated MYD88. We observed similar accumulation of random mutations in B lineages from both cohorts and unexpectedly found MYD88^L265P in normal precursor and mature B lymphocytes from patients with lymphoma. We uncovered genetic and transcriptional pathways driving malignant transformation and leveraged these to model lymphoplasmacytic lymphoma in mice, based on mutated MYD88 in B cell precursors and BCL2 overexpression. Thus, MYD88^L265P is a preneoplastic event, which challenges the current understanding of lymphomagenesis and may have implications for early detection of B cell lymphomas.

Germline sequence variants contributing to cancer susceptibility in South African breast cancer patients of African ancestry

Since the discovery of the breast cancer susceptibility genes, BRCA1 and BRCA2, various other genes conferring an increased risk for breast cancer have been identified. Studies to evaluate sequence variants in cancer predisposition genes among women of African ancestry are limited and mostly focused on BRCA1 and BRCA2. To characterize germline sequence variants in cancer susceptibility genes, we analysed a cohort of 165 South African women of self-identified African ancestry diagnosed with breast cancer, who were unselected for family history of cancer. With the exception of four cases, all others were previously investigated for BRCA1 and BRCA2 deleterious variants, and were negative for pathogenic variants. We utilized the Illumina TruSight cancer panel for targeted sequencing of 94 cancer susceptibility genes. A total of 3.6% of patients carried a pathogenic/likely pathogenic variant in a known breast cancer susceptibility gene: 1.2% in BRCA1, 0.6% in each of BRCA2, ATM, CHEK2 and PALB, none of whom had any family history of breast cancer. The mean age of patients who carried deleterious variant in BRCA1/BRCA2 was 39 years and 8 months compared to 47 years and 3 months among women who carried a deleterious variant in other breast cancer susceptibility genes.

Comprehensive Analysis of Co-Mutations Identifies Cooperating Mechanisms of Tumorigenesis

Somatic mutations are one of the most important factors in tumorigenesis and are the focus of most cancer-sequencing efforts. The co-occurrence of multiple mutations in one tumor has gained increasing attention as a means of identifying cooperating mutations or pathways that contribute to cancer. Using multi-omics, phenotypical, and clinical data from 29,559 cancer subjects and 1747 cancer cell lines covering 78 distinct cancer types, we show that co-mutations are associated with prognosis, drug sensitivity, and disparities in sex, age, and race. Some co-mutation combinations displayed stronger effects than their corresponding single mutations. For example, co-mutation TP53:KRAS in pancreatic adenocarcinoma is significantly associated with disease specific survival (hazard ratio = 2.87, adjusted p-value = 0.0003) and its prognostic predictive power is greater than either TP53 or KRAS as individually mutated genes. Functional analyses revealed that co-mutations with higher prognostic values have higher potential impact and cause greater dysregulation of gene expression. Furthermore, many of the prognostically significant co-mutations caused gains or losses of binding sequences of RNA binding proteins or micro RNAs with known cancer associations. Thus, detailed analyses of co-mutations can identify mechanisms that cooperate in tumorigenesis.

Identification of Missense Extracellular Matrix Gene Variants in a Large Glaucoma Pedigree and Investigation of the N700S Thrombospondin-1 Variant in Normal and Glaucomatous Trabecular Meshwork Cells

PURPOSE

Primary open-angle glaucoma (POAG) is a complex heterogeneous disease. While several POAG genes have been identified, a high proportion of estimated heritability remains unexplained. Elevated intraocular pressure (IOP) is a leading POAG risk factor and dysfunctional extracellular matrix (ECM) in the trabecular meshwork (TM) contributes to elevated IOP. In this study, we sought to identify missense variants in ECM genes that correlate with ocular hypertensive POAG.

METHODS

Whole-genome sequencing was used to identify genetic variants in five members of a large POAG family (n = 68) with elevated IOP. The remaining family members were screened by Sanger sequencing. Unrelated normal (NTM) and glaucomatous (GTM) cells were sequenced for the identified variants. The ECM protein levels were determined by Western immunoblotting and confocal and electron microscopy investigated ECM ultrastructural organization.

RESULTS

Three ECM gene variants were significantly associated with POAG or elevated IOP in a large POAG pedigree. These included rs2228262 (N700S; thrombospondin-1 (THBS1, TSP1)), rs112913396 (D563 G; collagen type VI, alpha 3 (COL6A3)) and rs34759087 (E987K; laminin subunit beta 2 (LAMB2)). Screening of unrelated TM cells (n = 27) showed higher prevalence of the THBS1 variant but not the LAMB2 variant, in GTM cells (39%) than NTM cells (11%). The rare COL6A3 variant was not detected. TSP1 protein was upregulated and COL6A3 was down-regulated in TM cells with N700S subject to mechanical stretch, an in vitro method that mimics elevated IOP. Immunofluorescence showed increased TSP1 immunostaining in cell strains with N700S compared to wild-type TM cells. Ultrastructural studies showed ECM disorganization and altered collagen type VI distribution in GTM versus NTM cells.

CONCLUSIONS

Our results suggest that missense variants in ECM genes may not cause catastrophic changes to the TM, but over many years, subtle changes in ECM may accumulate and cause structural disorganization of the outflow resistance leading to elevated IOP in POAG patients.

Investigation of CACNA1I Cav3.3 Dysfunction in Hemiplegic Migraine

Familial hemiplegic migraine (FHM) is a severe neurogenetic disorder for which three causal genes, CACNA1A, SCN1A, and ATP1A2, have been implicated. However, more than 80% of referred diagnostic cases of hemiplegic migraine (HM) are negative for exonic mutations in these known FHM genes, suggesting the involvement of other genes. Using whole-exome sequencing data from 187 mutation-negative HM cases, we identified rare variants in the CACNA1I gene encoding the T-type calcium channel Cav3.3. Burden testing of CACNA1I variants showed a statistically significant increase in allelic burden in the HM case group compared to gnomAD (OR = 2.30, P = 0.00005) and the UK Biobank (OR = 2.32, P = 0.0004) databases. Dysfunction in T-type calcium channels, including Cav3.3, has been implicated in a range of neurological conditions, suggesting a potential role in HM. Using patch-clamp electrophysiology, we compared the biophysical properties of five Cav3.3 variants (p.R111G, p.M128L, p.D302G, p.R307H, and p.Q1158H) to wild-type (WT) channels expressed in HEK293T cells. We observed numerous functional alterations across the channels with Cav3.3-Q1158H showing the greatest differences compared to WT channels, including reduced current density, right-shifted voltage dependence of activation and inactivation, and slower current kinetics. Interestingly, we also found significant differences in the conductance properties exhibited by the Cav3.3-R307H and -Q1158H variants compared to WT channels under conditions of acidosis and alkalosis. In light of these data, we suggest that rare variants in CACNA1I may contribute to HM etiology.

New mechanistic insights to PLOD1-mediated human vascular disease

Heritable thoracic aortic disease and familial thoracic aortic aneurysm/dissection are important causes of human morbidity/mortality, most without identifiable genetic cause. In a family with familial thoracic aortic aneurysm/dissection, we identified a missense p. (Ser178Arg) variant in PLOD1 segregating with disease, and evaluated PLOD1 enzymatic activity, collagen characteristics and in human aortic vascular smooth muscle cells, studied the effect on function. Comparison with homologous PLOD3 enzyme indicated that the pathogenic variant may affect the N-terminal glycosyltransferase domain, suggesting unprecedented PLOD1 activity. In vitro assays demonstrated that wild-type PLOD1 is capable of processing UDP-glycan donor substrates, and that the variant affects the folding stability of the glycosyltransferase domain and associated enzymatic functions. The PLOD1 substrate lysine was elevated in the proband, however the enzymatic product hydroxylysine and total collagen content was not different, albeit despite collagen fibril narrowing and preservation of collagen turnover. In VSMCs overexpressing wild-type PLOD1, there was upregulation in procollagen gene expression (secretory function) which was attenuated in the variant, consistent with loss-of-function. In comparison, si-PLOD1 cells demonstrated hypercontractility and upregulation of contractile markers, providing evidence for phenotypic switching. Together, the findings suggest that the PLOD1 product is preserved, however newly identified glucosyltransferase activity of PLOD1 appears to be affected by folding stability of the variant, and is associated with compensatory vascular smooth muscle cells phenotypic switching to support collagen production, albeit with less robust fibril girth. Future studies should focus on the impact of PLOD1 folding/variant stability on the tertiary structure of collagen and ECM interactions.

OGDHL Variant rs2293239: A Potential Genetic Driver of Chinese Familial Depressive Disorder

Depressive disorders are a severe psychiatric and social problem that affect more than 4% of the global population. Depressive disorders have explicit hereditary characteristics; however, the precise driving genetic force behind these disorders has not yet been clearly illustrated. In the present study, we recruited a three-generation Chinese pedigree in which 5 of 17 members had long-term depression. We conducted whole-exome sequencing to identify the genetic mutation profiles of the family, and a list of susceptible genetic variations that were highly associated with depression onset was revealed via multiple omics analysis. In particular, a non-synonymous single nucleotide variation in the oxoglutarate dehydrogenase-like (OGDHL) gene, rs2293239 (p.Asn725Ser), was identified as one of the major driving genetic forces for depression onset in the family. This variant causes an important conformational change in the transketolase domain of OGDHL, thus reducing its binding affinity with the cofactor thiamine pyrophosphate and eventually resulting in the abnormal accumulation of glutamate in the brain. Brain imaging analysis further linked the rs2293239 variant with an enlarged amygdala and cerebellum in depressive family members. In summary, the present study enhances the current genetic understanding of depressive disorders. It also provides new options for prioritizing better clinical therapeutic regimens, as well as identifying a new protein target for the design of highly specific drugs to treat depressive disorders.

Evaluation of in silico predictors on short nucleotide variants in HBA1, HBA2, and HBB associated with haemoglobinopathies

Haemoglobinopathies are the commonest monogenic diseases worldwide and are caused by variants in the globin gene clusters. With over 2400 variants detected to date, their interpretation using the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) guidelines is challenging and computational evidence can provide valuable input about their functional annotation. While many in silico predictors have already been developed, their performance varies for different genes and diseases. In this study, we evaluate 31 in silico predictors using a dataset of 1627 variants in HBA1, HBA2, and HBB. By varying the decision threshold for each tool, we analyse their performance (a) as binary classifiers of pathogenicity and (b) by using different non-overlapping pathogenic and benign thresholds for their optimal use in the ACMG/AMP framework. Our results show that CADD, Eigen-PC, and REVEL are the overall top performers, with the former reaching moderate strength level for pathogenic prediction. Eigen-PC and REVEL achieve the highest accuracies for missense variants, while CADD is also a reliable predictor of non-missense variants. Moreover, SpliceAI is the top performing splicing predictor, reaching strong level of evidence, while GERP++ and phyloP are the most accurate conservation tools. This study provides evidence about the optimal use of computational tools in globin gene clusters under the ACMG/AMP framework.

Screening and Functional Analysis of TEK Mutations in Chinese Children With Primary Congenital Glaucoma

Purposes: Recent studies have suggested that loss-of-function mutations of the tunica intima endothelial receptor tyrosine kinase (TEK) are responsible for approximately 5% of primary congenital glaucoma (PCG) cases in diverse populations. However, the causative role of TEK mutations has not been studied in Chinese PCG patients. Here, we report the mutation spectrum of TEK after screening a large cohort of PCG patients of Chinese Han origin and analyze the identified variants in functional assays.

Methods: TEK-targeted next-generation sequencing (NGS) was performed in 200 PCG patients. Candidate variants were prioritized by mutation type and allele frequency in public datasets. Plasmids containing wild type and identified variants of TEK were constructed and used to assess protein expression, solubility, receptor auto-phosphorylation, and response to ligand stimulation in cell-based assays.

Results: Ten missense and one nonsense heterozygous variants were detected by NGS in 11 families. The clinical features of TEK variants carriers were comparable to that of TEK-mutated patients identified in other populations and CYP1B1-mutated individuals from in-house database. Functional analysis confirmed four variants involving evolutionarily conserved residues to be loss-of-function, while one variant (p.R1003H) located in tyrosine kinase domain seemed to be an activating mutation. However, our results did not support the pathogenicity of the other five variants (p.H52R, p.M131I, p.M228V, p.H494Y, and p.L888P).

Conclusion: We provide evidence for TEK variants to be causative in Chinese PCG patients for the first time. Attention needs to be paid to TEK mutations in future genetic testing.

A rare CTSC mutation in Papillon-Lefèvre Syndrome results in abolished serine protease activity and reduced NET formation but otherwise normal neutrophil function

Papillon-Lefèvre Syndrome (PLS) is an autosomal recessive monogenic disease caused by loss-of-function mutations in the CTSC gene, thus preventing the synthesis of the protease Cathepsin C (CTSC) in a proteolytically active form. CTSC is responsible for the activation of the pro-forms of the neutrophil serine proteases (NSPs; Elastase, Proteinase 3 and Cathepsin G), suggesting its involvement in a variety of neutrophil functions. In PLS neutrophils, the lack of CTSC protease activity leads to inactivity of the NSPs. Clinically, PLS is characterized by an early, typically pre-pubertal, onset of severe periodontal pathology and palmoplantar hyperkeratosis. However, PLS is not considered an immune deficiency as patients do not typically suffer from recurrent and severe (bacterial and fungal) infections. In this study we investigated an unusual CTSC mutation in two siblings with PLS, a 503A>G substitution in exon 4 of the CTSC gene, expected to result in an amino acid replacement from tyrosine to cysteine at position 168 of the CTSC protein. Both patients bearing this mutation presented with pronounced periodontal pathology. The characteristics and functions of neutrophils from patients homozygous for the 503A>G CTSC mutation were compared to another previously described PLS mutation (755A>T), and a small cohort of healthy volunteers. Neutrophil lysates from patients with the 503A>G substitution lacked CTSC protein and did not display any CTSC or NSP activity, yet neutrophil counts, morphology, priming, chemotaxis, radical production, and regulation of apoptosis were without any overt signs of alteration. However, NET formation upon PMA-stimulation was found to be severely depressed, but not abolished, in PLS neutrophils.

Integration of Mutational Signature Analysis with 3D Chromatin Data Unveils Differential AID-Related Mutagenesis in Indolent Lymphomas

Activation-induced deaminase (AID) is required for somatic hypermutation in immunoglobulin genes, but also induces off-target mutations. Follicular lymphoma (FL) and chronic lymphocytic leukemia (CLL), the most frequent types of indolent B-cell tumors, are exposed to AID activity during lymphomagenesis. We designed a workflow integrating de novo mutational signatures extraction and fitting of COSMIC (Catalogue Of Somatic Mutations In Cancer) signatures, with tridimensional chromatin conformation data (Hi-C). We applied the workflow to exome sequencing data from lymphoma samples. In 33 FL and 30 CLL samples, 42% and 34% of the contextual mutations could be traced to a known AID motif. We demonstrate that both CLL and FL share mutational processes dominated by spontaneous deamination, failures in DNA repair, and AID activity. The processes had equiproportional distribution across active and nonactive chromatin compartments in CLL. In contrast, canonical AID activity and failures in DNA repair pathways in FL were significantly higher within the active chromatin compartment. Analysis of DNA repair genes revealed a higher prevalence of base excision repair gene mutations (p = 0.02) in FL than CLL. These data indicate that AID activity drives the genetic landscapes of FL and CLL. However, the final result of AID-induced mutagenesis differs between these lymphomas depending on chromatin compartmentalization and mutations in DNA repair pathways.

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons.

Genomic analysis to screen potential genes and mutations in children with non-syndromic early onset severe obesity: a multicentre study in Turkey

BACKGROUND

Obesity is a complex genetic-based pediatric disorder which triggers life-threatening conditions. Therefore, the understanding the molecular mechanisms of obesity has been a significant approach in medicine. Computational methods allow rapid and comprehensive pathway analysis, which is important for generation of diagnosis and treatment of obesity.

METHODS AND RESULTS

Aims of our study are to comprehensively investigate genetic characteristics of obesity in children with non-syndromic, early-onset (< 7 years), and severe obesity (BMI-SDS > 3) through computational approaches. First, the mutational analyses of 41 of obesity-related genes in 126 children with non-syndromic early-onset severe obesity and 76 healthy non-obese controls were performed using the next generation sequencing (NGS) technique, and the NGS data analyzed by using bioinformatics methods. Then, the relationship between pathogenic variants and anthropometric/biochemical parameters was further evaluated. Obtained results demonstrated that the 15 genes (ADIPOQ, ADRB2, ADRB3, IRS1, LEPR, NPY, POMC, PPARG, PPARGC1A, PPARGC1B, PTPN1, SLC22A1, SLC2A4, SREBF1 and UCP1) which directly related to obesity found linked together via biological pathways and/or functions. Among these genes, IRS1, PPARGC1A, and SLC2A4 stand out as the most central ones. Furthermore, 12 of non-synonymous pathogenic variants, including six novels, were detected on ADIPOQ (G90S and D242G), ADRB2 (V87M), PPARGC1A (E680G, A477T, and R656H), UCP1 (Q44R), and IRS1 (R302Q, R301H, R301C, H250P, and H250N) genes.

CONCLUSION

We propose that 12 of non-synonymous pathogenic variations detected on ADIPOQ, ADRB2, PPARGC1A, UCP1, and IRS1 genes might have a cumulative effect on the development and progression of obesity.

Desmoplakin and periplakin genetically and functionally contribute to eosinophilic esophagitis

Eosinophilic esophagitis (EoE) is a chronic allergic inflammatory disease with a complex underlying genetic etiology. Herein, we conduct whole-exome sequencing of a multigeneration EoE pedigree (discovery set) and 61 additional multiplex families with EoE (replication set). A series of rare, heterozygous, missense variants are identified in the genes encoding the desmosome-associated proteins DSP and PPL in 21% of the multiplex families. Esophageal biopsies from patients with these variants retain dilated intercellular spaces and decrease DSP and PPL expression even during disease remission. These variants affect barrier integrity, cell motility and RhoGTPase activity in esophageal epithelial cells and have increased susceptibility to calpain-14-mediated degradation. An acquired loss of esophageal DSP and PPL is present in non-familial EoE. Taken together, herein, we uncover a pathogenic role for desmosomal dysfunction in EoE, providing a deeper mechanistic understanding of tissue-specific allergic responses.

An integrated multi-omic analysis of iPSC-derived motor neurons from C9ORF72 ALS patients

Neurodegenerative diseases are challenging for systems biology because of the lack of reliable animal models or patient samples at early disease stages. Induced pluripotent stem cells (iPSCs) could address these challenges. We investigated DNA, RNA, epigenetics, and proteins in iPSC-derived motor neurons from patients with ALS carrying hexanucleotide expansions in C9ORF72. Using integrative computational methods combining all omics datasets, we identified novel and known dysregulated pathways. We used a C9ORF72 Drosophila model to distinguish pathways contributing to disease phenotypes from compensatory ones and confirmed alterations in some pathways in postmortem spinal cord tissue of patients with ALS. A different differentiation protocol was used to derive a separate set of C9ORF72 and control motor neurons. Many individual -omics differed by protocol, but some core dysregulated pathways were consistent. This strategy of analyzing patient-specific neurons provides disease-related outcomes with small numbers of heterogeneous lines and reduces variation from single-omics to elucidate network-based signatures.

Which Is the Best In Silico Program for the Missense Variations in IDUA Gene? A Comparison of 33 Programs Plus a Conservation Score and Evaluation of 586 Missense Variants

Mucopolysaccharidosis type I (MPS I) is an autosomal recessive disease characterized by the deficiency of alpha-L-iduronidase (IDUA), an enzyme involved in glycosaminoglycan degradation. More than 200 disease-causing variants have been reported and characterized in the IDUA gene. It also has several variants of unknown significance (VUS) and literature conflicting interpretations of pathogenicity. This study evaluated 586 variants obtained from the literature review, five population databases, in addition to dbSNP, Human Genome Mutation Database (HGMD), and ClinVar. For the variants described in the literature, two datasets were created based on the strength of the criteria. The stricter criteria subset had 108 variants with expression study, analysis of healthy controls, and/or complete gene sequence. The less stringent criteria subset had additional 52 variants found in the literature review, HGMD or ClinVar, and dbSNP with an allele frequency higher than 0.001. The other 426 variants were considered VUS. The two strength criteria datasets were used to evaluate 33 programs plus a conservation score. BayesDel (addAF and noAF), PON-P2 (genome and protein), and ClinPred algorithms showed the best sensitivity, specificity, accuracy, and kappa value for both criteria subsets. The VUS were evaluated with these five algorithms. Based on the results, 122 variants had total consensus among the five predictors, with 57 classified as predicted deleterious and 65 as predicted neutral. For variants not included in PON-P2, 88 variants were considered deleterious and 92 neutral by all other predictors. The remaining 124 did not obtain a consensus among predictors.

Gene-level analysis of rare variants in 379,066 whole exome sequences identifies an association of GIGYF1 loss of function with type 2 diabetes

Sequencing of large cohorts offers an unprecedented opportunity to identify rare genetic variants and to find novel contributors to human disease. We used gene-based collapsing tests to identify genes associated with glucose, HbA1c and type 2 diabetes (T2D) diagnosis in 379,066 exome-sequenced participants in the UK Biobank. We identified associations for variants in GCK, HNF1A and PDX1, which are known to be involved in Mendelian forms of diabetes. Notably, we uncovered novel associations for GIGYF1, a gene not previously implicated by human genetics in diabetes. GIGYF1 predicted loss of function (pLOF) variants associated with increased levels of glucose (0.77 mmol/L increase, p = 4.42 × 10^–12) and HbA1c (4.33 mmol/mol, p = 1.28 × 10^–14) as well as T2D diagnosis (OR = 4.15, p = 6.14 × 10^–11). Multiple rare variants contributed to these associations, including singleton variants. GIGYF1 pLOF also associated with decreased cholesterol levels as well as an increased risk of hypothyroidism. The association of GIGYF1 pLOF with T2D diagnosis replicated in an independent cohort from the Geisinger Health System. In addition, a common variant association for glucose and T2D was identified at the GIGYF1 locus. Our results highlight the role of GIGYF1 in regulating insulin signaling and protecting from diabetes.

Impact of Deleterious Mutations on Structure, Function and Stability of Serum/Glucocorticoid Regulated Kinase 1: A Gene to Diseases Correlation

Serum and glucocorticoid-regulated kinase 1 (SGK1) is a Ser/Thr protein kinase involved in regulating cell survival, growth, proliferation, and migration. Its elevated expression and dysfunction are reported in breast, prostate, hepatocellular, lung adenoma, and renal carcinomas. We have analyzed the SGK1 mutations to explore their impact at the sequence and structure level by utilizing state-of-the-art computational approaches. Several pathogenic and destabilizing mutations were identified based on their impact on SGK1 and analyzed in detail. Three amino acid substitutions, K127M, T256A, and Y298A, in the kinase domain of SGK1 were identified and incorporated structurally into original coordinates of SGK1 to explore their time evolution impact using all-atom molecular dynamic (MD) simulations for 200 ns. MD results indicate substantial conformational alterations in SGK1, thus its functional loss, particularly upon T256A mutation. This study provides meaningful insights into SGK1 dysfunction upon mutation, leading to disease progression, including cancer, and neurodegeneration.

Not out of the woods yet: Signatures of the prolonged negative genetic consequences of a population bottleneck in a rapidly re-expanding wader, the black-faced spoonbill Platalea minor

The long-term persistence of a population which has suffered a bottleneck partly depends on how historical demographic dynamics impacted its genetic diversity and the accumulation of deleterious mutations. Here we provide genomic evidence for the genetic effect of a recent population bottleneck in the endangered black-faced spoonbill (Platalea minor) after its rapid population recovery. Our data suggest that the bird's effective population size, N_e , had been relatively stable (7500-9000) since 22,000 years ago; however, a recent brief yet severe bottleneck (N_e  = 20) which we here estimated to occur around the 1940s wiped out >99% of its historical N_e in roughly three generations. Despite a >15-fold population recovery since 1988, we found that black-faced spoonbill population has higher levels of inbreeding (7.4 times more runs of homozygosity) than its sister species, the royal spoonbill (P. regia), which is not thought to have undergone a marked population contraction. Although the two spoonbills have similar levels of genome-wide genetic diversity, our results suggest that selection on more genes was relaxed in the black-faced spoonbill; moreover individual black-faced spoonbills carry more putatively deleterious mutations (Grantham's score > 50), and may therefore express more deleterious phenotypic effects than royal spoonbills. Here we demonstrate the value of using genomic indices to monitor levels of genetic erosion, inbreeding and mutation load in species with conservation concerns. To mitigate the prolonged negative genetic effect of a population bottleneck, we recommend that all possible measures should be employed to maintain population growth of a threatened species.

A novel synonymous ABCA3 variant identified in a Chinese family with lethal neonatal respiratory failure

Background

Lethal respiratory failure is primarily caused by a deficiency of pulmonary surfactant, and is the main cause of neonatal death among preterm infants. Pulmonary surfactant metabolism dysfunction caused by variants in the ABCA3 gene is a rare disease with very poor prognosis. Currently, the mechanisms associated with some ABCA3 variants have been determined, including protein mistrafficking and impaired phospholipid transport. However, some novel variants and their underlying pathogenesis has not been fully elucidated yet. In this study we aimed to identify the genetic features in a family with lethal respiratory failure.

Methods

We studied members of two generations of a Chinese family, including a female proband, her parents, her monozygotic twin sister, and her older sister. Trio whole exome sequencing (WES) were used on the proband and her parents to identify the ABCA3 variants. Sanger sequencing and real-time quantitative polymerase chain reaction (PCR) were used on the monozygotic twin sister of proband to validate the ABCA3 synonymous variant and exon deletion, respectively. The potential pathogenicity of the identified synonymous variant was predicted using the splice site algorithms dbscSNV11_AdaBoost, dbscSNV11_RandomForest, and Human Splicing Finder (HSF).

Results

All patients showed severe respiratory distress, which could not be relieved by mechanical ventilation, supplementation of surfactant, or steroid therapy, and died at an early age. WES analysis revealed that the proband had compound heterozygous ABCA3 variants, including a novel synonymous variant c.G873A (p.Lys291Lys) in exon 8 inherited from the mother, and a heterozygous deletion of exons 4–7 inherited from the father. The synonymous variant was consistently predicted to be a cryptic splice donor site that may lead to aberrant splicing of the pre-mRNA by three different splice site algorithms. The deletion of exons 4–7 of the ABCA3 gene was determined to be a likely pathogenic variant. The variants were confirmed in the monozygotic twin sister of proband by Sanger sequencing and qPCR respectively. The older sister of proband was not available to determine if she also carried both ABCA3 variants, but it is highly likely based on her clinical course.

Conclusions

We identified a novel synonymous variant and a deletion in the ABCA3 gene that may be responsible for the pathogenesis in patients in this family. These results add to the known mutational spectrum of the ABCA3 gene. The study of ABCA3 variants may be helpful for the implementation of patient-specific therapies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-01098-4.

Improved pathogenicity prediction for rare human missense variants

The success of personalized genomic medicine depends on our ability to assess the pathogenicity of rare human variants, including the important class of missense variation. There are many challenges in training accurate computational systems, e.g., in finding the balance between quantity, quality, and bias in the variant sets used as training examples and avoiding predictive features that can accentuate the effects of bias. Here, we describe VARITY, which judiciously exploits a larger reservoir of training examples with uncertain accuracy and representativity. To limit circularity and bias, VARITY excludes features informed by variant annotation and protein identity. To provide a rationale for each prediction, we quantified the contribution of features and feature combinations to the pathogenicity inference of each variant. VARITY outperformed all previous computational methods evaluated, identifying at least 10% more pathogenic variants at thresholds achieving high (90% precision) stringency.

Rare, Damaging DNA Variants in CORIN and Risk of Coronary Artery Disease: Insights From Functional Genomics and Large-Scale Sequencing Analyses

BACKGROUND

Corin is a protease expressed in cardiomyocytes that plays a key role in salt handling and intravascular volume homeostasis via activation of natriuretic peptides. It is unknown if Corin loss-of-function (LOF) is causally associated with risk of coronary artery disease (CAD).

METHODS

We analyzed all coding CORIN variants in an Italian case-control study of CAD. We functionally tested all 64 rare missense mutations in Western Blot and Mass Spectroscopy assays for proatrial natriuretic peptide cleavage. An expanded rare variant association analysis for Corin LOF mutations was conducted in whole exome sequencing data from 37 799 CAD cases and 212 184 controls.

RESULTS

We observed LOF variants in CORIN in 8 of 1803 (0.4%) CAD cases versus 0 of 1725 controls (P, 0.007). Of 64 rare missense variants profiled, 21 (33%) demonstrated <30% of wild-type activity and were deemed damaging in the 2 functional assays for Corin activity. In a rare variant association study that aggregated rare LOF and functionally validated damaging missense variants from the Italian study, we observed no association with CAD-21 of 1803 CAD cases versus 12 of 1725 controls with adjusted odds ratio of 1.61 ([95% CI, 0.79-3.29]; P=0.17). In the expanded sequencing dataset, there was no relationship between rare LOF variants with CAD was also observed (odds ratio, 1.15 [95% CI, 0.89-1.49]; P=0.30). Consistent with the genetic analysis, we observed no relationship between circulating Corin concentrations with incident CAD events among 4744 participants of a prospective cohort study-sex-stratified hazard ratio per SD increment of 0.96 ([95% CI, 0.87-1.07], P=0.48).

CONCLUSIONS

Functional testing of missense mutations improved the accuracy of rare variant association analysis. Despite compelling pathophysiology and a preliminary observation suggesting association, we observed no relationship between rare damaging variants in CORIN or circulating Corin concentrations with risk of CAD.