CHCHD10S59L/+ mouse model: Behavioral and neuropathological features of frontotemporal dementia.

CHCHD10-related disease causes a spectrum of clinical presentations including mitochondrial myopathy, cardiomyopathy, amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). We generated a knock-in mouse model bearing the p.Ser59Leu (S59L) CHCHD10 variant. Chchd10S59L/+ mice have been shown to phenotypically replicate the disorders observed in patients: myopathy with mtDNA instability, cardiomyopathy and typical ALS features (protein aggregation, neuromuscular junction degeneration and spinal motor neuron loss). Here, we conducted a comprehensive behavioral, electrophysiological and neuropathological assessment of Chchd10S59L/+ mice. These animals show impaired learning and memory capacities with reduced long-term potentiation (LTP) measured at the Perforant Pathway-Dentate Gyrus (PP-DG) synapses. In the hippocampus of Chchd10S59L/+ mice, neuropathological studies show the involvement of protein aggregates, activation of the integrated stress response (ISR) and neuroinflammation in the degenerative process. These findings contribute to decipher mechanisms associated with CHCHD10 variants linking mitochondrial dysfunction and neuronal death. They also validate the Chchd10S59L/+ mice as a relevant model for FTD, which can be used for preclinical studies to test new therapeutic strategies for this devastating disease.

Combining full-length gene assay and SpliceAI to interpret the splicing impact of all possible SPINK1 coding variants.

BACKGROUND: Single-nucleotide variants (SNVs) within gene coding sequences can significantly impact pre-mRNA splicing, bearing profound implications for pathogenic mechanisms and precision medicine. In this study, we aim to harness the well-established full-length gene splicing assay (FLGSA) in conjunction with SpliceAI to prospectively interpret the splicing effects of all potential coding SNVs within the four-exon SPINK1 gene, a gene associated with chronic pancreatitis. RESULTS: Our study began with a retrospective analysis of 27 SPINK1 coding SNVs previously assessed using FLGSA, proceeded with a prospective analysis of 35 new FLGSA-tested SPINK1 coding SNVs, followed by data extrapolation, and ended with further validation. In total, we analyzed 67 SPINK1 coding SNVs, which account for 9.3% of the 720 possible coding SNVs. Among these 67 FLGSA-analyzed SNVs, 12 were found to impact splicing. Through detailed comparison of FLGSA results and SpliceAI predictions, we inferred that the remaining 653 untested coding SNVs in the SPINK1 gene are unlikely to significantly affect splicing. Of the 12 splice-altering events, nine produced both normally spliced and aberrantly spliced transcripts, while the remaining three only generated aberrantly spliced transcripts. These splice-impacting SNVs were found solely in exons 1 and 2, notably at the first and/or last coding nucleotides of these exons. Among the 12 splice-altering events, 11 were missense variants (2.17% of 506 potential missense variants), and one was synonymous (0.61% of 164 potential synonymous variants). Notably, adjusting the SpliceAI cut-off to 0.30 instead of the conventional 0.20 would improve specificity without reducing sensitivity. CONCLUSIONS: By integrating FLGSA with SpliceAI, we have determined that less than 2% (1.67%) of all possible coding SNVs in SPINK1 significantly influence splicing outcomes. Our findings emphasize the critical importance of conducting splicing analysis within the broader genomic sequence context of the study gene and highlight the inherent uncertainties associated with intermediate SpliceAI scores (0.20 to 0.80). This study contributes to the field by being the first to prospectively interpret all potential coding SNVs in a disease-associated gene with a high degree of accuracy, representing a meaningful attempt at shifting from retrospective to prospective variant analysis in the era of exome and genome sequencing.

How local reference panels improve imputation in French populations.

Imputation servers offer the exclusive possibility to harness the largest public reference panels which have been shown to deliver very high precision in the imputation of European genomes. Many studies have nonetheless stressed the importance of 'study specific panels' (SSPs) as an alternative and have shown the benefits of combining public reference panels with SSPs. But such combined approaches are not attainable when using external imputation servers. To investigate how to confront this challenge, we imputed 550 French individuals using either the University of Michigan imputation server with the Haplotype Reference Consortium (HRC) panel or an in-house SSP of 850 whole-genome sequenced French individuals. With approximate geo-localization of both our target and SSP individuals we are able to pinpoint different scenarios where SSP-based imputation would be preferred over server-based imputation or vice-versa. This is achieved by showing to a high degree of resolution the importance of the proximity of the reference panel to target individuals; with a focus on the clear added value of SSPs for estimating haplotype phase and for the imputation of rare variants (minor allele-frequency below 0.01). Such benefits were most evident for individuals from the same geographical regions in France as the SSP individuals. Overall, only 42.3% of all 125,442 variants evaluated were better imputed with an SSP from France compared to an external reference panel, however this rises to 58.1% for individuals from geographic regions well covered by the SSP. By investigating haplotype sharing and population fine-structure in France, we show the importance of including SSP haplotypes for imputation but also that they should ideally be combined with large public panels. In the absence of the unattainable results from a combined panel of the HRC and our French SSP, we put forward a pragmatic solution where server-based and SSP-based imputation outcomes can be combined based on comparing posterior genotype probabilities. We show that such an approach can give a level of imputation accuracy in excess of what could be achieved with either strategy alone. The results presented provide detailed insights into the accuracy of imputation that should be expected from different strategies for European populations.

Mitochondria, a Key Target in Amyotrophic Lateral Sclerosis Pathogenesis.

Mitochondrial dysfunction occurs in numerous neurodegenerative diseases, particularly amyotrophic lateral sclerosis (ALS), where it contributes to motor neuron (MN) death. Of all the factors involved in ALS, mitochondria have been considered as a major player, as secondary mitochondrial dysfunction has been found in various models and patients. Abnormal mitochondrial morphology, defects in mitochondrial dynamics, altered activities of respiratory chain enzymes and increased production of reactive oxygen species have been described. Moreover, the identification of CHCHD10 variants in ALS patients was the first genetic evidence that a mitochondrial defect may be a primary cause of MN damage and directly links mitochondrial dysfunction to the pathogenesis of ALS. In this review, we focus on the role of mitochondria in ALS and highlight the pathogenic variants of ALS genes associated with impaired mitochondrial functions. The multiple pathways demonstrated in ALS pathogenesis suggest that all converge to a common endpoint leading to MN loss. This may explain the disappointing results obtained with treatments targeting a single pathological process. Fighting against mitochondrial dysfunction appears to be a promising avenue for developing combined therapies in the future.

Classification of PRSS1 variants responsible for chronic pancreatitis: An expert perspective from the Franco-Chinese GREPAN study group.

BACKGROUND: PRSS1 was the first reported chronic pancreatitis (CP) gene. The existence of both gain-of-function (GoF) and gain-of-proteotoxicity (GoP) pathological PRSS1 variants, together with the fact that PRSS1 variants have been identified in CP subtypes spanning the range from monogenic to multifactorial, has made the classification of PRSS1 variants very challenging. METHODS: All currently reported PRSS1 variants (derived primarily from two databases) were manually reviewed with respect to their clinical genetics, functional analysis and population allele frequency. They were classified by variant type and pathological mechanism within the framework of our recently proposed ACMG/AMP guidelines-based seven-category system. RESULTS: The total number of distinct germline PRSS1 variants included for analysis was 100, comprising 3 copy number variants (CNVs), 12 5' and 3' variants, 19 intronic variants, 5 nonsense variants, 1 frameshift deletion variant, 6 synonymous variants, 1 in-frame duplication, 3 gene conversions and 50 missense variants. Based upon a combination of clinical genetic and functional analysis, population data and in silico analysis, we classified 26 variants (all 3 CNVs, the in-frame duplication, all 3 gene conversions and 19 missense) as "pathogenic", 3 variants (missense) as "likely pathogenic", 5 variants (four missense and one promoter) as "predisposing", 13 variants (all missense) as "unknown significance", 2 variants (missense) as "likely benign", and all remaining 51 variants as "benign". CONCLUSIONS: We describe an expert classification of the 100 PRSS1 variants reported to date. The results have immediate implications for reclassifying many ClinVar-registered PRSS1 variants as well as providing optimal guidelines/standards for reporting PRSS1 variants.

Ravages: An R package for the simulation and analysis of rare variants in multicategory phenotypes.

Current software packages for the analysis and the simulations of rare variants are only available for binary and continuous traits. Ravages provides solutions in a single R package to perform rare variant association tests for multicategory, binary and continuous phenotypes, to simulate datasets under different scenarios and to compute statistical power. Association tests can be run in the whole genome thanks to C++ implementation of most of the functions, using either RAVA-FIRST, a recently developed strategy to filter and analyse genome-wide rare variants, or user-defined candidate regions. Ravages also includes a simulation module that generates genetic data for cases who can be stratified into several subgroups and for controls. Through comparisons with existing programmes, we show that Ravages complements existing tools and will be useful to study the genetic architecture of complex diseases. Ravages is available on the CRAN at https://cran.r-project.org/web/packages/Ravages/ and maintained on Github at https://github.com/genostats/Ravages.

WGS Revealed Novel BBS5 Pathogenic Variants, Missed by WES, Causing Ciliary Structure and Function Defects.

Bardet-Biedl syndrome (BBS) is an autosomal recessive ciliopathy that affects multiple organs, leading to retinitis pigmentosa, polydactyly, obesity, renal anomalies, cognitive impairment, and hypogonadism. Until now, biallelic pathogenic variants have been identified in at least 24 genes delineating the genetic heterogeneity of BBS. Among those, BBS5 is a minor contributor to the mutation load and is one of the eight subunits forming the BBSome, a protein complex implied in protein trafficking within the cilia. This study reports on a European BBS5 patient with a severe BBS phenotype. Genetic analysis was performed using multiple next-generation sequencing (NGS) tests (targeted exome, TES and whole exome, WES), and biallelic pathogenic variants could only be identified using whole-genome sequencing (WGS), including a previously missed large deletion of the first exons. Despite the absence of family samples, the biallelic status of the variants was confirmed. The BBS5 protein's impact was confirmed on the patient's cells (presence/absence and size of the cilium) and ciliary function (Sonic Hedgehog pathway). This study highlights the importance of WGS and the challenge of reliable structural variant detection in patients' genetic explorations as well as functional tests to assess a variant's pathogenicity.

Opening the Black Box of Imputation Software to Study the Impact of Reference Panel Composition on Performance.

Genotype imputation is widely used to enrich genetic datasets. The operation relies on panels of known reference haplotypes, typically with whole-genome sequencing data. How to choose a reference panel has been widely studied and it is essential to have a panel that is well matched to the individuals who require missing genotype imputation. However, it is broadly accepted that such an imputation panel will have an enhanced performance with the inclusion of diversity (haplotypes from many different populations). We investigate this observation by examining, in fine detail, exactly which reference haplotypes are contributing at different regions of the genome. This is achieved using a novel method of inserting synthetic genetic variation into the reference panel in order to track the performance of leading imputation algorithms. We show that while diversity may globally improve imputation accuracy, there can be occasions where incorrect genotypes are imputed following the inclusion of more diverse haplotypes in the reference panel. We, however, demonstrate a technique for retaining and benefitting from the diversity in the reference panel whilst avoiding the occasional adverse effects on imputation accuracy. What is more, our results more clearly elucidate the role of diversity in a reference panel than has been shown in previous studies.

Heritable defects in telomere and mitotic function selectively predispose to sarcomas.

Cancer genetics has to date focused on epithelial malignancies, identifying multiple histotype-specific pathways underlying cancer susceptibility. Sarcomas are rare malignancies predominantly derived from embryonic mesoderm. To identify pathways specific to mesenchymal cancers, we performed whole-genome germline sequencing on 1644 sporadic cases and 3205 matched healthy elderly controls. Using an extreme phenotype design, a combined rare-variant burden and ontologic analysis identified two sarcoma-specific pathways involved in mitotic and telomere functions. Variants in centrosome genes are linked to malignant peripheral nerve sheath and gastrointestinal stromal tumors, whereas heritable defects in the shelterin complex link susceptibility to sarcoma, melanoma, and thyroid cancers. These studies indicate a specific role for heritable defects in mitotic and telomere biology in risk of sarcomas.

Exome sequencing identifies rare damaging variants in ATP8B4 and ABCA1 as risk factors for Alzheimer's disease.

Alzheimer's disease (AD), the leading cause of dementia, has an estimated heritability of approximately 70%1. The genetic component of AD has been mainly assessed using genome-wide association studies, which do not capture the risk contributed by rare variants2. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals-16,036 AD cases and 16,522 controls. Next to variants in TREM2, SORL1 and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4 and ABCA1 with AD risk, and a suggestive signal in ADAM10. Additionally, the rare-variant burden in RIN3, CLU, ZCWPW1 and ACE highlighted these genes as potential drivers of respective AD-genome-wide association study loci. Variants associated with the strongest effect on AD risk, in particular loss-of-function variants, are enriched in early-onset AD cases. Our results provide additional evidence for a major role for amyloid-ß precursor protein processing, amyloid-ß aggregation, lipid metabolism and microglial function in AD.

Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score.

Rare variant association tests (RVAT) have been developed to study the contribution of rare variants widely accessible through high-throughput sequencing technologies. RVAT require to aggregate rare variants in testing units and to filter variants to retain only the most likely causal ones. In the exome, genes are natural testing units and variants are usually filtered based on their functional consequences. However, when dealing with whole-genome sequence (WGS) data, both steps are challenging. No natural biological unit is available for aggregating rare variants. Sliding windows procedures have been proposed to circumvent this difficulty, however they are blind to biological information and result in a large number of tests. We propose a new strategy to perform RVAT on WGS data: "RAVA-FIRST" (RAre Variant Association using Functionally-InfoRmed STeps) comprising three steps. (1) New testing units are defined genome-wide based on functionally-adjusted Combined Annotation Dependent Depletion (CADD) scores of variants observed in the gnomAD populations, which are referred to as "CADD regions". (2) A region-dependent filtering of rare variants is applied in each CADD region. (3) A functionally-informed burden test is performed with sub-scores computed for each genomic category within each CADD region. Both on simulations and real data, RAVA-FIRST was found to outperform other WGS-based RVAT. Applied to a WGS dataset of venous thromboembolism patients, we identified an intergenic region on chromosome 18 enriched for rare variants in early-onset patients. This region that was missed by standard sliding windows procedures is included in a TAD region that contains a strong candidate gene. RAVA-FIRST enables new investigations of rare non-coding variants in complex diseases, facilitated by its implementation in the R package Ravages.

The False Dawn of Polygenic Risk Scores for Human Disease Prediction.

Polygenic risk scores (PRSs) are being constructed for many diseases and are presented today as a promising avenue in the field of human genetics. These scores aim at predicting the risk of developing a disease by leveraging the many genome-wide association studies (GWAS) conducted during the two last decades. Important investments are being made to improve score estimates by increasing GWAS sample sizes, by developing more sophisticated methods, and by proposing different corrections for potential biases. PRSs have entered the market with direct-to-consumer companies proposing to compute them from saliva samples and even recently to help parents select the healthiest embryos. In this paper, we recall how PRSs arose and question the credit they are given by revisiting underlying assumptions in light of the history of human genetics and by comparing them with estimated breeding values (EBVs) used for selection in livestock.

Expanding ACMG variant classification guidelines into a general framework.

BACKGROUND: The American College of Medical Genetics and Genomics (ACMG)-recommended five variant classification categories (pathogenic, likely pathogenic, uncertain significance, likely benign, and benign) have been widely used in medical genetics. However, these guidelines are fundamentally constrained in practice owing to their focus upon Mendelian disease genes and their dichotomous classification of variants as being either causal or not. Herein, we attempt to expand the ACMG guidelines into a general variant classification framework that takes into account not only the continuum of clinical phenotypes, but also the continuum of the variants' genetic effects, and the different pathological roles of the implicated genes. MAIN BODY: As a disease model, we employed chronic pancreatitis (CP), which manifests clinically as a spectrum from monogenic to multifactorial. Bearing in mind that any general conceptual proposal should be based upon sound data, we focused our analysis on the four most extensively studied CP genes, PRSS1, CFTR, SPINK1 and CTRC. Based upon several cross-gene and cross-variant comparisons, we first assigned the different genes to two distinct categories in terms of disease causation: CP-causing (PRSS1 and SPINK1) and CP-predisposing (CFTR and CTRC). We then employed two new classificatory categories, "predisposing" and "likely predisposing", to replace ACMG's "pathogenic" and "likely pathogenic" categories in the context of CP-predisposing genes, thereby classifying all pathologically relevant variants in these genes as "predisposing". In the case of CP-causing genes, the two new classificatory categories served to extend the five ACMG categories whilst two thresholds (allele frequency and functional) were introduced to discriminate "pathogenic" from "predisposing" variants. CONCLUSION: Employing CP as a disease model, we expand ACMG guidelines into a five-category classification system (predisposing, likely predisposing, uncertain significance, likely benign, and benign) and a seven-category classification system (pathogenic, likely pathogenic, predisposing, likely predisposing, uncertain significance, likely benign, and benign) in the context of disease-predisposing and disease-causing genes, respectively. Taken together, the two systems constitute a general variant classification framework that, in principle, should span the entire spectrum of variants in any disease-related gene. The maximal compliance of our five-category and seven-category classification systems with the ACMG guidelines ought to facilitate their practical application.

Burden of rare variants in arrhythmogenic cardiomyopathy with right dominant form-associated genes provides new insights for molecular diagnosis and clinical management.

Arrhythmogenic cardiomyopathy with right dominant form (ACR) is a rare heritable cardiac cardiomyopathy disorder associated with sudden cardiac death. Pathogenic variants (PVs) in desmosomal genes have been causally related to ACR in 40% of cases. Other genes encoding nondesmosomal proteins have been described in ACR, but their contribution in this pathology is still debated. A panel of 71 genes associated with inherited cardiopathies was screened in an ACR population of 172 probands and 856 individuals from the general population. PVs and uncertain significance variants (VUS) have been identified in 36% and 18.6% of patients, respectively. Among the cardiopathy-associated genes, burden tests show a significant enrichment in PV and VUS only for desmosomal genes PKP2 (plakophilin-2), DSP (desmoplakin), DSC2 (desmocollin-2), and DSG2 (desmoglein-2). Importantly, VUS may account for 15% of ACR cases and should then be considered for molecular diagnosis. Among the other genes, no evidence of enrichment was detected, suggesting an extreme caution in the interpretation of these genetic variations without associated functional or segregation data. Genotype-phenotype correlation points to (1) a more severe and earlier onset of the disease in PV and VUS carriers, underlying the importance to carry out presymptomatic diagnosis in relatives and (2) to a more prevalent left ventricular dysfunction in DSP variant carriers.

CHCHD10 and SLP2 control the stability of the PHB complex: a key factor for motor neuron viability.

CHCHD10 is an amyotrophic lateral sclerosis/frontotemporal dementia gene that encodes a mitochondrial protein whose precise function is unclear. Here we show that Coiled-Coil-Helix-Coiled-Coil-Helix Domain Containing protein 10 interacts with the Stomatin-Like Protein 2 and participates in the stability of the prohibitin complex in the inner mitochondrial membrane. By using patient fibroblasts and mouse models expressing the same CHCHD10 variant (p.Ser59Leu), we show that Stomatin-Like Protein 2 forms aggregates with prohibitins, found in vivo in the hippocampus and as aggresome-like inclusions in spinal motor neurons of Chchd10S59L/+ mice. Affected cells and tissues display instability of the prohibitin complex, which participates at least in part in the activation of the OMA1 cascade with OPA1 processing leading to mitochondrial fragmentation, abnormal mitochondrial cristae morphogenesis and neuronal death found in spinal cord and the hippocampus of Chchd10S59L/+ animals. Destabilization of the prohibitin complex leads to the instability of the mitochondrial contact site and cristae organizing the system complex, probably by the disruption of OPA1-mitofilin interaction. Thus, Stomatin-Like Protein 2/prohibitin aggregates and destabilization of the prohibitin complex are critical in the sequence of events leading to motor neuron death in CHCHD10S59L-related disease.

RAVAQ: An integrative pipeline from quality control to region-based rare variant association analysis.

Next-generation sequencing technologies have opened up the possibility to sequence large samples of cases and controls to test for association with rare variants. To limit cost and increase sample sizes, data from controls could be used in multiple studies and might thus be generated on different sequencing platforms. This could pose some problems of comparability between cases and controls due to batch effects that could be confounding factors, leading to false-positive association signals. To limit batch effects and ensure comparability of datasets, stringent quality controls are required. We propose an integrative five-steps pipeline, RAVAQ, that (a) performs a specific three-step quality control taking into account the case-control status to ensure data comparability, (b) selects qualifying variants as defined by the user, and (c) performs rare variant association tests per genomic region. The RAVAQ pipeline is wrapped in an R package. It is user-friendly and flexible in its arguments to adapt to the specificity of each research project. We provide examples showing how RAVAQ improves rare variant association tests. The default RAVAQ quality control outperformed the widely used Variant Quality Score Recalibration method, removing inflation due to spurious signals. RAVAQ is open source and freely available at https://gitlab.com/gmarenne/ravaq.

Heritability: What's the point? What is it not for? A human genetics perspective.

In this paper, we explain the concept of heritability and describe the different methods and the genotype-phenotype correspondences used to estimate heritability in the specific field of human genetics. Heritability studies are conducted on extremely diverse human traits: quantitative traits (physical, biological, but also cognitive and behavioral measurements) and binary traits (as is the case of most human diseases). Instead of variables such as education and socio-economic status as covariates in genetic studies, they are now the direct object of genetic analysis. We make a review of the different assumptions underlying heritability estimates and dispute the validity of most of them. Moreover, and maybe more importantly, we show that they are very often misinterpreted. These erroneous interpretations lead to a vision of a genetic determinism of human traits. This vision is currently being widely disseminated not only by the mass media and the mainstream press, but also by the scientific press. We caution against the dangerous implication it has both medically and socially. Contrarily to the field of animal and plant genetics for which the polygenic model and the concept of heritability revolutionized selection methods, we explain why it does not provide answer in human genetics.

Functionally deficient TRPV6 variants contribute to hereditary and familial chronic pancreatitis.

The recent discovery of TRPV6 as a pancreatitis susceptibility gene served to identify a novel mechanism of chronic pancreatitis (CP) due to Ca2+ dysregulation. Herein, we analyzed TRPV6 in 81 probands with hereditary CP (HCP), 204 probands with familial CP (FCP), and 462 patients with idiopathic CP (ICP) by targeted next-generation sequencing. We identified 25 rare nonsynonymous TRPV6 variants, 18 of which had not been previously reported. All 18 variants were characterized by a Ca2+ imaging assay, with 8 being identified as functionally deficient. Evaluation of functionally deficient variants in the three CP cohorts revealed two novel findings: (i) functionally deficient TRPV6 variants appear to occur more frequently in HCP/FCP patients than in ICP patients (3.2% vs. 1.5%) and (ii) functionally deficient TRPV6 variants found in HCP and FCP probands appear to be more frequently coinherited with known risk variants in SPINK1, CTRC, and/or CFTR than those found in ICP patients (66.7% vs 28.6%). Additionally, genetic analysis of available HCP and FCP family members revealed complex patterns of inheritance in some families. Our findings confirm that functionally deficient TRPV6 variants represent an important contributor to CP. Importantly, functionally deficient TRPV6 variants account for a significant proportion of cases of HCP/FCP.