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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.

Background One of the approaches to detect genetics variants affecting fitness traits is to identify their surrounding genomic signatures of past selection. With established methods for detecting selection signatures and the current and future availability of large datasets, such studies should have the power to not only detect these signatures but also to infer their selective histories. Domesticated animals offer a powerful model for these approaches as they adapted rapidly to environmental and human-mediated constraints in a relatively short time. We investigated this question by studying a large dataset of 542 individuals from 27 domestic sheep populations raised in France, genotyped for more than 500,000 SNPs. Results Population structure analysis revealed that this set of populations harbour a large part of European sheep diversity in a small geographical area, offering a powerful model for the study of adaptation. Identification of extreme SNP and haplotype frequency differences between populations listed 126 genomic regions likely affected by selection. These signatures revealed selection at loci commonly identified as selection targets in many species (“selection hotspots”) including ABCG2 , LCORL / NCAPG , MSTN , and coat colour genes such as ASIP , MC1R , MITF , and TYRP1 . For one of these regions ( ABCG2 , LCORL / NCAPG ), we could propose a historical scenario leading to the introgression of an adaptive allele into a new genetic background. Among selection signatures, we found clear evidence for parallel selection events in different genetic backgrounds, most likely for different mutations. We confirmed this allelic heterogeneity in one case by resequencing the MC1R gene in three black-faced breeds. Conclusions Our study illustrates how dense genetic data in multiple populations allows the deciphering of evolutionary history of populations and of their adaptive mutations.

Background Despite the successes in GWAS, there is still a large gap between the known heritability and the part explained by the SNPs identified by GWAS. Set-based analysis is one of the approaches that has tried to identify associations between multiple variants in a locus a trait, leveraging allelic heterogeneity to increase power in association testing. MARS is a set-based analysis method that integrates likelihood ratio test with a recently developed fine mapping technique to accurately account for causal status of variants in a risk locus. Unfortunately, due to its complex running process, time complexity, and the requirement of high-performance computing resources, it is not widely used. Results To address these issues, we proposed a fully automated web-based analysis service, MARSweb. By providing a web service, we minimized the effort required for initial configuration. Additionally, users can perform analyses by simply uploading their data without needing to familiarize themselves with intricate analysis procedures. Furthermore, it facilitates easier interpretation of results by integrating advanced visualization tools. We confirmed the performance of MARSweb by detecting eGenes and performing pathway analysis of the genes using a Yeast Dataset. Conclusions MARSweb is a web-based analysis service that fully automates set-based analysis. It offers an intuitive user interface, making complex analyses more accessible while significantly reducing processing time for enhanced efficiency. MARSweb is available for use at http://cblab.dongguk.edu/MARSweb and its source code is available at https://github.com/DGU-CBLAB/MARSweb .

To identify bipolar disorder (BD) genetic susceptibility factors, we conducted two genome-wide association (GWA) studies: one involving a sample of individuals of European ancestry (EA; n =1001 cases; n =1033 controls), and one involving a sample of individuals of African ancestry (AA; n =345 cases; n =670 controls). For the EA sample, single-nucleotide polymorphisms (SNPs) with the strongest statistical evidence for association included rs5907577 in an intergenic region at Xq27.1 ( P =1.6 × 10 −6 ) and rs10193871 in NAP5 at 2q21.2 ( P =9.8 × 10 −6 ). For the AA sample, SNPs with the strongest statistical evidence for association included rs2111504 in DPY19L3 at 19q13.11 ( P =1.5 × 10 −6 ) and rs2769605 in NTRK2 at 9q21.33 ( P =4.5 × 10 −5 ). We also investigated whether we could provide support for three regions previously associated with BD, and we showed that the ANK3 region replicates in our sample, along with some support for C15Orf53 ; other evidence implicates BD candidate genes such as SLITRK2 . We also tested the hypothesis that BD susceptibility variants exhibit genetic background-dependent effects. SNPs with the strongest statistical evidence for genetic background effects included rs11208285 in ROR1 at 1p31.3 ( P =1.4 × 10 −6 ), rs4657247 in RGS5 at 1q23.3 ( P =4.1 × 10 −6 ), and rs7078071 in BTBD16 at 10q26.13 ( P =4.5 × 10 −6 ). This study is the first to conduct GWA of BD in individuals of AA and suggests that genetic variations that contribute to BD may vary as a function of ancestry.

Stargardt disease (STGD1), the most common retinal dystrophy caused by pathogenic variants of the biallelic ABCA4 gene, results in irreversible vision loss. This cross-sectional case series study analyzes 18 unrelated Stargardt disease (STGD1) patients from southeast China, examining clinical and genetic features. Ophthalmological assessments included BCVA, ophthalmoscopy, fundus photography, and autofluorescence, with ultra-widefield OCT angiography carried out on one patient. Genetic testing uses targeted exome sequencing for eye disease genes. The mean age of onset was 44.3 years for adult onset (6 patients) and 9.6 years for childhood/adolescent onset (12 patients). The mean logMAR visual acuity was 0.96 (right eye) and 0.91 (left eye). Eight novel ABCA4 variants were found, including two nonsense, two frameshift deletions, one copy number variant, one splice-site alternation, and two deep intronic variants. The genotypes are as follows: 77.8% (14/18) biallelic heterozygous, 16.7% (3/18) homozygous, and one patient with three variants. The study underscores STGD1’s phenotypic and genotypic diversity, expands the ABCA4 mutation spectrum, and offers insights into therapeutic strategies.

Two recent reports have highlighted ANK3 as a susceptibility gene for bipolar disorder (BD). We first reported association between BD and the ANK3 marker rs9804190 in a genome-wide association study (GWAS) of two independent samples (Baum et al. , 2008). Subsequently, a meta-analysis of GWAS data based on samples from the US and the UK reported association with a different ANK3 marker, rs10994336 (Ferreira et al. , 2008). The markers lie about 340 kb apart in the gene. Here, we test both markers in additional samples and characterize the contribution of each marker to BD risk. Our previously reported findings at rs9804190, which had been based on DNA pooling, were confirmed by individual genotyping in the National Institute of Mental Health (NIMH) waves 1–4 ( P =0.05; odds ratio (OR)=1.24) and German ( P =0.0006; OR=1.34) samples. This association was replicated in an independent US sample known as NIMH wave 5 (466 cases, 212 controls; P =0.017; OR=1.38). A random-effects meta-analysis of all three samples was significant ( P =3 × 10 −6 ; OR=1.32), with no heterogeneity. Individual genotyping of rs10994336 revealed a significant association in the German sample ( P =0.0001; OR=1.70), and similar ORs in the NIMH 1–4 and NIMH 5 samples that were not significant at the P <0.05 level. Meta-analysis of all three samples supported an association with rs10994336 ( P =1.7 × 10 −5 ; OR=1.54), again with no heterogeneity. There was little linkage disequilibrium between the two markers. Further analysis suggested that each marker contributed independently to BD, with no significant marker × marker interaction. Our findings strongly support ANK3 as a BD susceptibility gene and suggest true allelic heterogeneity.

Purpose: Newborn screening (NBS) for cystic fibrosis (CF) was implemented throughout France in 2002. It involves a four-tiered procedure: immunoreactive trypsin (IRT)/DNA/IRT/sweat test was implemented throughout France in 2002. The aim of this study was to assess the performance of molecular CFTR gene analysis from the French NBS cohort, to evaluate CF incidence, mutation detection rate, and allelic heterogeneity. Methods: During the 8-year period, 5,947,148 newborns were screened for cystic fibrosis. The data were collected by the Association Française pour le Dépistage et la Prévention des Handicaps de l’Enfant. The mutations identified were classified into four groups based on their potential for causing disease, and a diagnostic algorithm was proposed. Results: Combining the genetic and sweat test results, 1,160 neonates were diagnosed as having cystic fibrosis. The corresponding incidence, including both the meconium ileus (MI) and false-negative cases, was calculated at 1 in 4,726 live births. The CF30 kit, completed with a comprehensive CFTR gene analysis, provides an excellent detection rate of 99.77% for the mutated alleles, enabling the identification of a complete genotype in 99.55% of affected neonates. With more than 200 different mutations characterized, we confirmed the French allelic heterogeneity. Conclusion: The very good sensitivity, specificity, and positive predictive value obtained suggest that the four-tiered IRT/DNA/IRT/sweat test procedure may provide an effective strategy for newborn screening for cystic fibrosis. Genet Med 17 2, 108–116.

Background An alternative approach to investigate associations between genetic variants and disease is to examine deviations from the Hardy–Weinberg equilibrium (HWE) in genotype frequencies within a case population, instead of case–control association analysis. The HWE analysis requires disease cases and demonstrates a notable ability in mapping recessive variants. Allelic heterogeneity is a common phenomenon in diseases. While gene-based case–control association analysis successfully incorporates this heterogeneity, there are no such approaches for HWE analysis. Therefore, we proposed a gene-based HWE test (gene-HWT) by aggregating single-nucleotide polymorphism (SNP)-level HWE test statistics in a gene to address allelic heterogeneity. Results This method used only genotype count data and publicly available linkage disequilibrium information and has a very low computational cost. Extensive simulations demonstrated that gene-HWT effectively controls the type I error at a low significance level and outperforms SNP-level HWE test in power when there are multiple causal variants within a gene. Using gene-HWT, we analyzed genotype count data from a genome-wide association study of six cancer types in Japanese individuals and suggest DGKE and ANO3 as potential germline factors in colorectal cancer. Furthermore, FSTL4 was suggested through a combined analysis across the six cancer types, with particularly notable associations observed in colorectal and prostate cancers. Conclusions These findings indicate the potential of gene-HWT to elucidate the genetic basis of complex diseases, including cancer.

Mutations in the potassium channel gene KCNC3 (Kv3.3) cause the autosomal dominant neurological disease, spinocerebellar ataxia 13 (SCA13). In this study, we expand the genotype-phenotype repertoire of SCA13 by describing the novel KCNC3 deletion p.Pro583_Pro585del highlighting the allelic heterogeneity observed in SCA13 patients. We characterize adult-onset, progressive clinical symptoms of two afflicted kindred and introduce the symptom of profound spasticity not previously associated with the SCA13 phenotype. We also present molecular and electrophysiological characterizations of the mutant protein in mammalian cell culture. Mechanistically, the p.Pro583_Pro585del protein showed normal membrane trafficking with an altered electrophysiological profile, including slower inactivation and decreased sensitivity to the inactivation-accelerating effects of the actin depolymerizer latrunculin B. Taken together, our results highlight the clinical importance of the intracellular C-terminal portion of Kv3.3 and its association with ion channel function.

Background Cystic fibrosis (CF) is a life-threatening disease affecting about 1:3000 newborns in Caucasian populations. The introduction of newborn screening for cystic fibrosis (CF NBS) has improved the clinical outcomes of individuals with CF through early diagnosis and early treatment. NBS strategies have been implemented over time. CF NBS was introduced extensively in 1984 in Tuscany, a region with 3.7 million people, characterized by a high allelic heterogeneity of CFTR gene. Aim and methods The aim of the study is to present the results from 34 years (1984–2018) of CF NBS, retrospectively evaluating the sensitivity, specificity and predictive values of the tests. In particular, we studied the impact of the introduction of DNA molecular analysis in NBS in a region with high allelic heterogeneity, such as Tuscany. Results Over these 34 years, 919,520 neonates were screened, using four different NBS strategies. From 1984 to 1991, CF NBS was performed by the determination of albumin on dried meconium (sensitivity 68.75%; specificity 99.82%). Subsequently, the analysis of immunoreactive trypsinogen on a blood spot was adopted as CF NBS protocol (sensitivity 83.33%; specificity 99.77%). From 1992 to 2010, this strategy was associated with lactase meconium dosage: IRT1/IRT2 + LACT protocol (sensitivity 87.50%; specificity 99.82%). From 2011, when the existing algorithm was integrated by analysis of CF causing variants of the CFTR gene (IRT1/IRT2 + LACT + IRT1/DNA protocol), a substantial improvement in sensitivity was seen (senisitivity 96.15%; specificity 99.75%). Other improved parameters with DNA analysis in the NBS programme, compared with the previous method, were the diagnosis time (52 days vs. 38 days) and the recall rate (0.58 to 0.38%). Conclusion The inclusion of DNA analysis in the NBS was a fundamental step in improving sensitivity, even in a region with high allelic variability.