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Fluoroquinolones are a widely used class of chemotherapeutics within veterinary medicine, prized for their broad-spectrum bactericidal activity. These drugs present a known risk of retinal phototoxicity in domestic cats (Felis catus); therefore, using lower doses and alternative antibiotic classes is encouraged in this species. This adverse drug effect of fluoroquinolones, and enrofloxacin specifically, has been determined to be species-specific in domestic felids. Four feline-specific missense variants in ABCG2 result in four amino acid changes (E159M, S279L, H283Q, and T644I) that are unique to the domestic cat compared with multiple other nonfeline mammalian species. These changes alter the ABCG2 protein involved with the cellular transmembrane transport of drugs, including fluoroquinolones, making the protein functionally defective in domestic cats. The predisposition to fluoroquinolone-mediated phototoxicity in nondomestic felids was explored in this study. At least eight nondomestic felids share the four ABCG2 missense variants with domestic cats, and eleven other felids shared at least three of the four domestic cat variants. Taken together, these results suggest the genetic potential for nondomestic felids to also experience fluoroquinolone-induced retinal phototoxicity; therefore, cautions similar to those for domestic cats should be followed for these drugs in the entire feline taxon.

Interpretation of the colossal number of genetic variants identified from sequencing applications is one of the major bottlenecks in clinical genetics, with the inference of the effect of amino acidsubstituting missense variations on protein structure and function being especially challenging. Here we characterize the three-dimensional (3D) amino acid positions affected in pathogenic and population variants from 1,330 disease-associated genes using over 14,000 experimentally solved human protein structures. By measuring the statistical burden of variations (i.e., point mutations) from all genes on 40 3D protein features, accounting for the structural, chemical, and functional context of the variations’ positions, we identify features that are generally associated with pathogenic and population missense variants. We then perform the same amino acid-level analysis individually for 24 protein functional classes, which reveals unique characteristics of the positions of the altered amino acids: We observe up to 46% divergence of the class-specific features from the general characteristics obtained by the analysis on all genes, which is consistent with the structural diversity of essential regions across different protein classes. We demonstrate that the function-specific 3D features of the variants match the readouts of mutagenesis experiments for BRCA1 and PTEN, and positively correlate with an independent set of clinically interpreted pathogenic and benign missense variants. Finally, we make our results available through a web server to foster accessibility and downstream research. Our findings represent a crucial step toward translational genetics, from highlighting the impact of mutations on protein structure to rationalizing the variants’ pathogenicity in terms of the perturbed molecular mechanisms.

Background Deep mutational scanning (DMS) studies exploit the mutational landscape of sequence variation by systematically and comprehensively assaying the effect of single amino acid variants (SAVs; also referred to as missense mutations, or non-synonymous Single Nucleotide Variants – missense SNVs or nsSNVs) for particular proteins. We assembled SAV annotations from 22 different DMS experiments and normalized the effect scores to evaluate variant effect prediction methods. Three trained on traditional variant effect data (PolyPhen-2, SIFT, SNAP2), a regression method optimized on DMS data (Envision), and a naïve prediction using conservation information from homologs. Results On a set of 32,981 SAVs, all methods captured some aspects of the experimental effect scores, albeit not the same. Traditional methods such as SNAP2 correlated slightly more with measurements and better classified binary states (effect or neutral). Envision appeared to better estimate the precise degree of effect. Most surprising was that the simple naïve conservation approach using PSI-BLAST in many cases outperformed other methods. All methods captured beneficial effects (gain-of-function) significantly worse than deleterious (loss-of-function). For the few proteins with multiple independent experimental measurements, experiments differed substantially, but agreed more with each other than with predictions. Conclusions DMS provides a new powerful experimental means of understanding the dynamics of the protein sequence space. As always, promising new beginnings have to overcome challenges. While our results demonstrated that DMS will be crucial to improve variant effect prediction methods, data diversity hindered simplification and generalization.

Accurate discrimination of benign and pathogenic rare variation remains a priority for clinical genome interpretation. State-of-the-art machine learning variant prioritization tools are imprecise and ignore important parameters defining gene–disease relationships, e.g., distinct consequences of gain-of-function versus loss-of-function variants. We hypothesized that incorporating disease-specific information would improve tool performance. We developed a disease-specific variant classifier, CardioBoost, that estimates the probability of pathogenicity for rare missense variants in inherited cardiomyopathies and arrhythmias. We assessed CardioBoost’s ability to discriminate known pathogenic from benign variants, prioritize disease-associated variants, and stratify patient outcomes. CardioBoost has high global discrimination accuracy (precision recall area under the curve [AUC] 0.91 for cardiomyopathies; 0.96 for arrhythmias), outperforming existing tools (4–24% improvement). CardioBoost obtains excellent accuracy (cardiomyopathies 90.2%; arrhythmias 91.9%) for variants classified with >90% confidence, and increases the proportion of variants classified with high confidence more than twofold compared with existing tools. Variants classified as disease-causing are associated with both disease status and clinical severity, including a 21% increased risk (95% confidence interval [CI] 11–29%) of severe adverse outcomes by age 60 in patients with hypertrophic cardiomyopathy. A disease-specific variant classifier outperforms state-of-the-art genome-wide tools for rare missense variants in inherited cardiac conditions (https://www.cardiodb.org/cardioboost/), highlighting broad opportunities for improved pathogenicity prediction through disease specificity.

Background The use of next-generation sequencing approaches in clinical diagnostics has led to a tremendous increase in data and a vast number of variants of uncertain significance that require interpretation. Therefore, prediction of the effects of missense mutations using in silico tools has become a frequently used approach. Aim of this study was to assess the reliability of in silico prediction as a basis for clinical decision making in the context of hereditary breast and/or ovarian cancer. Methods We tested the performance of four prediction tools (Align-GVGD, SIFT, PolyPhen-2, MutationTaster2) using a set of 236 BRCA1/2 missense variants that had previously been classified by expert committees. However, a major pitfall in the creation of a reliable evaluation set for our purpose is the generally accepted classification of BRCA1/2 missense variants using the multifactorial likelihood model, which is partially based on Align-GVGD results. To overcome this drawback we identified 161 variants whose classification is independent of any previous in silico prediction. In addition to the performance as stand-alone tools we examined the sensitivity, specificity, accuracy and Matthews correlation coefficient (MCC) of combined approaches. Results PolyPhen-2 achieved the lowest sensitivity (0.67), specificity (0.67), accuracy (0.67) and MCC (0.39). Align-GVGD achieved the highest values of specificity (0.92), accuracy (0.92) and MCC (0.73), but was outperformed regarding its sensitivity (0.90) by SIFT (1.00) and MutationTaster2 (1.00). All tools suffered from poor specificities, resulting in an unacceptable proportion of false positive results in a clinical setting. This shortcoming could not be bypassed by combination of these tools. In the best case scenario, 138 families would be affected by the misclassification of neutral variants within the cohort of patients of the German Consortium for Hereditary Breast and Ovarian Cancer. Conclusion We show that due to low specificities state-of-the-art in silico prediction tools are not suitable to predict pathogenicity of variants of uncertain significance in BRCA1/2 . Thus, clinical consequences should never be based solely on in silico forecasts. However, our data suggests that SIFT and MutationTaster2 could be suitable to predict benignity, as both tools did not result in false negative predictions in our analysis.

The indigenous inhabitants of Siberia live in some of the harshest environments on earth, experiencing extended periods of severe cold temperatures, dramatic variation in photoperiod, and limited and highly variable food resources. While the successful long-term settlement of this area by humans required multiple behavioral and cultural innovations, the nature of the underlying genetic changes has generally remained elusive. In this study, we used a three-part approach to identify putative targets of positive natural selection in Siberians. We first performed selection scans on whole exome and genome-wide single nucleotide polymorphism array data from multiple Siberian populations. We then annotated candidates in the tails of the empirical distributions, focusing on candidates with evidence linking them to biological processes and phenotypes previously identified as relevant to adaptation in circumpolar groups. The top candidates were then genotyped in additional populations to determine their spatial allele frequency distributions and associations with climate variables. Our analysis reveals missense mutations in three genes involved in lipid metabolism (PLA2G2A, PLIN1, and ANGPTL8) that exhibit genomic and spatial patterns consistent with selection for cold climate and/or diet. These variants are unified by their connection to brown adipose tissue and may help to explain previously observed physiological differences in Siberians such as low serum lipid levels and increased basal metabolic rate. These results support the hypothesis that indigenous Siberians have genetically adapted to their local environment by selection on multiple genes.

The Z-disc acts as a protein-rich structure to tether thin filament in the contractile units, the sarcomeres, of striated muscle cells. Proteins found in the Z-disc are integral for maintaining the architecture of the sarcomere. They also enable it to function as a (bio-mechanical) signalling hub. Numerous proteins interact in the Z-disc to facilitate force transduction and intracellular signalling in both cardiac and skeletal muscle. This review will focus on six key Z-disc proteins: α-actinin 2, filamin C, myopalladin, myotilin, telethonin and Z-disc alternatively spliced PDZ-motif (ZASP), which have all been linked to myopathies and cardiomyopathies. We will summarise pathogenic variants identified in the six genes coding for these proteins and look at their involvement in myopathy and cardiomyopathy. Listing the Minor Allele Frequency (MAF) of these variants in the Genome Aggregation Database (GnomAD) version 3.1 will help to critically re-evaluate pathogenicity based on variant frequency in normal population cohorts.

Most classical aniridia is caused by PAX6 haploinsufficiency. PAX6 missense variants can be hypomorphic or mimic haploinsufficiency. We hypothesized that missense variants also cause previously undescribed disease by altering the affinity and/or specificity of PAX6 genomic interactions. We screened PAX6 in 372 individuals with bilateral microphthalmia, anophthalmia, or coloboma (MAC) from the Medical Research Council Human Genetics Unit eye malformation cohort (HGUeye) and reviewed data from the Deciphering Developmental Disorders study. We performed cluster analysis on PAX6-associated ocular phenotypes by variant type and molecular modeling of the structural impact of 86 different PAX6 causative missense variants. Eight different PAX6 missense variants were identified in 17 individuals (15 families) with MAC, accounting for 4% (15/372) of our cohort. Seven altered the paired domain (p.[Arg26Gln]x1, p.[Gly36Val]x1, p.[Arg38Trp]x2, p.[Arg38Gln]x1, p.[Gly51Arg]x2, p.[Ser54Arg]x2, p.[Asn124Lys]x5) and one the homeodomain (p.[Asn260Tyr]x1). p.Ser54Arg and p.Asn124Lys were exclusively associated with severe bilateral microphthalmia. MAC-associated variants were predicted to alter but not ablate DNA interaction, consistent with the electrophoretic mobility shifts observed using mutant paired domains with well-characterized PAX6-binding sites. We found no strong evidence for novel PAX6-associated extraocular disease. Altering the affinity and specificity of PAX6-binding genome-wide provides a plausible mechanism for the worse-than-null effects of MAC-associated missense variants.

Hereditary spastic paraplegia (HSP) is a heterogeneous group of neurological disorders that are characterized by progressive spasticity and weakness in the lower limbs. SPG26 is a complicated form of HSP, which includes not only weakness in the lower limbs, but also cognitive impairment, developmental delay, cerebellar ataxia, dysarthria, and peripheral neuropathy, and is caused by biallelic mutations in the B4GALNT1 (beta-1,4- N -acetylgalactosaminyltransferase 1) gene. The B4GALNT1 gene encodes ganglioside GM2/GD2 synthase (GM2S), which catalyzes the transfer of N -acetylgalactosamine to lactosylceramide, GM3, and GD3 to generate GA2, GM2, and GD2, respectively. The present study attempted to characterize a novel B4GALNT1 variant (NM_001478.5:c.937G>A p.Asp313Asn) detected in a patient with progressive multi-system neurodegeneration as well as deleterious variants found in the general population in Japan. Peripheral blood T cells from our patient lacked the ability for activation-induced ganglioside expression assessed by cell surface cholera toxin binding. Structural predictions suggested that the amino acid substitution, p.Asp313Asn, impaired binding to the donor substrate UDP-GalNAc. An in vitro enzyme assay demonstrated that the variant protein did not exhibit GM2S activity, leading to the diagnosis of HSP26. This is the first case diagnosed with SPG26 in Japan. We then extracted 10 novel missense variants of B4GALNT1 from the whole-genome reference panel jMorp (8.3KJPN) of the Tohoku medical megabank organization, which were predicted to be deleterious by Polyphen-2 and SIFT programs. We performed a functional evaluation of these variants and demonstrated that many showed perturbed subcellular localization. Five of these variants exhibited no or significantly decreased GM2S activity with less than 10% activity of the wild-type protein, indicating that they are carrier variants for HSP26. These results provide the basis for molecular analyses of B4GALNT1 variants present in the Japanese population and will help improve the molecular diagnosis of patients suspected of having HSP.

Background A20 haploinsufficiency (HA20) is an early-onset autoinflammatory disease caused by mutations in the TNFAIP3 gene, which encodes the protein A20. Numerous truncating mutations in the TNFAIP3 gene have been reported in HA20 patients, whereas fewer missense variants have had their pathogenicity confirmed. Here, we evaluated the pathogenic significance of three previously unreported missense variants of the TNFAIP3 gene in suspected cases of HA20. Methods We obtained the clinical features and immunological data of three patients with missense variants (Glu192Lys, Ile310Thr, and Gln709Arg) of unknown significance of TNFAIP3 . We then performed in vitro functional assays including analysis of nuclear factor (NF)-κB reporter gene activity, detection of A20 expression and phosphorylation of A20 by IκB kinase β (IKKβ), and K63-deubiquitination assay using TNFAIP3 -deficient HEK293 cells. Three known pathogenic missense mutations reported previously were also investigated. Results The inhibitory effect on NF-κB reporter gene activity was significantly disrupted by A20 Glu192Lys and the three known mutations. The variants Ile310Thr and Gln709Arg did not show a difference from the wild type in any of the assays performed in this study. Conclusions Among the three variants in the TNFAIP3 gene, Glu192Lys was interpreted as being likely pathogenic, but Ile310Thr and Gln709Arg as being not pathogenic (uncertain significance and likely benign, respectively), based on the American College of Medical Genetics and Genomics standards and guidelines. Our study highlights the necessity of performing in vitro functional assays, notably, NF-κB reporter gene assay, to evaluate the pathogenicity of TNFAIP3 missense variants for the accurate diagnosis of HA20.