Arrhythmogenic cardiomyopathy (ACM) is hallmarked by ventricular fibro‐adipogenic alterations, contributing to cardiac dysfunctions and arrhythmias. Although genetically determined (e.g., PKP2 mutations), ACM phenotypes are highly variable. More data on phenotype modulators, clinical prognosticators, and etiological therapies are awaited. We hypothesized that oxidized low‐density lipoprotein (oxLDL)‐dependent activation of PPARγ, a recognized effector of ACM adipogenesis, contributes to disease pathogenesis. ACM patients showing high plasma concentration of oxLDL display severe clinical phenotypes in terms of fat infiltration, ventricular dysfunction, and major arrhythmic event risk. In ACM patient‐derived cardiac cells, we demonstrated that oxLDLs are major cofactors of adipogenesis. Mechanistically, the increased lipid accumulation is mediated by oxLDL cell internalization through CD36, ultimately resulting in PPARγ upregulation. By boosting oxLDL in a Pkp2 heterozygous knock‐out mice through high‐fat diet feeding, we confirmed in vivo the oxidized lipid dependency of cardiac adipogenesis and right ventricle systolic impairment, which are counteracted by atorvastatin treatment. The modulatory role of oxidized lipids on ACM adipogenesis, demonstrated at cellular, mouse, and patient levels, represents a novel risk stratification tool and a target for ACM pharmacological strategies.

Genome-wide association studies have discovered hundreds of associations between common genotypes and kidney function but cannot comprehensively investigate rare coding variants. Here, we apply a genotype imputation approach to whole exome sequencing data from the UK Biobank to increase sample size from 166,891 to 408,511. We detect 158 rare variants and 105 genes significantly associated with one or more of five kidney function traits, including genes not previously linked to kidney disease in humans. The imputation-powered findings derive support from clinical record-based kidney disease information, such as for a previously unreported splice allele in PKD2, and from functional studies of a previously unreported frameshift allele in CLDN10. This cost-efficient approach boosts statistical power to detect and characterize both known and novel disease susceptibility variants and genes, can be generalized to larger future studies, and generates a comprehensive resource (https://ckdgen-ukbb.gm.eurac.edu/) to direct experimental and clinical studies of kidney disease.

Metabolites are intermediates or end products of biochemical processes involved in both health and disease. Here, we take advantage of the well-characterized Cooperative Health Research in South Tyrol (CHRIS) study to perform an exome-wide association study (ExWAS) on absolute concentrations of 175 metabolites in 3294 individuals. To increase power, we imputed the identified variants into an additional 2211 genotyped individuals of CHRIS. In the resulting dataset of 5505 individuals, we identified 85 single-variant genetic associations, of which 39 have not been reported previously. Fifteen associations emerged at ten variants with >5-fold enrichment in CHRIS compared to non-Finnish Europeans reported in the gnomAD database. For example, the CHRIS-enriched ETFDH stop gain variant p.Trp286Ter (rs1235904433-hexanoylcarnitine) and the MCCC2 stop lost variant p.Ter564GlnextTer3 (rs751970792-carnitine) have been found in patients with glutaric acidemia type II and 3-methylcrotonylglycinuria, respectively, but the loci have not been associated with the respective metabolites in a genome-wide association study (GWAS) previously. We further identified three gene-trait associations, where multiple rare variants contribute to the signal. These results not only provide further evidence for previously described associations, but also describe novel genes and mechanisms for diseases and disease-related traits.

Arrhythmogenic cardiomyopathy (ACM) is an inherited genetic disorder, characterized by the substitution of heart muscle with fibro-fatty tissue and severe ventricular arrhythmias, often leading to heart failure and sudden cardiac death. ACM is considered a monogenic disorder, but the low penetrance of mutations identified in patients suggests the involvement of additional genetic or environmental factors. We used whole exome sequencing to investigate digenic inheritance in two ACM families where previous diagnostic tests have revealed a PKP2 mutation in all affected and some healthy individuals. In family members with PKP2 mutations we determined all genes that harbor variants in affected but not in healthy carriers or vice versa. We computationally prioritized the most likely candidates, focusing on known ACM genes and genes related to PKP2 through protein interactions, functional relationships, or shared biological processes. We identified four candidate genes in family 1, namely DAG1, DAB2IP, CTBP2 and TCF25, and eleven candidate genes in family 2. The most promising gene in the second family is TTN, a gene previously associated with ACM, in which the affected individual harbors two rare deleterious-predicted missense variants, one of which is located in the protein’s only serine kinase domain. In this study we report genes that might act as digenic players in ACM pathogenesis, on the basis of co-segregation with PKP2 mutations. Validation in larger cohorts is still required to prove the utility of this model.

Mutations in SZT2 have been previously reported in several cases of early onset epilepsy and intellectual disability. In this study we investigate potential causal mutations in two male siblings affected by early onset epilepsy, intellectual disability and macrocephaly. We use family-based whole-exome sequencing to identify candidate variants. We report the identification of two potential causal SZT2 mutations in compound heterozygous state. We observe considerable differences in the clinical phenotype severity of the two affected individuals. The cerebral MRI revealed no abnormalities in the older affected brother, while in the youngest one it revealed a right frontal polymicrogiria. Moreover, while good seizure control was achieved in the older affected individual the younger brother is affected by pharmacoresistant epilepsy, progressive spastic paraplegia, cortical myoclonus and a more severe intellectual disability. We also analyzed the relative location of the reported pathogenic mutations in the SZT2 protein. Variable phenotypic expressivity is observed for this condition, while the location and type of mutations in SZT2 also has a potential impact on epilepsy severity. These findings extend our knowledge of epileptogenic conditions related to SZT2 and mTOR signaling.

Background Although several methods have been proposed for predicting the effects of genetic variants and their role in disease, it is still a challenge to identify and prioritize pathogenic variants within sequencing studies. Methods Here, we compare different variant and gene-specific features as well as existing methods and investigate their best combination to explore potential performance gains. Results We found that combining the number of “biological process” Gene Ontology annotations of a gene with the methods PON-P2, and PROVEAN significantly improves prediction of pathogenic variants, outperforming all individual methods. A comprehensive analysis of the Gene Ontology feature suggests that it is not a variant-dependent annotation bias but reflects the multifunctional nature of disease genes. Furthermore, we identified a set of difficult variants where different prediction methods fail. Conclusion Existing pathogenicity prediction methods can be further improved.