Analysis of incidental findings in Qatar genome participants reveals novel functional variants in LMNA and DSP

Analysis of 14,392 whole genomes reveals 3.5% of Qataris carry medically actionable variants

Arabic populations are underrepresented in large genome projects; therefore, the frequency of clinically actionable variants among Arabs is largely unknown. Here, we investigated genetic variation in 14,392 whole genomes from the Qatar Genome Program (QGP) across the list of 78 actionable genes (v3.1) determined by the American College of Medical Genetics and Genomics (ACMG). Variants were categorized into one of the following groups: (1) Pathogenic (P), (2) Likely pathogenic (LP), and (3) Rare variants of uncertain significance with evidence of pathogenicity. For the classification, we used variant databases, effect predictors, and the disease-relevant phenotypes available for the cohort. Data on cardiovascular disease, cancer, and hypercholesterolemia allowed us to assess the disease-relevant phenotype association of rare missense variants. We identified 248 distinct variants in 50 ACMG genes that fulfilled our criteria to be included in one of the three groups affecting 1036 genotype-positive participants of the QGP cohort. The most frequent variants were in TTN, followed by RYR1 and ATP7B. The prevalence of reportable secondary findings was 3.5%. A further 46 heterozygous variants in six genes with an autosomal recessive mode of inheritance were detected in 200 individuals, accounting for an additional 1.4%. Altogether, they affect 5% of the population. Due to the high consanguinity rate in the QGP cohort (28% in spouses and 60% in parents), P and LP variants both in genes with dominant and recessive inheritance are important for developing better treatment options and preventive strategies in Qatar and the Arabic population of the Middle East.

Deciphering metabolomics and lipidomics landscape in zebrafish hypertrophic cardiomyopathy model

To elucidate the lipidomic and metabolomic alterations associated with hypertrophic cardiomyopathy (HCM) pathogenesis, we utilized cmybpc3-/- zebrafish model. Fatty acid profiling revealed variability of 10 fatty acids profiles, with heterozygous (HT) and homozygous (HM) groups exhibiting distinct patterns. Hierarchical cluster analysis and multivariate analyses demonstrated a clear separation of HM from HT and control (CO) groups related to cardiac remodeling. Lipidomic profiling identified 257 annotated lipids, with two significantly dysregulated between CO and HT, and 59 between HM and CO. Acylcarnitines and phosphatidylcholines were identified as key contributors to group differentiation, suggesting a shift in energy source. Untargeted metabolomics revealed 110 and 53 significantly dysregulated metabolites. Pathway enrichment analysis highlighted perturbations in multiple metabolic pathways in the HM group, including nicotinate, nicotinamide, purine, glyoxylate, dicarboxylate, glycerophospholipid, pyrimidine, and amino acid metabolism. Our study provides comprehensive insights into the lipidomic and metabolomic unique signatures associated with cmybpc3-/- induced HCM in zebrafish. The identified biomarkers and dysregulated pathways shed light on the metabolic perturbations underlying HCM pathology, offering potential targets for further investigation and potential new therapeutic interventions.

Ratios of Acetaminophen Metabolites Identify New Loci of Pharmacogenetic Relevance in a Genome-Wide Association Study

Genome-wide association studies (GWAS) with non-targeted metabolomics have identified many genetic loci of biomedical interest. However, metabolites with a high degree of missingness, such as drug metabolites and xenobiotics, are often excluded from such studies due to a lack of statistical power and higher uncertainty in their quantification. Here we propose ratios between related drug metabolites as GWAS phenotypes that can drastically increase power to detect genetic associations between pairs of biochemically related molecules. As a proof-of-concept we conducted a GWAS with 520 individuals from the Qatar Biobank for who at least five of the nine available acetaminophen metabolites have been detected. We identified compelling evidence for genetic variance in acetaminophen glucuronidation and methylation by UGT2A15 and COMT, respectively. Based on the metabolite ratio association profiles of these two loci we hypothesized the chemical structure of one of their products or substrates as being 3-methoxyacetaminophen, which we then confirmed experimentally. Taken together, our study suggests a novel approach to analyze metabolites with a high degree of missingness in a GWAS setting with ratios, and it also demonstrates how pharmacological pathways can be mapped out using non-targeted metabolomics measurements in large population-based studies.