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A male factor, commonly associated with poor semen quality, is revealed in about 50% of infertile couples. CFTR gene (Cystic Fibrosis Transmembrane Conduction Regulator) variants are one of the common genetic causes of azoospermia-related male infertility. Notably, the spectrum and frequency of pathogenic CFTR variants vary between populations and geographical regions. In this work, we made an attempt to evaluate the allele frequency (AF) of 12 common CFTR variants in infertile Russian men and healthy individuals from different districts of Russia. Because of the limited number of population-based studies on Russian individuals, we characterized the population AFs based on data from the Registry of Russian cystic fibrosis (CF) patients. In addition to the CF patient registry, we estimated the local frequencies of the same set of variants based on the results of genotyping of CF patients in local biocollections (from St. Petersburg and Yugra regions). AFs of common CFTR variants calculated based on registry and biocollection data showed good concordance with directly measured population AFs. The estimated region-specific frequencies of CFTR variants allowed us to uncover statistically significant regional differences in the frequencies of the F508del (c.1521_1523del; p.Phe508del) and CFTRdele2,3(21kb) (c.54-5940_273+10250del21kb; p.Ser18ArgfsX) variants. The data from population-based studies confirmed previous observations that F508del, CFTRdele2,3(21kb), and L138ins (c.413_415dup; p.Leu138dup)variants are the most abundant among infertile patients, and their frequencies are significantly lower in healthy individuals and should be taken into account during genetic monitoring of the reproductive health of Russian individuals. [ABSTRACT FROM AUTHOR]

Phenotypicheterogeneity is a phenomenon in which distinct phenotypes can develop in individuals bearing pathogenic variants in the same gene. Genetic factors, gene interactions, and environmental factors are usually considered the key mechanisms of this phenomenon. Phenotypic heterogeneity may impact the prognosis of the disease severity and symptoms. In our work, we used publicly available data on the association between genetic variants and Mendelian disease to investigate the genetic factors (such as the intragenic localization and type of a variant) driving the heterogeneity of gene–disease relationships. First, we showed that genes linked to multiple rare diseases (GMDs) are more constrained and tend to encode more transcripts with high levels of expression across tissues. Next, we assessed the role of variant localization and variant types in specifying the exact phenotype for GMD variants. We discovered that none of these factors is sufficient to explain the phenomenon of such heterogeneous gene–disease relationships. In total, we identified only 38 genes with a weak trend towards significant differences in variant localization and 30 genes with nominal significant differences in variant type for the two associated disorders. Remarkably, four of these genes showed significant differences in both tests. At the same time, our analysis suggests that variant localization and type are more important for genes linked to autosomal dominant disease. Taken together, our results emphasize the gene-level factors dissecting distinct Mendelian diseases linked to one common gene based on open-access genetic data and highlight the importance of exploring other factors that contributed to phenotypic heterogeneity. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has drawn the attention of many researchers to the interaction between pathogen and host genomes. Over the last two years, numerous studies have been conducted to identify the genetic risk factors that predict COVID-19 severity and outcome. However, such an analysis might be complicated in cohorts of limited size and/or in case of limited breadth of genome coverage. In this work, we tried to circumvent these challenges by searching for candidate genes and genetic variants associated with a variety of quantitative and binary traits in a cohort of 840 COVID-19 patients from Russia. While we found no gene- or pathway-level associations with the disease severity and outcome, we discovered eleven independent candidate loci associated with quantitative traits in COVID-19 patients. Out of these, the most significant associations correspond to rs1651553 in MYH14p = 1.4 × 10−7), rs11243705 in SETX (p = 8.2 × 10−6), and rs16885 in ATXN1 (p = 1.3 × 10−5). One of the identified variants, rs33985936 in SCN11A, was successfully replicated in an independent study, and three of the variants were found to be associated with blood-related quantitative traits according to the UK Biobank data (rs33985936 in SCN11A, rs16885 in ATXN1, and rs4747194 in CDH23). Moreover, we show that a risk score based on these variants can predict the severity and outcome of hospitalization in our cohort of patients. Given these findings, we believe that our work may serve as proof-of-concept study demonstrating the utility of quantitative traits and extensive phenotyping for identification of genetic risk factors of severe COVID-19. [ABSTRACT FROM AUTHOR]

The present study reports on the frequency and the spectrum of genetic variants causative of monogenic diabetes in Russian children with non-type 1 diabetes mellitus. The present study included 60 unrelated Russian children with non-type 1 diabetes mellitus diagnosed before the age of 18 years. Genetic variants were screened using whole-exome sequencing (WES) in a panel of 35 genes causative of maturity onset diabetes of the young (MODY) and transient or permanent neonatal diabetes. Verification of the WES results was performed using PCR-direct sequencing. A total of 38 genetic variants were identified in 33 out of 60 patients (55%). The majority of patients (27/33, 81.8%) had variants in MODY-related genes: GCK (n=19), HNF1A (n=2), PAX4 (n=1), ABCC8 (n=1), KCNJ11 (n=1), GCK+HNF1A (n=1), GCK+BLK (n=1) and GCK+BLK+WFS1 (n=1). A total of 6 patients (6/33, 18.2%) had variants in MODY-unrelated genes: GATA6 (n=1), WFS1 (n=3), EIF2AK3 (n=1) and SLC19A2 (n=1). A total of 15 out of 38 variants were novel, including GCK, HNF1A, BLK, WFS1, EIF2AK3 and SLC19A2. To summarize, the present study demonstrates a high frequency and a wide spectrum of genetic variants causative of monogenic diabetes in Russian children with non-type 1 diabetes mellitus. The spectrum includes previously known and novel variants in MODY-related and unrelated genes, with multiple variants in a number of patients. The prevalence of GCK variants indicates that diagnostics of monogenic diabetes in Russian children may begin with testing for MODY2. However, the remaining variants are present at low frequencies in 9 different genes, altogether amounting to ~50% of the cases and highlighting the efficiency of using WES in non-GCK-MODY cases. [ABSTRACT FROM AUTHOR]