Publications by authors named "Yury Barbitoff"
Article Synopsis
- Population allele frequency is essential for understanding genetic variants in medicine, and large databases like gnomAD serve as references.
- Variances in rare allele frequencies between populations suggest that local data can be more informative than global averages; many regions, including Russia, lack comprehensive genetic studies.
- The RUSeq project created a large genetic variant reference set from 7,452 exome samples in Moscow and St. Petersburg, revealing significant genetic diversity and identifying notable pathogenic variants specific to Russia.
Article Synopsis
- * A study using ClinVar data found that 5.7% of genetic variants have conflicting interpretations, mainly among variants of uncertain significance (VUS), affecting the diagnosis of rare diseases.
- * The research highlights that genes with high rates of conflicting interpretations are often associated with serious conditions like cardiac disorders and suggests that consistent interpretation rules and better reporting of variant evidence could improve diagnosis accuracy.
Article Synopsis
- Over the past 20 years, genome-wide association studies (GWAS) have explored the genetic basis of complex human traits, but a comprehensive analysis of variant-level properties influencing the replication of these associations has been lacking in biobank studies.
- A comparison of GWAS summary statistics from the UK Biobank and FinnGen identified 37,148 index variants linked to complex traits, with only 9.5% of these variants being shared between the two cohorts; a significant number (9230 loci) did not replicate.
- The study found that non-replicated variants tend to be rarer and exhibit lower effect sizes, while variants identified only in meta-analysis were more common but still had low effects, underscoring the challenges
Article Synopsis
- Yeast have two critical translation termination factors, eRF1 and eRF3, whose mutations lead to the amplification of their mutant alleles, which is vital for cell survival.
- The study used RNA-Seq and proteome analysis to explore how yeast cells adapt to nonsense mutations and found significant gene expression changes affecting the cell cycle.
- The researchers suggest that the adaptation involves a delay in cell cycle progression, particularly at the G2-M transition, resulting in extended S and G2 phases that promote the replication of the mutant alleles.
Article Synopsis
- The study investigates how humans adapt to extreme environmental conditions, focusing on high altitude mountaineers facing low oxygen levels (hypoxia).
- Researchers analyzed the genetic makeup of 22 elite climbers and discovered two significant genetic variants associated with hypoxic adaptation, which may lead to respiratory issues.
- The findings suggest that certain genetic losses in function could play a crucial role in enabling adaptation to harsh conditions, aligning with previous research on human adaptation.
Article Synopsis
- Next-generation sequencing (NGS) has transformed rare disease diagnostics, yet the diagnosis rate is still lower than anticipated despite using whole exome and genome sequencing.
- * Challenges in NGS data analysis include issues with the reference genome quality, coverage bias, and accuracy in detecting variants, especially in complex genomic regions.
- * The paper emphasizes the difficulties in annotating and interpreting genetic variants, particularly for coding and non-coding regions, while pointing towards future research to improve the effectiveness of NGS in diagnosing diseases.*
Article Synopsis
- - Male infertility, particularly linked to poor semen quality, is found in roughly 50% of infertile couples, with specific CFTR gene variants being common causes of azoospermia.
- - This study analyzed the allele frequency of 12 CFTR variants in fertile and infertile men across different regions of Russia, using data from a CF patient registry and local biocollections.
- - Findings revealed significant regional differences in CFTR variant frequencies, confirming that certain variants like F508del and CFTRdele2,3(21kb) are more prevalent in infertile patients compared to healthy individuals, highlighting the need for genetic monitoring in Russian populations.
Article Synopsis
- Recent studies suggest that there may be a connection between lysosomal storage disorders (LSDs) and symptoms of schizophrenia (SCZ), indicating that lysosomal dysfunction could play a role in SCZ development.
- The research involved analyzing lysosomal enzyme activities and alpha-synuclein levels in blood samples from patients with late-onset SCZ and comparing them to patients with Parkinson's disease and healthy controls.
- Significant differences were found, including decreased enzyme activity, higher concentrations of certain lysosphingolipids, and genetic variants linked to LSDs in early-onset SCZ patients, which may contribute to understanding the overlap between these conditions.
Article Synopsis
- Genome-wide association studies (GWAS) help identify genetic factors related to complex human traits and uncover biological processes linked to these traits.* -
- The bioGWAS tool was developed to simulate genotypes, phenotypes, and GWAS summary statistics, making it easier to generate results based on specific genetic variants or pathways.* -
- bioGWAS can recreate complete GWAS datasets and be used to evaluate tools for gene set enrichment analysis, providing valuable resources for improving GWAS data analysis methods.*
Article Synopsis
- Pregnancy loss is a common and devastating complication during pregnancy, with genetic factors playing a significant role, yet over 30% of causes remain unexplained.
- This review synthesizes a decade's worth of research on genetic risk factors for pregnancy loss, identifying 270 genetic variants across 196 unique genes linked to the condition.
- The findings highlight that many of these genes are evolutionarily conserved and involved in essential developmental processes, providing a basis for predicting pregnancy loss risk and guiding future genetic studies.
Article Synopsis
- Type 2 diabetes mellitus (T2D) is a chronic condition marked by insulin resistance and dysfunction of β-cells, leading to various health complications.
- A study analyzed plasma samples from 44 T2D patients and 22 healthy individuals, revealing 229 miRNAs with significant expression differences, including increased levels of miR-5588-5p and decreased levels of miR-496 in T2D patients.
- The researchers also found that obesity affects miRNA expression, specifically miR-144-3p and miR-99a-5p, and identified key pathways related to chromatin modification and apoptosis linked to certain miRNAs.
Article Synopsis
- * Our study analyzed data on genetic variants and Mendelian disease, finding that genes associated with multiple rare diseases are more constrained and usually express more transcripts across various tissues.
- * We found that while variant localization and type affect phenotype, they don't fully explain gene-disease relationships; further research is needed to understand other contributing factors to phenotypic heterogeneity.
Single-cell RNA sequencing (scRNA-seq) is a method that focuses on the analysis of gene expression profile in individual cells. This method has been successfully applied to answer the challenging questions of the pathogenesis of multifactorial diseases and open up new possibilities in the prognosis and prevention of reproductive diseases. In this article, we have reviewed the application of scRNA-seq to the analysis of the various cell types and their gene expression changes in normal pregnancy and pregnancy complications.
View Article and Find Full Text PDFAn increasing number of studies emphasize the role of non-coding variants in the development of hereditary diseases. However, the interpretation of such variants in clinical genetic testing still remains a critical challenge due to poor knowledge of their pathogenicity mechanisms. It was previously shown that variants in 5'-untranslated regions (5'UTRs) can lead to hereditary diseases due to disruption of upstream open reading frames (uORFs).
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- Significant advancements in collecting, storing, and analyzing biological samples have led to the establishment of large biobanks worldwide, some housing over a million samples alongside clinical data.
- Biobanks play a crucial role in medical genetics and genomics by offering allele frequency information and enabling large-scale studies across different ancestries.
- Recently, combining data from multiple biobanks has enhanced research capabilities, allowing for more robust genetic association findings, though researchers must be mindful of certain limitations in this trans-biobank approach.
Complications endangering mother or fetus affect around one in seven pregnant women. Investigation of the genetic susceptibility to such diseases is of high importance for better understanding of the disease biology as well as for prediction of individual risk. In this study, we collected and analyzed GWAS summary statistics from the FinnGen cohort and UK Biobank for 24 pregnancy complications.
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- Yeast serves as a useful model for studying protein aggregation due to its ability to propagate amyloid prions, specifically the prion form of eRF3 (Sup35), which can disrupt translation termination.
- Sup35's N-terminal and middle domains are essential for maintaining its prion properties, and researchers often fuse these proteins to fluorescent markers for detection; however, not all fluorescent proteins are reliable for this purpose.
- The study found that while Sup35NM-mCherry showed diffuse fluorescence and was actively degraded, Sup35NM-TagRFP-T effectively detected prion aggregates, highlighting that the choice of fluorescent tags can significantly impact research outcomes and potentially lead to false negatives in detecting prion-bearing cells.
Article Synopsis
- Metformin is commonly used to treat type 2 diabetes, but individual responses to the drug can vary significantly, potentially due to genetic differences.
- A study analyzed the effects of specific genetic variants on metformin response in 299 patients, identifying the rs12208357 variant as significantly impacting treatment outcomes.
- Machine learning models incorporating genetic and clinical factors, like gender and body measurements, were developed to better predict metformin response, showing potential for personalized diabetes treatment approaches.
Article Synopsis
- Type 2 diabetes (T2D) is influenced by genetics, but traditional methods only partially explain its hereditary factors.
- Advances in genomic sequencing and transcriptomic studies, like RNA-sequencing and single-cell technologies, can help identify new biomarkers for T2D risk and complications.
- The article reviews recent transcriptomic research methods and discoveries related to T2D, while addressing challenges faced in these experiments.
Article Synopsis
- * Over a hundred proteins exhibiting amyloid or amyloid-like properties have been identified, showing a variety of protein structures.
- * The review highlights the different characteristics and forms of amyloid aggregates, explaining their unique properties like stability and interactions with specific dyes, along with their significance for living organisms.
Article Synopsis
- Floating Harbor syndrome (FHS) is a very rare genetic disorder affecting over 100 people globally, caused by mutations in a specific gene, with limited knowledge on its pathogenesis and treatment effectiveness.
- A case study in Russia presented a male with typical symptoms of FHS, such as short stature and intellectual impairment, and demonstrated that growth hormone (GH) therapy led to modest growth improvements before puberty.
- Whole-exome sequencing identified a specific pathogenic mutation linked to FHS and suggested a new model explaining the nature of these mutations, as well as the observed inefficacy of GH treatment in patients with this syndrome.
Although high altitude training has been increasingly popular among endurance athletes, the molecular and cellular bases of this adaptation remain poorly understood. We aimed to define the underlying physiological changes and screen for potential biomarkers of adaptation using transcriptional profiling of whole blood. Seven elite female speed skaters were profiled on the 18th day of high-altitude adaptation.
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- The study investigates the genetic factors influencing COVID-19 severity using a cohort of 840 patients from Russia, aiming to address challenges of cohort size and genome coverage in previous research.
- While no significant gene or pathway-level associations were found, the researchers identified eleven candidate loci linked to various quantitative traits in COVID-19 patients.
- Notably, a risk score derived from certain genetic variants was able to predict hospitalization severity and outcomes, showcasing the potential of using quantitative traits for identifying genetic risk factors in COVID-19 research.
Article Synopsis
- Baker's yeast is used as a model organism to study eukaryotic cell biology and the behavior of prions, which are protein aggregates that can self-replicate.
- Over ten prions have been identified in yeast, and various molecular chaperones influence their propagation in different ways.
- The review highlights the crucial role of Hsp40 proteins in prion propagation, emphasizing the importance of direct interactions between prions and chaperones, as well as the involvement of cell asymmetry, cytoskeleton, and signaling in prion dynamics.
Article Synopsis
- Accurate variant detection in coding regions is crucial for diagnosing Mendelian disorders, and the efficiency of variant discovery from next-generation sequencing (NGS) is impacted by several factors, including software performance and sequencing biases.
- This study evaluated four popular short read aligners and nine variant calling methods using 14 "gold standard" datasets from the Genome In A Bottle consortium, revealing that Bowtie2 fared poorly compared to others.
- Among the variant callers, DeepVariant demonstrated the best performance and robustness, while tools like Clair3, Octopus, and Strelka2 also performed well but were more dependent on the quality of input data.