Plasma microRNA Profiling in Type 2 Diabetes Mellitus: A Pilot Study.

Type 2 diabetes mellitus (T2D) is a chronic metabolic disease characterized by insulin resistance and ß-cell dysfunction and leading to many micro- and macrovascular complications. In this study we analyzed the circulating miRNA expression profiles in plasma samples from 44 patients with T2D and 22 healthy individuals using next generation sequencing and detected 229 differentially expressed miRNAs. An increased level of miR-5588-5p, miR-125b-2-3p, miR-1284, and a reduced level of miR-496 in T2D patients was verified. We also compared the expression landscapes in the same group of patients depending on body mass index and identified differential expression of miR-144-3p and miR-99a-5p in obese individuals. Identification and functional analysis of putative target genes was performed for miR-5588-5p, miR-125b-2-3p, miR-1284, and miR-496, showing chromatin modifying enzymes and apoptotic genes being among the significantly enriched pathways.

Pharmacogenetics of Type 2 Diabetes-Progress and Prospects.

Type 2 diabetes mellitus (T2D) is a chronic metabolic disease resulting from insulin resistance and progressively reduced insulin secretion, which leads to impaired glucose utilization, dyslipidemia and hyperinsulinemia and progressive pancreatic beta cell dysfunction. The incidence of type 2 diabetes mellitus is increasing worldwide and nowadays T2D already became a global epidemic. The well-known interindividual variability of T2D drug actions such as biguanides, sulfonylureas/meglitinides, DPP-4 inhibitors/GLP1R agonists and SGLT-2 inhibitors may be caused, among other things, by genetic factors. Pharmacogenetic findings may aid in identifying new drug targets and obtaining in-depth knowledge of the causes of disease and its physiological processes, thereby, providing an opportunity to elaborate an algorithm for tailor or precision treatment. The aim of this article is to summarize recent progress and discoveries for T2D pharmacogenetics and to discuss the factors which limit the furthering accumulation of genetic variability knowledge in patient response to therapy that will allow improvement the personalized treatment of T2D.

Case report: Preimplantation genetic testing for infantile GM1 gangliosidosis.

Ganglioside-monosialic acid (GM1) gangliosidosis (ICD-10: E75.1; OMIM: 230500, 230600, 230650) is a rare autosomal recessive hereditary disease, lysosomal storage disorder caused by mutations in the GLB1 gene that lead to the absence or insufficiency of ß-galactosidase. In this study, we report a case of a Russian family with a history of GM1 gangliosidosis. The family had a child who, from the age of 6 months, experienced a gradual loss of developmental skills, marked by muscle flaccidity, psychomotor retardation, hepatosplenomegaly, and the onset of tonic seizures by the age of 8 months. Funduscopic examination revealed a «cherry red spot¼ in the macula, which is crucial for the diagnosis of lipid storage disorders. To find the pathogenic variants responsible for these clinical symptoms, the next-generation sequencing approach was used. The analysis revealed two variants in the heterozygous state: a frameshift variant c.699delG (rs1452318343, ClinVar ID 928700) in exon 6 and a missense variant c.809A>C (rs371546950, ClinVar ID 198727) in exon 8 of the GLB1 gene. The spouses were advised to plan the pregnancy with assisted reproductive technology (ART), followed by preimplantation genetic testing for monogenic disorder (PGT-M) on the embryos. Trophectoderm biopsy was performed on 8 out of 10 resulting embryos at the blastocyst stage. To perform PGT-M, we developed a novel testing system, allowing for direct analysis of disease-causing mutations, as well as haplotype analysis based on the study of polymorphic markers-short tandem repeats (STR), located upstream and downstream of the GLB1 gene. The results showed that four embryos were heterozygous carriers of pathogenic variants in the GLB1 gene (#1, 2, 5, 8). Two embryos had a compound heterozygous genotype (#3, 4), while the embryos #7 and 9 did not carry disease-causing alleles of the GLB1 gene. The embryo #7 without pathogenic variants was transferred after consideration of its morphology and growth rate. Prenatal diagnosis in the first trimester showed the absence of the variants analyzed in the GLB1 gene in the fetus. The pregnancy resulted in the delivery of a female infant who did not inherit the disease-causing variants in the GLB1 gene.

Overview of Transcriptomic Research on Type 2 Diabetes: Challenges and Perspectives.

Type 2 diabetes (T2D) is a common chronic disease whose etiology is known to have a strong genetic component. Standard genetic approaches, although allowing for the detection of a number of gene variants associated with the disease as well as differentially expressed genes, cannot fully explain the hereditary factor in T2D. The explosive growth in the genomic sequencing technologies over the last decades provided an exceptional impetus for transcriptomic studies and new approaches to gene expression measurement, such as RNA-sequencing (RNA-seq) and single-cell technologies. The transcriptomic analysis has the potential to find new biomarkers to identify risk groups for developing T2D and its microvascular and macrovascular complications, which will significantly affect the strategies for early diagnosis, treatment, and preventing the development of complications. In this article, we focused on transcriptomic studies conducted using expression arrays, RNA-seq, and single-cell sequencing to highlight recent findings related to T2D and challenges associated with transcriptome experiments.

Genetic and Phenotypic Factors Affecting Glycemic Response to Metformin Therapy in Patients with Type 2 Diabetes Mellitus.

Metformin is an oral hypoglycemic agent widely used in clinical practice for treatment of patients with type 2 diabetes mellitus (T2DM). The wide interindividual variability of response to metformin therapy was shown, and recently the impact of several genetic variants was reported. To assess the independent and combined effect of the genetic polymorphism on glycemic response to metformin, we performed an association analysis of the variants in ATM, SLC22A1, SLC47A1, and SLC2A2 genes with metformin response in 299 patients with T2DM. Likewise, the distribution of allele and genotype frequencies of the studied gene variants was analyzed in an extended group of patients with T2DM (n = 464) and a population group (n = 129). According to our results, one variant, rs12208357 in the SLC22A1 gene, had a significant impact on response to metformin in T2DM patients. Carriers of TT genotype and T allele had a lower response to metformin compared to carriers of CC/CT genotypes and C allele (p-value = 0.0246, p-value = 0.0059, respectively). To identify the parameters that had the greatest importance for the prediction of the therapy response to metformin, we next built a set of machine learning models, based on the various combinations of genetic and phenotypic characteristics. The model based on a set of four parameters, including gender, rs12208357 genotype, familial T2DM background, and waist-hip ratio (WHR) showed the highest prediction accuracy for the response to metformin therapy in patients with T2DM (AUC = 0.62 in cross-validation). Further pharmacogenetic studies may aid in the discovery of the fundamental mechanisms of type 2 diabetes, the identification of new drug targets, and finally, it could advance the development of personalized treatment.

Genetics of macrovascular complications in type 2 diabetes.

Type 2 diabetes mellitus (T2DM) is a metabolic disorder that currently affects more than 400 million worldwide and is projected to cause 552 million cases by the year 2030. Long-term vascular complications, such as coronary artery disease, myocardial infarction, stroke, are the leading causes of morbidity and mortality among diabetic patients. The recent advances in genome-wide technologies have given a powerful impetus to the study of risk markers for multifactorial diseases. To date, the role of genetic and epigenetic factors in modulating susceptibility to T2DM and its vascular complications is being successfully studied that provides the accumulation of genomic knowledge. In the future, this will provide an opportunity to reveal the pathogenetic pathways in the development of the disease and allow to predict the macrovascular complications in T2DM patients. This review is focused on the evidence of the role of genetic variants and epigenetic changes in the development of macrovascular pathology in diabetic patients.

Analysis of the Spectrum of ACE2 Variation Suggests a Possible Influence of Rare and Common Variants on Susceptibility to COVID-19 and Severity of Outcome.

OBJECTIVES: In March 2020, the World Health Organization declared that an infectious respiratory disease caused by a new severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2, causing coronavirus disease 2019 (COVID-19)] became a pandemic. In our study, we have analyzed a large publicly available dataset, the Genome Aggregation Database (gnomAD), as well as a cohort of 37 Russian patients with COVID-19 to assess the influence of different classes of genetic variants in the angiotensin-converting enzyme-2 (ACE2) gene on the susceptibility to COVID-19 and the severity of disease outcome. RESULTS: We demonstrate that the European populations slightly differ in alternative allele frequencies at the 2,754 variant sites in ACE2 identified in the gnomAD database. We find that the Southern European population has a lower frequency of missense variants and slightly higher frequency of regulatory variants. However, we found no statistical support for the significance of these differences. We also show that the Russian population is similar to other European populations when comparing the frequencies of the ACE2 variants. Evaluation of the effect of various classes of ACE2 variants on COVID-19 outcome in a cohort of Russian patients showed that common missense and regulatory variants do not explain the differences in disease severity. At the same time, we find several rare ACE2 variants (including rs146598386, rs73195521, rs755766792, and others) that are likely to affect the outcome of COVID-19. Our results demonstrate that the spectrum of genetic variants in ACE2 may partially explain the differences in severity of the COVID-19 outcome.

Targeted sequencing analysis of ACVR2A gene identifies novel risk variants associated with preeclampsia.

Background: Preeclampsia (PE) is the most common complication of pregnancy that remains to be a major cause of maternal and fetal mortality. Prediction and early diagnosis of PE would allow for timely initiation of preventive therapy. According to recent studies of ACVR2A gene polymorphism is associated with PE, but it is still unclear whether these findings reflect specific pathogenetic mechanisms of this disease. Methods: We performed targeted next-generation sequencing (NGS) sequencing of ACVR2A gene by means of Ion Torrent Personal Genome machine (PGM) Sequencer. A genetic analysis of patients with PE and control group was performed. Bioinformatics analysis using Polyphen2 (Boston, MA), SIFT (La Jolla, CA), and SnpSift software were used. To select genetic markers in PE patients two additive models and score analysis were applied. Results: Based on the score analysis, we detected two substitutions (rs145399059 and rs17692648) and one insertion insAA at position 148642724 that were associated with PE in our cohorts. We also detected a variant rs17742573 that can be considered as protective against preeclampsia. Conclusions: Our data suggest that some variants in ACVR2A gene are associated with PE. But more studies are required to reveal the role of ACVR2A gene in the pathogenesis of this disease during pregnancy.

Targeted next-generation sequencing (NGS) of nine candidate genes with custom AmpliSeq in patients and a cardiomyopathy risk group.

BACKGROUND: Hypertrophic cardiomyopathy is a common genetic cardiac disease. Prevention and early diagnosis of this disease are very important. Because of the large number of causative genes and the high rate of mutations involved in the pathogenesis of this disease, traditional methods of early diagnosis are ineffective. METHODS: We developed a custom AmpliSeq panel for NGS sequencing of the coding sequences of ACTC1, MYBPC3, MYH7, MYL2, MYL3, TNNI3, TNNT2, TPM1, and CASQ2. A genetic analysis of student cohorts (with and without cardiomyopathy risk in their medical histories) and patients with cardiomyopathies was performed. For the statistical and bioinformatics analysis, Polyphen2, SIFT, SnpSift and PLINK software were used. To select genetic markers in the patients with cardiomyopathy and in the students of the high risk group, four additive models were applied. RESULTS: Our AmpliSeq custom panel allowed us to efficiently explore targeted sequences. Based on the score analysis, we detected three substitutions in the MYBPC3 and CASQ2 genes and six combinations between loci in the MYBPC3, MYH7 and CASQ2 genes that were responsible for cardiomyopathy risk in our cohorts. We also detected substitutions in the TNNT2 gene that can be considered as protective against cardiomyopathy. CONCLUSION: We used NGS with AmpliSeq libraries and Ion PGM sequencing to develop improved predictive information for patients at risk of cardiomyopathy.