A peripheral blood transcriptomic signature predicts autoantibody development in infants at risk of type 1 diabetes

ZNF714 Supports Pro-Oncogenic Features in Lung Cancer Cells

Despite the ongoing progress in diagnosis and treatments, cancer remains a threat to more than one-third of the human population. The emerging data indicate that many Krüppel-associated box zinc finger proteins (KRAB-ZNF) belonging to a large gene family may be involved in carcinogenesis. Our previous study identified Zinc Finger Protein 714 (ZNF714), a KRAB-ZNF gene of unknown function, as being commonly overexpressed in many tumors, pointing to its hypothetical oncogenic role. Here, we harnessed The Cancer Genome Atlas (TCGA)-centered databases and performed functional studies with transcriptomic and methylomic profiling to explore ZNF714 function in cancer. Our pan-cancer analyses confirmed frequent ZNF714 overexpression in multiple tumors, possibly due to regional amplification, promoter hypomethylation, and Nuclear Transcription Factor Y Subunit Beta (NFYB) signaling. We also showed that ZNF714 expression correlates with tumor immunosuppressive features. The in vitro studies indicated that ZNF714 expression positively associates with proliferation, migration, and invasion. The transcriptomic analysis of ZNF714 knocked-down cells demonstrated deregulation of cell adhesion, migration, proliferation, apoptosis, and differentiation. Importantly, we provided evidence that ZNF714 negatively regulates the expression of several known TSGs indirectly via promoter methylation. However, as ZNF714 did not show nuclear localization in our research model, the regulatory mechanisms exerted by ZNF714 require further investigation. In conclusion, our results reveal, for the first time, that ZNF714 may support pro-oncogenic features in lung cancer cells.

Genome-Wide Association Study in Acute Tubulointerstitial Nephritis

SIGNIFICANCE STATEMENT

Polymorphisms of HLA genes may confer susceptibility to acute tubulointerstitial nephritis (ATIN), but small sample sizes and candidate gene design have hindered their investigation. The first genome-wide association study of ATIN identified two significant loci, risk haplotype DRB1*14-DQA1*0101-DQB1*0503 (DR14 serotype) and protective haplotype DRB1*1501-DQA1*0102-DQB1*0602 (DR15 serotype), with amino acid position 60 in the peptide-binding groove P10 of HLA-DR β 1 key. Risk alleles were shared among different causes of ATIN and HLA genotypes associated with kidney injury and immune therapy response. HLA alleles showed the strongest association. The findings suggest that a genetically conferred risk of immune dysregulation is part of the pathogenesis of ATIN.

BACKGROUND

Acute tubulointerstitial nephritis (ATIN) is a rare immune-related disease, accounting for approximately 10% of patients with unexplained AKI. Previous elucidation of the relationship between genetic factors that contribute to its pathogenesis was hampered because of small sample sizes and candidate gene design.

METHODS

We undertook the first two-stage genome-wide association study and meta-analysis involving 544 kidney biopsy-defined patients with ATIN and 2346 controls of Chinese ancestry. We conducted statistical fine-mapping analysis, provided functional annotations of significant variants, estimated single nucleotide polymorphism (SNP)-based heritability, and checked genotype and subphenotype correlations.

RESULTS

Two genome-wide significant loci, rs35087390 of HLA-DQA1 ( P =3.01×10 -39 ) on 6p21.32 and rs2417771 of PLEKHA5 on 12p12.3 ( P =2.14×10 -8 ), emerged from the analysis. HLA imputation using two reference panels suggested that HLA-DRB1*14 mainly drives the HLA risk association . HLA-DRB1 residue 60 belonging to pocket P10 was the key amino acid position. The SNP-based heritability estimates with and without the HLA locus were 20.43% and 10.35%, respectively. Different clinical subphenotypes (drug-related or tubulointerstitial nephritis and uveitis syndrome) seemed to share the same risk alleles. However, the HLA risk genotype was associated with disease severity and response rate to immunosuppressive therapy.

CONCLUSIONS

We identified two candidate genome regions associated with susceptibility to ATIN. The findings suggest that a genetically conferred risk of immune dysregulation is involved in the pathogenesis of ATIN.

Circulating biomarkers during progression to type 1 diabetes: A systematic review

AIM

Progression to type 1 diabetes (T1D) is defined in stages and clinical disease is preceded by a period of silent autoimmunity. Improved prediction of the risk and rate of progression to T1D is needed to reduce the prevalence of diabetic ketoacidosis at presentation as well as for staging participants for clinical trials. This systematic review evaluates novel circulating biomarkers associated with future progression to T1D.

METHODS

PubMed, Ovid, and EBSCO databases were used to identify a comprehensive list of articles. The eligibility criteria included observational studies that evaluated the usefulness of circulating markers in predicting T1D progression in at-risk subjects <20 years old.

RESULTS

Twenty-six studies were identified, seventeen were cohort studies and ten were case control studies. From the 26 studies, 5 found evidence for protein and lipid dysregulation, 11 identified molecular markers while 12 reported on changes in immune parameters during progression to T1D. An increased risk of T1D progression was associated with the presence of altered gene expression, immune markers including regulatory T cell dysfunction and higher short-lived effector CD8⁺ T cells in progressors.

DISCUSSION

Several circulating biomarkers are dysregulated before T1D diagnosis and may be useful in predicting either the risk or rate of progression to T1D. Further studies are required to validate these biomarkers and assess their predictive accuracy before translation into broader use.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero, identifier (CRD42020166830).

Environmental pathways affecting gene expression (E.PAGE) as an R package to predict gene-environment associations

The purpose of this study is to manually and semi-automatically curate a database and develop an R package that will act as a comprehensive resource to understand how biological processes are dysregulated due to interactions with environmental factors. The initial database search run on the Gene Expression Omnibus and the Molecular Signature Database retrieved a total of 90,018 articles. After title and abstract screening against pre-set criteria, a total of 237 datasets were selected and 522 gene modules were manually annotated. We then curated a database containing four environmental factors, cigarette smoking, diet, infections and toxic chemicals, along with a total of 25,789 genes that had an association with one or more of gene modules. The database and statistical analysis package was then tested with the differentially expressed genes obtained from the published literature related to type 1 diabetes, rheumatoid arthritis, small cell lung cancer, COVID-19, cobalt exposure and smoking. On testing, we uncovered statistically enriched biological processes, which revealed pathways associated with environmental factors and the genes. The curated database and enrichment tool are available as R packages at https://github.com/AhmedMehdiLab/E.PATH and https://github.com/AhmedMehdiLab/E.PAGE respectively.

Transcriptional regulatory networks of circulating immune cells in type 1 diabetes: A community knowledgebase

Investigator-generated transcriptomic datasets interrogating circulating immune cell (CIC) gene expression in clinical type 1 diabetes (T1D) have underappreciated re-use value. Here, we repurposed these datasets to create an open science environment for the generation of hypotheses around CIC signaling pathways whose gain or loss of function contributes to T1D pathogenesis. We firstly computed sets of genes that were preferentially induced or repressed in T1D CICs and validated these against community benchmarks. We then inferred and validated signaling node networks regulating expression of these gene sets, as well as differentially expressed genes in the original underlying T1D case:control datasets. In a set of three use cases, we demonstrated how informed integration of these networks with complementary digital resources supports substantive, actionable hypotheses around signaling pathway dysfunction in T1D CICs. Finally, we developed a federated, cloud-based web resource that exposes the entire data matrix for unrestricted access and re-use by the research community.

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Re-use of transcriptomic type 1 diabetes (T1D) circulating immune cells (CICs) datasets

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We generated transcriptional regulatory networks for T1D CICs

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Use cases generate substantive hypotheses around signaling pathway dysfunction in T1D CICs

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Networks are freely accessible on the web for re-use by the research community

Cytotoxicity-Related Gene Expression and Chromatin Accessibility Define a Subset of CD4+ T Cells That Mark Progression to Type 1 Diabetes

Type 1 diabetes in children is heralded by a preclinical phase defined by circulating autoantibodies to pancreatic islet antigens. How islet autoimmunity is initiated and then progresses to clinical diabetes remains poorly understood. Only one study has reported gene expression in specific immune cells of children at risk associated with progression to islet autoimmunity. We analyzed gene expression with RNA sequencing in CD4+ and CD8+ T cells, natural killer (NK) cells, and B cells, and chromatin accessibility by assay for transposase-accessible chromatin sequencing (ATAC-seq) in CD4+ T cells, in five genetically at risk children with islet autoantibodies who progressed to diabetes over a median of 3 years ("progressors") compared with five children matched for sex, age, and HLA-DR who had not progressed ("nonprogressors"). In progressors, differentially expressed genes (DEGs) were largely confined to CD4+ T cells and enriched for cytotoxicity-related genes/pathways. Several top-ranked DEGs were validated in a semi-independent cohort of 13 progressors and 11 nonprogressors. Flow cytometry confirmed that progression was associated with expansion of CD4+ cells with a cytotoxic phenotype. By ATAC-seq, progression was associated with reconfiguration of regulatory chromatin regions in CD4+ cells, some linked to differentially expressed cytotoxicity-related genes. Our findings suggest that cytotoxic CD4+ T cells play a role in promoting progression to type 1 diabetes.

Prevalence of Inflammatory Pathways Over Immuno-Tolerance in Peripheral Blood Mononuclear Cells of Recent-Onset Type 1 Diabetes

Background

Changes in innate and adaptive immunity occurring in/around pancreatic islets had been observed in peripheral blood mononuclear cells (PBMC) of Caucasian T1D patients by some, but not all researchers. The aim of our study was to investigate whether gene expression patterns of PBMC of the highly admixed Brazilian population could add knowledge about T1D pathogenic mechanisms.

Methods

We assessed global gene expression in PBMC from two groups matched for age, sex and BMI: 20 patients with recent-onset T1D (≤ 6 months from diagnosis, in a time when the autoimmune process is still highly active), testing positive for one or more islet autoantibodies and 20 islet autoantibody-negative healthy controls.

Results

We identified 474 differentially expressed genes between groups. The most expressed genes in T1D group favored host defense, inflammatory and anti-bacterial/antiviral effects (LFT, DEFA4, DEFA1, CTSG, KCNMA1) and cell cycle progression. Several of the downregulated genes in T1D target cellular repair, control of inflammation and immune tolerance. They were related to T helper 2 pathway, induction of FOXP3 expression (AREG) and immune tolerance (SMAD6). SMAD6 expression correlated negatively with islet ZnT8 antibody. The expression of PDE12, that offers resistance to viral pathogens was decreased and negatively related to ZnT8A and GADA levels. The increased expression of long non coding RNAs MALAT1 and NEAT1, related to inflammatory mediators, autoimmune diseases and innate immune response against viral infections reinforced these data.

Conclusions

Our analysis suggested the activation of cell development, anti-infectious and inflammatory pathways, indicating immune activation, whereas immune-regulatory pathways were downregulated in PBMC from recent-onset T1D patients with a differential genetic profile.

Insights From Single Cell RNA Sequencing Into the Immunology of Type 1 Diabetes- Cell Phenotypes and Antigen Specificity

In the past few years, huge advances have been made in techniques to analyse cells at an individual level using RNA sequencing, and many of these have precipitated exciting discoveries in the immunology of type 1 diabetes (T1D). This review will cover the first papers to use scRNAseq to characterise human lymphocyte phenotypes in T1D in the peripheral blood, pancreatic lymph nodes and islets. These have revealed specific genes such as IL-32 that are differentially expressed in islet -specific T cells in T1D. scRNAseq has also revealed wider gene expression patterns that are involved in T1D and can predict its development even predating autoantibody production. Single cell sequencing of TCRs has revealed V genes and CDR3 motifs that are commonly used to target islet autoantigens, although truly public TCRs remain elusive. Little is known about BCR repertoires in T1D, but scRNAseq approaches have revealed that insulin binding BCRs commonly use specific J genes, share motifs between donors and frequently demonstrate poly-reactivity. This review will also summarise new developments in scRNAseq technology, the insights they have given into other diseases and how they could be leveraged to advance research in the type 1 diabetes field to identify novel biomarkers and targets for immunotherapy.

Transcriptional networks in at-risk individuals identify signatures of type 1 diabetes progression

Type 1 diabetes (T1D) is a disease of insulin deficiency that results from autoimmune destruction of pancreatic islet β cells. The exact cause of T1D remains unknown, although asymptomatic islet autoimmunity lasting from weeks to years before diagnosis raises the possibility of intervention before the onset of clinical disease. The number, type, and titer of islet autoantibodies are associated with long-term disease risk but do not cause disease, and robust early predictors of individual progression to T1D onset remain elusive. The Environmental Determinants of Diabetes in the Young (TEDDY) consortium is a prospective cohort study aiming to determine genetic and environmental interactions causing T1D. Here, we analyzed longitudinal blood transcriptomes of 2013 samples from 400 individuals in the TEDDY study before both T1D and islet autoimmunity. We identified and interpreted age-associated gene expression changes in healthy infancy and age-independent changes tracking with progression to both T1D and islet autoimmunity, beginning before other evidence of islet autoimmunity was present. We combined multivariate longitudinal data in a Bayesian joint model to predict individual risk of T1D onset and validated the association of a natural killer cell signature with progression and the model's predictive performance on an additional 356 samples from 56 individuals in the independent Type 1 Diabetes Prediction and Prevention study. Together, our results indicate that T1D is characterized by early and longitudinal changes in gene expression, informing the immunopathology of disease progression and facilitating prediction of its course.

Parallel Multi-Omics in High-Risk Subjects for the Identification of Integrated Biomarker Signatures of Type 1 Diabetes

BACKGROUND

Biomarkers are crucial for detecting early type-1 diabetes (T1D) and preventing significant β-cell loss before the onset of clinical symptoms. Here, we present proof-of-concept studies to demonstrate the potential for identifying integrated biomarker signature(s) of T1D using parallel multi-omics.

METHODS

Blood from human subjects at high risk for T1D (and healthy controls; n = 4 + 4) was subjected to parallel unlabeled proteomics, metabolomics, lipidomics, and transcriptomics. The integrated dataset was analyzed using Ingenuity Pathway Analysis (IPA) software for disturbances in the at-risk subjects compared to controls.

RESULTS

The final quadra-omics dataset contained 2292 proteins, 328 miRNAs, 75 metabolites, and 41 lipids that were detected in all samples without exception. Disease/function enrichment analyses consistently indicated increased activation, proliferation, and migration of CD4 T-lymphocytes and macrophages. Integrated molecular network predictions highlighted central involvement and activation of NF-κB, TGF-β, VEGF, arachidonic acid, and arginase, and inhibition of miRNA Let-7a-5p. IPA-predicted candidate biomarkers were used to construct a putative integrated signature containing several miRNAs and metabolite/lipid features in the at-risk subjects.

CONCLUSIONS

Preliminary parallel quadra-omics provided a comprehensive picture of disturbances in high-risk T1D subjects and highlighted the potential for identifying associated integrated biomarker signatures. With further development and validation in larger cohorts, parallel multi-omics could ultimately facilitate the classification of T1D progressors from non-progressors.

Dietary SCFAs Immunotherapy: Reshaping the Gut Microbiota in Diabetes

Diet-microbiota related inflammatory conditions such as obesity, autoimmune type 1 diabetes (T1D), type 2 diabetes (T2D), cardiovascular disease (CVD) and gut infections have become a stigma in Western societies and developing nations. This book chapter examines the most relevant pre-clinical and clinical studies about diet-gut microbiota approaches as an alternative therapy for diabetes. We also discuss what we and others have extensively investigated- the power of dietary short-chain fatty acids (SCFAs) technology that naturally targets the gut microbiota as an alternative method to prevent and treat diabetes and its related complications.

Next steps in the identification of gene targets for type 1 diabetes

The purpose of this review is to provide a view of the future of genomics and other omics approaches in defining the genetic contribution to all stages of risk of type 1 diabetes and the functional impact and clinical implementations of the associated variants. From the recognition nearly 50 years ago that genetics (in the form of HLA) distinguishes risk of type 1 diabetes from type 2 diabetes, advances in technology and sample acquisition through collaboration have identified over 60 loci harbouring SNPs associated with type 1 diabetes risk. Coupled with HLA region genes, these variants account for the majority of the genetic risk (~50% of the total risk); however, relatively few variants are located in coding regions of genes exerting a predicted protein change. The vast majority of genetic risk in type 1 diabetes appears to be attributed to regions of the genome involved in gene regulation, but the target effectors of those genetic variants are not readily identifiable. Although past genetic studies clearly implicated immune-relevant cell types involved in risk, the target organ (the beta cell) was left untouched. Through emergent technologies, using combinations of genetics, gene expression, epigenetics, chromosome conformation and gene editing, novel landscapes of how SNPs regulate genes have emerged. Furthermore, both the immune system and the beta cell and their biological pathways have been implicated in a context-specific manner. The use of variants from immune and beta cell studies distinguish type 1 diabetes from type 2 diabetes and, when they are combined in a genetic risk score, open new avenues for prediction and treatment. Graphical abstract.

Sphingolipids in Type 1 Diabetes: Focus on Beta-Cells

Type 1 diabetes (T1DM) is a chronic autoimmune disease, with a strong genetic background, leading to a gradual loss of pancreatic beta-cells, which secrete insulin and control glucose homeostasis. Patients with T1DM require life-long substitution with insulin and are at high risk for development of severe secondary complications. The incidence of T1DM has been continuously growing in the last decades, indicating an important contribution of environmental factors. Accumulating data indicates that sphingolipids may be crucially involved in T1DM development. The serum lipidome of T1DM patients is characterized by significantly altered sphingolipid composition compared to nondiabetic, healthy probands. Recently, several polymorphisms in the genes encoding the enzymatic machinery for sphingolipid production have been identified in T1DM individuals. Evidence gained from studies in rodent islets and beta-cells exposed to cytokines indicates dysregulation of the sphingolipid biosynthetic pathway and impaired function of several sphingolipids. Moreover, a number of glycosphingolipids have been suggested to act as beta-cell autoantigens. Studies in animal models of autoimmune diabetes, such as the Non Obese Diabetic (NOD) mouse and the LEW.1AR1-iddm (IDDM) rat, indicate a crucial role of sphingolipids in immune cell trafficking, islet infiltration and diabetes development. In this review, the up-to-date status on the findings about sphingolipids in T1DM will be provided, the under-investigated research areas will be identified and perspectives for future studies will be given.

The chilling of adenylyl cyclase 9 and its translational potential

A recent break-through paper has revealed for the first time the high-resolution, three-dimensional structure of a mammalian trans-membrane adenylyl cyclase (tmAC) obtained by cryo-electronmicroscopy (cryo-EM). Reporting the structure of adenylyl cyclase 9 (AC9) in complex with activated Gsα, the cryo-EM study revealed that AC9 has three functionally interlinked, yet structurally distinct domains. The array of the twelve transmembrane helices is connected to the cytosolic catalytic core by two helical segments that are stabilized through the formation of a parallel coiled-coil. Surprisingly, in the presence of Gsα, the isoform-specific carboxyl-terminal tail of AC9 occludes the forskolin- as well as the active substrate-sites, resulting in marked autoinhibition of the enzyme. As AC9 has the lowest primary sequence homology with the eight further mammalian tmAC paralogues, it appears to be the best candidate for selective pharmacologic targeting. This is now closer to reality as the structural insight provided by the cryo-EM study indicates that all of the three structural domains are potential targets for bioactive agents. The present paper summarizes for molecular physiologists and pharmacologists what is known about the biological role of AC9, considers the potential modes of physiologic regulation, as well as pharmacologic targeting on the basis of the high-resolution cryo-EM structure. The translational potential of AC9 is considered upon highlighting the current state of genome-wide association screens, and the corresponding experimental evidence. Overall, whilst the high- resolution structure presents unique opportunities for the full understanding of the control of AC9, the data on the biological role of the enzyme and its translational potential are far from complete, and require extensive further study.

IL-23 favours outgrowth of spondyloarthritis-associated pathobionts and suppresses host support for homeostatic microbiota

Objectives

Certain gut bacterial families, including Bacteroidaceae, Porphyromonadaceae and Prevotellaceae, are increased in people suffering from spondyloarthropathy (SpA), a disease group associated with IL23R signalling variants. To understand the relationship between host interleukin (IL)-23 signalling and gut bacterial dysbiosis in SpA, we inhibited IL-23 in dysbiotic ZAP-70-mutant SKG mice that develop IL-23-dependent SpA-like arthritis, psoriasis-like skin inflammation and Crohn’s-like ileitis in response to microbial beta 1,3-glucan (curdlan).

Methods

We treated SKG mice weekly with anti-IL-23 or isotype mAb for 3 weeks, rested them for 3 weeks, then administered curdlan or saline. We collected faecal samples longitudinally, assessed arthritis, spondylitis, psoriasis and ileitis histologically, and analysed the microbiota community profiles using next-generation sequencing. We used multivariate sparse partial least squares discriminant analysis to identify operational taxonomic unit (OTU) signatures best classifying treatment groups and linear regression to develop a predictive model of disease severity.

Results

IL-23p19 inhibition in naïve SKG mice decreased Bacteroidaceae, Porphyromonadaceae and Prevotellaceae. Abundance of Clostridiaceae and Lachnospiraceae families concomitantly increased, and curdlan-mediated SpA development decreased. Abundance of Enterobacteriaceae and Porphyromonadaceae family and reduction in Lachnospiraceae Dorea genus OTUs early in disease course were associated with disease severity in affected tissues.

Conclusions

Dysbiosis in SKG mice reflects human SpA and is IL-23p19 dependent. In genetically susceptible hosts, IL-23p19 favours outgrowth of SpA-associated pathobionts and reduces support for homeostatic-inducing microbiota. The relative abundance of specific pathobionts is associated with disease severity.

High genetic risk scores of SLIT3, PLEKHA5 and PPP2R2C variants increased insulin resistance and interacted with coffee and caffeine consumption in middle-aged adults

BACKGROUNDS AND AIMS

Insulin resistance is a common feature of metabolic syndrome that may be influenced by genetic risk factors. We hypothesized that genetic risk scores (GRS) of SNPs that influence insulin resistance and signaling interact with lifestyles to modulate insulin resistance in Korean adults.

METHODS AND RESULTS

Genome-wide association studies (GWAS) of subjects aged 40-65 years who participated in the Ansung/Ansan cohorts (8842 adults) in Korea revealed 52 genetic variants that influence insulin resistance. The best gene-gene interaction model was explored using the generalized multifactor dimensionality reduction (GMDR) method. GRS from the best model were calculated and the GRS were divided into low, medium and high groups. The best model for representing insulin resistance included SLIT3_rs2974430, PLEKHA5_rs1077044, and PPP2R2C_rs16838853. The odds ratios for insulin resistance were increased by 150% in the High-GRS group compared to the Low-GRS group. However, ORs for insulin secretion capacity, measured by HOMA-B, were not associated with GRS. Coffee and caffeine intake and GRS had an interaction with insulin resistance: In subjects with high coffee (≥10 cups/week) or caffeine intake (≥220 mg caffeine/day), insulin resistance was significantly elevated in the High-GRS group, but not in the Low-GRS. However, alcohol intake, smoking and physical activity did not have an interaction with GRS. Insulin secretion capacity was not significantly influenced by GRS when evaluating the adjusted odds ratios.

CONCLUSIONS

Subjects with High-GRS may be susceptible to increased insulin resistance by 50% and its risk may be exacerbated by consuming more than 10 cups coffee/week or 220 mg caffeine/day.

Identification of Novel Candidate Markers of Type 2 Diabetes and Obesity in Russia by Exome Sequencing with a Limited Sample Size

Type 2 diabetes (T2D) and obesity are common chronic disorders with multifactorial etiology. In our study, we performed an exome sequencing analysis of 110 patients of Russian ethnicity together with a multi-perspective approach based on biologically meaningful filtering criteria to detect novel candidate variants and loci for T2D and obesity. We have identified several known single nucleotide polymorphisms (SNPs) as markers for obesity (rs11960429), T2D (rs9379084, rs1126930), and body mass index (BMI) (rs11553746, rs1956549 and rs7195386) (p < 0.05). We show that a method based on scoring of case-specific variants together with selection of protein-altering variants can allow for the interrogation of novel and known candidate markers of T2D and obesity in small samples. Using this method, we identified rs328 in LPL (p = 0.023), rs11863726 in HBQ1 (p = 8 × 10⁻⁵), rs112984085 in VAV3 (p = 4.8 × 10⁻⁴) for T2D and obesity, rs6271 in DBH (p = 0.043), rs62618693 in QSER1 (p = 0.021), rs61758785 in RAD51B (p = 1.7 × 10⁻⁴), rs34042554 in PCDHA1 (p = 1 × 10⁻⁴), and rs144183813 in PLEKHA5 (p = 1.7 × 10⁻⁴) for obesity; and rs9379084 in RREB1 (p = 0.042), rs2233984 in C6orf15 (p = 0.030), rs61737764 in ITGB6 (p = 0.035), rs17801742 in COL2A1 (p = 8.5 × 10⁻⁵), and rs685523 in ADAMTS13 (p = 1 × 10⁻⁶) for T2D as important susceptibility loci in Russian population. Our results demonstrate the effectiveness of whole exome sequencing (WES) technologies for searching for novel markers of multifactorial diseases in cohorts of limited size in poorly studied populations.