Type 1 diabetes: genes associated with disease development

Klak, Marta; Gomółka, Magdalena; Kowalska, Patrycja; Cichoń, Justyna; Ambrożkiewicz, Filip; Serwańska-Świętek, Marta; Berman, Andrzej; Wszoła, Michał

doi:10.5114/ceji.2020.103386

Cited by 16 publications

(13 citation statements)

References 104 publications

(86 reference statements)

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“…In addition, we also checked the selection frequency of non-HLA genes including INS , IL32 , TNFAIP3 , and LMO7 that have been associated with T1D pathology. 31 , 32 The expression of HLA class I and II genes among all the AAb+ cells from HPAP092 classified as T1D had a similar expression pattern to the T1D group ( Figures 6 D and 6E). Previous studies have shown the inherited risk for T1D to be largely determined by specific HLA-DQA1 , HLA-DQB1 , HLA-DRA , HLA-DPA1 , and HLA-DRB1 alleles.…”

Section: Resultsmentioning

confidence: 79%

Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets

Patil,

Schug,

Liu

et al. 2024

Cell Reports Medicine

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Section: Resultsmentioning

confidence: 79%

Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets

Patil,

Schug,

Liu

et al. 2024

Cell Reports Medicine

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“…For the GWAS Catalog, a query was made using the previous MONDO ID and all associated genes were extracted. Table 1 of Klak et al (Klak et al, 2020) summarizes genes that have been associated with T1D and gene symbols were extracted from this resource.…”

Section: Construction and Contentmentioning

confidence: 99%

Loop Catalog: a comprehensive HiChIP database of human and mouse samples

Reyna,

Fetter,

Ignacio

et al. 2024

Preprint

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HiChIP enables cost-effective and high-resolution profiling of regulatory and structural loops. To leverage the increasing number of publicly available HiChIP datasets from diverse cell lines and primary cells, we developed the Loop Catalog (https://loopcatalog.lji.org), a web-based database featuring HiChIP loop calls for 1319 samples across 133 studies and 44 high-resolution Hi-C loop calls. We demonstrate its utility in interpreting fine-mapped GWAS variants (SNP-to-gene linking), in identifying enriched sequence motifs and motif pairs at loop anchors, and in network-level analysis of loops connecting regulatory elements (community detection). Our comprehensive catalog, spanning over 4M unique 5kb loops, along with the accompanying analysis modalities constitutes an important resource for studies in gene regulation and genome organization.

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“…In addition, various other immune-related loci (non-HLA) connected to T1DM are recognized, such as CTLA4 (cytotoxic T-lymphocyte antigen 4) and PTPN22 (protein tyrosine phosphatase non-receptor type 22). Furthermore, various candidate genes as well as noncoding RNAs have been identified based on genome-wide association studies (GWAS)[ 15 ]. This strong genetic component of T1DM has stimulated efforts to develop a T1DM genetic risk score based on single-nucleotide polymorphism genotyping, as it would be useful for evaluating and predicting islet autoimmunity progression as well as T1DM development in high-risk individuals[ 16 ].…”

Section: The Basic Characteristics Of T1dm and Aitdmentioning

confidence: 99%

Association of autoimmune thyroid disease with type 1 diabetes mellitus and its ultrasonic diagnosis and management

Wang,

Wan,

Chang

et al. 2024

World J Diabetes

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As a common hyperglycemic disease, type 1 diabetes mellitus (T1DM) is a complicated disorder that requires a lifelong insulin supply due to the immune-mediated destruction of pancreatic β cells. Although it is an organ-specific autoimmune disorder, T1DM is often associated with multiple other autoimmune disorders. The most prevalent concomitant autoimmune disorder occurring in T1DM is autoimmune thyroid disease (AITD), which mainly exhibits two extremes of phenotypes: hyperthyroidism [Graves' disease (GD)] and hypo-thyroidism [Hashimoto's thyroiditis, (HT)]. However, the presence of comorbid AITD may negatively affect metabolic management in T1DM patients and thereby may increase the risk for potential diabetes-related complications. Thus, routine screening of thyroid function has been recommended when T1DM is diagnosed. Here, first, we summarize current knowledge regarding the etiology and pathogenesis mechanisms of both diseases. Subsequently, an updated review of the association between T1DM and AITD is offered. Finally, we provide a relatively detailed review focusing on the application of thyroid ultrasonography in diagnosing and managing HT and GD, suggesting its critical role in the timely and accurate diagnosis of AITD in T1DM.

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Type 1 diabetes: genes associated with disease development

Cited by 16 publications

References 104 publications

Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets

Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets

Loop Catalog: a comprehensive HiChIP database of human and mouse samples

Association of autoimmune thyroid disease with type 1 diabetes mellitus and its ultrasonic diagnosis and management

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