Transcriptional features of autoimmune diabetes: differentially expressed genes in CD4+ and CD8+ subpopulations of blood T cells

BACKGROUND: Latent autoimmune diabetes in adults (LADA) is considered an intermediate form between type 1 (T1DM) and type 2 diabetes mellitus (T2DM). However, the molecular mechanisms underlying its unique clinical and pathogenetic features remain insufficiently studied. Identifying differentially expressed genes (DEGs) in LADA compared to T1DM is essential for developing more personalized diagnostic and therapeutic approaches. OBJECTIVE: To identify DEGs in peripheral blood mononuclear cells (PBMCs) of patients with LADA compared to those with T1DM, and to evaluate differences in DEGs between these patient groups and healthy volunteers. MATERIALS AND METHODS: The study included 60 participants (23 T1DM patients with disease duration of up to 1 year, 15 LADA patients with disease duration of up to 5 years, and 22 healthy volunteers). The median age of LADA patients was 40 [34; 45] years, and for T1DM patients, 26 [21; 31] years. This was a single-center, cross-sectional observational study. PBMCs were isolated from all participants, and single-cell RNA sequencing (scRNA-seq) was performed. Differential gene expression analysis was conducted using a pseudo-bulk approach (pyDEseq2, p<0.05 adjusted for multiple comparisons, |log2FoldChange| ≥0.5). Statistical analyses employed nonparametric tests (Kruskal–Wallis, Mann–Whitney). RESULTS: In LADA patients, reduced expression of HLA-G , SPARC , and C20orf204 and increased expression of AC002460.2 were observed compared to healthy volunteers (p<0.05) in CD4+ Naive T-cells. In the T1DM group, the most significant differences were identified in CD4+ Central memory T-cells ( IFIT1 , CASP3 , LAMP3 , HIST1H2BN ). When comparing LADA to T1DM, only one transcript, C20orf204 , showed statistically significant differential expression (p<0.05) in CD4+ Naive T-cells. CONCLUSION: The findings indicate that LADA and T1DM share similar molecular patterns, with LADA exhibiting moderate changes in the expression of genes associated with immune regulation and inflammation. The minimal differences between these forms of diabetes highlight their pathogenetic similarity.

Authors

Institutions

Publication Details

Journal
Diabetes Mellitus
Published
2025-05-23
DOI
https://doi.org/10.14341/dm13316
Primary Topic
Diabetes and associated disorders
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Transcriptional features of autoimmune diabetes: differentially expressed genes in CD4+ and CD8+ subpopulations of blood T cells

Vadim Chechekhin, М. В. Шестакова, Ya. V. Dvoryanchikov, Elizaveta Podshivalova et al.
Diabetes Mellitus
Diabetes and associated disorders
article

Transcriptional features of autoimmune diabetes: differentially expressed genes in CD4+ and CD8+ subpopulations of blood T cells

Vadim Chechekhin, М. В. Шестакова, Ya. V. Dvoryanchikov, Elizaveta Podshivalova, Tatiana Vasil'evna Nikonova, Alina Matrosova, Margarita Samsonova, Anatoliy Zubritskiy, I.I. Golodnikov, Илдар Минниахметов, E. V. Bondarenko, Yulia A. Medvedeva, Sergey Popov, Eugenia Markelova
article en

Abstract

BACKGROUND: Latent autoimmune diabetes in adults (LADA) is considered an intermediate form between type 1 (T1DM) and type 2 diabetes mellitus (T2DM). However, the molecular mechanisms underlying its unique clinical and pathogenetic features remain insufficiently studied. Identifying differentially expressed genes (DEGs) in LADA compared to T1DM is essential for developing more personalized diagnostic and therapeutic approaches. OBJECTIVE: To identify DEGs in peripheral blood mononuclear cells (PBMCs) of patients with LADA compared to those with T1DM, and to evaluate differences in DEGs between these patient groups and healthy volunteers. MATERIALS AND METHODS: The study included 60 participants (23 T1DM patients with disease duration of up to 1 year, 15 LADA patients with disease duration of up to 5 years, and 22 healthy volunteers). The median age of LADA patients was 40 [34; 45] years, and for T1DM patients, 26 [21; 31] years. This was a single-center, cross-sectional observational study. PBMCs were isolated from all participants, and single-cell RNA sequencing (scRNA-seq) was performed. Differential gene expression analysis was conducted using a pseudo-bulk approach (pyDEseq2, p<0.05 adjusted for multiple comparisons, |log2FoldChange| ≥0.5). Statistical analyses employed nonparametric tests (Kruskal–Wallis, Mann–Whitney). RESULTS: In LADA patients, reduced expression of HLA-G , SPARC , and C20orf204 and increased expression of AC002460.2 were observed compared to healthy volunteers (p<0.05) in CD4+ Naive T-cells. In the T1DM group, the most significant differences were identified in CD4+ Central memory T-cells ( IFIT1 , CASP3 , LAMP3 , HIST1H2BN ). When comparing LADA to T1DM, only one transcript, C20orf204 , showed statistically significant differential expression (p<0.05) in CD4+ Naive T-cells. CONCLUSION: The findings indicate that LADA and T1DM share similar molecular patterns, with LADA exhibiting moderate changes in the expression of genes associated with immune regulation and inflammation. The minimal differences between these forms of diabetes highlight their pathogenetic similarity.

Diabetes MellitusVol. 28(2)
Russian Academy of Sciences (RU), Lomonosov Moscow State University (RU), Endocrinology Research Center (RU), Federal Research Centre «Fundamentals of Biotechnology» of the Russian Academy of Sciences (RU)
Openalex Percentile: Top 86%
Diabetes and associated disorders
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.