A set of circulating microRNAs belonging to the 14q32 chromosomic locus identifies two clinically and phenotypically different subgroups of individuals with recent onset Stage 3 type 1 diabetes
Sebastiani, G.; Grieco, G. E.; Bruttini, M.; Auddino, S.; Mori, A.; Toniolli, M.; Fignani, D.; Licata, G.; Nigi, L.; Formichi, C.; Pugliese, A.; Evans-Molina, C.; Overbergh, L.; Tree, T.; Peakman, M.; Mathieu, C.; Dotta, F.; INNODIA,
Show abstract
Previous research has indicated that circulating microRNAs are linked to the onset and progression of type 1 diabetes mellitus (T1DM), making them potential biomarkers for the disease. In this study, we employed a multiplatform sequencing approach to analyze circulating microRNAs in an extended cohort of individuals recently diagnosed with T1DM from the European INNODIA consortium. Our findings revealed that a specific set of microRNAs located within the T1DM susceptibility chromosomal locus 14q32 distinguishes two distinct subgroups of T1DM individuals. To validate our results, we conducted additional analyses on a second cohort of T1DM individuals, independently confirming the identification of these two subgroups, which we have named Cluster A and Cluster B. Remarkably, Cluster B T1DM individuals, who exhibited increased expression of 14q32 miRNAs, displayed a different peripheral blood immunomics profile, possessed a lower T1DM risk HLA genotype, and showed better glycaemic control during follow-up visits compared to Cluster A individuals. Taken together, our findings suggest that this specific set of circulating microRNAs located in the 14q32 locus can effectively identify T1DM subgroups with distinct characteristics and different clinical outcomes during follow-up. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=161 SRC="FIGDIR/small/23296650v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@2daf5org.highwire.dtl.DTLVardef@175161dorg.highwire.dtl.DTLVardef@1fed4ecorg.highwire.dtl.DTLVardef@14cefb3_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LICirculating miRNA profiles in individuals with newly diagnosed Type 1 Diabetes Mellitus (T1DM) can distinguish two subgroups: Cluster A and Cluster B. C_LIO_LImiR-409-3p, miR-127-3p, and miR-382-5p are increased in the plasma of individuals in Cluster B. C_LIO_LIIndividuals in Cluster B showed lower IAA titers, a reduced prevalence of HLA risk genotype, and an improved glycaemic profile during the follow-up period. C_LIO_LIImmunomic profiling revealed a reduced frequency of pro-inflammatory immune cells and a higher frequency of exhausted T lymphocytes among individuals in Cluster B. C_LI
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Integrative proteogenomic analyses provide novel interpretations of type 1 diabetes risk loci through circulating proteins 95%
- Glucose-dependent miR-125b is a negative regulator of β-cell function 94%
- Characterizing common and rare variations in non-traditional glycemic biomarkers using multivariate approaches on multi-ancestry ARIC study 93%
Similar papers in this journal
Similar papers in this journal
- Interferons are the key cytokines acting on pancreatic islets in type 1 diabetes 95%
- The power of TOPMed imputation for the discovery of Latino enriched rare variants associated with type 2 diabetes 94%
- Epigenome-wide association study of incident type 2 diabetes in Black and White participants from the Atherosclerosis Risk in Communities Study 93%
Similar papers in this journal
Similar papers in this journal
- Poor in-utero growth, reduced beta cell secretion and high plasma glucose in childhood are harbingers of glucose intolerance in young Indians 92%
- Metabolome-defined obesity and the risk of future diabetes and mortality 92%
- Exploring diseases/traits and blood proteins causally related to expression of ACE2, the putative receptor of SARS-CoV-2: A Mendelian Randomization analysis highlights tentative relevance of diabetes-related traits 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.