Abstract
Background: Local specific biomarkers for MASLD risk stratification are urgently needed in Argentina. Aim: The aim of the study was to characterize the interaction of gut microbiome signatures and genetic and clinical risk factors for MASLD in patients with diabetes from different regions of Argentina. Materials and Methods: We recruited 214 patients with diabetes from different regions of Argentina. Anthropometric, clinical, and lifestyle data were obtained from all participants, who also underwent abdominal ultrasound for MASLD diagnosis and oral swabbing. The PNPLA3 gene was amplified by PCR from the swabs, and the rs738409 genotype was determined via bidirectional sequencing. To profile the MASLD-associated microbiome, stool was collected from 170 participants. V4 16S rRNA gene sequencing was performed, and reads were analyzed using QIIME2 2024.10.1. R Studio 2023.05.1 was used for statistical analyses. Results: MASLD prevalence was 77.9%, with similar rates of occurrence in all regions represented. FIB-4 scores < 1.3 and > 2.67 were detected in 55.3% and 7.4% of patients, respectively. Half of the diabetic patients had the PNPLA3 GG genotype, with the highest rates occurring in patients from Northwestern Argentina (64.9%; p = 0.02 vs. Buenos Aires). The PNPLA3 GG genotype was an independent risk factor for FIB-4 score (p = 0.0008) and a protective factor against glycated hemoglobin (p = 0.004), fasting plasma glucose (p = 0.008), and cholesterol levels (p = 0.02). Marked regional differences were observed in microbiota diversity and composition in Argentina. After adjusting for geographical region, Negativibacillus genus was exclusively detected in diabetic patients with MASLD and GG carriers. The Catenibacterium genus was related to FIB-4 > 2.67. Short-chain fatty acid-producing bacteria were linked to the absence of MASLD. Conclusions: Although some geographical regions of Argentina were not represented in this study and these results therefore cannot be generalized to the country as a whole, these specific signatures could be useful as biomarkers for MASLD risk stratification in Argentines with diabetes.