Introduction: The ALMS1 gene encodes a large protein primarily localized at the base of primary cilia and centrosomes, playing a critical role in ciliary structure, intracellular trafficking, and microtubule organization. Dysfunction of ALMS1 underlies Alström syndrome, a rare autosomal recessive disorder characterized by early-onset obesity, insulin resistance, and type 2 diabetes, among other multisystemic symptoms. Our study aimed to investigate the association between common ALMS1 gene variants and the development of obesity and diabetes.
Methods: Following NGS analysis of an Iranian population of early-onset obesity and early-onset diabetes, 17 common SNPs were recurrent in both populations. SNPStats, a web tool for SNP analysis, was used to evaluate the association of each SNP and multiple SNPs (haplotype analysis) with body mass index (BMI) and diabetes as a response under all genetic model including codominant, dominant, recessive, over-dominant and log additive, when it was adjusted for sex, age, and disease status. The p-value<0.05 was considered statistically significant.
Results: Results showed that rs10496192 was associated with BMI under an over-dominant genetic model (OR=2.23; 95%CI: 0.14-4.33, p-value=0.038). Additionally, compared with the control group (comprising individuals with other disease statuses, such as only obesity, only diabetes, and normal-weight individuals without diabetes), all SNPs showed a significantly positive association with disease status in patients with both diabetes and obesity across all genetic models. Haplotype analysis showed all 17 SNPs were in strong linkage disequilibrium (LD), and only 8 combinations of these SNPs’ alleles were frequent over the other 30 expected. The most frequent haplotype was CCTCTGAGATTGGACCGGTA, with a total frequency of 0.56 among patients with both diabetes and obesity.
Conclusion: The results of this study show how common SNPs in strong LD can be a great trigger of diseases like early-onset obesity, diabetes, and their comorbidities, in addition to a monogenic cause of these conditions. The evaluation of such SNP blocks in causative genes can contribute to better classification of such prevalent complex diseases and suggest more effective treatment strategies. A study of other related well-known genes with common SNP blocks is warranted in our population to draw a conclusion.