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Background & objectives: Diabetes genomics research has illuminated single nucleotide polymorphism (SNP) in several genes including, fat mass and obesity associated (FTO) (rs9939609 and rs9926289), potassium voltage-gated channel subfamily J member 11 (rs5219), SLC30A 8 (rs13266634) and peroxisome proliferator-activated receptor gamma 2 (rs1805192). The present study was conducted to investigate the involvement of these polymorphisms in conferring susceptibility to type 2 diabetes (T2D) in the North East Indian population, and also to establish their association with anthropometric parameters. Methods: DNA was extracted from blood samples of 155 patients with T2D and 100 controls. Genotyping was performed by polymerase chain reaction-restriction fragment length polymorphism and DNA sequencing. To confirm the association between the inheritance of SNP and T2D development, logistic regression analysis was performed. Results: For the rs9939609 variant (FTO), the dominant model AA/(AT+TT) revealed significant association with T2D [odds ratio (OR)=2.03, P=0.021], but was non-significant post correction for multiple testing (P=0.002). For the rs13266634 variant (SLC30A 8), there was considerable but non-significant difference in the distribution pattern of genotypic polymorphisms between the patients and the controls (P=0.004). Significant association was observed in case of the recessive model (CC+CT)/TT (OR=4.56 P=0.001), after adjusting for age, gender and body mass index. In addition, a significant association (P=0.001) of low-density lipoprotein (mg/dl) could be established with the FTO (rs9926289) polymorphism assuming dominant model. Interpretation & conclusions: The current study demonstrated a modest but significant effect of SLC30A8 (rs13266634) polymorphisms on T2D predisposition. Considering the burgeoning prevalence of T2D in the Indian population, the contribution of these genetic variants studied, to the ever-increasing number of T2D cases, appears to be relatively low. This study may serve as a foundation for performing future genome-wide association studies (GWAS) involving larger populations. [ABSTRACT FROM AUTHOR]