Association between inflammatory markers and cardiovascular risk factors in women from Kolkata, W.B, India.

Background: Recent research has focused on the use of inflammatory biomarkers in the prediction of cardiovascular risk. However, information is scant regarding the association between these inflammatory markers with other cardiovascular risk factors in Asian Indians, particularly in women.

Objective: To explore the association between inflammatory markers such as high-sensitivity C-reactive protein (hs-CRP) and white blood cell (WBC) count and cardiovascular risk factors such as overall and central adiposity, blood pressure, lipid and lipoprotein variables and fasting glucose.

Association of calpain 10 gene polymorphisms with type 2 diabetes mellitus in Southern Indians.

The aim was to investigate the association between the CAPN10 gene single nucleotide polymorphisms (SNPs) -44 (rs2975760), -43 (rs3792267), -19 (rs3842570), and -63 (rs5030952) and type 2 diabetes mellitus in an Asian Indian population in Southern India. A total of 1443 subjects, 794 normal glucose tolerant (NGT) and 649 type 2 diabetes mellitus subjects, were randomly selected from the Chennai Urban Rural Epidemiology Study. These subjects were genotyped for the 4 CAPN10 SNPs using polymerase chain reaction-restriction fragment length polymorphism and validated by direct sequencing.

Single nucleotide polymorphisms in homocysteine metabolism pathway genes: association of CHDH A119C and MTHFR C677T with hyperhomocysteinemia.

Background: An elevated level of homocysteine (hyperhomocysteinemia) has been implicated as an independent risk factor for cardiovascular diseases. Deficiency of dietary factors like vitamin B(12), folate, and genetic variations can cause hyperhomocysteinemia. The prevalence of hyperhomocysteinemia in the Indian population is likely to be high because most Indians adhere to a vegetarian diet, deficient in vitamin B(12).

Evaluating epistatic interaction signals in complex traits using quantitative traits.

Rheumatoid arthritis (RA) is a complex, chronic inflammatory disease implicated to have several plausible candidate loci; however, these may not account for all the genetic variations underlying RA. Common disorders are hypothesized to be highly complex with interaction among genes and other risk factors playing a major role in the disease process. This complexity is further magnified because such interactions may be with or without a strong independent effect and are thus difficult to detect using traditional statistical methodologies.

A quantile-based method for association mapping of quantitative phenotypes: an application to rheumatoid arthritis phenotypes.

Genetic association of population-based quantitative trait data has traditionally been analyzed using analysis of variance (ANOVA). However, violations of certain statistical assumptions may lead to false-positive association results. In this study, we have explored model-free alternatives to ANOVA using correlations between allele frequencies in the different quantile intervals of the quantitative trait and the quantile values.