Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study.

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.

Gender-Specific Effects of Genetic Variants within Th1 and Th17 Cell-Mediated Immune Response Genes on the Risk of Developing Rheumatoid Arthritis.

The present study was conducted to explore whether single nucleotide polymorphisms (SNPs) in Th1 and Th17 cell-mediated immune response genes differentially influence the risk of rheumatoid arthritis (RA) in women and men. In phase one, 27 functional/tagging polymorphisms in C-type lectins and MCP-1/CCR2 axis were genotyped in 458 RA patients and 512 controls. Carriers of Dectin-2 rs4264222T allele had an increased risk of RA (OR = 1.47, 95%CI 1.10-1.96) whereas patients harboring the DC-SIGN rs4804803G, MCP-1 rs1024611G, MCP-1 rs13900T and MCP-1 rs4586C alleles had a decreased risk of developing the disease (OR = 0.66, 95%CI 0.49-0.88; OR = 0.66, 95%CI 0.50-0.89; OR = 0.73, 95%CI 0.55-0.97 and OR = 0.68, 95%CI 0.51-0.91). Interestingly, significant gender-specific differences were observed for Dectin-2 rs4264222 and Dectin-2 rs7134303: women carrying the Dectin-2 rs4264222T and Dectin-2 rs7134303G alleles had an increased risk of RA (OR = 1.93, 95%CI 1.34-2.79 and OR = 1.90, 95%CI 1.29-2.80). Also five other SNPs showed significant associations only with one gender: women carrying the MCP-1 rs1024611G, MCP-1 rs13900T and MCP-1 rs4586C alleles had a decreased risk of RA (OR = 0.61, 95%CI 0.43-0.87; OR = 0.67, 95%CI 0.47-0.95 and OR = 0.60, 95%CI 0.42-0.86). In men, carriers of the DC-SIGN rs2287886A allele had an increased risk of RA (OR = 1.70, 95%CI 1.03-2.78), whereas carriers of the DC-SIGN rs4804803G had a decreased risk of developing the disease (OR = 0.53, 95%CI 0.32-0.89). In phase 2, we genotyped these SNPs in 754 RA patients and 519 controls, leading to consistent gender-specific associations for Dectin-2 rs4264222, MCP-1 rs1024611, MCP-1 rs13900 and DC-SIGN rs4804803 polymorphisms in the pooled sample (OR = 1.38, 95%CI 1.08-1.77; OR = 0.74, 95%CI 0.58-0.94; OR = 0.76, 95%CI 0.59-0.97 and OR = 0.56, 95%CI 0.34-0.93). SNP-SNP interaction analysis of significant SNPs also showed a significant two-locus interaction model in women that was not seen in men. This model consisted of Dectin-2 rs4264222 and Dectin-2 rs7134303 SNPs and suggested a synergistic effect between the variants. These findings suggest that Dectin-2, MCP-1 and DC-SIGN polymorphisms may, at least in part, account for gender-associated differences in susceptibility to RA.