%0 Generic %A Lyngdoh, Tanica %A Vuistiner, Philippe %A Marques-Vidal, Pedro %A Rousson, Valentin %A Waeber, Gérard %A Vollenweider, Peter %A Bochud, Murielle %D 2012 %T Association of adiposity measures (using combined SNPs from the FTO, MC4R and TMEM18 gene as instrument) with SUA (dependent variable of interest) in the overall sample. %U https://plos.figshare.com/articles/dataset/_Association_of_adiposity_measures_using_combined_SNPs_from_the_FTO_MC4R_and_TMEM18_gene_as_instrument_with_SUA_dependent_variable_of_interest_in_the_overall_sample_/292825 %R 10.1371/journal.pone.0039321.t005 %2 https://plos.figshare.com/ndownloader/files/622339 %K adiposity %K measures %K snps %K sua %X

BMI = body mass index; SNP = single-nucleotide polymorphism; SUA = serum uric acid; WC = waist circumference.

The β(95%CI) represents the association of SUA with adiposity markers as tested by the conventional epidemiological method (ordinary least square [OLS]) and by the instrumental variable analysis in a two-stage least square (2 SLS) regression (so called Mendelian randomization approach whenever the instruments are genetic variants). Similar magnitude and direction of coefficients derived from both the OLS and 2 SLS regressions suggest a causal effect of exposure (in this case adiposity) on the outcome of interest (in this case SUA). Further, a P value2SLS <0.05 against the null hypothesis favors a causal effect of adiposity on SUA.

a

P value from the Durbin-Hausman test which compares the difference between estimates derived from the OLS and 2 SLS regressions.

Results are expressed as standardized regression coefficient (β) along with 95% confidence interval (CI).

Adjusted analysis controlled for age, sex, smoking, alcohol use, estimated glomerular filtration rate (GFR) and diuretic use.

%I PLOS ONE