In order to further illuminate the potential role of dominant genetic variation in the "missing heritability" debate, we investigated the additive (narrow-sense heritability, h(2)) and dominant (δ(2)) genetic variance for 18 human complex traits. Within the same study base (10,682 Swedish twins), we calculated and compared the estimates from classic twin-based structural equation model with SNP-based genomic-relatedness-matrix restricted maximum likelihood [GREML(d)] method. Contributions of δ(2) were evident for 14 traits in twin models (average δ(2)twin = 0.25, range 0.14-0.49), two of which also displayed significant δ(2) in the GREMLd analyses (triglycerides δ(2)SNP = 0.28 and waist circumference δ(2)SNP = 0.19). On average, the proportion of h(2)SNP/h(2)twin was 70% for ADE-fitted traits (for which the best-fitting model included additive and dominant genetic and unique environmental components) and 31% for AE-fitted traits (for which the best-fitting model included additive genetic and unique environmental components). Independent evidence for contribution from shared environment, also in ADE-fitted traits, was obtained from self-reported within-pair contact frequency and age at separation. We conclude that despite the fact that additive genetics appear to constitute the bulk of genetic influences for most complex traits, dominant genetic variation might often be masked by shared environment in twin and family studies and might therefore have a more prominent role than what family-based estimates often suggest. The risk of erroneously attributing all inherited genetic influences (additive and dominant) to the h(2) in too-small twin studies might also lead to exaggerated "missing heritability" (the proportion of h(2) that remains unexplained by SNPs).
BackgroundDecreased renal function is an established risk factor for cardiovascular disease (CVD). Causal mechanisms between estimates of renal function and CVD are intricate and investigation of the relative importance of genetic and environmental factors for the variability of these phenotypes could provide new knowledge.Methods and ResultsCystatin C and creatinine levels in 12 313 twins were analyzed. Uni‐ and bivariate heritability for these traits and CVD was estimated through structured equation modelling and genome‐wide complex trait analysis (GCTA) in order to independently confirm additive genetic effects. Twin model‐estimated heritability of Cystatin C was 0.55 (95% confidence interval [CI], 0.49 to 0.60) in men, 0.63 (0.59 to 0.66) in women, and 0.60 (0.56 to 0.63) in both sexes combined. For creatinine, heritability estimates were in the same range. Heritability of CVD was 0.39 (0.02 to 0.67) in men and 0.20 (0.00 to 0.61) in women. The phenotypic correlation between Cystatin C and CVD correlation was 0.16 (0.12 to 0.20) in men and 0.17 (0.13 to 0.21) in women, whereas the genetic correlation in males was 0.41 (0.21 to 0.62) while it was non‐significant in females. Trough GCTA, the heritability of Cystatin C and creatinine in both sexes combined was estimated to 0.40 (SE 0.07, P=8E−9) and 0.19 (SE 0.07, P=0.003), respectively.ConclusionsTwin model‐based heritability of Cystatin C was higher compared to previous studies. Co‐variation between Cystatin C and CVD in males was partly explained by additive genetic components, indicating that Cystatin C and CVD share genetic influences. The GCTA provided independent evidence for significant contribution of additive genetics to trait variance of Cystatin C.
BACKGROUNDEpidemiological studies show that high circulating cystatin C is associated with risk of cardiovascular disease (CVD), independent of creatinine-based renal function measurements. It is unclear whether this relationship is causal, arises from residual confounding, and/or is a consequence of reverse causation.OBJECTIVESThe aim of this study was to use Mendelian randomization to investigate whether cystatin C is causally related to CVD in the general population.METHODSWe incorporated participant data from 16 prospective cohorts (n = 76,481) with 37,126 measures of cystatin C and added genetic data from 43 studies (n = 252,216) with 63,292 CVD events. We used the common variant rs911119 in CST3 as an instrumental variable to investigate the causal role of cystatin C in CVD, including coronary heart disease, ischemic stroke, and heart failure.RESULTSCystatin C concentrations were associated with CVD risk after adjusting for age, sex, and traditional risk factors (relative risk: 1.82 per doubling of cystatin C; 95% confidence interval [CI]: 1.56 to 2.13; p = 2.12 × 10−14). The minor allele of rs911119 was associated with decreased serum cystatin C (6.13% per allele; 95% CI: 5.75 to 6.50; p = 5.95 × 10−211), explaining 2.8% of the observed variation in cystatin C. Mendelian randomization analysis did not provide evidence for a causal role of cystatin C, with a causal relative risk for CVD of 1.00 per doubling cystatin C (95% CI: 0.82 to 1.22; p = 0.994), which was statistically different from the observational estimate (p = 1.6 × 10−5). A causal effect of cystatin C was not detected for any individual component of CVD.CONCLUSIONSMendelian randomization analyses did not support a causal role of cystatin C in the etiology of CVD. As such, therapeutics targeted at lowering circulating cystatin C are unlikely to be effective in preventing CVD.
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