Damia Noce, Martin Gögele, Christine Schwienbacher, Giulia Caprioli, Alessandro De Grandi, Luisa Foco, Stefan Platzgummer, Peter P. Pramstaller, Cristian Pattaro

After the success of genome-wide association studies to uncover complex trait loci, attempts to explain the remaining genetic heritability (h (2)) are mainly focused on unraveling rare variant associations and gene-gene or gene-environment interactions. Little attention is paid to the possibility that h (2) estimates are inflated as a consequence of the epidemiological study design. We studied the time series of 54 biochemical traits in 4373 individuals from the Cooperative Health Research In South Tyrol (CHRIS) study, a pedigree-based study enrolling ten participants/day over several years, with close relatives preferentially invited within the same day. We observed distributional changes of measured traits over time. We hypothesized that the combination of such changes with the pedigree structure might generate a shared-environment component with consequent h (2) inflation. We performed variance components (VC) h (2) estimation for all traits after accounting for the enrollment period in a linear mixed model (two-stage approach). Accounting for the enrollment period caused a median h (2) reduction of 4%. For 9 traits, the reduction was of >20%. Results were confirmed by a Bayesian Markov chain Monte Carlo analysis with all VCs included at the same time (one-stage approach). The electrolytes were the traits most affected by the enrollment period. The h (2) inflation was independent of the h (2) magnitude, laboratory protocol changes, and length of the enrollment period. The enrollment process may induce shared-environment effects even under very stringent and standardized operating procedures, causing h (2) inflation. Including the day of participation as a random effect is a sensitive way to avoid overestimation.