This study mapped the personality and genetics of risky excitement-seekers focusing on skydiving behavior. We compared 298 skydivers to 298 demographically matched controls across the NEO Personality Inventory-3 domains, facets, and 240 items. The most significant item-level effects were aggregated into a poly-item score of skydiving-associated personality markers (Study 1), where higher scores describe individuals who enjoy risky situations but have no self-control issues. The skydiving-associated personality marker score was associated with greater physical activity, higher rate of traumatic injuries, and better mental health in a sample of 3558 adults (Study 2). From genetic perspective, we associated skydiving behavior with 19 candidate variants that have previously been linked to excitement-seeking (Study 1). Polymorphisms in the SERT gene were the strongest predictors of skydiving, but the false discovery rate-adjusted (FDR-adjusted) p-values were non-significant. In Study 2, we predicted the skydiving-associated personality marker score and E5: Excitement-seeking from multiple risk-taking polygenic scores, using publicly available summary data from genome-wide association studies. While E5: Excitement-seeking was most strongly predicted by general risk tolerance and risky behaviors’ polygenic scores, the skydiving-associated personality marker score was most strongly associated with the adventurousness polygenic scores. Phenotypic and polygenic scores associations suggest that skydiving is a specific—perhaps more functional—form of excitement-seeking, which may nevertheless lead to physical injuries.

Background/Objectives: Metabolomics, in combination with genetic data, is a powerful approach to study the biochemical consequences of genetic variation. We assessed the impact of human gene knockouts (KOs) on the metabolite levels of Estonia Biobank (EstBB) participants and integrated the results with electronic health record data. Methods: In 150,000 EstBB genotyped participants, we identified 723 KOs with 152 different predicted loss of function (pLoF) variants in 115 genes. For those KOs and 258 controls, 1387 metabolites were profiled using ultra-high-performance liquid chromatography–tandem mass spectrometry. Results: We identified 48 associations linking rare pLoF variants in 22 genes to 43 metabolites. Out of 48 associations, 27 (56%) were found in genes that cause inborn errors of metabolism. The top associations identified in our analysis included genes and metabolites involved in the degradation pathway of the pyrimidine bases uracil and thymine (DPYD and UPB1). We found DPYD gene KOs to be associated with elevated levels of Uracil, confirming that DPD-deficiency is a leading cause of severe 5-Fluorouracil toxicity. Overall, 54% of reported associations are gene targets of approved drugs or bioactive drug-like compounds. Conclusions: Our findings contribute to assessing the impact of human KOs on metabolite levels and offer insights into gene functions, disease mechanism, and drug target validation.