Background Despite well‐recognized differences in the atherosclerotic cardiovascular disease risk between men and women, sex differences in risk factors and sex‐specific mechanisms in the pathophysiology of atherosclerotic cardiovascular disease remain poorly understood. Lipid metabolism plays a central role in the development of atherosclerotic cardiovascular disease. Understanding sex differences in lipids and their genetic determinants could provide mechanistic insights into sex differences in atherosclerotic cardiovascular disease and aid in precise risk assessment. Herein, we examined sex differences in plasma lipidome and heterogeneity in genetic influences on lipidome in men and women through sex‐stratified genome‐wide association analyses. Methods and Results We used data consisting of 179 lipid species measured by shotgun lipidomics in 7266 individuals from the Finnish GeneRISK cohort and sought for replication using independent data from 2045 participants. Significant sex differences in the levels of 141 lipid species were observed ( P <7.0×10 −4 ). Interestingly, 121 lipid species showed significant age‐sex interactions, with opposite age‐related changes in 39 lipid species. In general, most of the cholesteryl esters, ceramides, lysophospholipids, and glycerides were higher in 45‐ to 50‐year‐old men compared with women of same age, but the sex differences narrowed down or reversed with age. We did not observe any major differences in genetic effect in the sex‐stratified genome‐wide association analyses, which suggests that common genetic variants do not have a major role in sex differences in lipidome. Conclusions Our study provides a comprehensive view of sex differences in circulatory lipids pointing to potential sex differences in lipid metabolism and highlights the need for sex‐ and age‐specific prevention strategies.

Background: Rocuronium, a common neuromuscular blocking agent, is mainly excreted unchanged in urine (10e25%) and bile (>70%). Age, sex, liver blood flow, smoking, medical conditions, and ethnic background can affect its pharmacological actions. However, reasons for the wide variation in rocuronium requirements are mostly unknown. We hypothesised that pharmacogenetic factors might explain part of the variation. Methods: One thousand women undergoing surgery for breast cancer were studied. Anaesthesia was maintained with propofol (50e100 mg kg À1 min À1 ) and remifentanil (0.05e0.25 mg kg À1 min À1 ). Neuromuscular block was maintained with rocuronium to keep the train-of-four ratio at 0e10%. DNA was extracted from peripheral blood and genotyped with a next-generation genotyping array. The genome-wide association study (GWAS) was conducted using an additive linear regression model with PLINK software. The FINEMAP tool and data from the Genotype-Tissue Expression project v8 were utilised to study the locus further. Results: The final patient population comprised 918 individuals. Of the clinical variables tested, age, BMI, ASA physical status, and total dose of propofol correlated significantly (all P<0.001) with the rocuronium dose in a linear regression model. The GWAS highlighted one genome-wide significant locus in chromosome 12. The single-nucleotide polymorphisms (SNPs) with the most significant evidence of association were located in or near SLCO1A2. The two top SNPs, rs7967354 (P¼5.3e À11 ) and rs11045995 (P¼1.4e À10 ), and the clinical variables accounted for 41% of the variability in rocuronium dosage. Conclusions: Genetic variation in the gene SLCO1A2, encoding OATP1A2, an uptake transporter, accounted for 4% of the variability in rocuronium consumption. The underlying mechanism remains unknown.

Human plasma lipidome captures risk for cardio-metabolic diseases. To discover new lipid-associated variants and understand link between lipid species and cardiometabolic disorders, we performed univariate and multivariate genome-wide analyses of 179 lipid species in 7,174 Finnish individuals. We further fine-mapped the associated loci, prioritized genes, and examined their disease links in 377,277 FinnGen participants. We identified 495 genome-trait associations in 56 genetic loci including 9 novel loci, with a considerable boost provided by multivariate analysis. For 26 loci, fine-mapping identified variants with a high causal probability, including 14 coding variants indicating likely causal genes. Phenome-wide analysis across 953 disease endpoints in FinnGen revealed disease associations for 40 lipid loci. For 11 known coronary artery disease risk variants, we detected strong associations with lipid species. Our study demonstrates the power of multivariate genetic analysis in correlated lipidomics data and reveals genetic links between diseases and detailed lipid measures beyond standard lipids.