ATP-citrate lyase as a therapeutic target in chronic kidney disease: a Mendelian Randomization analysis

Background: ATP-citrate lyase (ACLY) inhibition is a promising therapeutic target for dyslipidemia, atherosclerotic cardiovascular disease, non-alcoholic steatohepatitis, and metabolic syndrome. Genetic analysis of its role in chronic kidney disease (CKD) has not been performed. Methods: We constructed a genetic instrument by selecting variants associated with ACLY expression level in the expression quantitative trait loci genetics consortium (eQTLGen) that includes blood samples from 31,684 participants. In a two-sample Mendelian randomization analysis, we then evaluated the effect of genetically predicted ACLY expression on risk of CKD, estimated glomerular filtration rate (eGFR), and microalbuminuria using the CKD Genetics consortium (CKDGen), United Kingdom biobank, and the Finnish Genetics consortium (FinnGen) totaling 66,396 CKD cases and 958,517 controls. Results: ACLY is constitutively expressed in all cell types including in whole blood. The genetic instrument included 13 variants and explained 1.5% of variation in whole blood ACLY gene expression. A 34% reduction in genetically predicted ACLY expression was associated with a 0.04 mmol/L reduced low-density lipoprotein cholesterol (P = 3.4 x 10-4) and a 9% reduced risk of CKD (stage 3,4,5, dialysis or eGFR below 60 ml/min/1.73m2) (OR = 0.91, 95% C.I. 0.85-0.98, P = 0.008), but no association was observed with eGFR nor microalbuminuria. Conclusion: Mendelian Randomization analysis provides cautious optimism regarding the possibility of ACLY as a therapeutic target for CKD.

Genetic and phenotypic analysis of the causal relationship between aging and COVID-19

Background Epidemiological studies revealed that the elderly and those with comorbidities are most affected by COVID-19, but it is important to investigate shared genetic mechanisms between COVID-19 risk and aging. Methods We conducted a multi-instrument Mendelian Randomization analysis of multiple lifespan-related traits and COVID-19. Aging clock models were applied to the subjects with different COVID-19 conditions in the UK-Biobank cohort. We performed a bivariate genomic scan for age-related COVID-19 and Mendelian Randomization analysis of 389 immune cell traits to investigate their effect on lifespan and COVID-19 risk. Results We show that the genetic variation that supports longer life is significantly associated with the lower risk of COVID-19 infection and hospitalization. The odds ratio is 0.31 (P = 9.7 × 10−6) and 0.46 (P = 3.3 × 10−4), respectively, per additional 10 years of life. We detect an association between biological age acceleration and future incidence and severity of COVID-19 infection. Genetic profiling of age-related COVID-19 infection indicates key contributions of Notch signaling and immune system development. We reveal a negative correlation between the effects of immune cell traits on lifespan and COVID-19 risk. We find that lower B-cell CD19 levels are indicative of an increased risk of COVID-19 and decreased life expectancy, which is further validated by COVID-19 clinical data. Conclusions Our analysis suggests that the factors that accelerate aging lead to an increased COVID-19 risk and point to the importance of Notch signaling and B cells in both. Interventions that target these factors to reduce biological age may reduce the risk of COVID-19.