Genetic evidence implicating natriuretic peptide receptor-3 in cardiovascular disease risk: a Mendelian randomization study

Abstract

Background C-type natriuretic peptide (CNP) is a known target for promoting growth and has been implicated as a therapeutic opportunity for the prevention and treatment of cardiovascular disease (CVD). This study aimed to explore the effect of CNP on CVD risk using the Mendelian randomization (MR) framework. Methods Instrumental variables mimicking the effects of pharmacological intervention on CNP were identified as uncorrelated genetic variants located in the genes coding for its primary receptors, natriuretic peptide receptors-2 and 3 (NPR2 and NPR3), that associated with height. We performed MR and colocalization analyses to investigate the effects of NPR2 signalling and NPR3 function on CVD outcomes and risk factors. MR estimates were compared to those obtained when considering height variants from throughout the genome. Results Genetically-proxied reduced NPR3 function was associated with a lower risk of CVD, with odds ratio (OR) 0.74 per standard deviation (SD) higher NPR3-predicted height, and 95% confidence interval (95% CI) 0.64–0.86. This effect was greater in magnitude than observed when considering height variants from throughout the genome. For CVD subtypes, similar MR associations for NPR3-predicted height were observed when considering the outcomes of coronary artery disease (0.75, 95% CI 0.60–0.92), stroke (0.69, 95% CI 0.50–0.95) and heart failure (0.77, 95% CI 0.58–1.02). Consideration of CVD risk factors identified systolic blood pressure (SBP) as a potential mediator of the NPR3-related CVD risk lowering. For stroke, we found that the MR estimate for NPR3 was greater in magnitude than could be explained by a genetically predicted SBP effect alone. Colocalization results largely supported the MR findings, with no evidence of results being driven by effects due to variants in linkage disequilibrium. There was no MR evidence supporting effects of NPR2 on CVD risk, although this null finding could be attributable to fewer genetic variants being identified to instrument this target. Conclusions This genetic analysis supports the cardioprotective effects of pharmacologically inhibiting NPR3 receptor function, which is only partly mediated by an effect on blood pressure. There was unlikely sufficient statistical power to investigate the cardioprotective effects of NPR2 signalling.

The non‐causative role of abnormal serum uric acid in intervertebral disc degeneration: A Mendelian randomization study

“…13,21 We used summary-level data from large genome-wide association studies (GWAS) for serum uric acid and IDD, ensuring sufficient statistical power to detect causal effects. 22 Furthermore, the genetic variants used as instrumental variables were strong predictors of serum uric acid levels, as evidenced by the F-statistics well above the threshold of 10. 23 One potential concern in Mendelian randomization studies is the possibility of horizontal pleiotropy, where genetic variants affect the outcome through pathways other than the exposure.…”

“… 13 , 21 We used summary‐level data from large genome‐wide association studies (GWAS) for serum uric acid and IDD, ensuring sufficient statistical power to detect causal effects. 22 Furthermore, the genetic variants used as instrumental variables were strong predictors of serum uric acid levels, as evidenced by the F‐statistics well above the threshold of 10. 23 …”

Genetic assessment of efficacy and safety profiles of coagulation cascade proteins identifies Factors II and XI as actionable anticoagulant targets

“…We used the default priors for the analysis. We used a posterior probability H4 > 0.50 as a threshold for evidence of colocalization signifying that colocalisation is more likely than any other scenario combined (Cronjé et al 2023).…”

Associations of genetically determined circulating proteins with breast cancer risk or survival

“…We next performed linkage disequilibrium (LD) clumping and identi ed nearly independent genetic instrument variables using plink software (V1.9). LD was de ned as r 2 < 0.1 within the clumping distance of 100kb, and SNPs with LD were excluded (Cronjé et al 2023). The F value of each instrumental variable was calculated using this formula: F= (R 2 : interpretability of instrumental variables, N: sample size) and R 2 could be calculated using this formula: (EAF: effect elle frequency, β: beta size) (Palmer et al 2012).…”