Aims Sleep disorders are associated with increased risk of cardiometabolic diseases in observational studies, but the causality remains unclear. In this study, we leveraged two-sample Mendelian randomization (MR) analyses to assess the causal associations of self-reported daytime napping, daytime sleepiness, and other sleep phenotypes with cardiometabolic diseases including ischemic stroke (IS), coronary artery disease (CAD), heart failure (HF), and type 2 diabetes mellitus (T2DM). Methods We selected genetic variants as instrumental variables for self-reported daytime napping, daytime sleepiness, morning person, insomnia, short sleep duration, and long sleep duration from European-descent genome-wide association studies (GWASs). Summary statistics for cardiometabolic diseases originated from four different GWASs with a total of 2,500,086 participants. We used the inverse-variance weighted method to explore the role of self-reported sleep phenotypes on the etiology of cardiometabolic diseases in the main analyses, followed by several sensitivity analyses for robustness validation. Results Genetically predicted self-reported daytime napping (T2DM: OR, 1.56 [95% CI, 1.21-2.02]), insomnia (IS: OR, 1.07 [1.04-1.11]; CAD: OR, 1.13 [1.08-1.17]; HF: OR, 1.10 [1.07-1.14]; T2DM: OR, 1.16 [1.11-1.22]) and short sleep duration (CAD: OR, 1.37 [1.21-1.55]) were causally associated with elevated risk of cardiometabolic diseases. Moreover, genetically determined self-reported daytime sleepiness (CAD: OR, 2.05 [1.18-3.57]; HF: OR, 1.82 [1.15-2.87]) and morning person (HF: 1.06 OR, [1.01-1.11]) had potential detrimental effect on cardiometabolic risks. Conclusions Self-reported daytime napping, insomnia, and short sleep duration had causal roles in the development of cardiometabolic diseases, while self-reported daytime sleepiness and morning person was the potential risk factor for cardiometabolic diseases.
Background Preclinical and epidemiological studies indicate a potential chemopreventive role of low-density lipoprotein cholesterol (LDL-C) -lowering drugs in the risks of breast cancer and prostate cancer, but the causality remains unclear. We aimed to evaluate the association of genetically proxied inhibition of 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase, Niemann-Pick C1-Like 1 (NPC1L1), and proprotein convertase subtilisin/kexin type 9 (PCSK9) with risks of breast cancer and prostate cancer using a two-sample Mendelian randomization (MR) method. Methods Single-nucleotide polymorphisms (SNPs) in HMGCR, NPC1L1, and PCSK9 associated with LDL-C in a genome-wide association study (GWAS) meta-analysis from the Global Lipids Genetics Consortium (GLGC; up to 188,577 European individuals) were used to proxy inhibition of HMG-CoA reductase, NPC1L1, and PCSK9. Summary statistics with outcomes were obtained from a GWAS meta-analysis of the Breast Cancer Association Consortium (BCAC; 228,951 European females) and a Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL; 140,254 European males) consortium. SNPs were combined into multiallelic models and MR estimates representing lifelong inhibition of targets were generated using the inverse-variance weighted method. Results Genetically proxied inhibition of HMG-CoA reductase (OR: 0.84; 95% CI 0.74–0.95; P = 0.005) and NPC1L1 (OR: 0.72; 95% CI 0.58–0.90; P = 0.005) equivalent to a 1-mmol/L (38.7 mg/dL) reduction in LDL-C was associated with reduced breast cancer risk. There were no significant associations of genetically proxied inhibition of PCSK9 with breast cancer. In contrast, genetically proxied inhibition of PCSK9 (OR: 0.81; 95% CI 0.73–0.90; P < 0.001) but not HMG-CoA reductase and NPC1L1 was negatively associated with prostate cancer. In the secondary analysis, genetically proxied inhibition of HMG-CoA reductase (OR: 0.82; 95% CI 0.71–0.95; P = 0.008) and NPC1L1 (OR: 0.66; 95% CI 0.50–0.86; P = 0.002) was associated with estrogen receptor-positive breast cancer, whereas there was no association of HMG-CoA reductase and NPC1L1 with estrogen receptor-negative breast cancer. Conclusions Genetically proxied inhibition of HMG-CoA reductase and NPC1L1 was significantly associated with lower odds of breast cancer, while genetically proxied inhibition of PCSK9 was associated with reduced risk of prostate cancer. Further randomized controlled trials are needed to confirm the respective roles of these LDL-C-lowering drugs in breast cancer and prostate cancer.
Background Breast cancer is the most common cancer among women with limited treatment options. To identify promising drug targets for breast cancer, we conducted a systematical Mendelian randomization (MR) study to screen blood metabolome for potential causal mediators of breast cancer and further predict target-mediated side effects. Methods We selected 112 unique blood metabolites from 3 large-scale European ancestry-based genome-wide association studies (GWASs) with a total of 147,827 participants. Breast cancer data were obtained from a GWAS in the Breast Cancer Association Consortium (BCAC), involving 122,977 cases and 105,974 controls of European ancestry. We conducted MR analyses to systematically assess the associations of blood metabolites with breast cancer, and a phenome-wide MR analysis was further applied to ascertain the potential on-target side effects of metabolite interventions. Results Two blood metabolites were identified as the potential causal mediators for breast cancer, including high-density lipoprotein cholesterol (HDL-C) (odds ratio [OR], 1.09; 95% confidence interval [CI], 1.06–1.12; P = 9.67 × 10−10) and acetate (OR, 1.24; 95% CI, 1.13–1.37; P = 1.35 × 10−5). In the phenome-wide MR analysis, lowering HDL-C might have deleterious effects on the risk of the circulatory system and foreign body injury, while lowering acetate had deleterious effects on mental disorders disease. Conclusions The present systematic MR analysis revealed that HDL-C and acetate may be the causal mediators in the risk of developing breast cancer. Side-effect profiles were characterized to help inform drug target prioritization for breast cancer prevention. HDL-C and acetate might be promising drug targets for preventing breast cancer, but they should be applied under weighting advantages and disadvantages.
ObjectiveAlzheimer's disease (AD) is the most common degenerative neurological disorder with limited therapeutic options. Therefore, it is particularly important to explore the potential biomarkers implicated in the occurrence and progression of AD prior to clinical testing.MethodsWe selected 119 unique blood metabolites from 3 metabolome genome‐wide association studies (GWASs) with 147,827 European participants. Summary data about AD were obtained from a GWAS meta‐analysis with 63,926 European individuals from the International Genomics of Alzheimer's Project. MR analyses were performed to assess the associations of blood metabolites with AD, and a phenome‐wide MR analysis was further applied to ascertain the potential on‐target side effects of metabolite interventions.ResultsFour metabolites were identified as causal mediators for AD, including epiandrosterone sulfate (odds ratio [OR] per SD increase: 0.60; 95% confidence interval [CI]: 0.51–0.71; p = 6.14 × 10−9), 5alpha‐androstan‐3beta‐17beta‐diol disulfate (OR per SD increase: 0.69; 95% CI: 0.57–0.84; p = 1.98 × 10−4), sphingomyelin (OR per SD increase: 2.53; 95% CI: 1.78–3.59; p = 2.10 × 10−7), and glutamine (OR per SD increase: 0.83; 95% CI: 0.77–0.89; p = 2.09 × 10−6). Phenome‐wide MR analysis showed that epiandrosterone sulfate, 5alpha‐androstan‐3beta‐17beta‐diol disulfate and sphingomyelin mediated the risk of multiple diseases, and glutamine had beneficial effects on the risk of 4 diseases.InterpretationGenetically predicted increased epiandrosterone sulfate, 5alpha‐androstan‐3beta‐17beta‐diol disulfate, and glutamine might be associated with a decreased risk of AD, while sphingomyelin was associated with an increased risk. Side‐effect profiles were characterized to help inform drug target prioritization, and glutamine might be a promising target for the prevention and treatment of AD with no predicted detrimental side effects. ANN NEUROL 2022;92:756–767
Background and Objectives:Thrombomodulin has been suggested to be implicated in ischemic stroke due to its anticoagulant, anti-inflammatory, and cytoprotective properties. We aimed to investigate the associations of plasma thrombomodulin levels with clinical outcomes after ischemic stroke in a multicenter prognostic cohort study.Methods:Our multicenter prognostic cohort study included 3532 Chinese ischemic stroke patients from the China Antihypertensive Trial in Acute Ischemic Stroke (CATIS). All patients were followed up at 3 months after ischemic stroke onset. The primary outcome was the composite outcome of death and major disability (modified Rankin scale [mRS] score ≥3) at 3 months after ischemic stroke. Secondary outcomes included major disability (mRS score, 3-5), vascular events, and the ordered 7-level categorical score of the mRS.Results:During 3 months of follow-up, 867 participants experienced primary outcome. After multivariate adjustment, the adjusted odds ratios or hazard ratios associated with highest quartile of plasma thrombomodulin were 0.75 (95% CI, 0.59-0.97; ptrend=0.029) for primary outcome, 0.73 (95% CI, 0.56-0.94; ptrend=0.028) for major disability, and 0.80 (95% CI, 0.42-1.51; ptrend=0.232) for vascular events. In addition, a significantly better shift in the distribution of mRS score was observed with higher thrombomodulin quartiles (ptrend=0.005). Multivariable-adjusted spline regression model showed a linear relationship between plasma thrombomodulin and the risk of primary outcome (p for linearity=0.027). Subgroup analyses further confirmed these associations.Discussion:Increased plasma thrombomodulin levels at baseline were associated with decreased risks of adverse clinical outcomes at 3 months after ischemic stroke, suggesting a protective role of thrombomodulin in the development of ischemic stroke. Further studies from various populations are needed to replicate our findings.
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