Genetically predicted sex hormone binding globulin and ischemic heart disease in men and women: a univariable and multivariable Mendelian randomization study.
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ABSTRACT:
SUBMITTER: Zhao JV
PROVIDER: S-EPMC8632960 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveRecent evidence supports that leukocyte telomere length (LTL) may be positively associated with healthy living and inversely correlated with the risk of age-related diseases, including osteoporosis. Furthermore, it is important to note that sex hormone-binding globulin (SHBG) levels play a crucial role in the regulation of osteoporosis by influencing the availability of sex hormones. Hence, this study holds significant importance as it aims to unravel the roles of LTL and SHBG levels and determine which one acts as a predominant intermediary factor in influencing osteoporosis. Using Mendelian randomization (MR), we can gain valuable insights into the intricate relationships between aging, sex hormones, and bone health.MethodsUnivariable and multivariable and MR analyses were employed in this study. First, we used genetic variants associated with both LTL, as determined from a study involving 472,174 European participants by Codd et al., and SHBG levels, as identified in a study conducted by Ruth et al. with 370,125 participants, as instrumental variables (IVs). Then we aimed to establish a causal relationship between LTL and SHBG levels and their potential impact on osteoporosis using univariable MR. Finally, we conducted multivariable MR to provide insights into the independent and combined effects of LTL, SHBG levels on osteoporosis risk. We used various MR methods, with the primary analysis employing the inverse-variance weighted (IVW) model.ResultsUnivariable MR analysis reveals a potential causal effect of longer LTL on reduced risk of osteoporosis [odds ratio (OR): 0.85; 95% confidence interval (CI): 0.73-0.99; p = 0.03]. Conversely, higher genetically determined SHBG levels affect the risk of osteoporosis positively. (OR: 1.38; 95% CI: 1.09-1.75; p < 0.01). We observed a negative causal effect for LTL on the occurrence of SHBG (OR: 0.96; 95% CI 0.94-0.98, p < 0.01). After adjustment of using multivariable MR, the causal effect of LTL on osteoporosis (OR: 0.92; 95% CI: 0.84-1.03; p = 0.14), and the effect of SHBG on osteoporosis (OR: 1.43; 95% CI: 1.16-1.75; p < 0.01) were observed.ConclusionLonger LTL may confer a protective effect against osteoporosis. Additionally, the levels of SHBG appear to play a crucial role in mediating the relationship between LTL and osteoporosis. By understanding the interplay between these factors, we can gain valuable insights into the mechanisms underlying bone health and aging and potentially identify new avenues for prevention and intervention strategies.
| S-EPMC10834216 | biostudies-literature
Project description:PurposeSmall dense low-density lipoprotein cholesterol (S-LDL-C) has been suggested as a particularly atherogenic factor for ischemic stroke (IS) in observational studies, but the causality regarding the etiological subtype remains unclear. This study aims to explore the causal effects of small dense low-density lipoprotein cholesterol (S-LDL-C), medium (M-LDL-C) and large (L-LDL-C) subfractions on the lifetime risk of ischemic stroke (IS) and main subtypes using two-sample Mendelian randomization (TSMR) design.MethodsWe identified genetic instruments for S-LDL-C, M-LDL-C and L-LDL-C from a genome-wide association study of 115 082 UK Biobank participants. Summary-level data for genetic association of any ischemic stroke (AIS), large artery stroke (LAS), small vessel stroke (SVS) and cardioembolic stroke (CES) were obtained from MEGASTROKE consortium. Accounting for the pleiotropic effects of triglycerides (TG) and high-density lipoprotein cholesterol (HDL-C), we conducted multivariable TSMR analysis.ResultsIn univariable TSMR, we found a causal association between genetically predicted S-LDL-C and LAS (IVW-FE: odds ratio (OR) = 1.481, 95% confidence interval (CI): 1.117-1.963, P = 0.006, q = 0.076) but not AIS, SVS or CES. No causal effects were observed for M-LDL-C or L-LDL-C in terms of AIS and IS subtype. In multivariable analysis, the causal association between S-LDL-C and LAS remained significant (IVE-MRE: OR = 1.329, 95% CI: 1.106-1.597, P = 0.002).ConclusionsFindings supported a causal association between S-LDL-C and LAS. Further studies are warranted to elucidate the underlying mechanism and clinical benefit of targeting S-LDL-C.
| S-EPMC11317295 | biostudies-literature
Project description:BackgroundKidney function declines faster in men. Testosterone levels may mediate the sex disparity. Correspondingly, levels of sex hormone binding globulin (SHBG), which modulates sex hormones, might also be relevant to the lower kidney function in men. The sex-specific role of SHBG is unclear.MethodsA sex-specific, Mendelian randomization (MR) study provided unconfounded estimates of SHBG levels among the United Kingdom Biobank population. Univariable MR applied 357 single nucleotide polymorphisms (SNPs) in men and 359 SNPs in women. These published SNPs strongly (P<5×10-8) predict SHBG level. They were profiled in 179,916 white British men (6016 patients with CKD) and 212,079 white British women (5958 patients with CKD), to obtain the effect of SHBG on CKD, albuminuria, and eGFR. Multivariable MR controlling for testosterone was used to assess the effect of SHBG on CKD and kidney function independent of testosterone in men.ResultsGenetically predicted higher SHBG was associated with a lower risk of CKD in men (odds ratio [OR], 0.78 per SD; 95% confidence interval [95% CI], 0.65 to 0.93) but had no benefit in women. The effect in men remained in multivariable MR, allowing for testosterone (OR, 0.61; 95% CI, 0.45 to 0.82).ConclusionsGenetically predicted higher SHBG was associated with a lower risk of CKD and better kidney function in men, but not in women, suggesting that SHBG may play a role in CKD specifically in men. Identifying drivers of SHBG and the underlying pathways could provide new insights into CKD prevention and treatment.
| S-EPMC7920164 | biostudies-literature
Project description:BackgroundTo assess the relationship of genetically predicted sexual behavior (age at first sex (AFS) and the number of sexual partners (NSP)) on cardiovascular diseases (CVDs).Methods and resultsWe performed two-sample Mendelian randomization (MR) with publicly available datasets from the UK Biobank and FinnGen Study, and analyzed genome-wide association results for sexual behaviors and twelve types of CVDs. The univariable MR method provided a total effect of AFS and NSP on CVDs, and showed evidence that early AFS rather than NSP was associated with CVDs, including angina pectoris (AP), atrial fibrillation and flutter (AFF), coronary atherosclerosis (CAS), deep vein thrombosis of the lower extremity (DVT-LE), heart failure (HF), hypertension (HTN), ischaemic stroke (IS), and myocardial infarction (MI). Given sex as a social determinant of CVD risk, we used gender-stratified SNPs to investigate gender differences in the development of CVDs. These results showed a stronger causal relationship of AFS on CVDs in females than in males. Further multivariable MR analyses indicated a direct effect after accounting for insomnia, number of days of vigorous physical activity 10 + minutes (VPA 10 + min), and time spent watching television (TV). Two-step MR demonstrated these three risk factors act as a mediator in AFS associated AP/HTN/HF.ConclusionsWe provide evidence that early AFS increased the risk of CVDs. These associations may be partly caused by VPA 10 + min, insomnia, and the time spent on TV. The causality of AFS on CVDs in females was stronger than in males. Conversely, genetically predicted NSP was not associated with CVDs.
| S-EPMC10728475 | biostudies-literature
Project description:BackgroundWhether the positive associations of blood lipids with psychiatric disorders are causal is uncertain. We conducted this two-sample Mendelian randomization (MR) analysis to comprehensively investigate associations of blood lipids with psychiatric disorders.MethodsUnivariable and multivariable models were established for MR analyses. Inverse variance-weighted (IVW) MR was employed as the main approach; weighted median and MR-Egger were used as sensitivity analysis methods. The possibility of violating MR assumptions was evaluated utilizing several sensitivity analyses, including heterogeneity statistics, horizontal pleiotropy statistics, single SNP analysis, leave-one-out analysis and MR-PRESSO analysis. As instrumental variables, we screened 362 independent single-nucleotide polymorphisms (SNP) related to blood lipids from a recent genome-wide association study involving 76,627 individuals of European ancestry, with a genome-wide significance level of p < 5 × 10- 8. Summary-level information for the six psychiatric disorders was extracted from Psychiatric Genomics Consortium and Alzheimer Disease Genetics Consortium.ResultsWe observed eight significant associations in univariable MR analysis, four of which were corroborated by multivariable MR (MVMR) analysis modified for the other three lipid traits: high-density lipoprotein cholesterol (HDL-C) level with the risk of PTSD (OR = 0.91, 95% CI = 0.85-0.97, p = 0.002) and AD (OR = 0.79, 95% CI = 0.71-0.88, p < 0.001) and triglycerides (TG) level with the risk of MDD (OR = 1.02, 95% CI = 1.003-1.03, p = 0.01) and panic disorder (OR = 0.83, 95% CI = 0.74-0.92, p < 0.001). In addition, four associations were not significant in MVMR analysis after adjustment for three lipid traits: total cholesterol (TC) level with the risk of PTSD, low-density lipoprotein cholesterol (LDL-C) level with the risk of MDD and AD and TG level with the risk of AD.ConclusionsOur results show that blood lipids and psychiatric disorders may be related in a causal manner. This shows that abnormal blood lipid levels may act as reliable biomarker of psychiatric disorders and as suitable targets for their prevention and treatment.
| S-EPMC10585856 | biostudies-literature
Project description:ObjectiveIn this study, we employed a Mendelian randomization (MR) approach to investigate the independent causal associations of six body composition traits with gestational diabetes mellitus (GDM).MethodsGenome-wide significant levels (P < 10 × 5-8 ) of single nucleotide polymorphisms associated with body water mass, total protein, whole body fat-free mass, weight, whole body fat mass, and body fat percentage were used as instrumental variables. Data on GDM were obtained from the FinnGen Consortium, and both univariable and multivariable Mendelian randomization were performed. We utilized five different analytical methods including inverse-variance weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode to assess the robustness of the results.ResultsWith univariable Mendelian randomization, the risk of GDM increased per 1-standard deviation (SD) increase in weight (ORweight = 1.297, P = 3.06 × 10-5 ), whole body fat mass (ORwhole body fat mass = 1.408, P = 1.32 × 10-6 ), and the risk of GDM increased per percent increase in body fat percentage (ORbody fat percentage = 1.661, P = 1.01 × 10-8 ). Total protein had a protective effect on the risk of GDM (ORtotal protein = 0.880, P = 0.048). However, there was no significant causal association between increases in body water mass and whole body fat-free mass per SD and the risk of GDM. Causal associations between weight, whole body fat mass, body fat percentage, and total protein with GDM were reduced to null in multivariable Mendelian randomization.ConclusionThe present study furnishes genetic evidence to elucidate the causal relationship between body composition traits and GDM. Additionally, further studies are imperative to establish a causal connection between body composition traits and gestational diabetes mellitus.
| S-EPMC10906022 | biostudies-literature
Project description:BackgroundMental health has been found to be associated with risk of osteoarthritis (OA), but the causal relationship was not fully clarified.MethodsTwo-sample Mendelian randomization (MR) study was conducted to investigate the causal relationship between neuroticism (n = 329,821) and the two most frequently affected parts of osteoarthritis (OA) (knee OA: case/control =24,955/378,169; hip OA: case/control = 15,704/378,169) using large scale summary genome-wide association study (GWAS) data. Inverse variance weighted (IVW), weighted median, and MR-Egger were used to estimate the causal effects. Multiple sensitivity analyses were conducted to examine the robustness of the causal estimates. Multivariable MR analysis was used to estimate the direct effects of neuroticism on OA after accounting for the other OA risk factors. Two-step MR approach was employed to explore the potential mediators of the causal relationship.ResultsUnivariable MR analysis indicated that 1-SD increase in genetically predicted neuroticism score was associated with an increased risk of knee OA (IVW: OR, 1.17; 95% CI, 1.087-1.26; p = 2.72E-05) but not with hip OA. The causal effects remained significant after accounting for the effects of BMI, alcohol drinking, and vigorous physical activity but were attenuated with adjustment of smoking. Further mediation analysis revealed that smoking initiation mediated a significant proportion of the causal effects of neuroticism on knee OA (proportion of mediation effects in total effects: 22.3%; 95% CI, 5.9%-38.6%; p = 7.60E-03).ConclusionsNeuroticism has significant causal effects on knee OA risk. Smoking might partly mediate the causal relationship. Further studies were warranted to explore the underlying mechanisms and potential use of neuroticism management for OA treatment.
| S-EPMC10957734 | biostudies-literature
Project description:At the time of cancer diagnosis, body mass index (BMI) is inversely correlated with lung cancer risk, which may reflect reverse causality and confounding due to smoking behavior. We used two-sample univariable and multivariable Mendelian randomization (MR) to estimate causal relationships of BMI and smoking behaviors on lung cancer and histological subtypes based on an aggregated genome-wide association studies (GWASs) analysis of lung cancer in 29 266 cases and 56 450 controls. We observed a positive causal effect for high BMI on occurrence of small-cell lung cancer (odds ratio (OR) = 1.60, 95% confidence interval (CI) = 1.24-2.06, P = 2.70 × 10-4 ). After adjustment of smoking behaviors using multivariable Mendelian randomization (MVMR), a direct causal effect on small cell lung cancer (ORMVMR = 1.28, 95% CI = 1.06-1.55, PMVMR = .011), and an inverse effect on lung adenocarcinoma (ORMVMR = 0.86, 95% CI = 0.77-0.96, PMVMR = .008) were observed. A weak increased risk of lung squamous cell carcinoma was observed for higher BMI in univariable Mendelian randomization (UVMR) analysis (ORUVMR = 1.19, 95% CI = 1.01-1.40, PUVMR = .036), but this effect disappeared after adjustment of smoking (ORMVMR = 1.02, 95% CI = 0.90-1.16, PMVMR = .746). These results highlight the histology-specific impact of BMI on lung carcinogenesis and imply mediator role of smoking behaviors in the association between BMI and lung cancer.
| S-EPMC7845289 | biostudies-literature
Project description:BackgroundTelomere length has long been recognized as a valuable biomarker of aging and is inversely correlated with chronological age. Various lifestyle factors have been implicated in telomere shortening or preservation; however, the association between lifestyle factors and telomere length remains controversial. To address this issue, we conducted a Mendelian randomization (MR) analysis to investigate the potential causal associations between multiple lifestyle factors and telomere length.MethodsIndependent genetic variants strongly associated with lifestyle factors (tobacco smoking, sleep duration, insomnia, and physical activity) were selected as instrumental variables from corresponding genome-wide association studies (GWASs). Summary-level data for telomere length was obtained from a GWAS comprising 472,174 European ancestries. Univariable and multivariable MR analyses were performed to assess the relationships.ResultsThe genetic liability to lifetime smoking was robustly associated with shorter telomere length (odd ratio [OR]: 0.882; 95% confidence interval [CI]: 0.847-0.918). Genetically predicted insomnia was also linked to shorter telomere length (OR: 0.972; 95% CI: 0.959-0.985), while no significant association was observed between sleep duration and telomere length. Furthermore, a suggestive association was found between moderate-to-vigorous physical activity and longer telomere length (OR: 1.680; 95% CI: 1.115-2.531). In multivariable MR analyses, adjusting for potential mediators such as body mass index, type 2 diabetes, alcohol consumption, and alcohol use disorder, the associations of lifetime smoking and insomnia with telomere length remained robust.ConclusionOur findings suggest that smoking and insomnia may contribute to telomere shortening, while physical activity may play a role in telomere length maintenance. These findings underscore the importance of managing positive risk factors and adopting a healthy lifestyle to promote telomere health.
| S-EPMC10870665 | biostudies-literature
Project description:BackgroundPrevious studies have linked gut microbiota with cancer etiology, but the associations for specific gut microbiota are causal or owing to bias remain to be elucidated.MethodsWe performed a two-sample Mendelian randomization (MR) analysis to assess the causal effect of gut microbiota on cancer risk. Five common cancers, including breast, endometrial, lung, ovarian, and prostate cancer as well as their subtypes (sample sizes ranging from 27,209 to 228,951) were included as the outcomes. Genetic information for gut microbiota was obtained from a genome-wide association study (GWAS) comprising 18,340 participants. In univariable MR (UVMR) analysis, the inverse variance weighted (IVW) method was conducted as the primary method, with the robust adjusted profile scores, weighted median, and MR Egger used as supplementary methods for causal inference. Sensitivity analyses including the Cochran Q test, Egger intercept test, and leave-one-out analysis were performed to verify the robustness of the MR results. Multivariable MR (MVMR) was performed to evaluate the direct causal effects of gut microbiota on the risk of cancers.ResultsUVMR detected a higher abundance of genus Sellimonas predicted a higher risk of estrogen receptor-positive breast cancer (OR = 1.09, 95% CI 1.05-1.14, p = 2.01 × 10-5 ), and a higher abundance of class Alphaproteobacteria was associated with a lower risk of prostate cancer (OR = 0.84, 95% CI 0.75-0.93, p = 1.11 × 10-3 ). Sensitivity analysis found little evidence of bias in the current study. MVMR further confirmed that genus Sellimonas exerted a direct effect on breast cancer, while the effect of class Alphaproteobacteria on prostate cancer was driven by the common risk factors of prostate cancer.ConclusionOur study implies the involvement of gut microbiota in cancer development, which provides a novel potential target for cancer screening and prevention, and might have an implication for future functional analysis.
| S-EPMC10225193 | biostudies-literature