Corrigendum: Genetically Predicted Fibroblast Growth Factor 23 and Major Cardiovascular Diseases, Their Risk Factors, Kidney Function, and Longevity: A Two-Sample Mendelian Randomization Study.
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ABSTRACT:
SUBMITTER: Liang Y
PROVIDER: S-EPMC8632056 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionFibroblast growth factor 23 (FGF23), a potential biomarker for kidney function, is related to cardiovascular disease (CVD) and diabetes, although it is unclear whether the relation is causal. This study evaluated the associations of genetically predicted FGF23 with major CVDs, their risk factors, kidney function, and longevity using Mendelian randomization (MR).MethodsThis is a two-sample MR study using summary statistics from large genome-wide association studies. Primary outcomes included coronary artery disease (CAD), myocardial infarction, heart failure, and atrial fibrillation. Secondary outcomes included cardiovascular risk factors, kidney function, and longevity. We used four single-nucleotide polymorphisms (SNPs) predicting FGF23, excluding rs2769071 in the ABO gene, which likely violates the MR exclusion-restriction assumption. We used inverse-variance weighted (IVW) as the primary statistical method to assess associations of FGF23 with the outcomes. Sensitivity analyses included weighted median (WM) and MR-Egger. We repeated the analyses including all five SNPs. Last, we validated the positive findings from the main analyses in a smaller study, i.e., FinnGen.ResultsUsing IVW, genetically predicted higher FGF23 was inversely associated with risk of CAD [odds ratio (OR): 0.69 per logtransformed FGF23 (pg/ml) increase, 95% confidence interval (CI): 0.52-0.91] and type 2 diabetes mellitus (T2DM) (OR: 0.70, 95% CI: 0.52-0.96), but not with the other outcomes. The WM and MR-Egger estimates were directionally consistent.ConclusionThis study suggests that genetically predicted higher FGF23 may be protective against CAD and T2DM. Future studies should explore the underlying mechanisms related to the potential protective effect of FGF23. FGF23 was unlikely a cause of poorer renal function.
| S-EPMC8343174 | biostudies-literature
Project description:This study used a Mendelian randomization (MR) approach to investigate the causal relationship between genetically predicted endometriosis (EMS) and breast cancer risk. A total of 122,977 cases and 105,974 controls were included in the analysis, with gene-level summary data obtained from the Breast Cancer Association Consortium (BCAC). An inverse variance-weighting approach was applied to assess the causal relationship between EMS and breast cancer risk, and weighted median and MR-Egger regression methods were used to evaluate pleiotropy. Results showed a causal relationship between EMS and a decreased risk of overall breast cancer (odds ratio [OR] 0.95; 95% CI 0.90-0.99, p = 0.02). Furthermore, EMS was associated with a lower risk for estrogen receptor (ER)-positive breast cancer in a subgroup analysis based on immunohistochemistry type (OR 0.91; 95% CI 0.86-0.97, p = 0.005). However, there was no causal association between ER-negative breast cancer and survival (OR 1.00; 95% CI 0.94-1.06, p = 0.89). Pleiotropy was not observed. These findings provide evidence of a relationship between EMS and reduced breast cancer risk in invasive breast cancer overall and specific tissue types, and support the results of a previous observational study. Further research is needed to elucidate the mechanisms underlying this association.
| S-EPMC10570324 | biostudies-literature
Project description:BackgroundAlthough numerous observational studies have indicated a potential association between autoimmune diseases, such as rheumatoid arthritis (RA) and alopecia areata (AA), the research reports lack a clear causal relationship. In this study, our objective is to utilize the Mendelian randomization (MR) design to examine the potential causal association between RA and AA.MethodsTo investigate the causal relationship between RA and AA, we utilized large-scale gene aggregation data from genome-wide association studies (GWAS), including RA (n=58,284) and AA (n=361,822) based on previous observational studies. In our analysis, we mainly employed the inverse variance-weighted (IVW) method of the random effects model, supplemented by the weighted median (WM) method and the MR Egger method.ResultsThe findings from the IVW methods revealed a significant association between genetically predicted RA and an increased likelihood of AA, as evidenced by an odds ratio of 1.21 (95%CI = 1.11-1.32; P < 0.001. Both the WM method and MR-Egger regression consistently showed significant directional outcomes (Both P < 0.05), indicating a robust association between RA and AA. Additionally, both the funnel plot and the MR-Egger intercepts provided evidence of the absence of directional pleiotropy, suggesting that the observed association is not influenced by other common genetic factors.ConclusionsThe results of the study suggest a possible link between genetically predicted RA and AA. This finding highlights the importance for individuals diagnosed with RA to remain vigilant and aware of the potential development of AA. Regular monitoring and early detection can be crucial in managing and addressing this potential complication.
| S-EPMC10644376 | biostudies-literature
Project description:Background/Aim: Several observational studies showed a significant association between elevated iron status biomarkers levels and sepsis with the unclear direction of causality. A two-sample bidirectional mendelian randomization (MR) study was designed to identify the causal direction between seven iron status traits and sepsis. Methods: Seven iron status traits were studied, including serum iron, ferritin, transferrin saturation, transferrin, hemoglobin, erythrocyte count, and reticulocyte count. MR analysis was first performed to estimate the causal effect of iron status on the risk of sepsis and then performed in the opposite direction. The multiplicative random-effects and fixed-effects inverse-variance weighted, weighted median-based method and MR-Egger were applied. MR-Egger regression, MR pleiotropy residual sum and outlier (MR-PRESSO), and Cochran's Q statistic methods were used to assess heterogeneity and pleiotropy. Results: Genetically predicted high levels of serum iron (OR = 1.21, 95%CI = 1.13-1.29, p = 3.16 × 10-4), ferritin (OR = 1.32, 95%CI = 1.07-1.62, p =0.009) and transferrin saturation (OR = 1.14, 95%CI = 1.06-1.23, p = 5.43 × 10-4) were associated with an increased risk of sepsis. No significant causal relationships between sepsis and other four iron status biomarkers were observed. Conclusions: This present bidirectional MR analysis suggested the causal association of the high iron status with sepsis susceptibility, while the reverse causality hypothesis did not hold. The levels of transferrin, hemoglobin, erythrocytes, and reticulocytes were not significantly associated with sepsis. Further studies will be required to confirm the potential clinical value of such a prevention and treatment strategy.
| S-EPMC8639868 | biostudies-literature
Project description:BackgroundObservational studies have hinted at a correlation between the gut microbiota and spinal pain (SP). However, the impact of the gut microbiota on SP remains inconclusive.MethodsIn this study, we employed a two-sample Mendelian randomization (MR) analysis to explore the causal relationship between the gut microbiota and SP, encompassing neck pain (NP), thoracic spine pain (TSP), low back pain (LBP), and back pain (BP). The compiled gut microbiota data originated from a genome-wide association study (GWAS) conducted by the MiBioGen consortium (n = 18,340). Summary data for NP were sourced from the UK Biobank, TSP from the FinnGen Biobank, and LBP from both the UK Biobank and FinnGen Biobank. Summary data for BP were obtained from the UK Biobank. The primary analytical approach for assessing causal relationships was the Inverse Variance Weighted (IVW) method, supplemented by various sensitivity analyses to ensure result robustness.ResultsThe IVW analysis unveiled 37 bacterial genera with a potential causal relationship to SP. After Benjamini-Hochberg corrected test, four bacterial genera emerged with a strong causal relationship to SP. Specifically, Oxalobacter (OR: 1.143, 95% CI 1.061-1.232, P = 0.0004) and Tyzzerella 3 (OR: 1.145, 95% CI 1.059-1.238, P = 0.0007) were identified as risk factors for LBP, while Ruminococcaceae UCG011 (OR: 0.859, 95% CI 0.791-0.932, P = 0.0003) was marked as a protective factor for LBP, and Olsenella (OR: 0.893, 95% CI 0.839-0.951, P = 0.0004) was recognized as a protective factor for low back pain or/and sciatica. No significant heterogeneity or horizontal pleiotropy was observed through alternative testing methods.ConclusionThis study establishes a causal relationship between the gut microbiota and SP, shedding light on the "gut-spine" axis. These findings offer novel perspectives for understanding the etiology of SP and provide a theoretical foundation for potential interventions targeting the gut microbiota to prevent and treat SP.
| S-EPMC10999687 | biostudies-literature
Project description:BackgroundThe most commonly acknowledged non-scarring alopecia are androgenetic alopecia (AGA) and alopecia areata (AA). Previous studies have revealed various risk factors associated with alopecia. However, the relationship between leukocyte telomere length (LTL) and non-scarring alopecia remains unclear.MethodsA two-sample Mendelian randomization (MR) analysis was performed to evaluate the causality between genetically predicted LTL and the risk of non-scarring alopecia. MR analyses were performed using the inverse variance-weighted (IVW) method and complemented with other MR methods.ResultsThe summary statistics of the genome-wide association studies (GWAS) for AGA and AA were obtained from the FinnGen biobank, which included 119,185 and 211,428 individuals, respectively. A total of 126 single nucleotide polymorphisms (SNPs) with genome-wide significance were selected as the instrumental variables for LTL. The MR analyses suggested a causal relationship between LTL and AGA, and the risk of AGA increased by 3.19 times as the genetically predicted LTL was shortened by one standard deviation in log transformed form under the IVW method (OR = 4.19, 95% CI = 1.20-14.61, p = 0.024). The other MR methods also demonstrated a similar trend of the effect of LTL on AGA. There was no causal relationship between LTL and AA (p > 0.05). Sensitivity analyses further demonstrated that the current results were less likely to be affected by confounders and bias.ConclusionOur results suggested a potential causal relationship between LTL and AGA, and shortened LTL was associated with an increased risk of AGA.
| S-EPMC9926966 | biostudies-literature
Project description:ObjectivesObservationally, testosterone is negatively associated with systemic inflammation, but this association is open to both residual confounding and reverse causality. Large-scale randomized controlled trials (RCTs), assessing exogenous effects, are presently unavailable. We examined the association of endogenous testosterone with well-established systemic inflammatory markers (white blood cell, granulocyte, lymphocyte and high-sensitivity C-reactive protein (hsCRP)) using a separate-sample Mendelian randomization analysis to minimize reverse causality.MethodsA genetic prediction rule for serum testosterone was developed in 289 young Chinese men with mean age of 21.0, using selected testosterone-related SNPs (rs10046, rs1008805 and rs1256031). Multivariable linear regression was used to examine the association of genetically predicted serum testosterone with inflammatory markers among 4,212 older Chinese men from the Guangzhou Biobank Cohort Study.ResultsGenetically predicted testosterone was unrelated to white blood cell count (-0.01 109/L per nmol/L testosterone, 95% confidence interval (CI) -0.05 to 0.04), granulocyte count (-0.02 109/L, 95% CI -0.06 to 0.02), lymphocyte count (0.005 109/L, 95% CI -0.01 to 0.02) and hsCRP (-0.05 mg/L, 95% CI -0.15 to 0.06).ConclusionOur findings did not corroborate any anti-inflammatory effects of testosterone or corresponding potentially protective effects of testosterone on chronic diseases resulting from reduced low-grade systemic inflammation.
| S-EPMC4423952 | biostudies-literature
Project description:Observational studies have demonstrated that cardiovascular risk factors are associated with chronic kidney disease (CKD). However, these observational associations are potentially influenced by the residual confounding, including some unmeasured lifestyle factors and interaction risk factors. Two-sample mendelian randomization analysis was conducted in this study to evaluate whether genetically predicted cardiovascular risk factors have a causal effect on the risk of CKD. We selected genetic variants associated with cardiovascular risk factors and extracted the corresponding effect sizes from the largest GWAS summary-level dataset of CKD. Cardiovascular risk factors contain high density lipoprotein (HDL) cholesterol, low density lipoprotein (LDL) cholesterol, total cholesterol (TC), triglyceride (TG), glycated hemoglobin (HbA1c), fasting glucose, systolic blood pressure (SBP) and diastolic blood pressure (DBP). A Bonferroni corrected threshold of P = 0.006 was considered as significant, and 0.006 < P < 0.05 was considered suggestive of evidence for a potential association. Genetically predicted DBP was significantly associated with CKD [odds ratio (OR) was 1.35 (95% confidence interval (CI) (1.10, 1.65); P = 0.004)]. There was suggestive evidence for potential associations between genetically predicted higher HDL cholesterol [OR: 0.88, 95%CI (0.80, 0.98), P = 0.025] and lower adds of CKD, and between higher SBP [OR: 1.36, 95%CI (1.07, 1.73), P = 0.013] and higher adds of CKD. However, genetically predicted LDL cholesterol, TC, TG, HbA1c, and fasting glucose did not show any causal association with CKD.
| S-EPMC6509563 | biostudies-literature
Project description:BackgroundEpidemiologic findings suggested that bipolar disorder (BD) may be associated with an increased risk of breast cancer. However, there are few studies that comprehensively evaluating their correlation and the causal effect remains unknown. With a two-sample Mendelian randomization (MR) approach, we were able to investigate the causal relationship between genetically predicted BD and breast cancer risk.MethodsUtilizing 14 BD-related single nucleotide polymorphisms (SNPs) as instrumental variables (IVs) identified by the latest genome-wide association studies (GWASs), we investigated the correlation between genetically predicted BD and breast cancer risk using summary statistics from the Breast Cancer Association Consortium, with a total of 122,977 cases and 105,974 controls. Study-specific estimates were summarized using inverse variance weighted (IVW) method. To further evaluate the pleiotropy, the weighted median and the MR-Egger regression method were implemented. Subgroup analyses according to different immunohistochemical types of breast cancer were also conducted.ResultsMR analyses demonstrated that genetically predicted BD was causally associated with an increased risk of breast cancer (OR =1.059; 95% CI: 1.008-1.112, P=0.0229). When results were examined by immunohistochemical type, no causal effects between genetically predicted BD and estrogen receptor (ER)-positive breast cancer (OR =1.049, 95% CI: 0.999-1.102 P=0.0556) and ER-negative breast cancer (OR =1.032, 95% CI: 0.953-1.116 P=0.4407) were observed. Additionally, the results demonstrated the absence of the horizontal pleiotropy.ConclusionsOur findings provided evidence for a causal relationship between genetically predicted BD and an increased risk of breast cancer overall. Further studies are warranted to investigate the underlying mechanism.
| S-EPMC8033315 | biostudies-literature
Project description:Background Elevated blood pressure is a major cause of cardiovascular morbidity and mortality. However, it is not known whether midlife blood pressure affects later life cardiovascular risk independent of later life blood pressure. Methods and Results Using genetic association estimates from the UK Biobank and CARDIoGRAMplusC4D consortium, univariable mendelian randomization was performed to investigate the total effect of genetically predicted mean arterial pressure (MAP) at age ≤55 years on coronary artery disease (CAD) risk, and multivariable mendelian randomization was performed to investigate the effect of genetically predicted MAP on CAD risk after adjusting for genetically predicted MAP at age >55 years. In both univariable and multivariable mendelian randomization analyses, there was consistent evidence of higher genetically predicted MAP at age ≤55 years increasing CAD risk. This association persisted after adjusting for genetically predicted MAP at age >55 years, when considering nonoverlapping populations for the derivation of MAP and CAD risk genetic association estimates, when investigating only incident CAD events after age >55 years, and when restricting the analysis to variants with most heterogeneity in their associations with MAP ≤55 and >55 years. For a 10-mm Hg increase in genetically predicted MAP at age ≤55 years, the odds ratio of later life CAD was 1.43 (95% CI, 1.16-1.77; P=0.001) after adjusting for genetically predicted MAP at age >55 years. Conclusions These mendelian randomization findings support a cumulative lifetime effect of elevated blood pressure on increasing CAD risk. Clinical and public health efforts toward cardiovascular disease reduction should optimize blood pressure control throughout life.
| S-EPMC7660704 | biostudies-literature