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While numerous observational studies have indicated an association between lipids and Sudden Sensorineural Hearing Loss (SSNHL), it remains uncertain whether dyslipidemia serves as a causal risk factor for SSNHL. Our objective is to elucidate the potential causal relationship between lipid levels and SSNHL through Mendelian randomization analysis. The primary and secondary lipid data used in this study were sourced from the UK Biobank (UKBB) and the Global Lipid Genetics Consortium results (GLGC), respectively. These datasets were obtained from large, publicly available genome-wide association studies (GWAS). The outcome data for sudden sensorineural hearing loss (SSNHL) were acquired from the Finnegan Biobank, consisting of 1491 cases and 196,592 controls. Subsequently, both single-variable Mendelian randomization (SVMR) and multivariate Mendelian randomization (MVMR) methods were employed to evaluate the causal relationship between lipids and the occurrence of SSNHL. Among the primary lipid data, SVMR analysis showed a significant correlation between high density lipoprotein cholesterol (HDL-C) (OR: 0.822, 95 %CI: 0.694–0.974, p = 0.023) and SSNHL, and triglycerides (TG) (OR: 0.997, 95 %CI: 0.836–1.188, p = 0.975), low density lipoprotein cholesterol (LDL-C) (OR: 1.067, 95 %CI: 0.861–1.322, p = 0.552) did not correlate with SSNHL. In the secondary lipid data, SVMR analysis showed that HDL-C (OR: 0.987, 95 %CI: 0.805–1.210, p = 0.903), TG (OR: 0.991, 95 %CI: 0.787–1.246, p = 0.937) and LDL-C (OR: 1.092, 95 % CI: 0.926–1.287, p = 0.294) did not correlate with SSNHL. MVMR analysis of the primary lipid data showed that HDL-cholesterol (OR: 0.755, 95 % CI: 0.596–0.956, p = 0.019) was significantly associated with SSNHL, while TG (OR: 0.808, 95 %CI: 0.611–1.068, p = 0.134) and LDL-C (OR: 1.146, 95 %CI: 0.869–1.511, p = 0.333) did not correlate with SSNHL, consistent with the results of SVMR. Inverse MR results showed that SSNHL did not correlate with TG (OR: 0.999, 95 %CI: 0.997–1.001, p = 0.835), HDL-C (OR: 1.001, 95 %CI: 0.998–1.003), LDL-C (OR: 0.999, 95 %CI: 0.997–1.002, p = 0.863). Mendelian randomization (MR) results suggest that decreased serum HDL-C levels are an independent risk factor for SSNHL. Monitoring and focusing on lipid levels may be of value in the prevention and treatment of SSNHL. [ABSTRACT FROM AUTHOR]

Purpose: Coffee intake and apolipoprotein B levels have been linked to gastric, colorectal, and esophageal cancers in numerous recent studies. However, whether these associations are all causal remains unestablished. This study aimed to assess the potential causal associations of apolipoprotein B and coffee intake with the risk of gastric, colorectal, and esophageal cancers using Mendelian randomization analysis. Methods: In this study, we utilized a two-sample Mendelian randomization analysis to access the causal effects of coffee intake and apolipoprotein B on gastric, colorectal, and esophageal cancers. The summary statistics of coffee intake (n = 428,860) and apolipoprotein B (n = 439,214) were obtained from the UK Biobank. In addition, the summary statistics of gastric cancer, colorectal cancer, and esophageal cancer were obtained from the FinnGen biobank (n = 218,792). Inverse variance weighted, MR–Egger, weighted median, and weighted mode were applied to examine the causal relationship between coffee intake, apolipoprotein B and gastric, colorectal, and esophageal cancers. MR–Egger intercept test, Cochran's Q test, and leave-one-out analysis were performed to evaluate possible heterogeneity and pleiotropy. Steiger filtering and bidirectional mendelian randomization analysis were performed to evaluate the possible reverse causality. Results: The result of the inverse variance weighted method indicated that apolipoprotein B levels were significantly associated with a higher risk of gastric cancer (OR = 1.392, 95% CI 1.027–1.889, P = 0.0333) and colorectal cancer (OR = 1.188, 95% CI 1.001–1.411, P = 0.0491). Furthermore, multivariable Mendelian randomization analysis also revealed a positive association between apolipoprotein B levels and colorectal cancer risk, but the effect of apolipoprotein B on gastric cancer risk disappeared after adjustment of coffee intake, body mass index or lipid-related traits. However, we did not discover any conclusive evidence linking coffee intake to gastric, colorectal, or esophageal cancers. Conclusions: This study suggested a causal association between genetically increased apolipoprotein B levels and higher risk of colorectal cancer. No causal relationship was observed between coffee intake and gastric, colorectal, or esophageal cancers. [ABSTRACT FROM AUTHOR]

Background: This study aims to comprehensively investigate the phenotypic and genetic relationships between four common lipids (high-density lipoprotein cholesterol, HDL-C; low-density lipoprotein cholesterol, LDL-C; total cholesterol, TC; and triglycerides, TG), chronic kidney disease (CKD), and estimated glomerular filtration rate (eGFR). Methods: We first investigated the observational association of lipids (exposures) with CKD (primary outcome) and eGFR (secondary outcome) using data from UK Biobank. We then explored the genetic relationship using summary statistics from the largest genome-wide association study of four lipids (N = 1,320,016), CKD (Ncase = 41,395, Ncontrol = 439,303), and eGFR(N = 567,460). Results: There were significant phenotypic associations (HDL-C: hazard ratio (HR) = 0.76, 95%CI = 0.60–0.95; TG: HR = 1.08, 95%CI = 1.02–1.13) and global genetic correlations (HDL-C: r g = − 0.132, P = 1.00 × 10–4; TG: r g = 0.176; P = 2.66 × 10–5) between HDL-C, TG, and CKD risk. Partitioning the whole genome into 2353 LD-independent regions, twelve significant regions were observed for four lipids and CKD. The shared genetic basis was largely explained by 29 pleiotropic loci and 36 shared gene-tissue pairs. Mendelian randomization revealed an independent causal relationship of genetically predicted HDL-C (odds ratio = 0.91, 95%CI = 0.85–0.98), but not for LDL-C, TC, or TG, with the risk of CKD. Regarding eGFR, a similar pattern of correlation and pleiotropy was observed. Conclusions: Our work demonstrates a putative causal role of HDL-C in CKD and a significant biological pleiotropy underlying lipids and CKD in populations of European ancestry. Management of low HDL-C levels could potentially benefit in reducing the long-term risk of CKD. [ABSTRACT FROM AUTHOR]

Background: Statin use for cancer prevention has raised wide attention but the conclusions are still controversial. Whether statins use have exact causal effects on cancer prevention remains unclear. Methods: Based on the Genome-Wide Association Studies (GWAS) datasets from the large prospective UK Biobank and other consortium databases, two-sample mendelian randomization (MR) analysis was conducted to explore the causal effects of statins use on varied site-specific cancer risks. Five MR methods were applied to investigate the causality. The stability, heterogeneity, and pleiotropy of MR results were also evaluated. Results: The atorvastatin use could increase the risk of colorectal cancer (odd ratio (OR) = 1.041, p = 0.035 by fixed-effects inverse variance weighted (IVW) method (IVWFE), OR = 1.086, p = 0.005 by weighted median; OR = 1.101, p = 0.048 by weighted mode, respectively). According to the weighted median and weighted mode, atorvastatin could modestly decrease the risk of liver cell cancer (OR = 0.989, p = 0.049, and OR = 0.984, p = 0.004, respectively) and head and neck cancer (OR = 0.972, p = 0.020). Besides, rosuvastatin use could reduce the bile duct cancer risk by 5.2% via IVWEF method (OR = 0.948, p = 0.031). No significant causality was determined in simvastatin use and pan-cancers via the IVWFE or multiplicative random-effects IVW (IVWMRE) method if applicable (p > 0.05). There was no horizontal pleiotropy observed in the MR analysis and the leave-one-out analysis proved the stability of the results. Conclusion: The causalities between statin use and cancer risk were only observed in colorectal cancer and bile duct cancer in the European ancestry population. Future works are warranted to provide more robust evidence for supporting statin repurposing for cancer prevention. [ABSTRACT FROM AUTHOR]

Background: Observational studies have shown inconsistent findings of the relationships between aspirin use and the risk of Alzheimer's disease (AD). Objective: Since residual confounding and reverse causality were challenging issues inherent in observational studies, we conducted a 2-sample Mendelian randomization analysis (MR) to investigate whether aspirin use was causally associated with the risk of AD. Methods: We conducted 2-sample MR analyses utilizing summary genetic association statistics to estimate the potential causal relationship between aspirin use and AD. Single-nucleotide variants associated with aspirin use in a genome-wide association study (GWAS) of UK Biobank were considered as genetic proxies for aspirin use. The GWAS summary-level data of AD were derived from a meta-analysis of GWAS data from the International Genomics of Alzheimer's Project (IGAP) stage I. Results: Univariable MR analysis based on these two large GWAS data sources showed that genetically proxied aspirin use was associated with a decreased risk of AD (Odds Ratio (OR): 0.87; 95%CI: 0.77–0.99). In multivariate MR analyses, the causal estimates remained significant after adjusting for chronic pain, inflammation, heart failure (OR = 0.88, 95%CI = 0.78–0.98), or stroke (OR = 0.87, 95%CI = 0.77–0.99), but was attenuated when adjusting for coronary heart disease, blood pressure, and blood lipids. Conclusion: Findings from this MR analysis suggest a genetic protective effect of aspirin use on AD, possibly influenced by coronary heart disease, blood pressure, and lipid levels. [ABSTRACT FROM AUTHOR]

Fat mass and fat-free mass are found to be associated with different health outcomes in observational studies, but the underlying causality remains unclear. We aimed to investigate the causal relationships between body composition and cardiometabolic traits using a two-sample Mendelian randomization (MR) approach. Independent genetic variants associated with body fat mass, fat-free mass, and fat percentage in UK Biobank population were used as genetic instrumental variables, and their causal effects on circulatory diseases, type 2 diabetes, glycemic traits, and lipid fractions were estimated from large-scale genome-wide association studies (GWAS) in European populations. Univariable, multivariable, and bidirectional MR analyses were performed. Genetically predicted high fat mass and fat percentage significantly increased risks of most cardiometabolic diseases, and high fat-free mass had protective effects on most cardiometabolic diseases after accounting for fat mass. Fat mass, fat-free mass, and fat percentage were all positively associated with higher risks of atrial fibrillation and flutter, varicose veins, and deep vein thrombosis and pulmonary embolism. High fat mass increased fasting glucose, homeostasis model assessment-insulin resistance (HOMA-IR), triglycerides, decreased high-density lipoprotein cholesterol, and high fat-free mass reduced HOMA-IR, triglycerides, and low-density lipoprotein cholesterol. Genetically predicted fat-free mass was bidirectionally negatively associated with 2-h glucose and total cholesterol. The findings may be helpful in risk stratification and tailoring management of body composition in patients with different cardiometabolic statuses. [ABSTRACT FROM AUTHOR]

Fish oil supplementation is widely used for reducing serum triglycerides (TAGs) but has mixed effects on other circulating cardiovascular biomarkers. Many genetic polymorphisms have been associated with blood lipids, including high- and low-density-lipoprotein cholesterol (HDL-C, LDL-C), total cholesterol, and TAGs. Here, the gene-diet interaction effects of fish oil supplementation on these lipids were analyzed in a discovery cohort of up to 73,962 UK Biobank participants, using a 1-degree-of-freedom (1df) test for interaction effects and a 2-degrees-of-freedom (2df) test to jointly analyze interaction and main effects. Associations with P < 1×10−6 in either test (26,157; 18,300 unique variants) were advanced to replication in up to 7,284 participants from the Atherosclerosis Risk in Communities (ARIC) Study. Replicated associations reaching 1df P < 0.05 (2,175; 1,763 unique variants) were used in meta-analyses. We found 13 replicated and 159 non-replicated (UK Biobank only) loci with significant 2df joint tests that were predominantly driven by main effects and have been previously reported. Four novel interaction loci were identified with 1df P < 5×10−8 in meta-analysis. The lead variant in the GJB6-GJB2-GJA3 gene cluster, rs112803755 (A>G; minor allele frequency = 0.041), shows exclusively interaction effects. The minor allele is significantly associated with decreased TAGs in individuals with fish oil supplementation, but with increased TAGs in those without supplementation. This locus is significantly associated with higher GJB2 expression of connexin 26 in adipose tissue; connexin activity is known to change upon exposure to omega-3 fatty acids. Significant interaction effects were also found in three other loci in the genes SLC12A3 (HDL-C), ABCA6 (LDL-C), and MLXIPL (LDL-C), but highly significant main effects are also present. Our study identifies novel gene-diet interaction effects for four genetic loci, whose effects on blood lipids are modified by fish oil supplementation. These findings highlight the need and possibility for personalized nutrition. Author summary: We utilized the unprecedentedly large genotype and phenotype dataset in the UK Biobank to perform a genome-wide association study (GWAS) which accounts for the interplay between genotype and dietary intake. We examined the interaction effects of fish oil supplementation on levels of blood lipids (LDL-C, HDL-C, TAGs, and total cholesterol). Our findings were replicated in the Atherosclerosis Risk in Communities (ARIC) Study. We found that at the genetic variant rs112803755 (A>G), the minor allele (G) is associated with a decrease in TAGs among individuals with fish oil supplementation, but is associated with an increase in TAGs among those without supplementation. In other words, only individuals carrying the minor allele benefit from fish oil supplementation in reducing TAG levels. We further analyzed rs112803755 with functional genomics data from the Genotype-Tissue Expression (GTEx) project to identify potential target genes, and found a connexin coding gene which has been previously reported to respond to cellular omega-3 levels. This research suggests that inter-personal variation in TAG response to fish oil supplementation is in part explained by genotype, and that fish oil dose adjustment based on genotype should be investigated as a means to protect against cardiovascular disease risk. [ABSTRACT FROM AUTHOR]

Background: Lower birth weight is associated with diabetes although the underlying mechanisms are unclear. Muscle mass could be a modifiable link and hence a target of intervention. We assessed the associations of birth weight with muscle and fat mass observationally in a population with little socio-economic patterning of birth weight and using Mendelian randomization (MR) for validation. Methods: In the population-representative “Children of 1997” birth cohort (n = 8,327), we used multivariable linear regression to assess the adjusted associations of birth weight (kg) with muscle mass (kg) and body fat (%) at ~17.5 years. Genetically predicted birth weight (effect size) was applied to summary genetic associations with fat-free mass and fat mass (kg) from the UK Biobank (n = ~331,000) to obtain unconfounded estimates using inverse-variance weighting. Results: Observationally, birth weight was positively associated with muscle mass (3.29 kg per kg birth weight, 95% confidence interval (CI) 2.83 to 3.75) and body fat (1.09% per kg birth weight, 95% CI 0.54 to 1.65). Stronger associations with muscle mass were observed in boys than in girls (p for interaction 0.004). Using MR, birth weight was positively associated with fat-free mass (0.77 kg per birth weight z-score, 95% CI 0.22 to 1.33) and fat mass (0.58, 95% CI 0.01 to 1.15). No difference by sex was evident. Conclusion: Higher birth weight increasing muscle mass may be relevant to lower birth weight increasing the risk of diabetes and suggests post-natal muscle mass as a potential target of intervention. [ABSTRACT FROM AUTHOR]

Type 2 diabetes (T2D) is a complex disorder characterized by high blood sugar, insulin resistance, and relative lack of insulin. The collective effects of genome wide minor alleles of common SNPs, or the minor allele content (MAC) in an individual, have been linked with quantitative variations of complex traits and diseases. Here we studied MAC in T2D using previously published SNP datasets and found higher MAC in cases relative to matched controls. A set of 357 SNPs was found to have the best predictive accuracy in a British population. A weighted risk score calculated by using this set produced an area under the curve (AUC) score of 0.86, which is comparable to risk models built by phenotypic markers. These results identify a novel genetic risk element in T2D susceptibility and provide a potentially useful genetic method to identify individuals with high risk of T2D. [ABSTRACT FROM AUTHOR]