Iron status and sarcopenia-related traits: a bi-directional Mendelian randomization study

Although serum iron status and sarcopenia are closely linked, the presence of comprehensive evidence to establish a causal relationship between them remains insufficient. The objective of this study is to employ Mendelian randomization techniques to clarify the association between serum iron status and sarcopenia. We conducted a bi-directional Mendelian randomization (MR) analysis to investigate the potential causal relationship between iron status and sarcopenia. MR analyses were performed using inverse variance weighted (IVW), MR-Egger, and weighted median methods. Additionally, sensitivity analyses were conducted to verify the reliability of the causal association results. Then, we harvested a combination of SNPs as an integrated proxy for iron status to perform a MVMR analysis based on IVW MVMR model. UVMR analyses based on IVW method identified causal effect of ferritin on appendicular lean mass (ALM, β = - 0.051, 95% CI - 0.072, - 0.031, p = 7.325 × 10-07). Sensitivity analyses did not detect pleiotropic effects or result fluctuation by outlying SNPs in the effect estimates of four iron status on sarcopenia-related traits. After adjusting for PA, the analysis still revealed that each standard deviation higher genetically predicted ferritin was associated with lower ALM (β = - 0.054, 95% CI - 0.092, - 0.015, p = 0.006). Further, MVMR analyses determined a predominant role of ferritin (β = - 0.068, 95% CI - 0.12, - 0.017, p = 9.658 × 10-03) in the associations of iron status with ALM. Our study revealed a causal association between serum iron status and sarcopenia, with ferritin playing a key role in this relationship. These findings contribute to our understanding of the complex interplay between iron metabolism and muscle health.

Genetic study of the causal effect of lipid profiles on insomnia risk: a Mendelian randomization trial

OBJECTIVES

In response to the controversy surrounding observational studies of the association between lipid profiles and the risk of insomnia, the aim of this study was to analyze lipid profiles, including triglycerides (TG), apolipoprotein A-1 (ApoA-1), apolipoprotein B (ApoB) and lipoprotein A (LPA), in a European population to further assess the causal relationship between these lipid types and insomnia.

MATERIALS AND METHODS

This study explores the causal effect of lipid profiles on insomnia based on a genome-wide association study (GWAS)-derived public dataset using two-sample and multivariate Mendelian randomization (MVMR) analysis. The main MR analyses used inverse variance weighting (IVW) odds ratio (OR), and the sensitivity analyses included weighted median (WM) and MR‒Egger.

RESULTS

Both MR and MVMR showed that lowering ApoA-1 and LPA levels had causal effects on the risk of insomnia [MR: per 10 units, ApoA-1: OR: 0.7546, 95% CI: 0.6075-0.9372, P = 0.011; LPA: OR: 0.8392, 95% CI: 0.7202-0.9778, P = 0.025; MVMR: per 10 units, ApoA-1: OR: 0.7600, 95% CI: 0.6362-0.9079, P = 0.002; LPA, OR: 0.903, 95% CI: 0.8283-0.9845, P = 0.021]. There were no causal effects of TG or ApoB on insomnia (all P > 0.05). The MR‒Egger intercept test, funnel plot, and IVW methods all suggested an absence of strong directional pleiotropy, and leave-one-out permutation analysis did not detect any single single-nucleotide polymorphism that had a strong influence on the results.

CONCLUSION

Elevated levels of ApoA-1 and LPA were independently and causally associated with the risk of insomnia, suggesting that elevated ApoA-1 and LPA levels may contribute to a reduced risk of insomnia.

Causal Effects of Blood Metabolites and Obstructive Sleep Apnea: A Mendelian Randomization Study

BACKGROUND

Obstructive sleep apnea (OSA) is one of the most common forms of sleep-disordered breathing. Studies have shown that certain changes in metabolism play an important role in the pathophysiology of OSA. However, the causal relationship between these metabolites and OSA remains unclear.

AIMS

We use a mendelian randomization (MR) approach to investigate the causal associations between the genetic liability to metabolites and OSA.

METHODS

We performed a 2-sample inverse-variance weighted mendelian randomization analysis to evaluate the causal effects of genetically determined 486 metabolites on OSA. Multiple sensitivity analyses were performed to assess pleiotropy. We used multivariate mendelian randomization analyses to assess confounding factors and mendelian randomization Bayesian model averaging to rank the significant biomarkers by their genetic evidence. We also conducted a metabolic pathway analysis to identify potential metabolic pathways.

RESULTS

We identified 14 known serum metabolites (8 risk factors and 6 protective factors) and 12 unknown serum metabolites associated with OSA. These 14 known metabolites included 8 lipids( 1-arachidonoylglycerophosphoethanolamine, Tetradecanedioate, Epiandrosteronesulfate, Acetylca Glycerol3-phosphate, 3-dehydrocarnitine, Margarate17:0, Docosapentaenoaten3;22:5n3), 3 Aminoacids (Isovalerylcarnitine,3-methyl-2-oxobutyrate,Methionine), 2 Cofactors and vitamins [Bilirubin(E,ZorZ,E),X-11593--O-methylascorbate], 1Carbohydrate(1,6-anhydroglucose). We also identified several metabolic pathways that involved in the pathogenesis of OSA.

CONCLUSION

MR (mendelian randomization) approach was performed to identify 6 protective factors and 12 risk factors for OSA in the present study. 3-Dehydrocarnitine was the most significant risk factors for OSA. Our study also confirmed several significant metabolic pathways that were involved in the pathogenesis of OSA. Valine, leucine and isoleucine biosynthesis metabolic pathways were the most significant metabolic pathways that were involved in the pathogenesis of OSA.