Objective:To elucidate the causal relationship between serum metabolites and hepatocellular carcinoma (HCC) by the Mendelian randomization.Methods:The serum metabolite genome-wide association study (GWAS) data from the Metabolomics GWAS server was selected as the exposure group. The study sample includes 7 824 adults from two European population studies. The GWAS data of HCC was obtained from the IEU Open GWAS project as the outcome group, including a total sample of 197 611 cases, to evaluate the relationship between 486 serum metabolites and HCC. The inverse variance weighting method (IVW) was used as the primary analysis method. Supplementary analysis methods included MR-Egger, weighted median, simple mode, and weighted mode. Sensitivity analyses were conducted using Cochran's Q test, MR-Egger intercept test, leave-one-out analysis, and MR-PRESSO. Reverse MR and MR-Steiger tests were employed to exclude the influence of reverse causality. Metabolomic pathway analysis was performed using MetaboAnalyst 5.0. Results:The MR results finally identified six metabolites with potential causal relationships with HCC: mannose ( OR=0.38, 95% CI: 0.16-0.92, P=0.032), γ-glutamyltyrosine ( OR=3.34, 95% CI: 1.14-9.83, P=0.028), glycerol-3-phosphate ( OR=0.17, 95% CI: 0.04-0.70, P=0.014), 2-linoleoylglycerophosphocholine ( OR=0.33, 95% CI: 0.13-0.98, P=0.028), 1-stearoylglycerophosphoethanolamine ( OR=2.44, 95% CI: 1.05-5.65, P=0.038), and palmitoyl sphingomyelin ( OR=5.62, 95% CI: 1.56-20.18, P=0.008). Sensitivity analyses for the six metabolites showed robustness, with no abnormal variables in the heterogeneity tests, and no evidence of genetic pleio-tropy was observed. Both reverse MR and Steiger tests did not support the existence of reverse causality between the metabolites and HCC. Metabolic pathway analysis indicated that ether lipid metabolism is closely related to the occurrence of HCC ( P=0.002). Conclusion:Six serum metabolites (mannose, γ-glutamyltyrosine, glycerol-3-phosphate, 2-linoleoylglycerophosphocholine, 1-stearoylglycerophosphoethanolamine, and palmitoyl sphingomyelin) have causal relationships with HCC.

Objective:To elucidate the causal relationship between serum metabolites and hepatocellular carcinoma (HCC) by the Mendelian randomization.Methods:The serum metabolite genome-wide association study (GWAS) data from the Metabolomics GWAS server was selected as the exposure group. The study sample includes 7 824 adults from two European population studies. The GWAS data of HCC was obtained from the IEU Open GWAS project as the outcome group, including a total sample of 197 611 cases, to evaluate the relationship between 486 serum metabolites and HCC. The inverse variance weighting method (IVW) was used as the primary analysis method. Supplementary analysis methods included MR-Egger, weighted median, simple mode, and weighted mode. Sensitivity analyses were conducted using Cochran's Q test, MR-Egger intercept test, leave-one-out analysis, and MR-PRESSO. Reverse MR and MR-Steiger tests were employed to exclude the influence of reverse causality. Metabolomic pathway analysis was performed using MetaboAnalyst 5.0. Results:The MR results finally identified six metabolites with potential causal relationships with HCC: mannose ( OR=0.38, 95% CI: 0.16-0.92, P=0.032), γ-glutamyltyrosine ( OR=3.34, 95% CI: 1.14-9.83, P=0.028), glycerol-3-phosphate ( OR=0.17, 95% CI: 0.04-0.70, P=0.014), 2-linoleoylglycerophosphocholine ( OR=0.33, 95% CI: 0.13-0.98, P=0.028), 1-stearoylglycerophosphoethanolamine ( OR=2.44, 95% CI: 1.05-5.65, P=0.038), and palmitoyl sphingomyelin ( OR=5.62, 95% CI: 1.56-20.18, P=0.008). Sensitivity analyses for the six metabolites showed robustness, with no abnormal variables in the heterogeneity tests, and no evidence of genetic pleio-tropy was observed. Both reverse MR and Steiger tests did not support the existence of reverse causality between the metabolites and HCC. Metabolic pathway analysis indicated that ether lipid metabolism is closely related to the occurrence of HCC ( P=0.002). Conclusion:Six serum metabolites (mannose, γ-glutamyltyrosine, glycerol-3-phosphate, 2-linoleoylglycerophosphocholine, 1-stearoylglycerophosphoethanolamine, and palmitoyl sphingomyelin) have causal relationships with HCC.

BACKGROUND: Weather conditions are a possible contributing factor to age-related macular degeneration (AMD), a leading cause of irreversible loss of vision. The present study evaluated the joint effects of meteorological factors and fine particulate matter (PM_2.5) on AMD. METHODS: Data was extracted from a national cross-sectional survey conducted across 10 provinces in rural China. A total of 36,081 participants aged 40 and older were recruited. AMD was diagnosed clinically by slit-lamp ophthalmoscopy, fundus photography, and spectral domain optical coherence tomography (OCT). Meteorological data were calculated by European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis and were matched to participants' home addresses by latitude and longitude. Participants' individual PM_2.5 exposure concentrations were calculated by a satellite-based model at a 1-km resolution level. Multivariable-adjusted logistic regression models paired with interaction analysis were performed to investigate the joint effects of meteorological factors and PM_2.5 on AMD. RESULTS: The prevalence of AMD in the study population was 2.6% (95% CI 2.42-2.76%). The average annual PM_2.5 level during the study period was 63.1 ± 15.3 µg/m³. A significant positive association was detected between AMD and PM_2.5 level, temperature (T), and relative humidity (RH), in both the independent and the combined effect models. For PM_2.5, compared with the lowest quartile, the odds ratios (ORs) with 95% confidence intervals (CIs) across increasing quartiles were 0.828 (0.674,1.018), 1.105 (0.799,1.528), and 2.602 (1.516,4.468). Positive associations were observed between AMD and temperature, with ORs (95% CI) of 1.625 (1.059,2.494), 1.619 (1.026,2.553), and 3.276 (1.841,5.830), across increasing quartiles. In the interaction analysis, the estimated relative excess risk due to interaction (RERI) and the attributable proportion (AP) for combined atmospheric pressure and PM_2.5 was 0.864 (0.586,1.141) and 1.180 (0.768,1.592), respectively, indicating a synergistic effect between PM_2.5 and atmospheric pressure. CONCLUSIONS This study is among the first to characterize the coordinated effects of meteorological factors and PM_2.5 on AMD. The findings warrant further investigation to elucidate the relationship between ambient environment and AMD.
Humans ; Adult ; Middle Aged ; Cross-Sectional Studies ; Air Pollutants/analysis* ; Particulate Matter/analysis* ; China/epidemiology* ; Macular Degeneration/etiology* ; Meteorological Concepts