Search

Additional file 1: Methods. Table S1. Participant characteristics in the GNHS. Table S2. Participant characteristics of the CHNS. Table S3. Associations between α-diversity and cognitive impairment in the GNHS (n = 1430). Table S4. Associations between α-diversity and cognitive decline in the CHNS (n = 1300). Table S5. Weights for genus features contributing to the LASSO models. Table S6. Associations between bacterial taxonomy and cognitive performance in the CHNS (n = 1300). Table S7. Associations between Odoribacter and SCFAs in the GNHS. Table S8. Associations between serum acetic acid and brain structure in the GNHS. Table S9. Distribution of metagenomic features in the GNHS. Table S10. Associations between intra-individual alterations in gut microbial composition and cognitive impairment in the GNHS. Table S11. Metagenomic and metabolomic features associated with cognitive impairment in the GNHS. Table S12. Correlations of metagenomic and metabolic features with MMSE domains in the GNHS. Table S13. Correlations between metagenomic features and metabolites in the GNHS. Fig. S1 Overview of the multi-omics datasets of the GNHS. Fig. S2 Distribution of metagenomic and metabolomic features in the GNHS. Fig. S3 Correlation analyses on cognition-related metagenomic and metabolic traits in the GNHS. Fig. S4 Association of metagenomic pathways and serum metabolomics with cognitive function in the GNHS. Fig. S5 Networks of metagenomic pathways in the GNHS.

Additional file 3: Table S1-S2 & Figure S1-S8. Supplemental methods and results for the systematic review and meta-analysis. TableS1. PubMed search strategy. TableS2. Characteristics of the included prospective studies. FigS1. Flow diagrams of the literature research. FigS2. The association of dietary and supplemental vitamin C intakes with incident lung cancer. FigS3. The association of dietary, supplemental and total vitamin C intakes with incident breast cancer. FigS4. The association of dietary, supplemental and total vitamin C intakes with incident prostate cancer. FigS5. The association of dietary vitamin C intakes with incident colorectal cancer. FigS6. The association of supplemental vitamin C intakes with incident colorectal cancer. FigS7. The association of total vitamin C intakes with incident colorectal cancer. FigS8. Funnel plot for associations of vitamin C intakes with cancers, with Egger’s test adopted to examine the publication bias.

Additional file 1: Supplemental Table 1. The plasma vitamin C-related genetic variants used for the MR analyses. Supplemental Table 3. Characteristics of the genetic variants that were used as the instrumental variables for plasma vitamin C concentration. Supplemental Table 4. Genetic correlation between vitamin C and site-specific cancers, estimated through linkage disequilibrium score regression. Supplemental Table 5. Mendelian randomization estimates of the association between genetically predicted plasma vitamin C concentration and risk of secondary cancer outcomes based on cancer subtypes. Supplemental Table 6. Multivariate MR analysis exploring causal association between circulating Vitamin C and lung cancer with adjustment for smoking.

Additional file 4: Figure S1-S8. The forest and scatter plots for each SNP-CA association and the results of heterogeneity test. FigS1. Genetically predicted associations of plasma vitamin C with lung cancer in the UK biobank dataset. FigS2. Genetically predicted associations of plasma vitamin C with breast cancer in the UK biobank dataset. FigS3. Genetically predicted associations of plasma vitamin C with prostate cancer in the UK biobank dataset. FigS4. Genetically predicted associations of plasma vitamin C with colon cancer in the UK biobank dataset. FigS5. Genetically predicted associations of plasma vitamin C with rectal cancer in the UK biobank dataset. FigS6. Genetically predicted associations of plasma vitamin C with lung cancer in the dataset from International Lung Cancer Consortium (ILCCO). FigS7. Genetically predicted associations of plasma vitamin C with breast cancer in the dataset from the Breast Cancer Association Consortium (BCAC). FigS8. Genetically predicted associations of plasma vitamin C with prostate cancer in the dataset from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL).