Supplementary data

# Supplementary Data README<br>## General Information<br>**Title**: Meta-Analysis of Urinary Metabolite GWAS Studies Identifies Three Novel Genome-Wide Significant Loci **Authors**: Jihan K. Zaki, Jakub Tomasik, Jade McCune, Oren Scherman, Sabine Bahn **DOI**: [10.1101/2024.06.25.600593](https://doi.org/10.1101/2024.06.25.600593)<br>## Data File Description<br>This file contains the summary statistics from a genome-wide association meta-analysis focusing on urinary metabolites. Data fields include SNP identifiers, alleles, effect sizes, p-values, and sample sizes, among others.<br>- **Contents**: Summary statistics for GWAS meta-analysis of urinary metabolites- **Format**: CSV- **Columns**: - `Phenotype_chr`: Chromosome for the phenotype - `position`: Genomic position - `SNP`: SNP identifier - `other_allele`: Non-effect allele - `effect_allele`: Effect allele - `effect_pval`: P-value of the effect - `n`: Sample size - `eaf`: Effect allele frequency - `m-pval`: Meta-analysis p-value - `m-n`: Meta-analysis sample size - `studies`: Number of studies included<br>## Methodology<br>- **Study Design**: The study involved a meta-analysis of GWAS data to identify significant loci associated with urinary metabolites.- **Data Processing**: Data was obtained through the EMBL-EBI GWAS Catalog, PubMed, and metabolomix.com, we employed a sample size-based meta-analytic approach to evaluate the significance of previously reported GWAS associations. Further details can be found in the manuscript.<br>## Usage Notes<br>- **Intended Use**: These data are intended for use in academic and research settings. Users are encouraged to use the data to validate findings or for further analysis under the terms provided.<br>## Citation and Contact<br>- **Citation**: Please cite this dataset using the DOI provided above and by referring to the main manuscript.- **Contact**: For further inquiries, contact Jihan Zaki ([e-mail]), Oren Scherman ([e-mail]) or Sabine Bahn ([e-mail]).<br>## License<br>- **License Type**: CC BY-NC-SA<br>## Acknowledgments<br>- **Funding and Support**: This work was supported by the Stanley Medical Research Institute (grant number: O7R-1888) by grants to Sabine Bahn, and by the Oskar Huttunen Foundation grant to Jihan K. Zaki.<br>