This data set provides the summary statistics of dietary habits in the BioBank Japan Project
Matoba N. et al., Nat Hum. Behav. (2020)
This includes 13 phenotypes: (please also see a Supplementary table provided in the journal) 41562_2019_805_MOESM3_ESM.xlsx
Trait (Full name) | Trait (Abbr.) | SEX | Type | # Case | # Control | # Total |
---|---|---|---|---|---|---|
Ever vs never drinkers | EVERDRINK | All | Case-Control | 83,713 | 81,371 | 165,084 |
Ever vs never drinkers | EVERDRINK | Male | Case-Control | 62,526 | 26,909 | 89,435 |
Ever vs never drinkers | EVERDRINK | Female | Case-Control | 21,187 | 54,462 | 75,649 |
Drinks per week | DPW | All | QTL | 58,610 | ||
Drinks per week | DPW | Male | QTL | 44,232 | ||
Drinks per week | DPW | Female | QTL | 14,378 | ||
Coffee consumption | COFFEE | All | QTL (4 bins) | 152,634 | ||
Coffee consumption | COFFEE | Male | QTL (4 bins) | 83,038 | ||
Coffee consumption | COFFEE | Female | QTL (4 bins) | 69,596 | ||
Green tea consumption | TEA | All | QTL (4 bins) | 152,653 | ||
Green tea consumption | TEA | Male | QTL (4 bins) | 83,028 | ||
Green tea consumption | TEA | Female | QTL (4 bins) | 69,625 | ||
Milk consumption | MILK | All | QTL (4 bins) | 152,965 | ||
Milk consumption | MILK | Male | QTL (4 bins) | 83,228 | ||
Milk consumption | MILK | Female | QTL (4 bins) | 69,737 | ||
Yogurt consumption | YOGURT | All | QTL (4 bins) | 152,907 | ||
Yogurt consumption | YOGURT | Male | QTL (4 bins) | 83,150 | ||
Yogurt consumption | YOGURT | Female | QTL (4 bins) | 69,757 | ||
Cheese consumption | CHEESE | All | QTL (4 bins) | 152,714 | ||
Cheese consumption | CHEESE | Male | QTL (4 bins) | 83,049 | ||
Cheese consumption | CHEESE | Female | QTL (4 bins) | 69,665 | ||
Natto consumption | NATTO | All | QTL (4 bins) | 152,678 | ||
Natto consumption | NATTO | Male | QTL (4 bins) | 83,023 | ||
Natto consumption | NATTO | Female | QTL (4 bins) | 69,655 | ||
Tofu consumption | TOFU | All | QTL (4 bins) | 152,943 | ||
Tofu consumption | TOFU | Male | QTL (4 bins) | 83,190 | ||
Tofu consumption | TOFU | Female | QTL (4 bins) | 69,753 | ||
Fish consumption | FISH | All | QTL (4 bins) | 153,048 | ||
Fish consumption | FISH | Male | QTL (4 bins) | 83,262 | ||
Fish consumption | FISH | Female | QTL (4 bins) | 69,786 | ||
Small fish consumption | SMALL_FISH | All | QTL (4 bins) | 152,277 | ||
Small fish consumption | SMALL_FISH | Male | QTL (4 bins) | 82,791 | ||
Small fish consumption | SMALL_FISH | Female | QTL (4 bins) | 69,486 | ||
Vegetables consumption | VEGETABLE | All | QTL (4 bins) | 153,001 | ||
Vegetables consumption | VEGETABLE | Male | QTL (4 bins) | 83,229 | ||
Vegetables consumption | VEGETABLE | Female | QTL (4 bins) | 69,772 | ||
Meat consumption | MEAT | All | QTL (4 bins) | 152,857 | ||
Meat consumption | MEAT | Male | QTL (4 bins) | 83,167 | ||
Meat consumption | MEAT | Female | QTL (4 bins) | 69,690 |
65 summary statistics were included in this data set.
- 13 traits x 3 set (All, Male and Female) autosomes
- 13 traits x 2 set (Male and Female) Xchromosomes
File Names | # variants |
---|---|
${SEX}_2019_${Trait}_BBJ_autosome_Pcorrected.txt.gz | 5,961,480 |
Male_2019_${Trait}_BBJ_Xchromosome_Pcorrected.txt.gz | 170,117 |
Female_2018_${Trait}_BBJ_Xchromosome_Pcorrected.txt.gz | 148,568 |
Column | Description | |
---|---|---|
1 | SNP | rs number or ID string |
2 | CHR | chromosome |
3 | POS | physical position (hg19) |
4 | A1 | effect allele |
5 | A2 | other allele |
6 | A1Frq | frquency of effect allele |
7 | Rsq | imputation quality |
8 | BETA | effect size from BOLT-LMM approximation to infinitestimal mixed model |
9 | SE | standard error of effect size |
10 | P | LDSC-intercept corrected infinitestimal mixed model association test p-value |
When using these summary statistics, please cite the following paper.
Matoba, N., Akiyama, M., Ishigaki, K. et al. GWAS of 165,084 Japanese individuals identified nine loci associated with dietary habits. Nat Hum Behav 4, 308–316 (2020).
https://doi.org/10.1038/s41562-019-0805-1