Scholz et al., 2023
(accepted in principle)
X-chromosome and kidney function: Evidence from a multi-trait genetic analysis of 908,697 individuals reveals sex-specific and sex-differential findings in genes regulated by androgen-response elements
X-chromosomal genetic variants are understudied but can yield valuable insights into sexually dimorphic human traits and diseases. We performed a sex-stratified cross-ancestry X-chromosome-wide association meta-analysis of seven kidney-related traits (n=908,697), identifying 23 loci genome-wide significantly associated with two of the traits: 7 for uric acid and 16 for estimated glomerular filtration rate (eGFR), including four novel eGFR loci containing the functionally plausible prioritized genes ACSL4, CLDN2, TSPAN6 and the female-specific DRP2. Further, we identified five novel sex-interactions, comprising male-specific effects at FAM9B and AR/EDA2R, and three sex-differential findings with larger genetic effect sizes in males at DCAF12L1 and MST4 and larger effect sizes in females at HPRT1. All prioritized genes in loci showing significant sex-interactions were located next to androgen response elements (ARE). Five ARE genes showed sex-differential expressions. This study contributes new insights into sex-dimorphisms of kidney traits along with new prioritized gene targets for further molecular research.
Please refer to Scholz et al. 2023 for more details on the analyses.Contact markus.scholz@imise.uni-leipzig.de if you have questions.
Data set description
Trans-ethnic meta-analysis of GWAS data (chromosome X only) for eGFR, UA, BUN, CKD, UACR, MA and Gout from the Chronic Kidney Disease Genetics Consortium and the UK Biobank.
Within each file, the data are presented as follows:
- ID_Meta: standardised SNP ID for meta-analysis
- rsID: rsID of SNP
- ID_UKBB: rsID of SNP in UKBB data set
- chromosome: chromosome
- position: base position in HG19
- Cytoband: cytoband
- numberOfStudies: number of datasets with this SNP
- N: sample size
- I2: heterogeneity of SNP in meta-analysis
- EAF: effect allele frequency
- MAF: minor allele frequency
- infoScore: imputation info score
- effect_allele: effect allele
- other_allele: non-effect allele
- beta: effect estimate
- SE: standard error of effect estimate
- P: P-value
- logP: -log10(P-value)
- phenotype: phenotype and subgroup analysed
- invalid_assoc: flag for validity of the association (TRUE = not valid, does not fulfil all requirements, FALSE = valid, fulfils all requirements)
- reason_for_exclusion: reason for exclusion from analysis (why is association not valid)
Phenotypes
- eGFR
- UA
- BUN
- CKD
- UACR
- MA
- Gout
Files
- CKDGen_ChrX_BUN_ALL.csv.gz
- CKDGen_ChrX_BUN_FEMALE.csv.gz
- CKDGen_ChrX_BUN_MALE.csv.gz
- CKDGen_ChrX_CKD_ALL.csv.gz
- CKDGen_ChrX_CKD_FEMALE.csv.gz
- CKDGen_ChrX_CKD_MALE.csv.gz
- CKDGen_ChrX_Gout_ALL.csv.gz
- CKDGen_ChrX_Gout_FEMALE.csv.gz
- CKDGen_ChrX_Gout_MALE.csv.gz
- CKDGen_ChrX_MA_ALL.csv.gz
- CKDGen_ChrX_MA_FEMALE.csv.gz
- CKDGen_ChrX_MA_MALE.csv.gz
- CKDGen_ChrX_UACR_ALL.csv.gz
- CKDGen_ChrX_UACR_FEMALE.csv.gz
- CKDGen_ChrX_UACR_MALE.csv.gz
- CKDGen_ChrX_UA_ALL.csv.gz
- CKDGen_ChrX_UA_FEMALE.csv.gz
- CKDGen_ChrX_UA_MALE.csv.gz
- CKDGen_ChrX_eGFR_ALL.csv.gz
- CKDGen_ChrX_eGFR_FEMALE.csv.gz
- CKDGen_ChrX_eGFR_MALE.csv.gz