Summary Statistics for 17-OH-Progesterone Version 1
Summary statistics from meta GWAS of 17-OH-progesterone for
- all samples (adjusted for age, log(BMI) and sex)
- men only (adjusted for age and log(BMI))
- women only (adjusted for age and log(BMI))
These data are intended for research purposes only.
Citation: Pott et al. (2019) Genetic Association Study of Eight Steroid Hormones and Implications for Sexual Dimorphism of Coronary Artery Disease. J Clin Endocrinol Metab 104: 5008–5023. PubMed ID: 31169883
When using this data acknowledge the source as follows: 'Data on 17-OH-progesterone has been contributed by LIFE-Adult and LIFE-Heart investigators and has been downloaded from https://www.health-atlas.de/assays/27 '
For any enquiries about the datasets, please contact Janne Pott (janne.pott@imise.uni-leipzig.de) or Markus Scholz (markus.scholz@imise.uni-leipzig.de)
Files are in text delimited format and include: Markername, chr, bp_hg19, effect_allele, other_allele, effect_allele_freq, min_info, n, beta, se, p
LHA ID: 7YRGRVQVPX-8
Filename:
SummaryStatisticsOHP17.zip
Format: Zip file
Size: 802 MB
Data file type: Other OMICs Data
Human Diseases: No Human Disease specified
Export PNG
Creators and Submitter
Views: 3720 Downloads: 284
Created: 8th Nov 2019 at 14:44
Last updated: 16th Dec 2019 at 08:50
Last used: 21st Nov 2024 at 08:42
TagsThis item has not yet been tagged.
AttributionsNone
Version History
Version 1 Created 8th Nov 2019 at 14:44 by Janne Pott
No revision comments
Related items
The group is interested in omic-level studies including the genome, methylome, transcriptome, and metabolome of the general population as well as of various diseases including cardiovascular diseases, pneumonia, sepsis, obesity, and brain cancers. Additionally, we aim at transfering results of biomathematical model simulations into clinical practice e.g. by haematopoietic growth-factor opimization during cytotoxic chemotherapy and optimization of EPO applications in chronic kidney disease.
The ...
Programme: This Project is not associated with a Programme
Public web page: http://www.imise.uni-leipzig.de/en/Groups/GenStat/
Start date: 1st Jan 2013
Resutls of different OMICS-level using LIFE Adult and LIFE Heart data are presented (Publications, Supplemental Data, & Summary Statistics).
Submitter: René Hänsel
Studies: DNA methylation patterns reflect individual lifestyle independent from o..., GWAMA PCSK9, GWAMA Phytosterole, GWAMA Steroid hormones, GWAMA vaspin, GWAS Body Scanner Measures, GWAS Carotid Plaque Burden, GWAS Pulse Wave Velocity, GWAS Steroid Hormones, scRNA-Seq across species for pulmonologists
Resources: Gene Expression data, LIFE-Adult EPIC data, Summary Statistic for PWV GWAS, Summary Statistics, Summary Statistics, Summary Statistics, Summary Statistics, Summary Statistics, Summary Statistics - Phytosterols, Supplement Data, scRNA-Seq expression data as RDS Seurat file
Supplement Data for Publication including Supplement Material & Results (eQTL annotation, Mendelian Randomization (MR), further significant loci), Figures (correlation plot of steroid hormones, scatter plot of genetic effect sizes, regional association plots, scatter plots of MR) and Tables (Correlations, GWAS summary statistics, interaction tests, MR results)
Submitter: René Hänsel
Investigation: OMICS Investigations
Resources: Summary Statistics, Supplement Data
Study type: Genetic study
We are releasing the summary data from our meta-analyses of steroid hormones, to empower other researchers to examine variants or loci in which they are interested for association with these hormonal traits. These data are intended for research purposes only.
Citation: Pott et al. (2019) Genetic Association Study of Eight Steroid Hormones and Implications for Sexual Dimorphism of Coronary Artery Disease. J Clin Endocrinol Metab 104: 5008–5023. PubMed ID: 31169883
When using this data acknowledge ...
Submitter: Janne Pott
Resource type: Genome Wide Association
Technology type: SNP Array
Investigation: OMICS Investigations
Study: GWAS Steroid Hormones
https://orcid.org/0000-0002-5983-5331
