10.5281/zenodo.1319332
https://zenodo.org/records/1319332
oai:zenodo.org:1319332
Maxim B Freidin
Maxim B Freidin
Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, UK
Yakov A Tsepilov
Yakov A Tsepilov
0000-0002-4931-6052
Novosibirsk State University, Faculty of Natural Sciences, Novosibirsk, Russia
Melody Palmer
Melody Palmer
Department of Medical Genetics, University of Washington, Seattle, USA
Lennart Karssen
Lennart Karssen
0000-0002-1959-342X
PolyOmica, 's-Hertogenbosch, The Netherlands
CHARGE Musculoskeletal Working Group
CHARGE Musculoskeletal Working Group
Pradeep Suri
Pradeep Suri
Seattle Epidemiologic Research and Information Center (ERIC), Veterans Affairs Office of Research and Development, Seattle, USA
Yurii S Aulchenko
Yurii S Aulchenko
0000-0002-7899-1575
PolyOmica, 's-Hertogenbosch, The Netherlands
Frances MK Williams
Frances MK Williams
Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, UK
Genome-wide association summary statistics for back pain
Zenodo
2018
back pain
genetics
gwas
2018-07-23
10.5281/zenodo.1319331
https://zenodo.org/communities/gwasarchive
https://zenodo.org/communities/painomics
1
Creative Commons Attribution 4.0 International
The dataset contains results of a genome-wide association study of back pain. Two files contain association summary statistics for discovery GWAS based on the analysis of 350,000 white British individuals from the UK Biobank and meta-analysis GWAS based on the meta-analysis of the same 350,000 individuals and additional 103,862 individuals of European Ancestry from the UK biobank (total N = 453,862). The phenotype of back pain was defined by the answer provided by the UK biobank participants to the following question: "Pain type(s) experienced in last month". Those who reported “Back pain”, were considered as cases, all the rest were considered as controls. Individuals who did not reply or replied: "Prefer not to answer" or "Pain all over the body" were excluded. This dataset is also available for graphical exploration in the genomic context at http://gwasarchive.org.
The data are provided on an "AS-IS" basis, without warranty of any type, expressed or implied, including but not limited to any warranty as to their performance, merchantability, or fitness for any particular purpose. If investigators use these data, any and all consequences are entirely their responsibility. By downloading and using these data, you agree that you will cite the appropriate publication in any communications or publications arising directly or indirectly from these data; for utilisation of data available prior to publication, you agree to respect the requested responsibilities of resource users under 2003 Fort Lauderdale principles; you agree that you will never attempt to identify any participant. This research has been conducted using the UK Biobank Resource and the use of the data is guided by the principles formulated by the UK Biobank.
When using downloaded data, please cite corresponding paper and this repository:
Insight into the genetic architecture of back pain and its risk factors from a study of 509,000 individuals. Freidin, Maxim; Tsepilov, Yakov; Palmer, Melody; Karssen, Lennart; Suri, Pradeep; Aulchenko, Yurii; Williams, Frances MK,# CHARGE Musculoskeletal Working Group. PAIN: February 06, 2019 - Volume Articles in Press - Issue - p
doi: 10.1097/j.pain.0000000000001514
Maxim B Freidin, Yakov A Tsepilov, Melody Palmer, Lennart Karssen, CHARGE Musculoskeletal Working Group, Pradeep Suri, … Frances MK Williams. (2018). Genome-wide association summary statistics for back pain (Version 1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.1319332
Funding:
This study was supported by the European Community’s Seventh Framework Programme funded project PainOmics (Grant agreement # 602736).
The research has been conducted using the UK Biobank Resource (project # 18219).
The development of software implementing SMR/HEIDI test and database for GWAS results was supported by the Russian Ministry of Science and Education under the 5-100 Excellence Program”.
Dr. Suri’s time for this work was supported by VA Career Development Award # 1IK2RX001515 from the United States (U.S.) Department of Veterans Affairs Rehabilitation Research and Development Service. The contents of this work do not represent the views of the U.S. Department of Veterans Affairs or the United States Government.
Dr. Tsepilov’s time for this work was supported in part by the Russian Ministry of Science and Education under the 5-100 Excellence Program.
Column headers - discovery (350K)
CHR: chromosome
POS: position (GRCh37 build)
ID: SNP rsID
REF: reference allele (coded as "0")
ALT: effect allele (coded as "1")
CASE_ALLELE_CT: allele observation count in cases
CTRL_ALLELE_CT: allele observation count in controls
ALT_FREQ: effect allele frequency
MACH_R2: imputation quality
TEST: model of association test (additive)
OBS_CT: sample size
BETA: effect size of effect allele
SE: standard error of effect size
T_STAT: Z-value of effect allele
P: P-value of association (without GC correction)
MAF: minor allele frequency
Column headers - meta-analysis (450K)
MarkerName: SNP rsID
Allele1: effect allele (coded as "1")
Allele2: reference allele (coded as "0")
Freq1: effect allele frequency
FreqSE: standard error of effect allele frequency
Effect: effect size of effect allele
StdErr: standard error of effect size
P-value: P-value of association (without GC correction)
Direction: sign of effect in discovery and replication samples
n_total: Total sample size
CHR: chromosome
POS: position (GRCh37 build)
MACH_R2_discovery: imputation quality in discovery sample
European Commission
10.13039/501100000780
602736
Multi-dimensional omics approach to stratification of patients with low back pain