No retraction, correction or concern found when last checked on Oct 30, 2026.
LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis
Jie Zheng, A Mesut Erzurumluoglu, Benjamin L Elsworth and 17 more
Bioinformatics · 2016 · CC BY
doi:10.1093/bioinformatics/btw613
Abstract
Motivation. LD score regression is a reliable and efficient method of using genome-wide association study (GWAS) summary-level results data to estimate the SNP heritability of complex traits and diseases, partition this heritability into functional categories, and estimate the genetic correlation between different phenotypes. Because the method relies on summary level results data, LD score regression is computationally tractable even for very large sample sizes. However, publicly available GWAS summary-level data are typically stored in different databases and have different formats, making it difficult to apply LD score regression to estimate genetic correlations across many different traits simultaneously.
Results. In this manuscript, we describe LD Hub - a centralized database of summary-level GWAS results for 173 diseases/traits from different publicly available resources/consortia and a web interface that automates the LD score regression analysis pipeline. To demonstrate functionality and validate our software, we replicated previously reported LD score regression analyses of 49 traits/diseases using LD Hub; and estimated SNP heritability and the genetic correlation across the different phenotypes. We also present new results obtained by uploading a recent atopic dermatitis GWAS meta-analysis to examine the genetic correlation between the condition and other potentially related traits. In response to the growing availability of publicly accessible GWAS summary-level results data, our database and the accompanying web interface will ensure maximal uptake of the LD score regression methodology, provide a useful database for the public dissemination of GWAS results, and provide a method for easily screening hundreds of traits for overlapping genetic aetiologies.
Availability and Implementation. The web interface and instructions for using LD Hub are available at http://ldsc.broadinstitute.org/
Supplementary information. Supplementary data are available at Bioinformatics online.
References 61
- 1.
1000 Genomes Project Consortium. (2012 ) An integrated map of genetic variation from 1,092 human genomes. Nature, 491, 56–65. [TQ1]
Not in our library10.1038/nature11632
- 2.
Bataille V. et al (2012 ) The use of the twin model to investigate the genetics and epigenetics of skin diseases with genomic, transcriptomic and methylation data. J. Eur. Acad. Dermatol. Venereol., 26, 1067–1073.
Not in our library10.1111/j.1468-3083.2011.04444.x
- 3.
Benyamin B. et al (2013 ) Childhood intelligence is heritable, highly polygenic and associated with FNBP1L. Mol. Psychiatry, 19, 253–258.
Not in our library10.1038/mp.2012.184
- 4.
Berndt S. et al (2013 ) Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture. Nat. Genet., 45, 501–512.
Not in our library10.1038/ng.2606
- 5.
Boraska V. et al (2014 ) A genome-wide association study of anorexia nervosa. Mol. Psychiatry, 19, 1085–1094.
Not in our library10.1038/mp.2013.187
- 6.
Bradfield J. et al (2012 ) A genome-wide association meta-analysis identifies new childhood obesity loci. Nat. Genet., 44, 526–531.
Not in our library10.1038/ng.2247
- 7.
Bulik-Sullivan et al (2015a ) LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet., 47, 291–295.
Not in our library10.1038/ng.3211
- 8.
Bulik-Sullivan et al (2015b ) An atlas of genetic correlations across human diseases and traits. Nat. Genet., 47, 1236–1241.
Not in our library10.1038/ng.3406
- 9.
Cross-Disorder Group of the Psychiatric Genomics Consortium. (2013 ) Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet, 381, 1371–1379.
Not in our library10.1016/s0140-6736(12)62129-1
- 10.
- 11.
Davey Smith G., Ebrahim S. (2003 ) Mendelian randomization: can genetic epidemiology contribute to understanding environmental determinants of disease?Int. J. Epidemiol., 32, 1–22.
Not in our library10.1093/ije/dyg070
- 12.
de Moor M. et al (2010 ) Meta-analysis of genome-wide association studies for personality. Mol. Psychiatry, 17, 337–349.
Not in our library10.1038/mp.2010.128
- 13.
Dupuis J. et al (2010 ) New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat. Genet., 42, 105–116.
Not in our library10.1038/ng.520
- 14.
East E.M. (1916 ) Studies on size inheritance in Nicotiana. Genetics, 1, 164–176.
Not in our library10.1093/genetics/1.2.164
- 15.
Estrada K. et al (2012 ) Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture. Nat. Genet., 44, 491–501.
Not in our library10.1038/ng.2249
- 16.
Evans D.M., Davey Smith G. (2015 ) Mendelian randomization: new applications in the coming age of hypothesis-free causality. Annu. Rev. Genomics Hum. Genet., 16, 327–350.
Not in our library10.1146/annurev-genom-090314-050016
- 17.
Finucane H.K. et al (2015 ) Partitioning heritability by functional category using GWAS summary statistics. Nat. Genet., 47, 1228–1235.
Not in our library10.1038/ng.3404
- 18.
Fisher R.A. (1918 ) The correlation between relatives on the supposition of Mendelian inheritance. Philos. Transac. R. Soc. Edinburgh, 52, 399–433.
Not in our library
- 19.
Furberg H. et al (2010 ) Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nat. Genet., 42, 441–447.
Not in our library10.1038/ng.571
- 20.
Gusev A. et al (2014 ) Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases. Am. J. Hum. Genet., 95, 535–552.
Not in our library10.1016/j.ajhg.2014.10.004
- 21.
Hindorff L.A. et al (2009 ) Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl Acad. Sci. USA., 106, 9362–9367.
Not in our library10.1073/pnas.0903103106
- 22.
Horikoshi M. et al (2012 ) New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism. Nat. Genet., 45, 76–82.
Not in our library10.1038/ng.2477
- 23.
Huffman J. et al (2015 ) Modulation of genetic associations with serum urate levels by body-mass-index in humans. PLos One, 10, e0119752.
Not in our library10.1371/journal.pone.0119752
- 24.
International HapMap 3 Consortium. (2010 ) Integrating common and rare genetic variation in diverse human populations. Nature, 467, 52–58.
Not in our library10.1038/nature09298
- 25.
- 26.
Lambert J. et al (2013 ) Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nat. Genet., 45, 1452–1458.
Not in our library10.1038/ng.2802
- 27.
Lango Allen H. et al (2010 ) Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature, 467, 832–838.
Not in our library10.1038/nature09410
- 28.
Lee H. et al (2011 ) Estimating missing heritability for disease from genome-wide association studies. Am. J. Hum. Genet., 88, 294–305.
Not in our library10.1016/j.ajhg.2011.02.002
- 29.
Lee H. et al (2012 ) Estimation of pleiotropy between complex diseases using SNP-derived genomic relationships and restricted maximum likelihood. Bioinformatics, 28, 2540–2542.
Not in our library10.1093/bioinformatics/bts474
- 30.
Liu J.Z. et al (2015 ) Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat. Genet., 47, 979–986.
Not in our library10.1038/ng.3359
- 31.
Manning A. et al (2012 ) A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance. Nat. Genet., 44, 659–669.
Not in our library10.1038/ng.2274
- 32.
Moffatt M.F. et al (2007 ) Genetic variants regulating ORMDL3 expression contribute to the risk of childhood asthma. Nature, 448, 470–473.
Not in our library10.1038/nature06014
- 33.
Morris A. et al (2012 ) Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat. Genet., 44, 981–990.
Not in our library10.1038/ng.2383
- 34.
Neale B. et al (2010 ) Meta-analysis of genome-wide association studies of attention-deficit/hyperactivity disorder. J. Am. Acad. Child Adolesc. Psychiatry, 49, 884–897.
Not in our library10.1016/j.jaac.2010.06.008
- 35.
Nikpay M. et al (2015 ) A comprehensive 1,000 Genomes-based genome-wide association meta-analysis of coronary artery disease. Nat. Genet., 47, 1121–1130.
Not in our library10.1038/ng.3396
- 36.
Okada Y. et al (2013 ) Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature, 506, 376–381.
Not in our library10.1038/nature12873
- 37.
Paternoster L. et al (2015 ) Multi-ancestry genome-wide association study of 21,000 cases and 95,000 controls identifies new risk loci for atopic dermatitis. Nat. Genet., 47, 1449–1456.
Not in our library10.1038/ng.3424
- 38.
- 39.
Perry J. et al (2014 ) Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche. Nature, 514, 92–97.
Not in our library10.1038/nature13545
- 40.
Rietveld C. et al (2013 ) GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science, 340, 1467–1471.
Not in our library10.1126/science.1235488
Cited by papers we hold 70
- GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture · 2023No notice
- European and multi-ancestry genome-wide association meta-analysis of atopic dermatitis highlights importance of systemic immune regulation · 2023No notice
- Discovery of 42 genome-wide significant loci associated with dyslexia · 2022Corrected
- Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention · 2022No notice
- Complement C1q-dependent excitatory and inhibitory synapse elimination by astrocytes and microglia in Alzheimer’s disease mouse models · 2022No notice
- Genome-wide analyses of individual differences in quantitatively assessed reading- and language-related skills in up to 34,000 people · 2022No notice
- Genetic analysis of over half a million people characterises C-reactive protein loci · 2022Corrected
- Genome-wide meta-analysis for Alzheimer’s disease cerebrospinal fluid biomarkers · 2022No notice
- Multi-ancestry genome-wide association study of gestational diabetes mellitus highlights genetic links with type 2 diabetes · 2022No notice
- Multivariate analysis reveals shared genetic architecture of brain morphology and human behavior · 2021Not checked
- Joint Analysis of Genome-Wide Association Data Reveals No Genetic Correlations Between Low Back Pain and Neurodegenerative Diseases · 2021Not checked
- Identification of 38 novel loci for systemic lupus erythematosus and genetic heterogeneity between ancestral groups · 2021No notice
- The variant call format provides efficient and robust storage of GWAS summary statistics · 2021No notice
- Genetic and clinical characteristics of treatment-resistant depression using primary care records in two UK cohorts · 2021No notice
- Genetic predictors of participation in optional components of UK Biobank · 2021No notice
- SUPERGNOVA: local genetic correlation analysis reveals heterogeneous etiologic sharing of complex traits · 2021No notice
- webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study · 2021No notice
- GWAS of peptic ulcer disease implicates Helicobacter pylori infection, other gastrointestinal disorders and depression · 2021No notice
- An international genome-wide meta-analysis of primary biliary cholangitis: Novel risk loci and candidate drugs · 2021Corrected
- Genetic analysis in European ancestry individuals identifies 517 loci associated with liver enzymes · 2021No notice
and 50 more
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.