The DOI matches its Crossref record; 35 of the 37 references it cites were found in a registry or an index.
Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits
Open accessAbstract
We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium.
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“A conditional analysis 59 was used to identify independently-segregating variants in each of the merged loci that was genome-wide significant, using the linkage disequilibrium structure of UK Biobank as a reference panel.”
From Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions (2019) · cites this paper as [59]
In the citing paper
“GCTA COJO27 conditional analysis of the genome-wide loci indicates that TREM2 and three other loci (BIN1, ABCA7, and PTK2B/CLU) have multiple independent LOAD association signals”
From Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing (2019) · cites this paper as [27]
In the citing paper
“We performed approximate conditional analysis in each locus reaching genome-wide significance using Genome-wide Complex Trait Analysis27 (GCTA) but did not identify secondary signal in any locus.”
From GWAS identifies 14 loci for device-measured physical activity and sleep duration (2018) · cites this paper as [27]
In the citing paper
“Within these 136 loci, multi-SNP-based conditional analysis (Yang et al., 2012) identified 10 additional SNPs with independent associations, resulting in a total of 146 independent lead SNPs”
From Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders (2019) · cites this paper as Yang et al., 2012
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PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
GCTA: a tool for genome-wide complex trait analysis
Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.11.011 · Cited by 8,279
Self-citationA map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877
Genetics of Food Intake Self-Regulation in Childhood: Literature Review and Research Opportunities
Faith, M. S., Carnell, S., & Kral, T. V. E. (2013) · Human Heredity · doi:10.1159/000353879 · Cited by 7,633
Common SNPs explain a large proportion of the heritability for human height
Yang, J., Benyamin, B., McEvoy, B. P., Gordon, S., Henders, A. K., Nyholt, D. R., Madden, P. A., Heath, A. C., Martin, N. G., Montgomery, G. W., et al. (2010) · Nature Genetics · doi:10.1038/ng.608 · Cited by 4,446
Self-citationA second generation human haplotype map of over 3.1 million SNPs
The International HapMap Consortium (2007) · Nature · doi:10.1038/nature06258 · Cited by 4,438
Hindorff, L. A., Sethupathy, P., Junkins, H. A., Ramos, E. M., Mehta, J. P., Collins, F. S., & Manolio, T. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0903103106 · Cited by 4,013
Genomic Control for Association Studies
Devlin, B., & Roeder, K. (1999) · Biometrics · doi:10.1111/j.0006-341x.1999.00997.x · Cited by 3,162 · cited 1×
“(20) As in a joint analysis, if the individual-level genotype data of the discovery sample are unavailable, we can estimate the LD correlations from the reference sample and approximate a conditional analysis as”
Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index
MAGIC, Speliotes, E. K., on behalf of Procardis Consortium, Willer, C. J., Berndt, S. I., Monda, K. L., Thorleifsson, G., Jackson, A. U., Allen, H. L., Lindgren, C. M., et al. (2010) · Nature Genetics · doi:10.1038/ng.686 · Cited by 2,912
Self-citationHundreds of variants clustered in genomic loci and biological pathways affect human height
Lango Allen, H., Estrada, K., Lettre, G., Berndt, S. I., Weedon, M. N., Rivadeneira, F., Willer, C. J., Jackson, A. U., Vedantam, S., Raychaudhuri, S., et al. (2010) · Nature · doi:10.1038/nature09410 · Cited by 1,945
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Mendelian Randomization Analysis With Multiple Genetic Variants Using Summarized Data
Burgess, S., Butterworth, A., & Thompson, S. G. (2013) · Genetic Epidemiology · doi:10.1002/gepi.21758 · Cited by 6,050
Giambartolomei, C., Vukcevic, D., Schadt, E. E., Franke, L., Hingorani, A. D., Wallace, C., & Plagnol, V. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004383 · Cited by 4,261
Genetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534
Self-citation10 Years of GWAS Discovery: Biology, Function, and Translation
Visscher, P. M., Wray, N. R., Zhang, Q., Sklar, P., McCarthy, M. I., Brown, M. A., & Yang, J. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.06.005 · Cited by 3,719
Self-citationIntegration of summary data from GWAS and eQTL studies predicts complex trait gene targets
Zhu, Z., Zhang, F., Hu, H., Bakshi, A., Robinson, M. R., Powell, J. E., Montgomery, G. W., Goddard, M. E., Wray, N. R., Visscher, P. M., et al. (2016) · Nature Genetics · doi:10.1038/ng.3538 · Cited by 3,352
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Metadata
- Authors
- Genetic Investigation of ANthropometric Traits (GIANT) Consortium, Yang, J., DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Ferreira, T., Morris, A. P., Medland, S. E., Madden, P. A. F., Heath, A. C., Martin, N. G., Montgomery, G. W., Weedon, M. N., Loos, R. J., Frayling, T. M., McCarthy, M. I., Hirschhorn, J. N., Goddard, M. E., & Visscher, P. M.
- Affiliations
- QIMR Berghofer Medical Research Institute (AU)
- Centre for Human Genetics (GB)
- Washington University in St. Louis (US)
- University of Exeter (GB)
- Addenbrooke's Hospital (GB)
- Broad Institute (US)
- The University of Melbourne (AU)
- The University of Queensland (AU)
- Corresponding author
- Visscher, Peter M
- ORCID
- Venue
- Nature Genetics
- Published
- 2012-03-18
- Volume
- 44
- Issue
- 4
- Pages
- 369-375
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC3593158
- OpenAlex
- W2152885121
- Cited by
- 1,712
- References
- 37
- Citations by year
- 2026: 144 · 2025: 168 · 2024: 230 · 2023: 186 · 2022: 172 · 2021: 159 · 2020: 124 · 2019: 127 · 2018: 104 · 2017: 92 · 2016: 61 · 2015: 43 · 2014: 42 · 2013: 44 · 2012: 16
- FWCI
- 27.95
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Site cant be reached (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
- Funders
- Wellcome Trust (WT083270, 090532)
- U.S. Public Health Service (HHSN 268200625226C)
- National Institute on Alcohol Abuse and Alcoholism (AA-10248, K05AA017688, R01AA013321, AA13320, AA13321, AA-014041, R01AA013326, AA13326, R01AA013320, R01AA014041, R01AA007535)
- National Heart, Lung, and Blood Institute (HHSN268201 100012C, HHSN268201100007I, HHSN268201100007C, HHSN2682 01100008C, HH-SN-268201100006C, HHSN268201100011C, HHSN2682011-00005I, HHSN2682011-00009I, R01 HL-59367, HHSN268201100005C, HHSN268201100005G, HHSN268201100010C, HHSN268201100011I, R01HL087641, R01HL059367, HHSN26820 1100009C, HHSN2682011-00008I, R01HL086694)
- National Institute on Drug Abuse (R56DA012854, DA12854, R01DA012854)
- National Human Genome Research Institute (U01HG004402)
- National Center for Research Resources (UL1RR025005)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Keywords
- GWAS summary statistics, linkage disequilibrium, height, body mass index, type 2 diabetes, heritability, complex traits, case-control data
- MeSH terms
- Algorithms, Body Height, Data Interpretation, Statistical, Diabetes Mellitus, Type 2, Genotype, Humans, Phenotype, Genetic Variation, Meta-Analysis as Topic, Linkage Disequilibrium, Genome, Human, Body Mass Index, Case-Control Studies, Polymorphism, Single Nucleotide, Cyclin-Dependent Kinase Inhibitor p15, Genome-Wide Association Study, Genetic Loci
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