Abstract

Identifying genetic correlations between complex traits and diseases can provide useful etiological insights and help prioritize likely causal relationships. The major challenges preventing estimation of genetic correlation from genome-wide association study (GWAS) data with current methods are the lack of availability of individual-level genotype data and widespread sample overlap among meta-analyses. We circumvent these difficulties by introducing a technique—cross-trait LD Score regression—for estimating genetic correlation that requires only GWAS summary statistics and is not biased by sample overlap. We use this method to estimate 276 genetic correlations among 24 traits. The results include genetic correlations between anorexia nervosa and schizophrenia, anorexia and obesity, and educational attainment and several diseases. These results highlight the power of genome-wide analyses, as there currently are no significantly associated SNPs for anorexia nervosa and only three for educational attainment.

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Acknowledgements

We would like to thank P. Sullivan, C. Bulik, S. Caldwell, C. Arabica and O. Andreassen for helpful comments. This work was supported by US National Institutes of Health (NIH) grants R01 MH101244 (A.L.P.), R01 HG006399 (N.P.), 1R01 MH101244-02 (B.M.N.), 5U01 MH094432-03 (B.M.N.) and R03 CA173785 (H.K.F.) and by the Fannie and John Hertz Foundation (H.K.F.). Data on anorexia nervosa were obtained by funding from the Wellcome Trust Case Control Consortium 3 project titled “A Genome-Wide Association Study of Anorexia Nervosa” (WT088827/Z/09). Data on glycemic traits were contributed by MAGIC investigators and were downloaded from http://www.magicinvestigators.org/. Data on coronary artery disease and myocardial infarction were contributed by CARDIoGRAMplusC4D investigators and were downloaded from http://www.cardiogramplusc4d.org/.

We thank the International Genomics of Alzheimer's Project (IGAP) for providing summary results data for these analyses. The investigators within IGAP contributed to the design and implementation of IGAP and/or provided data but did not participate in the analysis or writing of this report. IGAP was made possible by the generous participation of the control subjects, the patients and their families. The work with iSelect chips was funded by the French National Foundation on Alzheimer's Disease and Related Disorders. EADI was supported by a LABEX (Laboratory of Excellence Program Investment for the Future) DISTALZ grant, INSERM, Institut Pasteur de Lille, Université de Lille 2 and the Lille University Hospital. GERAD was supported by the Medical Research Council, UK (grant 503480), Alzheimer's Research UK (grant 503176), the Wellcome Trust (grant 082604/2/07/Z) and the German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) grants 01GI0102 and 01GI0711, 01GI0420. CHARGE was partly supported by US NIH/National Institute on Aging grants R01 AG033193 and AG081220 and AGES contract N01-AG-12100, National Heart, Lung, and Blood Institute (NHLBI) grant R01 HL105756, the Icelandic Heart Association, and the Erasmus Medical Center and Erasmus University. ADGC was supported by US NIH/National Institute on Aging grants U01 AG032984, U24 AG021886 and U01 AG016976 and Alzheimer's Association grant ADGC-10-196728.

Author information

Author notes

    • Brendan Bulik-Sullivan
    •  & Hilary K Finucane

    These authors contributed equally to this work.

    • Alkes L Price
    •  & Benjamin M Neale

    These authors jointly supervised this work.

Affiliations

  1. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

    • Brendan Bulik-Sullivan
    • , Verneri Anttila
    • , Po-Ru Loh
    • , Laramie Duncan
    • , Nick Patterson
    • , Elise B Robinson
    • , Mark J Daly
    • , Alkes L Price
    •  & Benjamin M Neale
  2. Stanley Center for Psychiatric Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

    • Brendan Bulik-Sullivan
    • , Verneri Anttila
    • , Laramie Duncan
    • , Elise B Robinson
    • , Mark J Daly
    •  & Benjamin M Neale
  3. Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.

    • Brendan Bulik-Sullivan
    • , Verneri Anttila
    • , Laramie Duncan
    • , Elise B Robinson
    • , Mark J Daly
    •  & Benjamin M Neale
  4. Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.

    • Hilary K Finucane
  5. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.

    • Alexander Gusev
    • , Po-Ru Loh
    •  & Alkes L Price
  6. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.

    • Alexander Gusev
    •  & Alkes L Price
  7. Medical Research Council (MRC) Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK.

    • Felix R Day
    •  & John R B Perry

Consortia

  1. ReproGen Consortium

    A full list of members and affiliations appears in the Supplementary Note.

  2. Psychiatric Genomics Consortium

    A full list of members and affiliations appears in the Supplementary Note.

  3. Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control Consortium 3

    A full list of members and affiliations appears in the Supplementary Note.

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Contributions

M.J.D., A.G., P.-R.L., L.D., N.P., B.M.N. and A.L.P. provided reagents. E.B.R., V.A., J.R.B.P. and F.R.D. aided in the interpretation of results. J.R.B.P. and F.R.D. provided data on age at menarche. B.B.-S. and H.K.F. are responsible for the remainder. All authors revised and approved the final manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Brendan Bulik-Sullivan or Hilary K Finucane or Alkes L Price or Benjamin M Neale.

Supplementary information

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    Supplementary Text and Figures

    Supplementary Figures 1–6, Supplementary Tables 1–3 and Supplementary Note.

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    Supplementary Table 4

    Table of genetic correlations.

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DOI

https://doi.org/10.1038/ng.3406

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