Hostname: page-component-5cf477f64f-fcbfl Total loading time: 0 Render date: 2025-04-05T06:06:14.397Z Has data issue: false hasContentIssue false
  • English
  • Français

Investigation of convergent and divergent genetic influences underlying schizophrenia and alcohol use disorder

Published online by Cambridge University Press:  07 July 2021

Emma C. Johnson Open the ORCID record for Emma C. Johnson [Opens in a new window] ,
Manav Kapoor Open the ORCID record for Manav Kapoor [Opens in a new window] ,
Alexander S. Hatoum Open the ORCID record for Alexander S. Hatoum [Opens in a new window] ,
Hang Zhou ,
Renato Polimanti Open the ORCID record for Renato Polimanti [Opens in a new window] ,
Frank R. Wendt Open the ORCID record for Frank R. Wendt [Opens in a new window] ,
Raymond K. Walters Open the ORCID record for Raymond K. Walters [Opens in a new window] ,
Dongbing Lai Open the ORCID record for Dongbing Lai [Opens in a new window] ,
Rachel L. Kember Open the ORCID record for Rachel L. Kember [Opens in a new window]  and
Sarah Hartz Open the ORCID record for Sarah Hartz [Opens in a new window]
...Show all authors
Emma C. Johnson*
Affiliation:
Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
Manav Kapoor
Affiliation:
Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
Alexander S. Hatoum
Affiliation:
Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
Hang Zhou
Affiliation:
Department of Psychiatry, Division of Human Genetics, Yale University School of Medicine, New Haven, CT, USA Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
Renato Polimanti
Affiliation:
Department of Psychiatry, Division of Human Genetics, Yale University School of Medicine, New Haven, CT, USA Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
Frank R. Wendt
Affiliation:
Department of Psychiatry, Division of Human Genetics, Yale University School of Medicine, New Haven, CT, USA Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA
Raymond K. Walters
Affiliation:
Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
Dongbing Lai
Affiliation:
Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
Rachel L. Kember
Affiliation:
Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA VISN 4 MIRECC, Crescenz VAMC, Philadelphia, PA, USA
Sarah Hartz
Affiliation:
Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
Jacquelyn L. Meyers
Affiliation:
Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA Henri Begleiter Neurodynamics Laboratory, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
Roseann E. Peterson
Affiliation:
Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
Stephan Ripke
Affiliation:
Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Campus Mitte, Berlin, Germany
Tim B. Bigdeli
Affiliation:
Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
Ayman H. Fanous
Affiliation:
Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
Carlos N. Pato
Affiliation:
Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
Michele T. Pato
Affiliation:
Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, Brooklyn, NY, USA
Alison M. Goate
Affiliation:
Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
Henry R. Kranzler
Affiliation:
Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA VISN 4 MIRECC, Crescenz VAMC, Philadelphia, PA, USA
Michael C. O'Donovan
Affiliation:
Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, UK
James T.R. Walters
Affiliation:
Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, UK
Joel Gelernter
Affiliation:
Department of Psychiatry, Division of Human Genetics, Yale University School of Medicine, New Haven, CT, USA Department of Psychiatry, Veterans Affairs Connecticut Healthcare System, West Haven, CT, USA Department of Genetics, Yale University School of Medicine, New Haven, CT, USA Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA
Howard J. Edenberg
Affiliation:
Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
Arpana Agrawal
Affiliation:
Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
*
Author for correspondence: Emma C. Johnson, E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders.

Methods

We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific.

Results

We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001).

Conclusions

Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD.

Keywords

Alcoholschizophreniapleiotropygenome wide association studygenetic overlap
Type
Original Article
Information
Psychological Medicine , Volume 53 , Issue 4 , March 2023 , pp. 1196 - 1204
Check for updates
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aguet, F., Brown, A. A., Castel, S. E., Davis, J. R., He, Y., Jo, B., … Site—NDRI, B. C. S. (2017). Genetic effects on gene expression across human tissues. Nature, 550(7675), 204–213. doi: 10.1038/nature24277.Google Scholar
Akbarian, S., Liu, C., Knowles, J. A., Vaccarino, F. M., Farnham, P. J., Crawford, G. E., … Geschwind, D. H. (2015). The psychencode project. Nature Neuroscience, 18(12), 1707.CrossRefGoogle ScholarPubMed
Baselmans, B. M. L., Jansen, R., Ip, H. F., van Dongen, J., Abdellaoui, A., van de Weijer, M. P., … Bartels, M. (2019). Multivariate genome-wide analyses of the well-being spectrum. Nature Genetics, 51(3), 445–451. doi: 10.1038/s41588-018-0320-8.CrossRefGoogle ScholarPubMed
Bhattacharjee, S., Rajaraman, P., Jacobs, K. B., Wheeler, W. A., Melin, B. S., Hartge, P., … Chatterjee, N. (2012). A subset-based approach improves power and interpretation for the combined analysis of genetic association studies of heterogeneous traits. The American Journal of Human Genetics, 90(5), 821–835. doi: 10.1016/j.ajhg.2012.03.015.CrossRefGoogle ScholarPubMed
Bigdeli, T. B., Genovese, G., Georgakopoulos, P., Meyers, J. L., Peterson, R. E., Iyegbe, C. O., … Kotov, R. (2020). Contributions of common genetic variants to risk of schizophrenia among individuals of African and Latino ancestry. Molecular Psychiatry, 25, 2455–2467.CrossRefGoogle ScholarPubMed
Brady, K. T., Killeen, T., & Jarrell, P. (1993). Depression in alcoholic schizophrenic patients. American Journal of Psychiatry, 150(8), 1255–1256.Google ScholarPubMed
Bulik-Sullivan, B., Finucane, H. K., Anttila, V., Gusev, A., Day, F. R., Loh, P.-R., … Neale, B. M. (2015a). An atlas of genetic correlations across human diseases and traits. Nature Genetics, 47, 1236.CrossRefGoogle ScholarPubMed
Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., & Patterson, N., … Consortium, S. W. G. of the P. G. (2015b). LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nature Genetics, 47(3), 291–295.CrossRefGoogle ScholarPubMed
Castillo-Carniglia, A., Keyes, K. M., Hasin, D. S., & Cerdá, M. (2019). Psychiatric comorbidities in alcohol use disorder. The Lancet Psychiatry, 6(12), 1068–1080. doi: 10.1016/S2215-0366(19)30222-6.CrossRefGoogle ScholarPubMed
Clarke, T.-K., Adams, M. J., Davies, G., Howard, D. M., Hall, L. S., Padmanabhan, S., … McIntosh, A. M. (2017). Genome-wide association study of alcohol consumption and genetic overlap with other health-related traits in UK Biobank (N = 112117). Molecular Psychiatry., 22(10), 1376–1384. doi: 10.1038/mp.2017.153.CrossRefGoogle Scholar
Consortium, S. W. G. of the P. G. (2014). Biological insights from 108 schizophrenia-associated genetic loci. Nature, 511, 421.CrossRefGoogle Scholar
De Jager, P. L., Ma, Y., McCabe, C., Xu, J., Vardarajan, B. N., Felsky, D., … Bennett, D. A. (2018). A multi-omic atlas of the human frontal cortex for aging and Alzheimer's disease research. Scientific Data, 5(1), 180142. doi: 10.1038/sdata.2018.142.CrossRefGoogle ScholarPubMed
de Leeuw, C. A., Mooij, J. M., Heskes, T., & Posthuma, D. (2015). MAGMA: Generalized gene-set analysis of GWAS data. PLoS Computational Biology, 11(4), e1004219. doi: 10.1371/journal.pcbi.1004219.CrossRefGoogle ScholarPubMed
Demontis, D., Walters, R. K., Martin, J., Mattheisen, M., Als, T. D., Agerbo, E., … Bækvad-Hansen, M. (2019). Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nature Genetics, 51(1), 63.CrossRefGoogle ScholarPubMed
Drake, R. E., & Wallach, M. A. (1989). Substance abuse among the chronic mentally Ill. Psychiatric Services, 40(10), 1041–1046. doi: 10.1176/ps.40.10.1041.CrossRefGoogle ScholarPubMed
Duke, P. J., Pantelis, C., & Barnes, T. R. E. (1994). South Westminster schizophrenia survey. Alcohol use and its relationship to symptoms, tardive dyskinesia and illness onset. British Journal of Psychiatry, 164(MAY), 630–636. doi: 10.1192/bjp.164.5.630.CrossRefGoogle ScholarPubMed
Finucane, H. K., Reshef, Y. A., Anttila, V., Slowikowski, K., Gusev, A., Byrnes, A., … Consortium, T. B. (2018). Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Nature Genetics, 50(4), 621–629. doi: 10.1038/s41588-018-0081-4.CrossRefGoogle ScholarPubMed
Fisher, R. A. (1934). Statistical methods for research workers in Breakthroughs in Statistics (5th ed.). Edinburgh, UK: Oliver and Boyd.Google Scholar
Fromer, M., Roussos, P., Sieberts, S. K., Johnson, J. S., Kavanagh, D. H., Perumal, T. M., … Sklar, P. (2016). Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nature Neuroscience, 19(11), 1442–1453. doi: 10.1038/nn.4399.CrossRefGoogle ScholarPubMed
Hatoum, A. S., Johnson, E. C., Polimanti, R., Zhou, H., Walters, R., Consortium, S. U. D. W. G. of the P. G., … Agrawal, A. (2021). The addiction genetic factor a(g): A unitary genetic vulnerability characterizes substance use disorders and their associations with common correlates. MedRxiv, 2021.01.26.21250498. doi: 10.1101/2021.01.26.21250498.CrossRefGoogle Scholar
Howard, D. M., Adams, M. J., Clarke, T.-K., Hafferty, J. D., Gibson, J., Shirali, M., … Wigmore, E. M. (2019). Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nature Neuroscience, 22(3), 343–352.CrossRefGoogle ScholarPubMed
Hunt, G. E., Large, M. M., Cleary, M., Lai, H. M. X., & Saunders, J. B. (2018). Prevalence of comorbid substance use in schizophrenia spectrum disorders in community and clinical settings, 1990–2017: Systematic review and meta-analysis. Drug and Alcohol Dependence, 191, 234–258.CrossRefGoogle ScholarPubMed
Johnson, E. C., Demontis, D., Thorgeirsson, T. E., Walters, R. K., Polimanti, R., Hatoum, A. S., … Agrawal, A. (2020). A large-scale genome-wide association study meta-analysis of cannabis use disorder. The Lancet Psychiatry, 7(12), 1032–1045. doi: 10.1016/S2215-0366(20)30339-4.CrossRefGoogle ScholarPubMed
Kapoor, M., Wang, J.-C., Farris, S. P., Liu, Y., McClintick, J., Gupta, I., … Goate, A. (2019). Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism. Translational Psychiatry, 9(1), 89. doi: 10.1038/s41398-019-0384-y.CrossRefGoogle ScholarPubMed
Kranzler, H. R., Zhou, H., Kember, R. L., Vickers Smith, R., Justice, A. C., Damrauer, S., … Gelernter, J. (2019). Genome-wide association study of alcohol consumption and use disorder in 274424 individuals from multiple populations. Nature Communications, 10(1), 1499. doi: 10.1038/s41467-019-09480-8.CrossRefGoogle Scholar
Lam, M., Hill, W. D., Trampush, J. W., Yu, J., Knowles, E., Davies, G., … Lencz, T. (2019). Pleiotropic meta-analysis of cognition, education, and schizophrenia differentiates roles of early neurodevelopmental and adult synaptic pathways. The American Journal of Human Genetics, 105(2), 334–350. doi: 10.1016/J.AJHG.2019.06.012.CrossRefGoogle ScholarPubMed
Lee, P. H., Anttila, V., Won, H., Feng, Y.-C. A., Rosenthal, J., Zhu, Z., … Smoller, J. W. (2019). Genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders. Cell, 179(7), 1469–1482.e11. doi: 10.1016/j.cell.2019.11.020.CrossRefGoogle Scholar
Liberzon, A., Subramanian, A., Pinchback, R., Thorvaldsdóttir, H., Tamayo, P., & Mesirov, J. P. (2011). Molecular signatures database (MSigDB) 3.0. Bioinformatics (Oxford, England), 27(12), 1739–1740.Google Scholar
Liu, M., Jiang, Y., Wedow, R., Li, Y., Brazel, D. M., Chen, F., … Psychiatry, H. A.-I. (2019). Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use. Nature Genetics, 51(2), 237–244. doi: 10.1038/s41588-018-0307-5.CrossRefGoogle ScholarPubMed
Lonsdale, J., Thomas, J., Salvatore, M., Phillips, R., Lo, E., Shad, S., … Moore, H. F. (2013). The genotype-tissue expression (GTEx) project. Nature Genetics, 45, 580–585. doi: 10.1038/ng.2653.CrossRefGoogle Scholar
Lu, Q., Hu, Y., Sun, J., Cheng, Y., Cheung, K.-H., & Zhao, H. (2015). A statistical framework to predict functional non-coding regions in the human genome through integrated analysis of annotation data. Scientific Reports, 5, 10576.CrossRefGoogle ScholarPubMed
Lu, Q., Li, B., Ou, D., Erlendsdottir, M., Powles, R. L., Jiang, T., … Zhao, H. (2017a). A powerful approach to estimating annotation-stratified genetic covariance via GWAS summary statistics. The American Journal of Human Genetics, 101(6), 939–964. doi: 10.1016/j.ajhg.2017.11.001.CrossRefGoogle ScholarPubMed
Lu, Q., Powles, R. L., Abdallah, S., Ou, D., Wang, Q., Hu, Y., … Mukherjee, S. (2017b). Systematic tissue-specific functional annotation of the human genome highlights immune-related DNA elements for late-onset Alzheimer's disease. PLoS Genetics, 13(7), e1006933.CrossRefGoogle ScholarPubMed
Lu, Q., Powles, R. L., Wang, Q., He, B. J., & Zhao, H. (2016). Integrative tissue-specific functional annotations in the human genome provide novel insights on many complex traits and improve signal prioritization in genome wide association studies. PLoS Genetics, 12(4), e1005947.CrossRefGoogle ScholarPubMed
Marees, A. T., Smit, D. J. A., Abdellaoui, A., Nivard, M. G., van den Brink, W., Denys, D. (2021). Genetic correlates of socio-economic status influence the pattern of shared heritability across mental health traits. Nature Human Behavior, 1–9.Google ScholarPubMed
Marees, A. T., Smit, D. J. A., Ong, J.-S., MacGregor, S., An, J., Denys, D., … Derks, E. M. (2020). Potential influence of socioeconomic status on genetic correlations between alcohol consumption measures and mental health. Psychological Medicine, 50(3), 484–498.CrossRefGoogle ScholarPubMed
Miller, J. A., Ding, S.-L., Sunkin, S. M., Smith, K. A., Ng, L., Szafer, A., … Lein, E. S. (2014). Transcriptional landscape of the prenatal human brain. Nature, 508(7495), 199–206. doi: 10.1038/nature13185.CrossRefGoogle ScholarPubMed
Pardiñas, A. F., Holmans, P., Pocklington, A. J., Escott-Price, V., Ripke, S., Carrera, N., … Hamshere, M. L. (2018). Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection. Nature Genetics, 50(3), 381.CrossRefGoogle ScholarPubMed
Reginsson, G. W., Ingason, A., Euesden, J., Bjornsdottir, G., Olafsson, S., Sigurdsson, E., … Stefansson, K. (2018). Polygenic risk scores for schizophrenia and bipolar disorder associate with addiction. Addiction Biology, 23(1), 485–492. doi: 10.1111/adb.12496.CrossRefGoogle ScholarPubMed
Ruderfer, D. M., Ripke, S., McQuillin, A., Boocock, J., Stahl, E. A., Pavlides, J. M. W., … Kendler, K. S. (2018). Genomic dissection of bipolar disorder and schizophrenia, including 28 subphenotypes. Cell, 173(7), 1705–1715.e16. doi: 10.1016/j.cell.2018.05.046.CrossRefGoogle Scholar
SAMHSA (2019). 2018 National Survey on Drug Use and Health (NSDUH).Google Scholar
Sanchez-Roige, S., Palmer, A. A., Fontanillas, P., Elson, S. L., 23andMe Research Team, Substance Use Disorder Working Group of the Psychiatric Genomics Consortium, … Clarke, T.-K. (2019). Genome-wide association study meta-analysis of the alcohol use disorders identification test (AUDIT) in two population-based cohorts. American Journal of Psychiatry, 176(2), 107–118. doi: 10.1176/appi.ajp.2018.18040369.CrossRefGoogle ScholarPubMed
Stahl, E. A., Breen, G., Forstner, A. J., McQuillin, A., Ripke, S., & Trubetskoy, V., … Consortium, the B. D. W. G. of the P. G. (2019). Genome-wide association study identifies 30 loci associated with bipolar disorder. Nature Genetics, 51(5), 793–803. 10.1038/s41588-019-0397-8.CrossRefGoogle ScholarPubMed
Sullivan, P. F., Kendler, K. S., & Neale, M. C. (2003). Schizophrenia as a complex trait: Evidence from a meta-analysis of twin studies. Archives of General Psychiatry, 60(12), 1187–1192.CrossRefGoogle ScholarPubMed
Verhulst, B., Neale, M. C., & Kendler, K. S. (2015). The heritability of alcohol use disorders: A meta-analysis of twin and adoption studies. Psychological Medicine, 45(5), 1061–1072.CrossRefGoogle ScholarPubMed
Walters, R. K., Polimanti, R., Johnson, E. C., McClintick, J. N., Adams, M. J., & Adkins, A. E., … Team, 23andMe Research (2018). Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders. Nature Neuroscience, 21(12), 1656–1669. 10.1038/s41593-018-0275-1.CrossRefGoogle ScholarPubMed
Watanabe, K., Stringer, S., Frei, O., Umićević Mirkov, M., de Leeuw, C., Polderman, T. J. C., … Posthuma, D. (2019). A global overview of pleiotropy and genetic architecture in complex traits. Nature Genetics, 51(9), 1339–1348. doi: 10.1038/s41588-019-0481-0.CrossRefGoogle ScholarPubMed
Watanabe, K., Taskesen, E., van Bochoven, A., & Posthuma, D. (2017). Functional mapping and annotation of genetic associations with FUMA. Nature Communications, 8(1), 1826. doi: 10.1038/s41467-017-01261-5.CrossRefGoogle ScholarPubMed
Whiteford, H. A., Degenhardt, L., Rehm, J., Baxter, A. J., Ferrari, A. J., Erskine, H. E., … Vos, T. (2013). Global burden of disease attributable to mental and substance use disorders: Findings from the global burden of disease study 2010. The Lancet, 382(9904), 1575–1586. doi: 10.1016/S0140-6736(13)61611-6.CrossRefGoogle ScholarPubMed
Willer, C. J., Li, Y., & Abecasis, G. R. (2010). METAL: Fast and efficient meta-analysis of genomewide association scans. Bioinformatics (Oxford, England), 26(17), 2190–2191.Google ScholarPubMed
Zhou, H., Rentsch, C. T., Cheng, Z., Kember, R. L., Nunez, Y. Z., Sherva, R. M., … Program, V. A. M. V. (2020a). Association of OPRM1 functional coding variant with opioid use disorder: A genome-wide association study. JAMA Psychiatry, 77(10), 1072–1080. doi: 10.1001/jamapsychiatry.2020.1206.CrossRefGoogle ScholarPubMed
Zhou, H., Sealock, J. M., Sanchez-Roige, S., Clarke, T.-K., Levey, D. F., Cheng, Z., … Gelernter, J. (2020b). Genome-wide meta-analysis of problematic alcohol use in 435563 individuals yields insights into biology and relationships with other traits. Nature Neuroscience, 23(7), 809–818. doi: 10.1038/s41593-020-0643-5.CrossRefGoogle Scholar
Zhu, Z., Zhang, F., Hu, H., Bakshi, A., Robinson, M. R., Powell, J. E., … Yang, J. (2016). Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nature Genetics, 48(5), 481–487. doi: 10.1038/ng.3538.CrossRefGoogle ScholarPubMed
Zhu, Z., Zheng, Z., Zhang, F., Wu, Y., Trzaskowski, M., Maier, R., … Wray, N. R. (2018). Causal associations between risk factors and common diseases inferred from GWAS summary data. Nature Communications, 9(1), 224.CrossRefGoogle ScholarPubMed
Supplementary material: File

Johnson et al. supplementary material

Johnson et al. supplementary material 1

Download Johnson et al. supplementary material(File)
File 3.3 MB
Supplementary material: File

Johnson et al. supplementary material

Johnson et al. supplementary material 2

Download Johnson et al. supplementary material(File)
File 52.8 KB
Supplementary material: File

Johnson et al. supplementary material

Johnson et al. supplementary material 3

Download Johnson et al. supplementary material(File)
File 7.5 MB