Article

Common Genetic Variants Shared among Five Major Psychiatric Disorders: A Large-scale Genome-wide Cmbined Aalysis

Lu Xia1,2,  Kun Xia2,6, Daniel R Weinberger3, Fengyu Zhang1,4,5

1Global Clinical and Translational Research Institute, Bethesda, MD, USA;

2Center for Medical Genetics & Hunan Key Laboratory for Medical Genetics, College of Life Sciences, the Central South University, Changsha, Hunan, China;

3Lieber Institute for Brain Development, Department of Psychiatry and Behavioral Sciences, Neurology, Neuroscience, Institute of Genomic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA;

4The Second Xiangya Hospital & National Clinical Research Center for Mental Health Deriders, Central South University, Changsha, Hunan, China;

5Peking University Huilongguan Clinical Medical School & Beijing Huilongguan Hospital, Beijing, China;

6Chinese Academy of Sciences Center for Excellence in Brain Science and Intelligences Technology (CENSIT), Shanghai, China.

Received Feburary 7, 2019; Accepted Febueary 27, 2019

ABSTRACT

Background: Genetic correlation and pleiotropic effects among psychiatric disorders have been reported. This study aimed to identify specific common genetic variants shared between five adult psychiatric disorders: schizophrenia, bipolar, major depressive disorder, attention deficit-hyperactivity disorder, and autism spectrum disorder.

Methods: A combined p value of about 8 million single nucleotide polymorphisms (SNPs) were calculated in an equivalent sample of 151,672 cases and 284,444 controls of European ancestry from published data based on the latest genome-wide association studies of five major psychiatric disorder using Stouffer's Z-score method. SNPs that achieved genome-wide significance (P<5x10-08) were mapped to loci and genomic regions for further investigation; and gene functional annotation and clustering were performed to understand biological process and molecular function of the loci identified. We also examined CNVs and performed expression quantitative trait loci analysis for SNPs by genomic region.

Results: We find that 6,293 SNPs mapped to 336 loci are shared by the three adult psychiatric disorders, 1,108 variants at 73 loci are shared by the childhood disorders, and 713 variants at 47 genes are shared by all five disorders at genome-wide significance (p<5x10-08). Of the 2,583 SNPs at the extended major histocompatability complex identified for three adult disorders, none of them were associated with  two childhood disorders; and SNPs shared by all five disorders were located in the regions that have been identified as containing copy number variation associated with autism and had largely neurodevelopmental functions.

Conclusion: We show a number of specific SNPs associated with psychiatric disorders of childhood or adult onset, illustrating not only genetic heterogeneity across these disorders but also developmental genes shared by them all.  These results provide a manageable list of anchors from which to investigate epigenetic mechanism or gene-gene interaction on the development of neuropsychiatric disorders and for developing a measurement matrix for disease risk that could potentially be used for new taxonomy for precision medicine.

KEYWORDS

Psychiatric disorders; schizophrenia; bipolar disorder; major depressive disorder; attention deficit-hyperactivity disorder; autism spectrum disorder; genome-wide association study; combined analysis.

Copyright © 2019 by Global Clinical and Translational Research

How to cite this article:

Xia, L, Xia, K, Weinberger, DR, Zhang F. Common genetic variants shared among major psychiatric disorders: A genome-wide combined analysis. Glob Clin Transl Res. 2019; 1(1):21-30. DOI:10.36316/gcatr.01.0003.

References

1.        Hardy, J. and A. Singleton, Genomewide association studies and human disease. N Engl J Med, 2009. 360 (17): p. 1759-68.

2.        Scott, L.J., et al., A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science, 2007. 316(5829): p. 1341-5.

3.        Duerr, R.H., et al., A genome-wide association study identifies IL23R as an inflammatory bowel disease gene. Science, 2006. 314(5804): p. 1461-3.

4.        Schizophrenia Working Group of the Psychiatric Genomics, C., Biological insights from 108 schizophrenia-associated genetic loci. Nature, 2014. 511 (7510): p. 421-7.

5.        Manolio, T.A., In Retrospect: A decade of shared genomic associations. Nature, 2017. 546(7658): p. 360-361.

6.        Hyde, C.L., et al., Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nat Genet, 2016. 48(9): p. 1031-6.

7.        Wray, N.R., et al., Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet, 2018. 50(5): p. 668-681.

8.        Geschwind, D.H. and J. Flint, Genetics and genomics of psychiatric disease. Science, 2015. 349(6255): p. 1489-94.

9.        International Schizophrenia, C., et al., Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature, 2009. 460(7256): p. 748-52.

10.     Solovieff, N., et al., Pleiotropy in complex traits: challenges and strategies. Nat Rev Genet, 2013. 14(7): p. 483-95.

11.     Cross-Disorder Group of the Psychiatric Genomics, C., Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet, 2013. 381(9875): p. 1371-1379.

12.     Lee, S.H., et al., Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nat Genet, 2013. 45(9): p. 984-94.

13.     The US National Research Council Committee. A Framework for Developing a New Taxonomy of Disease, in Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease. 2011: Washington (DC).

14.     Collins, F.S. and H. Varmus, A new initiative on precision medicine. N Engl J Med, 2015. 372(9): p. 793-5.

15.     Bipolar, D., et al., Genomic dissection of bipolar disorder and schizophrenia, including 28 subphenotypes. Cell, 2018. 173 (7): p. 1705-1715 e16.

16.     Demontis, D., et al., Discovery of the first genome-wide significant risk loci for ADHD. bioRxiv 2017 (doi: 10.1101 /145581).

17.     Grove, J., et al., Common risk variants identified in autism spectrum disorder. bioRxiv, 2017. doi:10. 1101 /224774.

18.     Sullivan, P.F., et al., Genomewide association for schizophrenia in the CATIE study: results of stage 1. Mol Psychiatry, 2008. 13(6): p. 570-84.

19.     Xu, Z. and J.A. Taylor, SNPinfo: integrating GWAS and candidate gene information into functional SNP selection for genetic association studies. Nucleic Acids Res, 2009. 37(Web Server issue): p. W600-5.

20.     Huang da, W., B.T. Sherman, and R.A. Lempicki, Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc, 2009. 4(1): p. 44-57.

21.     de Bakker, P.I., et al., A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHC. Nat Genet, 2006. 38(10): p. 1166-72.

22.     Horton, R., et al., Gene map of the extended human MHC. Nat Rev Genet, 2004. 5(12): p. 889-99.

23.     Gandal, M.J., et al., Shared molecular neuropathology across major psychiatric disorders parallels polygennic overlap. Science, 2018. 359(6376): p. 693-697.

24.     Pidsley, R., et al., Methylomic profiling of human brain tissue supports a neurodevelopmental origin for schizophrenia. Genome Biol, 2014. 15(10): p. 483.

25.     Sanders, S.J., et al., Insights into autism spectrum disorder genomic architecture and biology from 71 risk loci. Neuron, 2015. 87(6): p. 1215-1233.

26.     State, M.W. and N. Sestan, Neuroscience. The emerging biology of autism spectrum disorders. Science, 2012. 337 (6100): p. 1301-3.

27.     Walsh, T., et al., Rare structural variants disrupt multiple genes in neurodevelopmental pathways in schizophrenia. Science, 2008. 320(5875): p. 539-43.

28.     Voineagu, I., et al., Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature, 2011. 474 (7351): p. 380-4.

29.     Fernandez, T., et al., Disruption of contactin 4 (CNTN4) results in developmental delay and other features of 3p deletion syndrome. Am J Hum Genet, 2004. 74(6): p. 1286-93.

30.     Hayashi, S., et al., Clinical application of array-based comparative genomic hybridization by two-stage screening for 536 patients with mental retardation and multiple congenital anomalies. J Hum Genet, 2011. 56 (2): p. 110-24.

31.     Schreurs, A., A. LatifHernandez, and A. Uwineza, Commentary: APP as a Mediator of the Synapse Pathology in Alzheimer's Disease. Front Cell Neurosci, 2018. 12: p. 150.

32.     Liang, X., et al., Genomic convergence to identify candidate genes for Alzheimer disease on chromosome 10. Hum Mutat, 2009. 30(3): p. 463-71.

33.     Martin, E.R., et al., Association of single-nucleotide polymorphisms of the tau gene with late-onset Parkinson disease. JAMA, 2001. 286(18): p. 2245-50.

34.     Desikan, R.S., et al., Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus. Mol Psychiatry, 2015. 20(12): p. 1588-95.