Genetic Architecture for Human Aggression: a Study of Gene–Phenotype Relationship in OMIM Yanli Zhang-James1 and Stephen V

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Genetic Architecture for Human Aggression: a Study of Gene–Phenotype Relationship in OMIM Yanli Zhang-James1 and Stephen V RESEARCH ARTICLE Neuropsychiatric Genetics Genetic Architecture for Human Aggression: A Study of Gene–Phenotype Relationship in OMIM Yanli Zhang-James1 and Stephen V. Faraone1,2,3* 1Department of Psychiatry, SUNY Upstate Medical University, Syracuse, New York 2Department of Neuroscience and Physiology, SUNY Upstate Medical University, Syracuse, New York 3K.G. Jebsen Centre for Research on Neuropsychiatric Disorders, University of Bergen, Bergen, Norway Manuscript Received: 22 June 2015; Manuscript Accepted: 5 August 2015 Genetic studies of human aggression have mainly focused on known candidate genes and pathways regulating serotonin and How to Cite this Article: dopamine signaling and hormonal functions. These studies have Zhang-James Y, Faraone SV. 2016. Genetic taught us much about the genetics of human aggression, but no Architecture for Human Aggression: A genetic locus has yet achieved genome-significance. We here Study of Gene–Phenotype Relationship in present a review based on a paradoxical hypothesis that studies OMIM. of rare, functional genetic variations can lead to a better under- Am J Med Genet Part B 171B:641–649. standing of the molecular mechanisms underlying complex multifactorial disorders such as aggression. We examined all aggression phenotypes catalogued in Online Mendelian Inheri- tance in Man (OMIM), an Online Catalog of Human Genes and 2014]. Thus, identifying causal genes and pathways underlying Genetic Disorders. We identified 95 human disorders that have aggressive behavior in humans requires additional work. documented aggressive symptoms in at least one individual with The lack of significant associations for common variants is likely a well-defined genetic variant. Altogether, we retrieved 86 causal due to many reasons such as sample heterogeneity, variants of small genes. Although most of these genes had not been implicated in effect sizes and gene-environment interaction effects. As has been human aggression by previous studies, the most significantly seen for other behavioral traits [Lee et al., 2013], very large samples enriched canonical pathways had been previously implicated in may be needed to pin down common variant associations. We aggression (e.g., serotonin and dopamine signaling). Our find- propose a novel approach based on the paradoxical hypothesis that ings provide strong evidence to support the causal role of these studies of rare, functional genetic variations can lead to a better pathways in the pathogenesis of aggression. In addition, the understanding of the molecular mechanisms underlying complex novel genes and pathways we identified suggest additional multifactorial disorders such as aggression. Empirical evidence mechanisms underlying the origins of human aggression. Ge- support the idea that a biological pathway implicated by a rare nome-wide association studies with very large samples will be variant could also be degraded by common variants or even by needed to determine if common variants in these genes are risk environmental risk factors. This has been observed for many factors for aggression. Ó 2015 Wiley Periodicals, Inc. genetically influenced multifactorial disorders. For example for Type 2 diabetes, many common and rare associated polymor- Key words: aggression; genetics; OMIM phisms and causal monogenic variants are clustered in or near the insulin signaling network [Sharma et al., 2005]. Studies of autism Grant sponsor: K.G. Jebsen Centre for Research on Neuropsychiatric Disorders, University of Bergen, Bergen, Norway; Grant sponsor: INTRODUCTION European Community’s Seventh Framework Programme (FP7/2007- Genetic variants account for about 50% of the variance in human 2013); Grant number: 602805; Grant sponsor: NIMH; Grant number: R01MH094469. aggression [Miles and Carey, 1997]. Genetic studies of human à aggression have mainly focused on known candidate genes and Corrrespondence to: Dr. Stephen V. Faraone, Department of Neuroscience and Physiology, pathways regulating serotonin and dopamine signaling and hor- SUNY Upstate Medical University, 750 E. Adams St., Syracuse, NY monal functions [Saudou et al., 1994]. However, a recent meta- 33136. analysis of common DNA variants in 31 candidate genes (including E-mail: [email protected] serotonin and catecholamine genes) selected from 185 studies Article first published online in Wiley Online Library constituting 277 independent associations, showed no significant (wileyonlinelibrary.com): 19 August 2015 associations with aggression or antisocial behavior [Vassos et al., DOI 10.1002/ajmg.b.32363 Ó 2015 Wiley Periodicals, Inc. 641 642 AMERICAN JOURNAL OF MEDICAL GENETICS PART B spectrum disorders (ASDs) have found substantial overlap in the edge, and indirect networks refer to interactions mediated via biological pathways implicated by rare Single Nucleotide Variants common interactor proteins (non-OMIM aggression genes) with (SNVs), rare copy number variants (CNVs) and common DNA which the associated proteins each share an edge. DAPPL uses the variants [Ben-David and Shifman, 2012]. Furthermore, genes high confidence physical interactions derived from InWeb database implicated by these variants were clustered in the same pathways [Lage et al., 2007] to define edges and using a within-degree node- as genes implicated by syndromic ASDs [Sakai et al., 2011]. Studies label permutation to evaluate whether the input seed protein, that is, of the ASD transcriptome have drawn the same conclusion [Lanz OMIM genes, were significantly connected by protein–protein et al., 2013]. Thus, although any single rare variant may be observed interactions. This method takes into the consideration of both in only one or two patients, different rare variants carried by the protein interaction density and publication bias. different patients implicate similar biological networks. We further extended the connectivity assessment to include all The discovery of biological pathways via rare variants has been type of biological interactions, such as activation/inhibition, phos- used to leverage drug development efforts that are relevant to more phorylation and gene expression regulation. Expert-curated bio- 1 than just the few patients carrying a given rare variant. For example, logical interactions from Ingenuity Knowledge Base via Ingenuity 1 rare variants of PCSK9 cause a rare autosomal dominant familial Pathway Analysis software (IPA , QIAGEN, Redwood City, CA hypercholesterolemia. Drugs that inhibit PCSK9 protein lower [An et al., 2012]) were used to retrieved direct interactions of all cholesterol and are a viable treatment for common forms of available types among the seed proteins using the least stringent hypercholesterolemia and atherosclerosis [Hooper and Burnett, confidence levels in IPA. These interactions were used to construct 2013; Urban et al., 2013]. Canakinumab is a human monoclonal the direct networks to visualize the connections among the input antibody that was developed and approved to treat cryopyrin- seed proteins. associated periodic syndrome, a rare autoinflammatory syndrome NLRP3 caused by mutations in , the gene encoding cryopyrin Functional Assessment [Verma et al., 2010]. Subsequently, canakinumab was approved for use in gout [Onuora, 2012; Schlesinger, 2012], a common Two types of functional assessment were performed to understand inflammatory syndrome having a different etiology; it is also the underlying biological functions represented by the OMIM effective in treating common rheumatoid arthritis [Alten et al., genes and their comparison with the Aggressotype candidate genes. 2011]. First method involves constructing empirical functional networks In the present study, we used the Online Mendelian Inheritance that these genes participate in. The second approach is to evaluate in Man (OMIM) data base [McKusick, 1998], to identify all genes the gene list enrichments in the predefined IPA canonical pathways. with known rare variants that cause aggressive phenotypes in We used IPA network generation algorithm (described in detail human Mendelian disorders. We examined the pathways and in IPA’s whitepaper, http://www.ingenuity.com/wp-content/ networks underlying these genes collectively and compared themes/ingenuity-qiagen/pdf/ipa/IPA-netgen-algorithm- them with a panel of known candidate genes (N ¼ 97) for aggres- whitepaper.pdf) to construct non-redundant densely connected sion assembled by experts from the Aggressotype Consortium empirical networks with default size of 35 molecules or less. Similar (http://www.Aggressotype.eu/). These pathways may reveal com- to the DAPPLE indirect network, additional non-seed interactors mon mechanisms underlying the aggressive behavior in humans. were allowed to be added in order to connect the seed proteins. Based on observations that highly-interconnected networks are likely to represent significant biological function [Ravasz et al., METHODS 2002; Ma et al., 2004], we examined the top three most significantly OMIM Record Search and Filtering enriched disease and biological functions, predefined pathways, that each networks represent in order to obtain an overview of We used search key worlds: “aggression OR aggressive behavior OR general biology associated with each network. IPA also calculates aggressiveness OR antisocial OR conduct disorder” in fields in- the probability of finding f numbers of seed genes (f ¼ the number cluding “title”, “text”, “allelic variants” and “clinical synopsis” of seed genes present in the network) in a set of n genes (n ¼ total (http://omim.org/search/advanced/entry).
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