The G2MH consortium is structured around four projects that will study the behavioral and cognitive symptoms in individuals with rare genetic variants that confer high risk for neurodevelopmental psychiatric disorders. Participants will be identified in hospital clinics as well as in the general population across three continents.

Project 1

Large-Scale Evaluation of the Effect of Rare Genetic Variants on Psychiatric Symptoms and Cognitive Ability

David Glahn, PhD, Boston Children’s Hospital and Harvard Medical School

Dr. Laura Almasy, Children’s Hospital of Philadelphia and Perelman School of Medicine, University of Pennsylvania

Dr. Sébastien Jacquemont, Centre Hospitalier Universitaire Sainte-Justine and University of Montreal

Rare copy number variants (CNVs) are strongly associated with neuropsychiatric disorders, suggesting that they might serve as a magnifying glass to study general mechanisms of psychopathology as otherwise subtle perturbations to neuropsychiatric functions may be more clearly discerned through the major ‘hit’ of the CNV. However, our understanding of the impact of CNVs on psychiatric symptomatology, RDoC domains and neurocognitive ability (termed ‘dimensional neuropsychiatric phenotypes’) is limited in at least three ways. First, the effects sizes of the vast majority of CNVs on neuropsychiatric phenotypes remain poorly understood and their rarity will likely to prevent individual association studies. Prior studies concentrated on the most recurrent CNVs, leaving more than 90% of these variants undocumented. Second, for CNVs frequent enough to be studied individually, the full spectrum of phenotypic variation is unknown because ascertainment has been performed through neurodevelopmental and specialty clinics, which presumably represent the severe end of the phenotypic spectrum. Only a few studies have been conducted in unselected populations. Finally, many CNVs seem to impact the same neuropsychiatric domains, suggesting a poly/omnigenic model for psychiatric symptomatology, RDoC domains and neurocognitive ability. Based on this hypothesis, our previous work has shown that genetic scores and functional annotations can accurately predict the effect of any CNV on IQ but these approaches have not yet been extended beyond IQ to other dimensional neuropsychiatric phenotypes. We will fill these knowledge gaps with a novel, multidisciplinary, collaborative project that leverages existing archival data (n=255,303) to estimate and predict the effect sizes of CNVs (duplications and deletions) on dimensional neuropsychiatric phenotypes. Our aims include 1) phenotypic harmonization; 2) characterizing previously identified risk CNVs for mental illness in a large in general population cohorts and in samples ascertained for mental illnesses; 3) examine the contribution of common variants to variable expressivity of rare CNVs via polygenic risk scores (PRS) in the domains of mood, psychosis, developmental disability, and general cognitive ability; and 4) develop novel models to explain the effect size of any rare CNVs on dimensional neuropsychiatric phenotypes. Finally, we will develop tools for data sharing.

Project 2

Dissecting the effects of genomic variants on neurobehavioral dimensions in CNVs enriched for neuropsychiatric disorders

Participating sites, PIs & NIMH grant numbers:

University of California, Los Angeles, USA; Carrie E Bearden, [U01 MH119736-01]

University of Pennsylvania, Philadelphia, USA; Raquel E. Gur [U01 MH119738-01]

University of Montreal, Canada; Sebastien Jacquemont [U01 MH119739-01]

Children’s Hospital of Philadelphia, USA; Donna M. McDonald-McGinn, [U01 MH119737-01]

University of California, San Diego, USA; Jonathan Sebat, [U01 MH119746-01]

Katholieke Universiteit Leuven, Belgium; Ann Swillen, [U01 MH119759-01]

Maastricht University, the Netherlands; Therese AMJ van Amelsvoort [U01 MH119740-01]

Cardiff University, Wales, United Kingdom; Marianne van den Bree [U01 MH119758-01]

University of Toronto, Canada; Jacob AS Vorstman [U01 MH119741-01]

In this collaborative project nine institutions across the United States, Canada and Europe work together to elucidate the mechanisms that influence the expression of the frequent neuropsychiatric manifestations in individuals with copy number variants (CNVs) at 22q11.2 and 16p11.2.

The objectives are to collect dimensional measures of neuropsychiatric symptoms and examine convergence and specificity of these phenotypes across the four CNV subpopulations. In addition, we aim to increase our understanding of the observed variable expression of neuropsychiatric phenotypes in carriers of the same pathogenic CNV, with a specific focus on the influence of additional genetic factors (rare and common) as well as environmental factors. In collaboration with the NIMH, data and analytic algorithms will be made available in the public research domain.

Methods: a cohort of 2,000 individuals with CNVs (deletions or duplications) at either 22q11.2 or 16p11.2 (500 per group), and their relatives whenever possible, are recruited in the different participating sites of this project. Prospective phenotype data will be collected in this cohort, including dimensional measures of psychopathology and cognition. In all individuals whole genome sequencing (WGS) will be performed (except for some individuals with WGS data available from previous studies). The influence of common risk variants on the neuropsychiatric expression will be examined using polygenic risk scores derived from available large sized genome-wide association studies. In addition, information on family and environmental factors will be collected to study their influence on neuropsychiatric expression in this population.


While deletions and duplications at 16p11.2 and 22q11.2 exert a large main effect on the variable psychopathologic manifestations in individual carriers, the nature and degree of phenotypic expression is likely multifactorial, with contributions from additional rare and common genetic variants, as well as environmental factors. Therefore, dissecting the effects of major CNV hits as well as additional rare and common variants on dimensional measures of psychopathology, as proposed in this project, can elucidate the combined contribution of genetic mechanisms to psychiatric conditions and build models of risk prediction. Notably, the presentation and course of psychopathology in the CNVs resemble these features in idiopathic disorders. Therefore, beyond the specific genetic syndromes investigated, such across-CNV effort will identify convergent risk mechanisms for developmental neuropsychiatric disorders that are of relevance to the broader population.

Project 3

Leveraging rare genetic etiologies to advance knowledge and treatment of neuropsychiatric disorders

Neuropsychiatric disorders (NPD), such as schizophrenia, bipolar disorder, and autism are behaviorally-defined and etiologically-heterogeneous conditions with a wide range of severity and outcomes. For cancer and other common diseases, the study of rare genetic disorders has illuminated key pathophysiological mechanisms, resulting in significant treatment advances. We hypothesize that this strategy can be successfully applied to NPD. New genomic technologies have led to the discovery of hundreds of rare genetic NPD due to copy number (CNVs) and single gene nucleotide variants (SNVs) of large effect size. However, detailed neuropsychiatric profiles have not been established for most of these conditions, due in part to difficulty recruiting adequate cohort sizes to power statistical analyses. We will capitalize on large NPD clinical populations at Geisinger, the University of Washington, and Washington University in St. Louis to recruit individuals with rare genetic disorders for this study. We will also examine the influence of additional contributors throughout the genome to the variable expressivity of neuropsychiatric symptoms in these disorders.

This study will systematically examine these aspects of rare genetic NPD through the following aims:

1) Employ a highly cost-effective, genetics-first strategy to achieve baseline characterization of a large cohort with genetic NPD etiologies. Every year, as part of psychiatric, developmental, and behavioral healthcare, valuable genotype and phenotype data are generated from individuals with rare genetic NPD. We will harmonize core assessment batteries used in clinical care to leverage this high-quality data for broad data sharing and analyses on >1,000 probands, accelerating discovery and greatly reducing the research cost of multidimensional phenotyping.

2) Describe detailed phenotypic signatures in selected rare genetic NPD, including the impact of family background on variable expressivity. We will characterize quantitative neuropsychiatric traits for selected rare genetic NPD (initially 1q21.1 and 15q13.3 CNVs and CHD8 SNVs). All three disorders have shown genome-wide significance for increased risk of neuropsychiatric phenotypes, including psychosis, mood disorders, and autism. We will assess behavioral, psychiatric, and cognitive traits in 250 probands with these rare genetic NPD and their first-degree family members to explore the impact of family background on variable expressivity of neuropsychiatric symptoms.

3) Assess the contributions of common and secondary rare genomic variants to variable expressivity in rare genetic NPD. Through two sub-aims, we will explore the impact of common (polygenic risk scores) and rare (‘second hits’) genomic contributors on risk or resilience for neuropsychiatric symptoms. Analyzing data collected through Aims 1 and 2, in addition to a broader exploration of genomic and electronic health record data from 250,000 individuals in Geisinger’s MyCode cohort, we will demonstrate how different genomic background contributors lead to clinical heterogeneity in individuals with rare genetic NPD. These studies may eventually inform individual-level prognoses for neuropsychiatric outcomes.

Project 4

Rare genetic disorders in NeuroDev: Insight into the genetic and phenotypic heterogeneity of ID, ASD and ADHD in South African Populations

Rare genetic disorders (RGDs) have provided a significant window into the genetic architecture of cognitive and behavioral variation. They have also posed questions about the relationship between idiopathic and syndromic forms of cognitive and behavioral disorders, and the role of genetic background in RGD expression. Further, most genetic studies to date have focused on populations of European ancestry, meaning little is known about RGD expression and variability in other populations. To address these gaps, we will leverage the ongoing NeuroDev South Africa collection to genetically and phenotypically characterize 1,000 children aged 2-17, ascertained for Autism Spectrum Disorders, Intellectual Disability/Global Developmental Delay, and Attention Deficit Hyperactive Disorder in Cape Town. The collection also includes 1,000 case parents and 1,000 unrelated, ancestry-matched controls. We will genetically characterize all 3,000 NeuroDev participants in order to identify and investigate an estimated 300 RGD cases in the NeuroDev sample. We propose to use medical record data to further characterize all NeuroDev cases which, in conjunction with the detailed phenotype data collected as part of the core collection activity, will create uncommon opportunities for the phenotypic comparison of RGD-based and idiopathic neuropsychiatric disorders (e.g. dimensional cognitive and behavioral data, brain imaging, audiology data). With the aggregated data, we will compare the phenotypic features of RGD-based and idiopathic neuropsychiatric disorders and highlight points of divergence, which will be useful for addressing heterogeneity in future research, as well as in eventual treatment trials. Lastly, we consider the role of genetic background in the variable expressivity of neuropsychiatrically-involved RGDs, in terms of both genome-wide genetic risk for behavioral disorders and ancestral variation. These analyses will address several critical questions about the biology and presentation of RGDs, as well as their relationship to cognitive and behavioral disorders. The wide sharing of these data will permit further investigation at the fieldwide level.

Elephant photo by Wolfgang Hasselmann via Unsplash