Advisors: Paul M Thompson
Advisors: Pierre Bellec
Mapping genome-wide neuropsychiatric mutation effects on functional brain connectivity: Copy number variants delineate dimensions contributing to autism and schizophrenia.
Co-supervised by: Sébastien Jacquemont (Geneticist, Sainte Justine Hospital) and Pierre L. Bellec (Computer Science Department, SIMEXP lab, CR-IUGM, University of Montreal)
Skills: MRI Protocol development and Scanning, Analyses (R, Matlab), Website development for family recruitment, neuropsychological assessment. S. Jacquemont’s laboratory
Ecole Normale Supérieure and Descartes University, Paris
Advisors: Marion Noulhiane and Lucie Hertz-Pannier UNIACT
Skills: fMRI analysis (SPM, Matlab), Neurodevelopmental cohort, memory tasks.
Advisor: Pr. P. Jolicoeur, Neuroscience department
Skills: MEG/EEG analyses for an auditory task.
Advisors: Pr. M. Noulhiane and Dr C. Chiron, Necker Children Hospital
Descartes University, Paris-V
Advisor: Pr. N. Ravel and Pr. Rémi Gervais
Skills: Recording olfactory cells in mice (electrophysiology) and signal processing
Victor Duruy High School, Paris 75007 France
Symposium Clinical applications
“Genetic heterogeneity and pleiotropy shape brain connectivity in psychiatric conditions”
Seminaire “Genetic heterogeneity in neurodevelopmental conditions shapes brain connectivity”
Lecture “Atlas of functional connectivity relationships across rare and common genetic variants, traits, and psychiatric conditions”
Symposium “Large Scale Imaging Studies of Rare Copy Number variants: Brain Imaging from Enigma and Other Large-Scale International Studies”
Symposium “Human and Animal Models: Impact of High-Risk Copy Number Variants on Brain Structure, Functional Connectivity, and Sexual Development.”
Campagne de l'institut Pasteur
Autism’s genetic heterogeneity evident in brain connectivity patterns
Q&A with Sébastien Jacquemont and Clara Moreau: Why brain imaging signatures for autism are so elusive
Gene mutations point to overlaps in brain connectivity for autism, schizophrenia
Gènes, connectivité cérébrale, et maladies neuropsychiatriques
Genomic information (C. Pernet).
Co-organizer with Pierre Bellec, Lausanne, Switzerland
Brain and Development research section at the Ste Justine Hospital, Montreal
For PhD students, n=6 editions
Lausanne (EPFL), and Paris (ENS, CogInnov, and ESPCI).
National political committee
French organization of researchers
Citizen lab in Paris
Symposium Conciliate Research, Innovation and Open Science
Consciousness process of intelligence across the animal, the human, and the computer
To promote Open Access of scientific publications
Open Knowledge Conference, Geneva, Switzerland
French Federation of Cognitive Science students)
Martin-Brevet, S., Rodríguez-Herreros, B., Nielsen, J. A., Moreau, C., Modenato, C., Maillard, A. M., Pain, A., Richetin, S., Jønch, A. E., Qureshi, A. Y., Zürcher, N. R., Conus, P., 16p11.2 European Consortium, Simons Variation in Individuals Project (VIP) Consortium, Chung, W. K., Sherr, E. H., Spiro, J. E., Kherif, F., Beckmann, J. S., … Jacquemont, S.
16p11.2 breakpoint 4 to 5 copy number variants (CNVs) increase the risk for developing autism spectrum disorder, schizophrenia, and language and cognitive impairment. In this multisite study, we aimed to quantify the effect of 16p11.2 CNVs on brain structure.
Using voxel- and surface-based brain morphometric methods, we analyzed structural magnetic resonance imaging collected at seven sites from 78 individuals with a deletion, 71 individuals with a duplication, and 212 individuals without a CNV.
Beyond the 16p11.2-related mirror effect on global brain morphometry, we observe regional mirror differences in the insula (deletion > control > duplication). Other regions are preferentially affected by either the deletion or the duplication: the calcarine cortex and transverse temporal gyrus (deletion > control; Cohen’s d > 1), the superior and middle temporal gyri (deletion > control; Cohen’s d inf −1), and the caudate and hippocampus (control > duplication; −0.5 > Cohen’s d > −1). Measures of cognition, language, and social responsiveness and the presence of psychiatric diagnoses do not influence these results. The global and regional effects on brain morphometry due to 16p11.2 CNVs generalize across site, computational method, age, and sex. Effect sizes on neuroimaging and cognitive traits are comparable. Findings partially overlap with results of meta-analyses performed across psychiatric disorders. However, the lack of correlation between morphometric and clinical measures suggests that CNV-associated brain changes contribute to clinical manifestations but require additional factors for the development of the disorder.
These findings highlight the power of genetic risk factors as a complement to studying groups defined by behavioral criteria.
Sønderby, I. E., Gústafsson, Ó., Doan, N. T., Hibar, D. P., Martin-Brevet, S., Abdellaoui, A., Ames, D., Amunts, K., Andersson, M., Armstrong, N. J., Bernard, M., Blackburn, N., Blangero, J., Boomsma, D. I., Bralten, J., Brattbak, H.-R., Brodaty, H., Brouwer, R. M., Bülow, R., … Moreau, C., … 16p11.2 European Consortium, for the ENIGMA-CNV working group.
Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia.
We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV.
After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = -0.71 to -1.37; P inf 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = -0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10-6, 1.7 × 10-9, 3.5 × 10-12 and 1.0 × 10-4, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers.
This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes.
van der Meer, D., Sønderby, I. E., Kaufmann, T., Walters, G. B., Abdellaoui, A., Ames, D., Amunts, K., Andersson, M., Armstrong, N. J., Bernard, M., Blackburn, N. B., Blangero, J., Boomsma, D. I., Brodaty, H., Brouwer, R. M., Bülow, R., Cahn, W., Calhoun, V. D., Caspers, S., ..., Moreau C., … Andreassen, O. A.
Recurrent microdeletions and duplications in the genomic region 15q11.2 between breakpoints 1 (BP1) and 2 (BP2) are associated with neurodevelopmental disorders. These structural variants are present in 0.5% to 1.0% of the population, making 15q11.2 BP1-BP2 the site of the most prevalent known pathogenic copy number variation (CNV). It is unknown to what extent this CNV influences brain structure and affects cognitive abilities. To determine the association of the 15q11.2 BP1-BP2 deletion and duplication CNVs with cortical and subcortical brain morphology and cognitive task performance.
In this genetic association study, T1-weighted brain magnetic resonance imaging were combined with genetic data from the ENIGMA-CNV consortium and the UK Biobank, with a replication cohort from Iceland. In total, 203 deletion carriers, 45 247 noncarriers, and 306 duplication carriers were included. Data were collected from August 2015 to April 2019, and data were analyzed from September 2018 to September 2019.
The associations of the CNV with global and regional measures of surface area and cortical thickness as well as subcortical volumes were investigated, correcting for age, age2, sex, scanner, and intracranial volume. Additionally, measures of cognitive ability were analyzed in the full UK Biobank cohort. Of 45 756 included individuals, the mean (SD) age was 55.8 (18.3) years, and 23 754 (51.9%) were female. Compared with noncarriers, deletion carriers had a lower surface area (Cohen d = -0.41; SE, 0.08; P = 4.9 × 10-8), thicker cortex (Cohen d = 0.36; SE, 0.07; P = 1.3 × 10-7), and a smaller nucleus accumbens (Cohen d = -0.27; SE, 0.07; P = 7.3 × 10-5). There was also a significant negative dose response on cortical thickness (β = -0.24; SE, 0.05; P = 6.8 × 10-7). Regional cortical analyses showed a localization of the effects to the frontal, cingulate, and parietal lobes. Further, cognitive ability was lower for deletion carriers compared with noncarriers on 5 of 7 tasks.
These findings, from the largest CNV neuroimaging study to date, provide evidence that 15q11.2 BP1-BP2 structural variation is associated with brain morphology and cognition, with deletion carriers being particularly affected. The pattern of results fits with known molecular functions of genes in the 15q11.2 BP1-BP2 region and suggests involvement of these genes in neuronal plasticity. These neurobiological effects likely contribute to the association of this CNV with neurodevelopmental disorders.
Cárdenas-de-la-Parra, A., Martin-Brevet, S., Moreau, C., Rodriguez-Herreros, B., Fonov, V. S., Maillard, A. M., Zürcher, N. R., 16p11.2 European Consortium, Hadjikhani, N., Beckmann, J. S., Reymond, A., Draganski, B., Jacquemont, S., and Collins, D. L.
Most of human genome is present in two copies (maternal and paternal). However, segments of the genome can be deleted or duplicated, and many of these genomic variations (known as Copy Number Variants) are associated with psychiatric disorders. 16p11.2 copy number variants (breakpoint 4-5) confer high risk for neurodevelopmental disorders and are associated with structural brain alterations of large effect-size. Methods used in previous studies were unable to investigate the onset of these alterations and whether they evolve with age.
In this study, we aim at characterizing age-related effects of 16p11.2 copy number variants by analyzing a group with a broad age range including younger individuals. A large normative developmental dataset was used to accurately adjust for effects of age. We normalized volumes of segmented brain regions as well as volumes of each voxel defined by tensor-based morphometry.
Results show that the total intracranial volumes, the global gray and white matter volumes are respectively higher and lower in deletion and duplication carriers compared to control subjects at 4.5 years of age. These differences remain stable through childhood, adolescence and adulthood until 23 years of age (range: 0.5 to 1.0 Z-score). Voxel-based results are consistent with previous findings in 16p11.2 copy number variant carriers, including increased volume in the calcarine cortex and insula in deletions, compared to controls, with an inverse effect in duplication carriers (1.0 Z-score). All large effect-size voxel-based differences are present at 4.5 years and seem to remain stable until the age of 23.
Our results highlight the stability of a neuroimaging endophenotype over 2 decades during which neurodevelopmental symptoms evolve at a rapid pace.
Jønch, A. E., Douard, E., Moreau, C., Van Dijck, A., Passeggeri, M., Kooy, F., Puechberty, J., Campbell, C., Sanlaville, D., Lefroy, H., Richetin, S., Pain, A., Geneviève, D., Kini, U., Le Caignec, C., Lespinasse, J., Skytte, A.-B., Isidor, B., Zweier, C., ..., Ousager LB., Jacquemont, S., on behalf of 15q11.2 Working Group
The 15q11.2 deletion is frequently identified in the neurodevelopmental clinic. Case–control studies have associated the 15q11.2 deletion with neurodevelopmental disorders, and clinical case series have attempted to delineate a microdeletion syndrome with considerable phenotypic variability. The literature on this deletion is extensive and confusing, which is a challenge for genetic counselling. The aim of this study was to estimate the effect size of the 15q11.2 deletion and quantify its contribution to neurodevelopmental disorders.
We performed meta-analyses on new and previously published case–control studies and used statistical models trained in unselected populations with cognitive assessments. We used new (n=241) and previously published (n=150) data from a clinically referred group of deletion carriers.
15q11.2 duplications (new n=179 and previously published n=35) were used as a neutral control variant. The deletion decreases IQ by 4.3 points. The estimated ORs and respective frequencies in deletion carriers for intellectual disabilities, schizophrenia and epilepsy are 1.7 (3.4%), 1.5 (2%) and 3.1 (2.1%), respectively. There is no increased risk for heart malformations and autism. In the clinically referred group, the frequency and nature of symptoms in deletions are not different from those observed in carriers of the 15q11.2 duplication suggesting that most of the reported symptoms are due to ascertainment bias.
We recommend that the deletion should be classified as ‘pathogenic of mild effect size’. Since it explains only a small proportion of the phenotypic variance in carriers, it is not worth discussing in the developmental clinic or in a prenatal setting.
Urchs, S., Armoza, J., Moreau, C., Benhajali, Y., St-Aubin, J., Orban, P., Bellec, P.
The functional architecture of the brain is organized across multiple levelsof spatial resolutions, from distributed networks to the localized areas theyare made of. A brain parcellation that defines functional nodes at multipleresolutions is required to investigate the functional connectome acrossthese scales.
Here we present the Multiresolution Intrinsic SegmentationTemplate (MIST), a multi-resolution group level parcellation of the cortical,subcortical and cerebellar gray matter. The individual MIST parcellationsmatch other published group parcellations in internal homogeneity andreproducibility and perform very well in real-world application benchmarks.In addition, the MIST parcellations are fully annotated and provide ahierarchical decomposition of functional brain networks across nineresolutions (7 to 444 functional parcels). We hope that the MISTparcellation will accelerate research in brain connectivity acrossresolutions. Because visualizing multiresolution parcellations is challenging,we provide to explore the MIST. The MIST isan interactive web interfacealso available through the popular toolbox.
Douard, E., Zeribi, A., Schramm, C., Tamer, P., Loum, M. A., Nowak, S., Saci, Z., Lord, M.-P., Rodriguez-Herreros, B., Jean-Louis, M., Moreau, C., Loth, E., Schumann, G., Pausova, Z., Elsabbagh, M., Almasy, L., Glahn, D. C., Bourgeron, T., Labbe, A., … Jacquemont, S.
Objective Deleterious copy number variants (CNVs) are identified in up to 20% of individuals with autism. However, only 13 genomic loci have been formally associated with autism because the majority of CNVs are too rare to perform individual association studies. To investigate the implication of undocumented CNVs in neurodevelopmental disorders, we recently developed a new framework to estimate their effect-size on intelligence quotient (IQ) and sought to extend this approach to autism susceptibility and multiple cognitive domains.
Methods We identified CNVs in two autism samples (Simons Simplex Collection and MSSNG) and two unselected populations (IMAGEN and Saguenay Youth Study). Statistical models integrating scores of genes encompassed in CNVs were used to explain their effect on autism susceptibility and multiple cognitive domains.
Results Among 9 scores of genes, the “probability-of-being loss-of-function intolerant” (pLI) best explains the effect of CNVs on IQ and autism risk. Deletions decrease IQ by a mean of 2.6 points per point of pLI. The effect of duplications on IQ is three-fold smaller. The odd ratios for autism increases when deleting or duplicating any point of pLI. This increased autism risk is similar in subgroups of individuals below or above median IQ. Once CNV effects on IQ are accounted for, autism susceptibility remains mostly unchanged for duplications but decreases for deletions. Model estimates for autism risk overlap with previously published observations. Deletions and duplications differentially affect social communication, behaviour, and phonological memory, whereas both equally affect motor skills.
Conclusions Autism risk conferred by duplications is less influenced by IQ compared to deletions. CNVs increase autism risk similarly in individuals with high and low IQ. Our model, trained on CNVs encompassing >4,500 genes, suggests highly polygenic properties of gene dosage with respect to autism risk. These models will help interpreting CNVs identified in the clinic.
Moreau, C., Martineau J.L., Blair, R., Markiewicz C, Turner J., Calhoun V., Nichols T, Pernet C.
Metadata are key in our ability to search databases. Without them, researchers would spend hours examining datasets in the hope to find data with features they are interested in. Brain imaging genetics is at the intersection of two disciplines each one with dedicated dictionaries and ontologies facilitating data search and analysis.
Here we present the genetics brain imaging data structure extension: it consists of metadata files for human brain imaging data to which they are linked to and describe succinctly the genomic and transcriptomic data associated to them, possibly in different databases. This extension will facilitate identifying micro-scale molecular features that are linked to macro-scale imaging repositories facilitating data aggregation across studies.
Moreau, C., Urchs, S., Orban, P., Schramm, C., Dumas, G., Labbe, A., Huguet, G., Douard, E., Quirion, P.-O., Lin, A., Kushan, L., Grot, S., Luck, D., Mendrek, A., Potvin, S., Stip, E., Bourgeron, T., Evans, A. C., SimonsVIP Consortium, Bearden, CE., Bellec, P., Jacquemont, S.
16p11.2 and 22q11.2 Copy Number Variants (CNVs) confer high risk for Autism Spectrum Disorder (ASD), schizophrenia (SZ), and Attention-Deficit-Hyperactivity-Disorder (ADHD), but their impact on functional connectivity (FC) networks remains unclear.
We analyzed resting-state functional magnetic resonance imaging data from 101 CNV carriers, 755 individuals with idiopathic ASD, SZ, or ADHD and 1,072 controls. We used CNV FC-signatures to identify major dimensions contributing to complex idiopathic conditions.
CNVs had large mirror effects on FC at the global and regional level, and their effect-sizes were twice as large as those of idiopathic conditions. Thalamus, somatomotor, and posterior insula regions played a critical role in dysconnectivity shared across deletions, duplications, idiopathic ASD, SZ but not ADHD. Individuals with higher similarity to deletion FC-signatures exhibited worse behavioral and cognitive symptoms. These seemingly distinct neuropsychiatric mutations showed similar gene co-expression patterns and converged on FC dimensions, that may represent mechanistic building blocks shared across idiopathic conditions.
Moreau, C., Raznahan, A., Bellec P.,, Chakravarty M., Thompson, P.M., Jacquemont, S.
Top-down neuroimaging and genomic studies of autism spectrum disorder and schizophrenia have revealed intriguingly small neuroimaging effect-sizes and an extreme polygenic architecture. It is also evident that both genomic variants and neuroimaging patterns are shared across psychiatric diagnoses - suggesting pleiotropic mechanisms. However, it remains unknown if variants and patterns are related to core cognitive dimensions or to comorbidities.
Bottom-up studies start at the level of molecular factors to study mechanisms related to biological risk irrespective of clinical manifestations. Such approaches reveal that the effect-sizes of high-risk psychiatric mutations are equally large for neuroimaging, cognitive and behavioural traits in stark contrast to top-down studies. Low specificity has been perplexing with studies showing that broad classes of genomic variants affect a similar range of psychiatric and cognitive dimensions.
We propose a roadmap based on multivariate strategies to integrate genomics, transcriptomics, neuroimaging and phenotypic data to deconvolve mechanisms involved in psychiatric conditions. New profiling based on specific biological processes and expression scores has considerable potential for parsing the contribution of genes and mechanisms to dimensions underlying psychiatric conditions. Such approaches will improve mechanistically informed predictive modelling for diagnosis and treatment outcomes.
Sønderby I, van der Meer D., Moreau C.A., (...) Jacquemont S., Thompson P., Andreassen O., Bøen R.
Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48 % male) derived from 15 distinct MRI scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers – the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.
Sønderby I, Ching C., (...) Moreau C.A., (...) Jacquemont S., Thompson P., Bearden C., Andreassen O.
The Enhancing Neuroimaging Genetics through Meta-Analysis copy number variant (ENIGMA-CNV) and 22q11.2 Deletion Syndrome Working Groups (22q-ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA-CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q-ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest-ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi-site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene-dosage effects on distinct brain regions also emerged, providing further insight into genotype-phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This ‘genotype-first’ approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior.
Banier E., (...), Moreau C.A., (...) Pernet C.
Having the means to share research data openly is essential to modern science. For human research, a key aspect in this endeavour is obtaining consent from participants, not just to take part in a study, which is a basic ethical principle, but also to share their data with the scientific community. To ensure that the participants’ privacy is respected, national and/or supranational regulations and laws are in place. It is, however, not always clear to researchers what the implications of those are, nor how to comply with them. The Open Brain Consent (https://open-brain-consent.readthedocs.io) is an international initiative that aims to provide researchers in the brain imaging community with information about data sharing options and tools. We present here a short history of this project and its latest developments, and share pointers to consent forms, including a template consent form that is compliant with the EU General Data Protection Regulation. We also share pointers to an associated data user agreement that is not only useful in the EU context, but also for any researchers dealing with personal (clinical) data elsewhere.
Modenato, C., Kumar, K., Moreau, C.A., Martin-Brevet, S., Huguet, G., Schramm, C., Martineau, J.-L., Martin, C.-O., Younis, N., Tamer, P., Douard, E. A., Thebault-Dagher, F., Cote, V., Charlebois, A.-R., Deguire, F., Maillard, A. M., Rodriguez-Herreros, B., Pain, A., Richetin, S., … Jacquemont.
Background: Copy Number Variants (CNVs) associated with autism and schizophrenia have large effects on brain anatomy. Yet, neuroimaging studies have been conducted one mutation at a time. We hypothesize that neuropsychiatric CNVs may exert general effects on brain morphometry because they confer risk for overlapping psychiatric conditions.
Methods: We analyzed T1-weighted MRIs and characterized shared patterns on brain anatomy across 8 neuropsychiatric CNVs. Clinically ascertained samples included 1q21.1 (n=48), 16p11.2 (n=156), or 22q11.2 (n=96) and 331 non-carriers. Non-clinically ascertained samples from the UK Biobank included 1q21.1 (n=19), 16p11.2 (n=8), 22q11.2 (n=9), 15q11.2 (n=148) and 965 non-carriers. Canonical correlation analysis (CCA) and univariate models were used to interrogate brain morphometry changes across 8 CNVs.
Results: Eight CNVs affect regional brain volumes along two main gene-morphometry dimensions identified by CCA. While fronto-temporal regions contributed to dimension 1, dimension 2 was driven by subcortical, parietal and occipital regions. Consistently, voxel-wise whole-brain analyses identified the same regions involved in patterns of alteration present across the 4 deletions and duplications. These neuroanatomical patterns are similar to those observed in cross-psychiatric disorder meta-analyses. Deletions and duplications at all 4 loci show mirror effects at either the global and/or the regional level.
Conclusion: Neuropsychiatric CNVs share neuroanatomical signatures characterized by a parsimonious set of brain dimensions. The latter may underlie the risk conferred by CNVs for a similar spectrum of neuropsychiatric conditions.
Urchs, S. G. W., Tam, A., Orban, P., Moreau, C., Benhajali, Y., Nguyen, H. D., Evans, A. C., Bellec, P.
Our understanding of the changes in functional brain organization in autism is hampered by the extensive heterogeneity that characterizes this neurodevelopmental disorder. Data driven clustering offers a straightforward way to decompose this heterogeneity into subtypes of distinguishable connectivity types and promises an unbiased framework to investigate behavioural symptoms and causative genetic factors. Yet the robustness and generalizability of these imaging subtypes is unknown.
Here, we show that unsupervised functional connectivity subtypes are moderately associated with the clinical diagnosis of autism, and that these associations generalize to independent replication data. We found that subtypes identified robust patterns of functional connectivity, but that a discrete assignment of individuals to these subtypes was not supported by the data.
Our results support the use of data driven subtyping as a data dimensionality reduction technique, rather than to establish clinical categories.
Moreau, C.A., Ching, C.R.K, Kumar, K., Jacquemont, S., Bearden C.E.
Copy Number Variants (CNVs) are associated with elevated rates of neuropsychiatric disorders. A ‘genetics-first’ approach, involving the CNV effects on the brain, irrespective of clinical symptomatology, allows investigation of mechanisms underlying neuropsychiatric disorders in the general population. Recent years have seen an increasing number of larger multisite neuroimaging studies investigating the effect of CNVs on structural and functional brain endophenotypes. Alterations overlap with those found in idiopathic psychiatric conditions but effect sizes are 2 to 5-fold larger. Here we review new CNV-associated structural and functional brain alterations and outline the future of neuroimaging genomics research with particular emphasis on developing new resources for the study of high-risk CNVs and rare genomic variants.
Benhajali Y, Badhwar A., Urchs S., Moreau C., Chouinard-Decorte F., Vainik U., Ferré P., Orban P., Pérusse D, Bellec P.
Many imaging and genetics studies have aimed to clarify whether the brain acts as an intermediate phenotype mediating the influence of genes in human behaviour. Brain activations in response to task demands are heterogeneous at the individual level, but also follow common patterns at the group level. Some studies have addressed this tension between heterogeneity and homogeneity by identifying groups of individuals that share the same brain activations patterns, called brain activation subtypes. In this work, we aimed to assess the viability of brain subtypes as endophenotypes intermediate between genes and behavior. We extracted brain activation subtypes separately for seven fMRI tasks, in 842 participants from the Human Connectome Project (HCP). We estimated the heritability of these subtypes and their genetic correlation with behavioral measures obtained inside and outside the scanner. Across all tasks, subtypes ranged from a predominantly ‘deactivating’ pattern towards a more ‘activating’ pattern of brain activity, with a heritability estimate ranging from 0 to 0.62. We observed high genetic and phenotypic correlation between behavioral measures and brain activation subtypes only for language and working memory tasks. Our results showed a significant genetic grounding of brain activation subtypes and they appear as a simple yet effective technique to tackle heterogeneity into imaging genetics studies.
Modenato C*, Martin-Brevet S*, Moreau C.A., Rodriguez-Herreros B., Kumar K., Draganski B., Sønderby I.E., Jacquemont S.
Pathogenic Copy Number Variants (CNVs) and aneuploidies are associated with autism spectrum disorder, schizophrenia, and are identified in up to 15% of patients referred for neuropsychiatric symptoms. Brain mechanisms mediating neuropsychiatric risk remain largely unknown, but there is a steady increase in computational anatomy publications investigating CNVs. Studies have been conducted one mutation at a time, leaving the field with a complex catalog of brain alterations linked to different genomic loci. The latter has hindered attempts to understand general principles linking CNVs to brain architecture. Our aim is to provide a general framework to understand the effects on neuroimaging phenotypes across multiple genomic loci. We conducted a systematic review of 64 computational anatomy studies on 16 CNVs and chromosomal aneuploidies (reciprocal 15q11.2, 22q11.2, 1q21.1 distal, 16p11.2 distal and proximal, 7q11.23 deletions and chromosomes, X, Y and 21). Large to moderate effect sizes on global and regional brain morphometry are observed across all neuropsychiatric CNVs, which is in stark contrast with the milder effects observed in idiopathic psychiatric disorders. Effect sizes at the regional level are in line with the symptom severity of CNVs. Data also suggest independent CNV effects on global versus regional measures as well as on surface versus thickness. Multivariate analyses suggest shared variance of morphometry alterations across multiple CNVs. This review highlights that to date, neuroimaging studies have only been conducted in a minute proportion of CNVs identified in the clinic and we propose strategies to transition from single variants to genome-wide studies.
Ecker C, Pretzch C, Bletsch A, … Moreau C, …, Bourgeron T, Beckmann C., the EU-AIMS LEAP Group, Murphy D.
Autism spectrum disorder (ASD) is accompanied by highly individualized neuroanatomical deviations that potentially map onto distinct genotypes and clinical phenotypes. This study aimed to link differences in brain anatomy to specific biological pathways to pave the way toward targeted therapeutic interventions. The authors examined neurodevelopmental differences in cortical thickness and their genomic underpinnings in a large and clinically diverse sample of 360 individuals with ASD and 279 typically developing control subjects (ages 6–30 years) within the EU-AIMS Longitudinal European Autism Project (LEAP). The authors also examined neurodevelopmental differences and their potential pathophysiological mechanisms between clinical ASD subgroups that differed in the severity and pattern of sensory features. In addition to significant between-group differences in “core” ASD brain regions (i.e., fronto-temporal and cingulate regions), individuals with ASD manifested as neuroanatomical outliers within the neurotypical cortical thickness range in a wider neural system, which was enriched for genes known to be implicated in ASD on the genetic and/or transcriptomic level. Within these regions, the individuals’ total (i.e., accumulated) degree of neuroanatomical atypicality was significantly correlated with higher polygenic scores for ASD and other psychiatric conditions, and it scaled with measures of symptom severity. Differences in cortical thickness deviations were also associated with distinct sensory subgroups, especially in brain regions expressing genes involved in excitatory rather than inhibitory neurotransmission. The study findings corroborate the link between macroscopic differences in brain anatomy and the molecular mechanisms underpinning heterogeneity in ASD, and provide future targets for stratification and subtyping.
Brownstein CA, Douard E, Mollon J, Smith R, Hojlo MA, Das A, … Moreau C, et al.
Objective: Copy number variants (CNVs) are strongly associated with neurodevelopmental and psychotic disorders. Early-onset psychosis (EOP), where symptoms appear before 18 years of age, is thought to be more strongly influenced by genetic factors than adult-onset psychotic disorders. However, the prevalence and effect of CNVs in EOP is unclear.
Methods: The authors documented the prevalence of recurrent CNVs and the functional impact of deletions and duplications genome-wide in 137 children and adolescents with EOP compared with 5,540 individuals with autism spectrum disorder (ASD) and 16,504 population control subjects. Specifically, the frequency of 47 recurrent CNVs previously associated with neurodevelopmental and neuropsychiatric illnesses in each cohort were compared. Next, CNV risk scores (CRSs), indices reflecting the dosage sensitivity for any gene across the genome that is encapsulated in a deletion or duplication separately, were compared between groups.
Results: The prevalence of recurrent CNVs was significantly higher in the EOP group than in the ASD (odds ratio=2.30) and control (odds ratio=5.06) groups. However, the difference between the EOP and ASD groups was attenuated when EOP participants with co-occurring ASD were excluded. CRS was significantly higher in the EOP group compared with the control group for both deletions (odds ratio=1.30) and duplications (odds ratio=1.09). In contrast, the EOP and ASD groups did not differ significantly in terms of CRS.
Conclusions: Given the high frequency of recurrent CNVs in the EOP group and comparable CRSs in the EOP and ASD groups, the findings suggest that all children and adolescents with a psychotic diagnosis should undergo genetic screening, as is recommended in ASD.
Moreau CA, Harvey A, Kumar K, Huguet G, Urchs S, Douard EA, ..., Thompson, P.M., Bourgeron T., Bellec, P., Jacquemont, S.
Background Polygenicity and genetic heterogeneity pose great challenges for studying psychiatric conditions. Genetically-informed approaches have been implemented in neuroimaging studies to address this issue. However, the effects on functional connectivity of rare and common genetic risks for psychiatric disorders are largely unknown. Our objectives were to estimate and compare the effect-sizes on brain connectivity of psychiatric genomic risk factors with various levels of complexity: oligo-, multi-genic copy number variants (CNVs), and polygenic risk scores (PRS) as well as idiopathic psychiatric conditions and traits.
Methods Resting-state functional-MRI data were processed using the same pipeline across nine datasets. Twenty-nine connectome-wide association studies were performed to characterize the effects of 15 CNVs (1003 carriers), 7 PRS, 4 idiopathic psychiatric conditions (1022 individuals with either autism, schizophrenia, bipolar conditions, or ADHD), and 2 traits (31424 unaffected controls).
Results Effect sizes on connectivity were largest for psychiatric CNVs (estimates: 0.2 to 0.65 z-score) followed by psychiatric conditions (0.15 to 0.42), neuroticism and fluid intelligence (0.02 to 0.03), and PRS (0.01 to 0.02). Effect-sizes of CNVs on connectivity were correlated to their effects on cognition and risk for disease (r=0.9, p=5.93e-06). However, effect sizes of CNVs adjusted for the number of genes significantly decreased from small oligogenic to large multigenic CNVs (r=-0.88, p=8.78e-06). PRS had disproportionately low effect sizes on connectivity compared to CNVs conferring similar risk for disease.
Conclusion Heterogeneity and polygenicity impact our ability to detect brain connectivity alterations underlying psychiatric manifestations.
Moreau CA, Kumar K, Harvey A, Huguet G, Urchs S, Schultz LM, ..., Thompson, P.M., Bourgeron T., Bellec, P., Jacquemont, S.
Pleiotropy occurs when a genetic variant influences more than one trait. This is a key property of the genomic architecture of psychiatric disorders and has been observed for rare and common genomic variants. It is reasonable to hypothesize that the microscale genetic overlap (pleiotropy) across psychiatric conditions and cognitive traits may lead to similar overlaps at the macroscale brain level such as large-scale brain functional networks. We took advantage of brain connectivity, measured by resting-state functional MRI to measure the effects of pleiotropy on large-scale brain networks, a putative step from genes to behavior. We processed nine resting-state functional MRI datasets including 32,726 individuals and computed connectome-wide profiles of seven neuropsychiatric copy-number-variants, five polygenic scores, neuroticism, and fluid intelligence as well as four idiopathic psychiatric conditions. Nine out of nineteen pairs of conditions and traits showed significant functional connectivity correlations (rFunctional connectivity), which could be explained by previously published levels of genomic (rGenetic) and transcriptomic (rTranscriptomic) correlations with moderate to high concordance: rGenetic - rFunctional connectivity= 0.71 [0.40-0.87] and rTranscriptomic - rFunctional connectivity= 0.83 [0.52; 0.94]. Extending this analysis to functional connectivity profiles associated with rare and common genetic risk showed that 30 out of 136 pairs of connectivity profiles were correlated above chance. These similarities between genetic risks and psychiatric disorders at the connectivity level were mainly driven by the overconnectivity of the thalamus and the somatomotor networks. Our findings suggest a substantial genetic component for shared connectivity profiles across conditions and traits, opening avenues to delineate general mechanisms - amenable to intervention - across psychiatric conditions and genetic risks.
Moreau CA, Deruelle C., Auzias G.
Neurodevelopmental disorders (NDDs) constitute a major health issue with >10% of the general worldwide population affected by at least one of these conditions-such as Autism Spectrum Disorders (ASD) and Attention Deficit Hyperactivity Disorders (ADHD). Each NDD is particularly complex to dissect for several reasons, including a high prevalence of comorbidities and a substantial heterogeneity of the clinical presentation. At the genetic level, several thousands of genes have been identified (polygenicity), while a part of them was already involved in other psychiatric conditions (pleiotropy). Given these multiple sources of variance, gathering sufficient data for the proper application and evaluation of machine learning (ML) techniques is essential but challenging. In this chapter, we offer an overview of the ML methods most widely used to tackle NDDs complexity-from stratification techniques to diagnosis prediction. We point out challenges specific to NDDs such as early diagnosis, that can benefit from the recent advances in the ML field. These techniques also have the potential to delineate homogeneous subgroups of patients that would enable a refined understanding of underlying physiopathology. We finally survey a selection of recent papers that we consider as particularly representative of the opportunities offered by contemporary ML techniques applied to large open datasets, or that illustrate the challenges faced by current approaches to be addressed in the near future.