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Bourque VR, Poulain C, Proulx C, Moreau CA, Joober R, Forgeot d'Arc B, Huguet G, Jacquemont S. Genetic and phenotypic similarity across major psychiatric disorders: a systematic review and quantitative assessment. Transl Psychiatry 2024; 14:171. [PMID: 38555309 PMCID: PMC10981737 DOI: 10.1038/s41398-024-02866-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 03/05/2024] [Accepted: 03/11/2024] [Indexed: 04/02/2024] Open
Abstract
There is widespread overlap across major psychiatric disorders, and this is the case at different levels of observations, from genetic variants to brain structures and function and to symptoms. However, it remains unknown to what extent these commonalities at different levels of observation map onto each other. Here, we systematically review and compare the degree of similarity between psychiatric disorders at all available levels of observation. We searched PubMed and EMBASE between January 1, 2009 and September 8, 2022. We included original studies comparing at least four of the following five diagnostic groups: Schizophrenia, Bipolar Disorder, Major Depressive Disorder, Autism Spectrum Disorder, and Attention Deficit Hyperactivity Disorder, with measures of similarities between all disorder pairs. Data extraction and synthesis were performed by two independent researchers, following the PRISMA guidelines. As main outcome measure, we assessed the Pearson correlation measuring the degree of similarity across disorders pairs between studies and biological levels of observation. We identified 2975 studies, of which 28 were eligible for analysis, featuring similarity measures based on single-nucleotide polymorphisms, gene-based analyses, gene expression, structural and functional connectivity neuroimaging measures. The majority of correlations (88.6%) across disorders between studies, within and between levels of observation, were positive. To identify a consensus ranking of similarities between disorders, we performed a principal component analysis. Its first dimension explained 51.4% (95% CI: 43.2, 65.4) of the variance in disorder similarities across studies and levels of observation. Based on levels of genetic correlation, we estimated the probability of another psychiatric diagnosis in first-degree relatives and showed that they were systematically lower than those observed in population studies. Our findings highlight that genetic and brain factors may underlie a large proportion, but not all of the diagnostic overlaps observed in the clinic.
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Affiliation(s)
| | - Cécile Poulain
- CHU Sainte-Justine Azrieli Research Center, Université de Montréal, Montreal, QC, Canada
| | - Catherine Proulx
- CHU Sainte-Justine Azrieli Research Center, Université de Montréal, Montreal, QC, Canada
| | - Clara A Moreau
- Imaging Genetics Center, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Ridha Joober
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montréal, QC, Canada
| | - Baudouin Forgeot d'Arc
- CHU Sainte-Justine Azrieli Research Center, Université de Montréal, Montreal, QC, Canada
| | - Guillaume Huguet
- CHU Sainte-Justine Azrieli Research Center, Université de Montréal, Montreal, QC, Canada
| | - Sébastien Jacquemont
- CHU Sainte-Justine Azrieli Research Center, Université de Montréal, Montreal, QC, Canada.
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2
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Kopal J, Kumar K, Shafighi K, Saltoun K, Modenato C, Moreau CA, Huguet G, Jean-Louis M, Martin CO, Saci Z, Younis N, Douard E, Jizi K, Beauchamp-Chatel A, Kushan L, Silva AI, van den Bree MBM, Linden DEJ, Owen MJ, Hall J, Lippé S, Draganski B, Sønderby IE, Andreassen OA, Glahn DC, Thompson PM, Bearden CE, Zatorre R, Jacquemont S, Bzdok D. Using rare genetic mutations to revisit structural brain asymmetry. Nat Commun 2024; 15:2639. [PMID: 38531844 PMCID: PMC10966068 DOI: 10.1038/s41467-024-46784-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 03/11/2024] [Indexed: 03/28/2024] Open
Abstract
Asymmetry between the left and right hemisphere is a key feature of brain organization. Hemispheric functional specialization underlies some of the most advanced human-defining cognitive operations, such as articulated language, perspective taking, or rapid detection of facial cues. Yet, genetic investigations into brain asymmetry have mostly relied on common variants, which typically exert small effects on brain-related phenotypes. Here, we leverage rare genomic deletions and duplications to study how genetic alterations reverberate in human brain and behavior. We designed a pattern-learning approach to dissect the impact of eight high-effect-size copy number variations (CNVs) on brain asymmetry in a multi-site cohort of 552 CNV carriers and 290 non-carriers. Isolated multivariate brain asymmetry patterns spotlighted regions typically thought to subserve lateralized functions, including language, hearing, as well as visual, face and word recognition. Planum temporale asymmetry emerged as especially susceptible to deletions and duplications of specific gene sets. Targeted analysis of common variants through genome-wide association study (GWAS) consolidated partly diverging genetic influences on the right versus left planum temporale structure. In conclusion, our gene-brain-behavior data fusion highlights the consequences of genetically controlled brain lateralization on uniquely human cognitive capacities.
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Affiliation(s)
- Jakub Kopal
- Mila - Québec Artificial Intelligence Institute, Montréal, QC, Canada
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, Canada
| | - Kuldeep Kumar
- Centre de recherche CHU Sainte-Justine, Montréal, Quebec, Canada
| | - Kimia Shafighi
- Mila - Québec Artificial Intelligence Institute, Montréal, QC, Canada
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, Canada
| | - Karin Saltoun
- Mila - Québec Artificial Intelligence Institute, Montréal, QC, Canada
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, Canada
| | - Claudia Modenato
- LREN - Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland
| | - Clara A Moreau
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Guillaume Huguet
- Centre de recherche CHU Sainte-Justine, Montréal, Quebec, Canada
| | | | | | - Zohra Saci
- Centre de recherche CHU Sainte-Justine, Montréal, Quebec, Canada
| | - Nadine Younis
- Centre de recherche CHU Sainte-Justine, Montréal, Quebec, Canada
| | - Elise Douard
- Centre de recherche CHU Sainte-Justine, Montréal, Quebec, Canada
| | - Khadije Jizi
- Centre de recherche CHU Sainte-Justine, Montréal, Quebec, Canada
| | - Alexis Beauchamp-Chatel
- Institut universitaire en santé mentale de Montréal, University of Montréal, Montréal, Canada
- Department of Psychiatry, University of Montreal, Montréal, Canada
| | - Leila Kushan
- Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, UCLA, Los Angeles, USA
| | - Ana I Silva
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Marianne B M van den Bree
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
- Neuroscience and Mental Health Innovation Institute, Cardiff University, Cardiff, UK
| | - David E J Linden
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
- Neuroscience and Mental Health Innovation Institute, Cardiff University, Cardiff, UK
| | - Michael J Owen
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Jeremy Hall
- Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
- Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Sarah Lippé
- Centre de recherche CHU Sainte-Justine, Montréal, Quebec, Canada
| | - Bogdan Draganski
- LREN - Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland
- Neurology Department, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Ida E Sønderby
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital and University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Carrie E Bearden
- Semel Institute for Neuroscience and Human Behavior, Departments of Psychiatry and Biobehavioral Sciences and Psychology, UCLA, Los Angeles, USA
| | - Robert Zatorre
- International Laboratory for Brain, Music and Sound Research, Montreal, QC, Canada
- TheNeuro - Montreal Neurological Institute (MNI), McConnell Brain Imaging Centre, Faculty of Medicine, McGill University, Montreal, QC, Canada
| | - Sébastien Jacquemont
- Centre de recherche CHU Sainte-Justine, Montréal, Quebec, Canada
- Department of Pediatrics, University of Montréal, Montréal, Quebec, Canada
| | - Danilo Bzdok
- Mila - Québec Artificial Intelligence Institute, Montréal, QC, Canada.
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, Canada.
- TheNeuro - Montreal Neurological Institute (MNI), McConnell Brain Imaging Centre, Faculty of Medicine, McGill University, Montreal, QC, Canada.
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3
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Auwerx C, Jõeloo M, Sadler MC, Tesio N, Ojavee S, Clark CJ, Mägi R, Reymond A, Kutalik Z. Rare copy-number variants as modulators of common disease susceptibility. Genome Med 2024; 16:5. [PMID: 38185688 PMCID: PMC10773105 DOI: 10.1186/s13073-023-01265-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 11/27/2023] [Indexed: 01/09/2024] Open
Abstract
BACKGROUND Copy-number variations (CNVs) have been associated with rare and debilitating genomic disorders (GDs) but their impact on health later in life in the general population remains poorly described. METHODS Assessing four modes of CNV action, we performed genome-wide association scans (GWASs) between the copy-number of CNV-proxy probes and 60 curated ICD-10 based clinical diagnoses in 331,522 unrelated white British UK Biobank (UKBB) participants with replication in the Estonian Biobank. RESULTS We identified 73 signals involving 40 diseases, all of which indicating that CNVs increased disease risk and caused earlier onset. We estimated that 16% of these associations are indirect, acting by increasing body mass index (BMI). Signals mapped to 45 unique, non-overlapping regions, nine of which being linked to known GDs. Number and identity of genes affected by CNVs modulated their pathogenicity, with many associations being supported by colocalization with both common and rare single-nucleotide variant association signals. Dissection of association signals provided insights into the epidemiology of known gene-disease pairs (e.g., deletions in BRCA1 and LDLR increased risk for ovarian cancer and ischemic heart disease, respectively), clarified dosage mechanisms of action (e.g., both increased and decreased dosage of 17q12 impacted renal health), and identified putative causal genes (e.g., ABCC6 for kidney stones). Characterization of the pleiotropic pathological consequences of recurrent CNVs at 15q13, 16p13.11, 16p12.2, and 22q11.2 in adulthood indicated variable expressivity of these regions and the involvement of multiple genes. Finally, we show that while the total burden of rare CNVs-and especially deletions-strongly associated with disease risk, it only accounted for ~ 0.02% of the UKBB disease burden. These associations are mainly driven by CNVs at known GD CNV regions, whose pleiotropic effect on common diseases was broader than anticipated by our CNV-GWAS. CONCLUSIONS Our results shed light on the prominent role of rare CNVs in determining common disease susceptibility within the general population and provide actionable insights for anticipating later-onset comorbidities in carriers of recurrent CNVs.
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Affiliation(s)
- Chiara Auwerx
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland.
- University Center for Primary Care and Public Health, 1005, Lausanne, Switzerland.
| | - Maarja Jõeloo
- Institute of Molecular and Cell Biology, University of Tartu, 51010, Tartu, Estonia
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia
| | - Marie C Sadler
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
- University Center for Primary Care and Public Health, 1005, Lausanne, Switzerland
| | - Nicolò Tesio
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
| | - Sven Ojavee
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
| | - Charlie J Clark
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, 51010, Tartu, Estonia
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Genopode building, 1015, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland.
- University Center for Primary Care and Public Health, 1005, Lausanne, Switzerland.
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Mudassir BU, Alotaibi MA, Kizilbash N, Alruwaili D, Alruwaili A, Alenezi M, Agha Z. Genome-wide CNV analysis uncovers novel pathogenic regions in cohort of five multiplex families with neurodevelopmental disorders. Heliyon 2023; 9:e19718. [PMID: 37810058 PMCID: PMC10558996 DOI: 10.1016/j.heliyon.2023.e19718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Revised: 08/26/2023] [Accepted: 08/30/2023] [Indexed: 10/10/2023] Open
Abstract
Structural reorganization of chromosomes by genomic duplications and/or deletions are known as copy number variations (CNVs). Pathogenic and disease susceptible CNVs alter gene dosage and its phenotypic expression that often leads to human genetic diseases including Neurological disorders. CNVs affecting same common genes in multiple neurodevelopmental disorders can better explain the shared clinical and genetic aetiology across brain diseases. Our study presents the novel copy number variations in a cohort of five multiplex consanguineous families with intellectual disability, microcephaly, ASD, epilepsy, and neurological syndromic features. Cytoscan HD microarray suite has revealed genome wide deletions, duplications and LOH regions which are co-segregating in the family members for the rare neurodevelopmental syndromic phenotypes. This study identifies 1q21.1 microduplication, 16p11.2 microduplication, Xp11.22 microduplication, 4p12 microdeletion and Xq21.1 microdeletion that significantly contribute to primary disease onset and its progression for the first time in Pakistani families. Our study has potential impact on the understanding of pathogenic genetic predisposition for appearance of complex and heterogeneous neurodevelopmental disorders with otherwise unexplained syndromic features. Identification of altered gene dosage across the genome is helpful in improved diagnosis, better disease management in day-to-day life activities of patients with cognitive impairment and genetic counselling of families where consanguinity is a tradition. Our study will contribute to expand the knowledge of genotype-phenotype expression and future gateways in therapeutics and precision medicine research will be open in Pakistan.
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Affiliation(s)
- Behjat Ul Mudassir
- Translational Genomics Laboratory, Department of Biosciences, COMSATS University Islamabad, Islamabad, Pakistan
| | | | - Nadeem Kizilbash
- Department of Medical Laboratory Technology, Northern Border University, Arar, Saudi Arabia
| | - Daliyah Alruwaili
- Department of Medical Laboratory Technology, Northern Border University, Arar, Saudi Arabia
| | - Anwar Alruwaili
- Department of Medical Laboratory Technology, Northern Border University, Arar, Saudi Arabia
| | - Modhi Alenezi
- Department of Medical Laboratory Technology, Northern Border University, Arar, Saudi Arabia
| | - Zehra Agha
- Translational Genomics Laboratory, Department of Biosciences, COMSATS University Islamabad, Islamabad, Pakistan
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5
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Kopal J, Kumar K, Shafighi K, Saltoun K, Modenato C, Moreau CA, Huguet G, Jean-Louis M, Martin CO, Saci Z, Younis N, Douard E, Jizi K, Beauchamp-Chatel A, Kushan L, Silva AI, van den Bree MBM, Linden DEJ, Owen MJ, Hall J, Lippé S, Draganski B, Sønderby IE, Andreassen OA, Glahn DC, Thompson PM, Bearden CE, Zatorre R, Jacquemont S, Bzdok D. Using rare genetic mutations to revisit structural brain asymmetry. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.17.537199. [PMID: 37131672 PMCID: PMC10153125 DOI: 10.1101/2023.04.17.537199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Asymmetry between the left and right brain is a key feature of brain organization. Hemispheric functional specialization underlies some of the most advanced human-defining cognitive operations, such as articulated language, perspective taking, or rapid detection of facial cues. Yet, genetic investigations into brain asymmetry have mostly relied on common variant studies, which typically exert small effects on brain phenotypes. Here, we leverage rare genomic deletions and duplications to study how genetic alterations reverberate in human brain and behavior. We quantitatively dissected the impact of eight high-effect-size copy number variations (CNVs) on brain asymmetry in a multi-site cohort of 552 CNV carriers and 290 non-carriers. Isolated multivariate brain asymmetry patterns spotlighted regions typically thought to subserve lateralized functions, including language, hearing, as well as visual, face and word recognition. Planum temporale asymmetry emerged as especially susceptible to deletions and duplications of specific gene sets. Targeted analysis of common variants through genome-wide association study (GWAS) consolidated partly diverging genetic influences on the right versus left planum temporale structure. In conclusion, our gene-brain-behavior mapping highlights the consequences of genetically controlled brain lateralization on human-defining cognitive traits.
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