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Agarwal I, Fuller ZL, Myers SR, Przeworski M. Relating pathogenic loss-of-function mutations in humans to their evolutionary fitness costs. eLife 2023; 12:83172. [PMID: 36648429 PMCID: PMC9937649 DOI: 10.7554/elife.83172] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 01/16/2023] [Indexed: 01/18/2023] Open
Abstract
Causal loss-of-function (LOF) variants for Mendelian and severe complex diseases are enriched in 'mutation intolerant' genes. We show how such observations can be interpreted in light of a model of mutation-selection balance and use the model to relate the pathogenic consequences of LOF mutations at present to their evolutionary fitness effects. To this end, we first infer posterior distributions for the fitness costs of LOF mutations in 17,318 autosomal and 679 X-linked genes from exome sequences in 56,855 individuals. Estimated fitness costs for the loss of a gene copy are typically above 1%; they tend to be largest for X-linked genes, whether or not they have a Y homolog, followed by autosomal genes and genes in the pseudoautosomal region. We compare inferred fitness effects for all possible de novo LOF mutations to those of de novo mutations identified in individuals diagnosed with one of six severe, complex diseases or developmental disorders. Probands carry an excess of mutations with estimated fitness effects above 10%; as we show by simulation, when sampled in the population, such highly deleterious mutations are typically only a couple of generations old. Moreover, the proportion of highly deleterious mutations carried by probands reflects the typical age of onset of the disease. The study design also has a discernible influence: a greater proportion of highly deleterious mutations is detected in pedigree than case-control studies, and for autism, in simplex than multiplex families and in female versus male probands. Thus, anchoring observations in human genetics to a population genetic model allows us to learn about the fitness effects of mutations identified by different mapping strategies and for different traits.
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Affiliation(s)
- Ipsita Agarwal
- Department of Biological Sciences, Columbia UniversityNew YorkUnited States
- Department of Statistics, University of OxfordOxfordUnited Kingdom
| | - Zachary L Fuller
- Department of Biological Sciences, Columbia UniversityNew YorkUnited States
| | - Simon R Myers
- Department of Statistics, University of OxfordOxfordUnited Kingdom
- The Wellcome Centre for Human Genetics, University of OxfordOxfordUnited Kingdom
| | - Molly Przeworski
- Department of Biological Sciences, Columbia UniversityNew YorkUnited States
- Department of Systems Biology, Columbia UniversityNew YorkUnited States
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Levchenko A, Plotnikova M. Genomic regulatory sequences in the pathogenesis of bipolar disorder. Front Psychiatry 2023; 14:1115924. [PMID: 36824672 PMCID: PMC9941178 DOI: 10.3389/fpsyt.2023.1115924] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 01/23/2023] [Indexed: 02/10/2023] Open
Abstract
The lifetime prevalence of bipolar disorder is estimated to be about 2%. Epigenetics defines regulatory mechanisms that determine relatively stable patterns of gene expression by controlling all key steps, from DNA to messenger RNA to protein. This Mini Review highlights recent discoveries of modified epigenetic control resulting from genetic variants associated with bipolar disorder in genome-wide association studies. The revealed epigenetic abnormalities implicate gene transcription and post-transcriptional regulation. In the light of these discoveries, the Mini Review focuses on the genes PACS1, MCHR1, DCLK3, HAPLN4, LMAN2L, TMEM258, GNL3, LRRC57, CACNA1C, CACNA1D, and NOVA2 and their potential biological role in the pathogenesis of bipolar disorder. Molecular mechanisms under control of these genes do not translate into a unified picture and substantially more research is needed to fill the gaps in knowledge and to solve current limitations in prognosis and treatment of bipolar disorder. In conclusion, the genetic and functional studies confirm the complex nature of bipolar disorder and indicate future research directions to explore possible targeted treatment options, eventually working toward a personalized approach.
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Affiliation(s)
- Anastasia Levchenko
- Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | - Maria Plotnikova
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia.,Center for Genetics and Life Science, Sirius University of Science and Technology, Sochi, Russia
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The autism risk factor CHD8 is a chromatin activator in human neurons and functionally dependent on the ERK-MAPK pathway effector ELK1. Sci Rep 2022; 12:22425. [PMID: 36575212 PMCID: PMC9794786 DOI: 10.1038/s41598-022-23614-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 11/02/2022] [Indexed: 12/28/2022] Open
Abstract
The chromodomain helicase DNA-binding protein CHD8 is the most frequently mutated gene in autism spectrum disorder. Despite its prominent disease involvement, little is known about its molecular function in the human brain. CHD8 is a chromatin regulator which binds to the promoters of actively transcribed genes through genomic targeting mechanisms which have yet to be fully defined. By generating a conditional loss-of-function and an endogenously tagged allele in human pluripotent stem cells, we investigated the molecular function and the interaction of CHD8 with chromatin in human neurons. Chromatin accessibility analysis and transcriptional profiling revealed that CHD8 functions as a transcriptional activator at its target genes in human neurons. Furthermore, we found that CHD8 chromatin targeting is cell context-dependent. In human neurons, CHD8 preferentially binds at ETS motif-enriched promoters. This enrichment is particularly prominent on the promoters of genes whose expression significantly changes upon the loss of CHD8. Indeed, among the ETS transcription factors, we identified ELK1 as being most highly correlated with CHD8 expression in primary human fetal and adult cortical neurons and most highly expressed in our stem cell-derived neurons. Remarkably, ELK1 was necessary to recruit CHD8 specifically to ETS motif-containing sites. These findings imply that ELK1 and CHD8 functionally cooperate to regulate gene expression and chromatin states at MAPK/ERK target genes in human neurons. Our results suggest that the MAPK/ERK/ELK1 axis potentially contributes to the pathogenesis caused by CHD8 mutations in human neurodevelopmental disorders.
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Cohen BM, Singh T, Öngür D, Konstantin GE, Gardner ME. Clinical phenotypes of five patients with psychotic disorders carrying rare schizophrenia-associated loss-of-function variants. Schizophr Res 2022; 250:100-103. [PMID: 36399898 DOI: 10.1016/j.schres.2022.11.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 09/30/2022] [Accepted: 11/05/2022] [Indexed: 11/17/2022]
Abstract
The Schizophrenia Exome Meta-Analysis (SCHEMA) consortium identified 10 genes in which loss-of-function (LoF) variants are highly associated with schizophrenia (SZ). In a well-characterized sample of 988 patients with psychotic disorders, we investigated whether patients bearing a SCHEMA variant presented with unusual or unique signs, symptoms, or course of illness. We identified 5 patients who carried a LoF variant in a SCHEMA gene, each in a different gene. None of the patients with a SCHEMA variant had unique symptoms. However, compared to the average of patients in the sample, all of the patients with a SCHEMA variant had earlier onset of any mental illness and more hospitalizations. Also, among SCHEMA carriers, 80 % were treated with clozapine, 60 % with ECT, all with either clozapine or ECT and 40 % with both clozapine and ECT, compared to only 2 % treated with clozapine and 18 % treated with ECT in the comparison group of patients without SCHEMA variants. All 5 patients with a SCHEMA variant had polysubstance abuse, and all had attempted suicide. Fewer than half had such presentations in the group without SCHEMA variants. In this small sample, SCHEMA variants appear to be associated with earlier onset, less favorable response to standard first-line treatments, and more severe illness, but not unique presentations of illness.
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Affiliation(s)
- Bruce M Cohen
- Program for Neuropsychiatric Research, McLean Hospital, 115 Mill St., Belmont, MA 02478, USA; Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA.
| | - Tarjinder Singh
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, 185 Cambridge Street, Boston, MA 02114, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
| | - Dost Öngür
- Harvard Medical School, 25 Shattuck St, Boston, MA 02115, USA; Schizophrenia and Bipolar Disorder Research Program, McLean Hospital, 115 Mill St., Belmont, MA 02478, USA.
| | - Grace E Konstantin
- Schizophrenia and Bipolar Disorder Research Program, McLean Hospital, 115 Mill St., Belmont, MA 02478, USA
| | - Margaret E Gardner
- Schizophrenia and Bipolar Disorder Research Program, McLean Hospital, 115 Mill St., Belmont, MA 02478, USA
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55
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Ahangari M, Kirkpatrick R, Nguyen TH, Gillespie N, Kendler KS, Bacanu SA, Webb BT, Verrelli BC, Riley BP. Examining the source of increased bipolar disorder and major depressive disorder common risk variation burden in multiplex schizophrenia families. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2022; 8:106. [PMID: 36434002 PMCID: PMC9700852 DOI: 10.1038/s41537-022-00317-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 11/03/2022] [Indexed: 11/27/2022]
Abstract
Psychotic and affective disorders often aggregate in the relatives of probands with schizophrenia, and genetic studies show substantial genetic correlation among schizophrenia, bipolar disorder, and major depressive disorder. In this study, we examined the polygenic risk burden of bipolar disorder and major depressive disorder in 257 multiplex schizophrenia families (N = 1005) from the Irish Study of High-Density Multiplex Schizophrenia Families versus 2205 ancestry-matched controls. Our results indicate that members of multiplex schizophrenia families have an increased polygenic risk for bipolar disorder and major depressive disorder compared to population controls. However, this observation is largely attributable to the part of the genetic risk that bipolar disorder or major depressive disorder share with schizophrenia due to genetic correlation, rather than the affective portion of the genetic risk unique to them. These findings suggest that a complete interpretation of cross-disorder polygenic risks in multiplex families requires an assessment of the relative contribution of shared versus unique genetic factors to account for genetic correlations across psychiatric disorders.
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Affiliation(s)
- Mohammad Ahangari
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA.
- Integrative Life Sciences PhD Program, Virginia Commonwealth University, Richmond, VA, USA.
| | - Robert Kirkpatrick
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Tan-Hoang Nguyen
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Nathan Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Silviu-Alin Bacanu
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Bradley T Webb
- GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, NC, USA
| | - Brian C Verrelli
- Center for Biological Data Science, Virginia Commonwealth University, Richmond, VA, USA
| | - Brien P Riley
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
- Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
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56
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Sun P, Wang L, Yang Y, Zhang CY, Yang L, Fang Y, Li M. Common variants associated with AKAP11 expression confer risk of bipolar disorder. Asian J Psychiatr 2022; 77:103271. [PMID: 36179529 DOI: 10.1016/j.ajp.2022.103271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 08/30/2022] [Accepted: 09/23/2022] [Indexed: 11/30/2022]
Affiliation(s)
- Ping Sun
- Clinical Research Center, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Qingdao Mental Health Center, Qingdao, Shandong, China
| | - Lu Wang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Yu Yang
- Qingdao Mental Health Center, Qingdao, Shandong, China; Binzhou Medical University, Yantai, Shandong, China
| | - Chu-Yi Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Lu Yang
- Clinical Research Center, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yiru Fang
- Clinical Research Center, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China; State Key Laboratory of Neuroscience, Shanghai Institute for Biological Sciences, Chinese Academy of Sciences, Shanghai, China; Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China.
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
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57
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Tielke A, Martins H, Pelzl MA, Maaser-Hecker A, David FS, Reinbold CS, Streit F, Sirignano L, Schwarz M, Vedder H, Kammerer-Ciernioch J, Albus M, Borrmann-Hassenbach M, Hautzinger M, Hünten K, Degenhardt F, Fischer SB, Beins EC, Herms S, Hoffmann P, Schulze TG, Witt SH, Rietschel M, Cichon S, Nöthen MM, Schratt G, Forstner AJ. Genetic and functional analyses implicate microRNA 499A in bipolar disorder development. Transl Psychiatry 2022; 12:437. [PMID: 36207305 PMCID: PMC9547016 DOI: 10.1038/s41398-022-02176-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 08/10/2022] [Accepted: 09/12/2022] [Indexed: 11/09/2022] Open
Abstract
Bipolar disorder (BD) is a complex mood disorder with a strong genetic component. Recent studies suggest that microRNAs contribute to psychiatric disorder development. In BD, specific candidate microRNAs have been implicated, in particular miR-137, miR-499a, miR-708, miR-1908 and miR-2113. The aim of the present study was to determine the contribution of these five microRNAs to BD development. For this purpose, we performed: (i) gene-based tests of the five microRNA coding genes, using data from a large genome-wide association study of BD; (ii) gene-set analyses of predicted, brain-expressed target genes of the five microRNAs; (iii) resequencing of the five microRNA coding genes in 960 BD patients and 960 controls and (iv) in silico and functional studies for selected variants. Gene-based tests revealed a significant association with BD for MIR499A, MIR708, MIR1908 and MIR2113. Gene-set analyses revealed a significant enrichment of BD associations in the brain-expressed target genes of miR-137 and miR-499a-5p. Resequencing identified 32 distinct rare variants (minor allele frequency < 1%), all of which showed a non-significant numerical overrepresentation in BD patients compared to controls (p = 0.214). Seven rare variants were identified in the predicted stem-loop sequences of MIR499A and MIR2113. These included rs142927919 in MIR2113 (pnom = 0.331) and rs140486571 in MIR499A (pnom = 0.297). In silico analyses predicted that rs140486571 might alter the miR-499a secondary structure. Functional analyses showed that rs140486571 significantly affects miR-499a processing and expression. Our results suggest that MIR499A dysregulation might contribute to BD development. Further research is warranted to elucidate the contribution of the MIR499A regulated network to BD susceptibility.
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Affiliation(s)
- Aileen Tielke
- grid.10388.320000 0001 2240 3300Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany ,Salus Clinic Hürth, Hürth, Germany
| | - Helena Martins
- grid.5801.c0000 0001 2156 2780Lab of Systems Neuroscience, Department of Health Science and Technology, Institute for Neuroscience, Swiss Federal Institute of Technology ETH & Neuroscience Center Zurich (ZNZ), Zurich, Switzerland
| | - Michael A. Pelzl
- grid.10253.350000 0004 1936 9756Institute for Physiological Chemistry, Philipps-University Marburg, Marburg, Germany ,grid.10392.390000 0001 2190 1447Present Address: Clinic for Psychiatry and Psychotherapy, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Anna Maaser-Hecker
- grid.10388.320000 0001 2240 3300Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Friederike S. David
- grid.10388.320000 0001 2240 3300Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Céline S. Reinbold
- grid.5510.10000 0004 1936 8921Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway ,grid.6612.30000 0004 1937 0642Department of Biomedicine, University of Basel, Basel, Switzerland ,grid.410567.1Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland
| | - Fabian Streit
- grid.7700.00000 0001 2190 4373Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Lea Sirignano
- grid.7700.00000 0001 2190 4373Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | | | | | | | - Margot Albus
- grid.419834.30000 0001 0690 3065Isar Amper Klinikum München Ost, kbo, Haar, Germany
| | | | - Martin Hautzinger
- grid.10392.390000 0001 2190 1447Department of Psychology, Clinical Psychology and Psychotherapy, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Karola Hünten
- grid.10388.320000 0001 2240 3300Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Franziska Degenhardt
- grid.10388.320000 0001 2240 3300Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany ,grid.410718.b0000 0001 0262 7331Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Duisburg, Germany
| | - Sascha B. Fischer
- grid.6612.30000 0004 1937 0642Department of Biomedicine, University of Basel, Basel, Switzerland ,grid.410567.1Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland
| | - Eva C. Beins
- grid.10388.320000 0001 2240 3300Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Stefan Herms
- grid.10388.320000 0001 2240 3300Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany ,grid.6612.30000 0004 1937 0642Department of Biomedicine, University of Basel, Basel, Switzerland ,grid.410567.1Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland
| | - Per Hoffmann
- grid.10388.320000 0001 2240 3300Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany ,grid.6612.30000 0004 1937 0642Department of Biomedicine, University of Basel, Basel, Switzerland ,grid.410567.1Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland
| | - Thomas G. Schulze
- grid.7700.00000 0001 2190 4373Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany ,grid.5252.00000 0004 1936 973XInstitute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany ,grid.411984.10000 0001 0482 5331Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Stephanie H. Witt
- grid.7700.00000 0001 2190 4373Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany ,grid.7700.00000 0001 2190 4373Center for Innovative Psychiatry and Psychotherapy Research, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Marcella Rietschel
- grid.7700.00000 0001 2190 4373Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Sven Cichon
- grid.10388.320000 0001 2240 3300Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany ,grid.6612.30000 0004 1937 0642Department of Biomedicine, University of Basel, Basel, Switzerland ,grid.410567.1Institute of Medical Genetics and Pathology, University Hospital Basel, Basel, Switzerland ,grid.8385.60000 0001 2297 375XInstitute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
| | - Markus M. Nöthen
- grid.10388.320000 0001 2240 3300Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Gerhard Schratt
- grid.5801.c0000 0001 2156 2780Lab of Systems Neuroscience, Department of Health Science and Technology, Institute for Neuroscience, Swiss Federal Institute of Technology ETH & Neuroscience Center Zurich (ZNZ), Zurich, Switzerland
| | - Andreas J. Forstner
- grid.10388.320000 0001 2240 3300Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany ,grid.8385.60000 0001 2297 375XInstitute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany ,grid.10253.350000 0004 1936 9756Centre for Human Genetics, University of Marburg, Marburg, Germany
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Liu Y, Yeung WSB, Chiu PCN, Cao D. Computational approaches for predicting variant impact: An overview from resources, principles to applications. Front Genet 2022; 13:981005. [PMID: 36246661 PMCID: PMC9559863 DOI: 10.3389/fgene.2022.981005] [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: 06/29/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
One objective of human genetics is to unveil the variants that contribute to human diseases. With the rapid development and wide use of next-generation sequencing (NGS), massive genomic sequence data have been created, making personal genetic information available. Conventional experimental evidence is critical in establishing the relationship between sequence variants and phenotype but with low efficiency. Due to the lack of comprehensive databases and resources which present clinical and experimental evidence on genotype-phenotype relationship, as well as accumulating variants found from NGS, different computational tools that can predict the impact of the variants on phenotype have been greatly developed to bridge the gap. In this review, we present a brief introduction and discussion about the computational approaches for variant impact prediction. Following an innovative manner, we mainly focus on approaches for non-synonymous variants (nsSNVs) impact prediction and categorize them into six classes. Their underlying rationale and constraints, together with the concerns and remedies raised from comparative studies are discussed. We also present how the predictive approaches employed in different research. Although diverse constraints exist, the computational predictive approaches are indispensable in exploring genotype-phenotype relationship.
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Affiliation(s)
- Ye Liu
- Shenzhen Key Laboratory of Fertility Regulation, Reproductive Medicine Center, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
| | - William S. B. Yeung
- Shenzhen Key Laboratory of Fertility Regulation, Reproductive Medicine Center, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
- Department of Obstetrics and Gynaecology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Philip C. N. Chiu
- Shenzhen Key Laboratory of Fertility Regulation, Reproductive Medicine Center, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
- Department of Obstetrics and Gynaecology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- *Correspondence: Philip C. N. Chiu, ; Dandan Cao,
| | - Dandan Cao
- Shenzhen Key Laboratory of Fertility Regulation, Reproductive Medicine Center, The University of Hong Kong-Shenzhen Hospital, Shenzhen, China
- *Correspondence: Philip C. N. Chiu, ; Dandan Cao,
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59
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Ahangari M, Gentry AE, Nguyen TH, Kirkpatrick R, Verrelli BC, Bacanu SA, Kendler KS, Webb BT, Riley BP. Evaluating the role of common risk variation in the recurrence risk of schizophrenia in multiplex schizophrenia families. Transl Psychiatry 2022; 12:291. [PMID: 35864105 PMCID: PMC9304393 DOI: 10.1038/s41398-022-02060-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 07/05/2022] [Indexed: 12/13/2022] Open
Abstract
Multiplex families have higher recurrence risk of schizophrenia compared to the families of sporadic cases, but the source of this increased recurrence risk is unknown. We used schizophrenia genome-wide association study data (N = 156,509) to construct polygenic risk scores (PRS) in 1005 individuals from 257 multiplex schizophrenia families, 2114 ancestry-matched sporadic cases, and 2205 population controls, to evaluate whether increased PRS can explain the higher recurrence risk of schizophrenia in multiplex families compared to ancestry-matched sporadic cases. Using mixed-effects logistic regression with family structure modeled as a random effect, we show that SCZ PRS in familial cases does not differ significantly from sporadic cases either with, or without family history (FH) of psychotic disorders (All sporadic cases p = 0.90, FH+ cases p = 0.88, FH- cases p = 0.82). These results indicate that increased burden of common schizophrenia risk variation as indexed by current SCZ PRS, is unlikely to account for the higher recurrence risk of schizophrenia in multiplex families. In the absence of elevated PRS, segregation of rare risk variation or environmental influences unique to the families may explain the increased familial recurrence risk. These findings also further validate a genetically influenced psychosis spectrum, as shown by a continuous increase of common SCZ risk variation burden from unaffected relatives to schizophrenia cases in multiplex families. Finally, these results suggest that common risk variation loading are unlikely to be predictive of schizophrenia recurrence risk in the families of index probands, and additional components of genetic risk must be identified and included in order to improve recurrence risk prediction.
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Affiliation(s)
- Mohammad Ahangari
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Integrative Life Sciences PhD Program, Virginia Commonwealth University, Richmond, VA USA
| | - Amanda E. Gentry
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA
| | | | - Tan-Hoang Nguyen
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA
| | - Robert Kirkpatrick
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA
| | - Brian C. Verrelli
- grid.224260.00000 0004 0458 8737Center for Biological Data Science, Virginia Commonwealth University, Richmond, VA USA
| | - Silviu-Alin Bacanu
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA
| | - Kenneth S. Kendler
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA USA
| | - Bradley T. Webb
- grid.505215.6GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI, Richmond, VA USA
| | - Brien P. Riley
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA USA
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