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Harvey PD, Bigdeli TB, Fanous AH, Li Y, Rajeevan N, Sayward F, Radhakrishnan K, Huang G, Aslan M. Cooperative Studies Program (CSP) #572: A Study of Serious Mental Illness in Veterans as a Pathway to personalized medicine in Schizophrenia and Bipolar Illness. PERSONALIZED MEDICINE IN PSYCHIATRY 2021; 27-28:10.1016/j.pmip.2021.100078. [PMID: 34222732 PMCID: PMC8247126 DOI: 10.1016/j.pmip.2021.100078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
BACKGROUND Personalization of psychiatric treatment includes treatment of symptoms, cognition and functional deficits, suicide, and medical co-morbidities. VA Collaborative Study 572 examined a large sample of male and female veterans with schizophrenia (n=3,942) and with bipolar disorder (n=5,414) with phenotyping and genomic analyses. We present the results to date and future directions. METHODS All veterans received a structured diagnostic interview and assessments of suicidal ideation and behavior, PTSD, and health. Veterans with schizophrenia were assessed for negative symptoms and lifetime depression. All were assessed with a cognitive and functional capacity assessment. Data for genome wide association studies were collected. Controls came from the VA Million Veteran Program. RESULTS Suicidal ideation or behavior was present in 66%. Cognitive and functional deficits were consistent with previous studies. 40% of the veterans with schizophrenia had a lifetime major depressive episode and PTSD was present in over 30%. Polygenic risk score (PRS) analyses indicated that cognitive and functional deficits overlapped with PRS for cognition, education, and intelligence in the general population and PRS for suicidal ideation and behavior correlated with previous PRS for depression and suicidal ideation and behavior, as did the PRS for PTSD. DISCUSSION Results to date provide directions for personalization of treatment in SMI, veterans with SMI, and veterans in general. The results of the genomic analyses suggest that cognitive deficits in SMI may be associated with general population features. Upcoming genomic analyses will reexamine the issues above, as well as genomic factors associated with smoking, substance abuse, negative symptoms, and treatment response.
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Affiliation(s)
- Philip D. Harvey
- Bruce W. Carter Miami Veterans Affairs (VA) Medical Center, Miami, FL
- University of Miami School of Medicine, Miami, FL
| | - Tim B. Bigdeli
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
| | - Ayman H. Fanous
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
| | - Yuli Li
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Nallakkandi Rajeevan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Frederick Sayward
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Yale University School of Medicine, New Haven, CT
| | - Krishnan Radhakrishnan
- Clinical Epidemiology Research Center (CERC), VA Connecticut Healthcare System, West Haven, CT
- Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration
- University of Kentucky School of Medicine, Lexington, KY
| | - Grant Huang
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Mihaela Aslan
- VA New York Harbor Healthcare System, Brooklyn, NY
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
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Mountford HS, Hill A, Barnett AL, Newbury DF. Genome-Wide Association Study of Motor Coordination. Front Hum Neurosci 2021; 15:669902. [PMID: 34177493 PMCID: PMC8219980 DOI: 10.3389/fnhum.2021.669902] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 05/10/2021] [Indexed: 11/13/2022] Open
Abstract
The ability to finely control our movement is key to achieving many of the educational milestones and life-skills we develop throughout our lives. Despite the centrality of coordination to early development, there is a vast gap in our understanding of the underlying biology. Like most complex traits, both genetics and environment influence motor coordination, however, the specific genes, early environmental risk factors and molecular pathways are unknown. Previous studies have shown that about 5% of school-age children experience unexplained difficulties with motor coordination. These children are said to have Developmental Coordination Disorder (DCD). For children with DCD, these motor coordination difficulties significantly impact their everyday life and learning. DCD is associated with poorer academic achievement, reduced quality of life, it can constrain career opportunities and increase the risk of mental health issues in adulthood. Despite the high prevalence of coordination difficulties, many children remain undiagnosed by healthcare professionals. Compounding under-diagnosis in the clinic, research into the etiology of DCD is severely underrepresented in the literature. Here we present the first genome-wide association study to examine the genetic basis of early motor coordination in the context of motor difficulties. Using data from the Avon Longitudinal Study of Parents and Children we generate a derived measure of motor coordination from four components of the Movement Assessment Battery for Children, providing an overall measure of coordination across the full range of ability. We perform the first genome-wide association analysis focused on motor coordination (N = 4542). No single nucleotide polymorphisms (SNPs) met the threshold for genome-wide significance, however, 59 SNPs showed suggestive associations. Three regions contained multiple suggestively associated SNPs, within five preliminary candidate genes: IQSEC1, LRCC1, SYNJ2B2, ADAM20, and ADAM21. Association to the gene IQSEC1 suggests a potential link to axon guidance and dendritic projection processes as a potential underlying mechanism of motor coordination difficulties. This represents an interesting potential mechanism, and whilst further validation is essential, it generates a direct window into the biology of motor coordination difficulties. This research has identified potential biological drivers of DCD, a first step towards understanding this common, yet neglected neurodevelopmental disorder.
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Affiliation(s)
- Hayley S. Mountford
- Department of Biological and Medical Sciences, Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, United Kingdom
| | - Amanda Hill
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Anna L. Barnett
- Centre for Psychological Research, Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, United Kingdom
| | - Dianne F. Newbury
- Department of Biological and Medical Sciences, Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, United Kingdom
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53
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Zhao B, Shan Y, Yang Y, Yu Z, Li T, Wang X, Luo T, Zhu Z, Sullivan P, Zhao H, Li Y, Zhu H. Transcriptome-wide association analysis of brain structures yields insights into pleiotropy with complex neuropsychiatric traits. Nat Commun 2021; 12:2878. [PMID: 34001886 PMCID: PMC8128893 DOI: 10.1038/s41467-021-23130-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Accepted: 04/16/2021] [Indexed: 02/03/2023] Open
Abstract
Structural variations of the human brain are heritable and highly polygenic traits, with hundreds of associated genes identified in recent genome-wide association studies (GWAS). Transcriptome-wide association studies (TWAS) can both prioritize these GWAS findings and also identify additional gene-trait associations. Here we perform cross-tissue TWAS analysis of 211 structural neuroimaging and discover 278 associated genes exceeding Bonferroni significance threshold of 1.04 × 10-8. The TWAS-significant genes for brain structures have been linked to a wide range of complex traits in different domains. Through TWAS gene-based polygenic risk scores (PRS) prediction, we find that TWAS PRS gains substantial power in association analysis compared to conventional variant-based GWAS PRS, and up to 6.97% of phenotypic variance (p-value = 7.56 × 10-31) can be explained in independent testing data sets. In conclusion, our study illustrates that TWAS can be a powerful supplement to traditional GWAS in imaging genetics studies for gene discovery-validation, genetic co-architecture analysis, and polygenic risk prediction.
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Affiliation(s)
- Bingxin Zhao
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yue Shan
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Yue Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Zhaolong Yu
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Tengfei Li
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Xifeng Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tianyou Luo
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ziliang Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Patrick Sullivan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Hongyu Zhao
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
- Department of Biostatistics, Yale University, New Haven, CT, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
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Tamman AJF, Wendt FR, Pathak GA, Krystal JH, Montalvo-Ortiz JL, Southwick SM, Sippel LM, Gelernter J, Polimanti R, Pietrzak RH. Attachment Style Moderates Polygenic Risk for Posttraumatic Stress in United States Military Veterans: Results From the National Health and Resilience in Veterans Study. Biol Psychiatry 2021; 89:878-887. [PMID: 33276944 DOI: 10.1016/j.biopsych.2020.09.018] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 09/15/2020] [Accepted: 09/15/2020] [Indexed: 12/21/2022]
Abstract
BACKGROUND A polygenic risk score (PRS) derived from genome-wide association studies of posttraumatic stress disorder (PTSD) may inform risk for this disorder. To date, however, no known study has examined whether social environmental factors such as attachment style may moderate the relation between PRS and PTSD. METHODS We evaluated main and interactive effects of PRS and attachment style on PTSD symptoms in a nationally representative sample of trauma-exposed European-American U.S. military veterans (N = 2030). PRS was derived from a genome-wide association study of PTSD re-experiencing symptoms (N = 146,660) in the Million Veteran Program cohort. Using one-sample Mendelian randomization with data from the UK Biobank (N = 115,099), we evaluated the effects of re-experiencing PRS and attachment style on PTSD symptoms. RESULTS Higher re-experiencing PRS and secure attachment style were independently associated with PTSD symptoms. A significant PRS-by-attachment style interaction was also observed (β = -.11, p = .006), with a positive association between re-experiencing PRS and PTSD symptoms observed only among veterans with an insecure attachment style. One-sample Mendelian randomization analyses suggested that the association between PTSD symptoms and attachment style is bidirectional. PRS enrichment analyses revealed a significant interaction between attachment style and a variant mapping to the IGSF11 gene (rs151177743, p = 2.1 × 10-7), which is implicated in regulating excitatory synaptic transmission and plasticity. CONCLUSIONS Attachment style may moderate polygenic risk for PTSD symptoms, and a novel locus implicated in synaptic transmission and plasticity may serve as a possible biological mediator of this association. These findings may help inform interpersonally oriented treatments for PTSD for individuals with high polygenic risk for this disorder.
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Affiliation(s)
| | - Frank R Wendt
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Gita A Pathak
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - John H Krystal
- Clinical Neurosciences Division, U.S. Department of Veterans Affairs National Center for PTSD, VA Connecticut Healthcare System, New Haven, Connecticut; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | | | - Steven M Southwick
- Clinical Neurosciences Division, U.S. Department of Veterans Affairs National Center for PTSD, VA Connecticut Healthcare System, New Haven, Connecticut; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Lauren M Sippel
- Executive Division, National Center for PTSD, White River Junction, Vermont; Geisel School of Medicine at Dartmouth, Hanover, New Hampshire
| | - Joel Gelernter
- Clinical Neurosciences Division, U.S. Department of Veterans Affairs National Center for PTSD, VA Connecticut Healthcare System, New Haven, Connecticut; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Renato Polimanti
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Robert H Pietrzak
- Clinical Neurosciences Division, U.S. Department of Veterans Affairs National Center for PTSD, VA Connecticut Healthcare System, New Haven, Connecticut; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
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55
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Identifying loci with different allele frequencies among cases of eight psychiatric disorders using CC-GWAS. Nat Genet 2021; 53:445-454. [PMID: 33686288 PMCID: PMC8038973 DOI: 10.1038/s41588-021-00787-1] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 01/14/2021] [Indexed: 01/31/2023]
Abstract
Psychiatric disorders are highly genetically correlated, but little research has been conducted on the genetic differences between disorders. We developed a new method (case-case genome-wide association study; CC-GWAS) to test for differences in allele frequency between cases of two disorders using summary statistics from the respective case-control GWAS, transcending current methods that require individual-level data. Simulations and analytical computations confirm that CC-GWAS is well powered with effective control of type I error. We applied CC-GWAS to publicly available summary statistics for schizophrenia, bipolar disorder, major depressive disorder and five other psychiatric disorders. CC-GWAS identified 196 independent case-case loci, including 72 CC-GWAS-specific loci that were not significant at the genome-wide level in the input case-control summary statistics; two of the CC-GWAS-specific loci implicate the genes KLF6 and KLF16 (from the Krüppel-like family of transcription factors), which have been linked to neurite outgrowth and axon regeneration. CC-GWAS loci replicated convincingly in applications to datasets with independent replication data.
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56
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Levchenko A, Kanapin A, Samsonova A, Fedorenko OY, Kornetova EG, Nurgaliev T, Mazo GE, Semke AV, Kibitov AO, Bokhan NA, Gainetdinov RR, Ivanova SA. A genome-wide association study identifies a gene network associated with paranoid schizophrenia and antipsychotics-induced tardive dyskinesia. Prog Neuropsychopharmacol Biol Psychiatry 2021; 105:110134. [PMID: 33065217 DOI: 10.1016/j.pnpbp.2020.110134] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 09/10/2020] [Accepted: 10/06/2020] [Indexed: 02/06/2023]
Abstract
In the present study we conducted a genome-wide association study (GWAS) in a cohort of 505 patients with paranoid schizophrenia (SCZ), of which 95 had tardive dyskinesia (TD), and 503 healthy controls. Using data generated by the PsychENCODE Consortium (PEC) and other bioinformatic databases, we revealed a gene network, implicated in neurodevelopment and brain function, associated with both these disorders. Almost all these genes are in gene or isoform co-expression PEC network modules important for the functioning of the brain; the activity of these networks is also altered in SCZ, bipolar disorder and autism spectrum disorders. The associated PEC network modules are enriched for gene ontology terms relevant to the brain development and function (CNS development, neuron development, axon ensheathment, synapse, synaptic vesicle cycle, and signaling receptor activity) and to the immune system (inflammatory response). Results of the present study suggest that orofacial and limbtruncal types of TD seem to share the molecular network with SCZ. Paranoid SCZ and abnormal involuntary movements that indicate the orofacial type of TD are associated with the same genomic loci on chromosomes 3p22.2, 8q21.13, and 13q14.2. The limbtruncal type of TD is associated with a locus on chromosome 3p13 where the best functional candidate is FOXP1, a high-confidence SCZ gene. The results of this study shed light on common pathogenic mechanisms for SCZ and TD, and indicate that the pathogenesis of the orofacial and limbtruncal types of TD might be driven by interacting genes implicated in neurodevelopment.
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Affiliation(s)
- Anastasia Levchenko
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, Saint Petersburg, Russia.
| | - Alexander Kanapin
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, Saint Petersburg, Russia
| | - Anastasia Samsonova
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, Saint Petersburg, Russia
| | - Olga Yu Fedorenko
- Mental Health Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia; National Research Tomsk Polytechnic University, Tomsk, Russia
| | - Elena G Kornetova
- Mental Health Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia; Siberian State Medical University, Tomsk, Russia
| | | | - Galina E Mazo
- Department of Endocrine Psychiatry, V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology, Saint Petersburg, Russia
| | - Arkadiy V Semke
- Mental Health Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia
| | - Alexander O Kibitov
- Department of Endocrine Psychiatry, V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology, Saint Petersburg, Russia; Laboratory of Molecular Genetics, Serbsky National Medical Research Center on Psychiatry and Addictions, Moscow, Russia
| | - Nikolay A Bokhan
- Mental Health Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia; Siberian State Medical University, Tomsk, Russia; National Research Tomsk State University, Tomsk, Russia
| | - Raul R Gainetdinov
- Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | - Svetlana A Ivanova
- Mental Health Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk, Russia; National Research Tomsk Polytechnic University, Tomsk, Russia; Siberian State Medical University, Tomsk, Russia
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57
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Belonogova NM, Zorkoltseva IV, Tsepilov YA, Axenovich TI. Gene-based association analysis identifies 190 genes affecting neuroticism. Sci Rep 2021; 11:2484. [PMID: 33510330 PMCID: PMC7844228 DOI: 10.1038/s41598-021-82123-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Accepted: 01/15/2021] [Indexed: 11/25/2022] Open
Abstract
Neuroticism is a personality trait, which is an important risk factor for psychiatric disorders. Recent genome-wide studies reported about 600 genes potentially influencing neuroticism. Little is known about the mechanisms of their action. Here, we aimed to conduct a more detailed analysis of genes that can regulate the level of neuroticism. Using UK Biobank-based GWAS summary statistics, we performed a gene-based association analysis using four sets of within-gene variants, each set possessing specific protein-coding properties. To guard against the influence of strong GWAS signals outside the gene, we used a specially designed procedure called “polygene pruning”. As a result, we identified 190 genes associated with neuroticism due to the effect of within-gene variants rather than strong GWAS signals outside the gene. Thirty eight of these genes are new. Within all genes identified, we distinguished two slightly overlapping groups obtained from using protein-coding and non-coding variants. Many genes in the former group included potentially pathogenic variants. For some genes in the latter group, we found evidence of pleiotropy with gene expression. Using a bioinformatics analysis, we prioritized the neuroticism genes and showed that the genes that contribute to neuroticism through their within-gene variants are the most appropriate candidate genes.
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Affiliation(s)
- Nadezhda M Belonogova
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Irina V Zorkoltseva
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Yakov A Tsepilov
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia.,Department of Natural Sciences, Novosibirsk State University, Novosibirsk, Russia
| | - Tatiana I Axenovich
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia. .,Department of Natural Sciences, Novosibirsk State University, Novosibirsk, Russia.
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58
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Integrative analysis of genome-wide association studies identifies novel loci associated with neuropsychiatric disorders. Transl Psychiatry 2021; 11:69. [PMID: 33479212 PMCID: PMC7820351 DOI: 10.1038/s41398-020-01195-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 12/10/2020] [Accepted: 12/11/2020] [Indexed: 01/30/2023] Open
Abstract
Neuropsychiatric disorders, such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), schizophrenia (SCZ), bipolar disorder (BIP), and major depressive disorder (MDD) share common clinical presentations, suggesting etiologic overlap. A substantial proportion of SNP-based heritability for neuropsychiatric disorders is attributable to genetic components, and genome-wide association studies (GWASs) focusing on individual diseases have identified multiple genetic loci shared between these diseases. Here, we aimed at identifying novel genetic loci associated with individual neuropsychiatric diseases and genetic loci shared by neuropsychiatric diseases. We performed multi-trait joint analyses and meta-analysis across five neuropsychiatric disorders based on their summary statistics from the Psychiatric Genomics Consortium (PGC), and further carried out a replication study of ADHD among 2726 cases and 16299 controls in an independent pediatric cohort. In the multi-trait joint analyses, we found five novel genome-wide significant loci for ADHD, one novel locus for BIP, and ten novel loci for MDD. We further achieved modest replication in our independent pediatric dataset. We conducted fine-mapping and functional annotation through an integrative multi-omics approach and identified causal variants and potential target genes at each novel locus. Gene expression profile and gene-set enrichment analysis further suggested early developmental stage expression pattern and postsynaptic membrane compartment enrichment of candidate genes at the genome-wide significant loci of these neuropsychiatric disorders. Therefore, through a multi-omics approach, we identified novel genetic loci associated with the five neuropsychiatric disorders which may help to better understand the underlying molecular mechanism of neuropsychiatric diseases.
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Chen J, Teng D, Wu Z, Li W, Feng Y, Tang Y, Liu G. Insights into the Molecular Mechanisms of Liuwei Dihuang Decoction via Network Pharmacology. Chem Res Toxicol 2020; 34:91-102. [PMID: 33332098 DOI: 10.1021/acs.chemrestox.0c00359] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
The traditional Chinese medicines (TCMs) have been used to treat diseases over a long history, but it is still a great challenge to uncover the underlying mechanisms for their therapeutic effects due to the complexity of their ingredients. Based on a novel network pharmacology-based approach, we explored in this study the potential therapeutic targets of Liuwei Dihuang (LWDH) decoction in its neuroendocrine immunomodulation (NIM) function. We not only collected the known targets of the compounds in LWDH but also predicted the targets for these compounds using the balanced substructure-drug-target network-based inference (bSDTNBI), which is a target prediction method based on network inferring developed by our laboratory. A "target-(pathway)-target" (TPT) network, in which targets of LWDH were connected by relevant pathways, was constructed and divided into several separate modules with strong internal connections. Then the target module that contributes the most to NIM function was determined through a contribution scoring algorithm. Finally, the targets with the highest contribution score to NIM-related diseases in this target module were recommended as potential therapeutic targets of LWDH.
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Affiliation(s)
- Jianhui Chen
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
| | - Dan Teng
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
| | - Zengrui Wu
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
| | - Weihua Li
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
| | - Yuqian Feng
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
| | - Yun Tang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
| | - Guixia Liu
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China
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60
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Bigdeli TB, Fanous AH, Li Y, Rajeevan N, Sayward F, Genovese G, Gupta R, Radhakrishnan K, Malhotra AK, Sun N, Lu Q, Hu Y, Li B, Chen Q, Mane S, Miller P, Cheung KH, Gur RE, Greenwood TA, Braff DL, Achtyes ED, Buckley PF, Escamilla MA, Lehrer D, Malaspina DP, McCarroll SA, Rapaport MH, Vawter MP, Pato MT, Pato CN, Zhao H, Kosten TR, Brophy M, Pyarajan S, Shi Y, O’Leary TJ, Gleason T, Przygodzki R, Muralidhar S, Gaziano JM, Huang GD, Concato J, Siever LJ, Aslan M, Harvey PD. Genome-Wide Association Studies of Schizophrenia and Bipolar Disorder in a Diverse Cohort of US Veterans. Schizophr Bull 2020; 47:517-529. [PMID: 33169155 PMCID: PMC7965063 DOI: 10.1093/schbul/sbaa133] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Schizophrenia (SCZ) and bipolar disorder (BIP) are debilitating neuropsychiatric disorders, collectively affecting 2% of the world's population. Recognizing the major impact of these psychiatric disorders on the psychosocial function of more than 200 000 US Veterans, the Department of Veterans Affairs (VA) recently completed genotyping of more than 8000 veterans with SCZ and BIP in the Cooperative Studies Program (CSP) #572. METHODS We performed genome-wide association studies (GWAS) in CSP #572 and benchmarked the predictive value of polygenic risk scores (PRS) constructed from published findings. We combined our results with available summary statistics from several recent GWAS, realizing the largest and most diverse studies of these disorders to date. RESULTS Our primary GWAS uncovered new associations between CHD7 variants and SCZ, and novel BIP associations with variants in Sortilin Related VPS10 Domain Containing Receptor 3 (SORCS3) and downstream of PCDH11X. Combining our results with published summary statistics for SCZ yielded 39 novel susceptibility loci including CRHR1, and we identified 10 additional findings for BIP (28 326 cases and 90 570 controls). PRS trained on published GWAS were significantly associated with case-control status among European American (P < 10-30) and African American (P < .0005) participants in CSP #572. CONCLUSIONS We have demonstrated that published findings for SCZ and BIP are robustly generalizable to a diverse cohort of US veterans. Leveraging available summary statistics from GWAS of global populations, we report 52 new susceptibility loci and improved fine-mapping resolution for dozens of previously reported associations.
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Affiliation(s)
- Tim B Bigdeli
- VA New York Harbor Healthcare System, Brooklyn, NY,Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
| | - Ayman H Fanous
- VA New York Harbor Healthcare System, Brooklyn, NY,Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
| | - Yuli Li
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Nallakkandi Rajeevan
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Frederick Sayward
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Giulio Genovese
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA,Department of Genetics, Harvard Medical School, Boston, MA
| | - Rishab Gupta
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
| | - Krishnan Radhakrishnan
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,College of Medicine, University of Kentucky, Lexington, KY
| | - Anil K Malhotra
- Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY,Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY,Department of Psychiatry, Hofstra Northwell School of Medicine, Hempstead, NY
| | - Ning Sun
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Qiongshi Lu
- Department of Medicine, Yale School of Medicine, New Haven, CT,Department of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, WI
| | - Yiming Hu
- Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Boyang Li
- Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Quan Chen
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Shrikant Mane
- Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Perry Miller
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Kei-Hoi Cheung
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Raquel E Gur
- Departments of Psychiatry and Child & Adolescent Psychiatry and Lifespan Brain Institute, University of Pennsylvania Perelman School of Medicine and Children’s Hospital of Philadelphia, Philadelphia, PA
| | | | - David L Braff
- Department of Psychiatry, University of California, La Jolla, San Diego, CA,VISN-22 Mental Illness, Research, Education and Clinical Center (MIRECC), VA San Diego Healthcare System, San Diego, CA
| | | | - Eric D Achtyes
- Cherry Health and Michigan State University College of Human Medicine, Grand Rapids, MI
| | - Peter F Buckley
- School of Medicine, Virginia Commonwealth University, Richmond, VA
| | - Michael A Escamilla
- Department of Psychiatry, School of Medicine, University of Texas Rio Grande Valley, Harlingen, TX
| | - Douglas Lehrer
- Department of Psychiatry, Wright State University, Dayton, OH
| | - Dolores P Malaspina
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Steven A McCarroll
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA,Department of Genetics, Harvard Medical School, Boston, MA
| | - Mark H Rapaport
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA
| | - Marquis P Vawter
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA
| | - Michele T Pato
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
| | - Carlos N Pato
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Medical Center, Brooklyn, NY
| | | | - Hongyu Zhao
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Thomas R Kosten
- Departments of Psychiatry, Neuroscience, Pharmacology, and Immunology and Rheumatology, Baylor College of Medicine, Houston, TX
| | - Mary Brophy
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain, MA,Section of Hematology and Medical Oncology, Boston University School of Medicine, Boston, MA
| | - Saiju Pyarajan
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain, MA
| | - Yunling Shi
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain, MA
| | - Timothy J O’Leary
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Theresa Gleason
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Ronald Przygodzki
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - Sumitra Muralidhar
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - J Michael Gaziano
- Massachusetts Area Veterans Epidemiology, Research, and Information Center (MAVERIC), Jamaica Plain, MA,Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | | | - Grant D Huang
- Office of Research and Development, Veterans Health Administration, Washington, DC
| | - John Concato
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Larry J Siever
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY,University of Miami Miller School of Medicine, James J. Peters Veterans Affairs Medical Center, Bronx, NY
| | - Mihaela Aslan
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT,Department of Medicine, Yale School of Medicine, New Haven, CT
| | - Philip D Harvey
- Research Service Bruce W. Carter VA Medical Center, Miami, FL,Department of Psychiatry, University of Miami Miller School of Medicine, Miami, FL,To whom correspondence should be addressed; Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, 1120 NW 14th Street, Suite 1450 Miami, FL 33136, USA; tel: (305)-243-4094, fax: (305)-243-1619, e-mail:
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61
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McMartin A, Conley D. Commentary: Mendelian randomization and education–Challenges remain. Int J Epidemiol 2020; 49:1193-1206. [DOI: 10.1093/ije/dyaa160] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/28/2020] [Indexed: 02/07/2023] Open
Affiliation(s)
- Andrew McMartin
- Department of Sociology and Office of Population Research, Wallace Hall, Princeton University, Princeton, NJ 08540, USA
| | - Dalton Conley
- Department of Sociology and Office of Population Research, Wallace Hall, Princeton University, Princeton, NJ 08540, USA
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62
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Kostović I. The enigmatic fetal subplate compartment forms an early tangential cortical nexus and provides the framework for construction of cortical connectivity. Prog Neurobiol 2020; 194:101883. [PMID: 32659318 DOI: 10.1016/j.pneurobio.2020.101883] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Revised: 06/05/2020] [Accepted: 07/06/2020] [Indexed: 12/19/2022]
Abstract
The most prominent transient compartment of the primate fetal cortex is the deep, cell-sparse, synapse-containing subplate compartment (SPC). The developmental role of the SPC and its extraordinary size in humans remain enigmatic. This paper evaluates evidence on the development and connectivity of the SPC and discusses its role in the pathogenesis of neurodevelopmental disorders. A synthesis of data shows that the subplate becomes a prominent compartment by its expansion from the deep cortical plate (CP), appearing well-delineated on MR scans and forming a tangential nexus across the hemisphere, consisting of an extracellular matrix, randomly distributed postmigratory neurons, multiple branches of thalamic and long corticocortical axons. The SPC generates early spontaneous non-synaptic and synaptic activity and mediates cortical response upon thalamic stimulation. The subplate nexus provides large-scale interareal connectivity possibly underlying fMR resting-state activity, before corticocortical pathways are established. In late fetal phase, when synapses appear within the CP, transient the SPC coexists with permanent circuitry. The histogenetic role of the SPC is to provide interactive milieu and capacity for guidance, sorting, "waiting" and target selection of thalamocortical and corticocortical pathways. The new evolutionary role of the SPC and its remnant white matter neurons is linked to the increasing number of associative pathways in the human neocortex. These roles attributed to the SPC are regulated using a spatiotemporal gene expression during critical periods, when pathogenic factors may disturb vulnerable circuitry of the SPC, causing neurodevelopmental cognitive circuitry disorders.
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Affiliation(s)
- Ivica Kostović
- Croatian Institute for Brain Research, School of Medicine, University of Zagreb, Scientific Centre of Excellence for Basic, Clinical and Translational Neuroscience, Salata 12, 10000 Zagreb, Croatia.
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63
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Abstract
Epilepsy encompasses a group of heterogeneous brain diseases that affect more than 50 million people worldwide. Epilepsy may have discernible structural, infectious, metabolic, and immune etiologies; however, in most people with epilepsy, no obvious cause is identifiable. Based initially on family studies and later on advances in gene sequencing technologies and computational approaches, as well as the establishment of large collaborative initiatives, we now know that genetics plays a much greater role in epilepsy than was previously appreciated. Here, we review the progress in the field of epilepsy genetics and highlight molecular discoveries in the most important epilepsy groups, including those that have been long considered to have a nongenetic cause. We discuss where the field of epilepsy genetics is moving as it enters a new era in which the genetic architecture of common epilepsies is starting to be unraveled.
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Affiliation(s)
- Piero Perucca
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria 3000, Australia.,Departments of Medicine and Neurology, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Victoria 3050, Australia.,Department of Neurology, Alfred Health, Melbourne, Victoria 3000, Australia
| | - Melanie Bahlo
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria 3052, Australia.,Department of Medical Biology, The University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Samuel F Berkovic
- Epilepsy Research Centre, Department of Medicine, Austin Health, The University of Melbourne, Melbourne, Victoria 3084, Australia;
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64
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Mallet J, Le Strat Y, Dubertret C, Gorwood P. Polygenic Risk Scores Shed Light on the Relationship between Schizophrenia and Cognitive Functioning: Review and Meta-Analysis. J Clin Med 2020; 9:E341. [PMID: 31991840 PMCID: PMC7074036 DOI: 10.3390/jcm9020341] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Revised: 01/14/2020] [Accepted: 01/23/2020] [Indexed: 12/26/2022] Open
Abstract
Schizophrenia is a multifactorial disease associated with widespread cognitive impairment. Although cognitive deficits are one of the factors most strongly associated with functional impairment in schizophrenia (SZ), current treatment strategies hardly tackle these impairments. To develop more efficient treatment strategies in patients, a better understanding of their pathogenesis is needed. Recent progress in genetics, driven by large genome-wide association studies (GWAS) and the use of polygenic risk scores (PRS), has provided new insights about the genetic architecture of complex human traits, including cognition and SZ. Here, we review the recent findings examining the genetic links between SZ and cognitive functions in population-based samples as well as in participants with SZ. The performed meta-analysis showed a negative correlation between the polygenetic risk score of schizophrenia and global cognition (p < 0.001) when the samples rely on general and healthy participants, while no significant correlation was detected when the three studies devoted to schizophrenia patients were meta-analysed (p > 0.05). Our review and meta-analysis therefore argues against universal pleiotropy for schizophrenia alleles and cognition, since cognition in SZ patients would be underpinned by the same genetic factors than in the general population, and substantially independent of common variant liability to the disorder.
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Affiliation(s)
- Jasmina Mallet
- APHP; Department of Psychiatry, Universitary Hospital Louis Mourier, 92700 Colombes, France; (Y.L.S.); (C.D.)
- Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, F-75014 Paris, France
| | - Yann Le Strat
- APHP; Department of Psychiatry, Universitary Hospital Louis Mourier, 92700 Colombes, France; (Y.L.S.); (C.D.)
- Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, F-75014 Paris, France
| | - Caroline Dubertret
- APHP; Department of Psychiatry, Universitary Hospital Louis Mourier, 92700 Colombes, France; (Y.L.S.); (C.D.)
- Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, F-75014 Paris, France
| | - Philip Gorwood
- Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, F-75014 Paris, France
- GHU Paris Psychiatrie et Neurosciences, Hôpital Sainte Anne, F-75014 Paris, France
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65
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Hill WD, Davies NM, Ritchie SJ, Skene NG, Bryois J, Bell S, Di Angelantonio E, Roberts DJ, Xueyi S, Davies G, Liewald DCM, Porteous DJ, Hayward C, Butterworth AS, McIntosh AM, Gale CR, Deary IJ. Genome-wide analysis identifies molecular systems and 149 genetic loci associated with income. Nat Commun 2019; 10:5741. [PMID: 31844048 PMCID: PMC6915786 DOI: 10.1038/s41467-019-13585-5] [Citation(s) in RCA: 90] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Accepted: 11/11/2019] [Indexed: 01/01/2023] Open
Abstract
Socioeconomic position (SEP) is a multi-dimensional construct reflecting (and influencing) multiple socio-cultural, physical, and environmental factors. In a sample of 286,301 participants from UK Biobank, we identify 30 (29 previously unreported) independent-loci associated with income. Using a method to meta-analyze data from genetically-correlated traits, we identify an additional 120 income-associated loci. These loci show clear evidence of functionality, with transcriptional differences identified across multiple cortical tissues, and links to GABAergic and serotonergic neurotransmission. By combining our genome wide association study on income with data from eQTL studies and chromatin interactions, 24 genes are prioritized for follow up, 18 of which were previously associated with intelligence. We identify intelligence as one of the likely causal, partly-heritable phenotypes that might bridge the gap between molecular genetic inheritance and phenotypic consequence in terms of income differences. These results indicate that, in modern era Great Britain, genetic effects contribute towards some of the observed socioeconomic inequalities.
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Affiliation(s)
- W David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.
| | - Neil M Davies
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
- Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Stuart J Ritchie
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
| | - Nathan G Skene
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
- UCL Institute of Neurology, Queen Square, London, UK
- Department of Medicine, Division of Brain Sciences, Imperial College, London, UK
| | - Julien Bryois
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Steven Bell
- The National Institute for Health Research Blood and Transplant Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK
- UK Medical Research Council/British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK
- British Heart Foundation Centre of Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Hills Road, Cambridge, CB2 0QQ, UK
| | - Emanuele Di Angelantonio
- The National Institute for Health Research Blood and Transplant Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK
- UK Medical Research Council/British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK
- British Heart Foundation Centre of Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Hills Road, Cambridge, CB2 0QQ, UK
- NHS Blood and Transplant, Cambridge, UK
| | - David J Roberts
- Cambridge Substantive Site, Health Data Research UK, Wellcome Genome Campus, Hinxton, UK
- BRC Haematology Theme and Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- NHS Blood and Transplant - Oxford Centre, Oxford, UK
| | - Shen Xueyi
- Division of Psychiatry, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Gail Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - David C M Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - David J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Adam S Butterworth
- The National Institute for Health Research Blood and Transplant Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK
- UK Medical Research Council/British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK
- British Heart Foundation Centre of Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Hills Road, Cambridge, CB2 0QQ, UK
| | - Andrew M McIntosh
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Division of Psychiatry, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Catharine R Gale
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, SO16 6YD, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
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66
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Hill WD, Davies NM, Ritchie SJ, Skene NG, Bryois J, Bell S, Di Angelantonio E, Roberts DJ, Xueyi S, Davies G, Liewald DCM, Porteous DJ, Hayward C, Butterworth AS, McIntosh AM, Gale CR, Deary IJ. Genome-wide analysis identifies molecular systems and 149 genetic loci associated with income. Nat Commun 2019; 10:5741. [PMID: 31844048 DOI: 10.1101/573691] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Accepted: 11/11/2019] [Indexed: 05/25/2023] Open
Abstract
Socioeconomic position (SEP) is a multi-dimensional construct reflecting (and influencing) multiple socio-cultural, physical, and environmental factors. In a sample of 286,301 participants from UK Biobank, we identify 30 (29 previously unreported) independent-loci associated with income. Using a method to meta-analyze data from genetically-correlated traits, we identify an additional 120 income-associated loci. These loci show clear evidence of functionality, with transcriptional differences identified across multiple cortical tissues, and links to GABAergic and serotonergic neurotransmission. By combining our genome wide association study on income with data from eQTL studies and chromatin interactions, 24 genes are prioritized for follow up, 18 of which were previously associated with intelligence. We identify intelligence as one of the likely causal, partly-heritable phenotypes that might bridge the gap between molecular genetic inheritance and phenotypic consequence in terms of income differences. These results indicate that, in modern era Great Britain, genetic effects contribute towards some of the observed socioeconomic inequalities.
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Affiliation(s)
- W David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.
| | - Neil M Davies
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2BN, UK
- Bristol Medical School, University of Bristol, Bristol, BS8 2BN, UK
| | - Stuart J Ritchie
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
| | - Nathan G Skene
- Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
- UCL Institute of Neurology, Queen Square, London, UK
- Department of Medicine, Division of Brain Sciences, Imperial College, London, UK
| | - Julien Bryois
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Steven Bell
- The National Institute for Health Research Blood and Transplant Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK
- UK Medical Research Council/British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK
- British Heart Foundation Centre of Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Hills Road, Cambridge, CB2 0QQ, UK
| | - Emanuele Di Angelantonio
- The National Institute for Health Research Blood and Transplant Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK
- UK Medical Research Council/British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK
- British Heart Foundation Centre of Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Hills Road, Cambridge, CB2 0QQ, UK
- NHS Blood and Transplant, Cambridge, UK
| | - David J Roberts
- Cambridge Substantive Site, Health Data Research UK, Wellcome Genome Campus, Hinxton, UK
- BRC Haematology Theme and Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- NHS Blood and Transplant - Oxford Centre, Oxford, UK
| | - Shen Xueyi
- Division of Psychiatry, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Gail Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - David C M Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - David J Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Adam S Butterworth
- The National Institute for Health Research Blood and Transplant Unit in Donor Health and Genomics at the University of Cambridge, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK
- UK Medical Research Council/British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Wort's Causeway, Cambridge, CB1 8RN, UK
- British Heart Foundation Centre of Excellence, Division of Cardiovascular Medicine, Addenbrooke's Hospital, Hills Road, Cambridge, CB2 0QQ, UK
| | - Andrew M McIntosh
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Division of Psychiatry, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Catharine R Gale
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, SO16 6YD, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
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67
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Comes AL, Senner F, Budde M, Adorjan K, Anderson-Schmidt H, Andlauer TFM, Gade K, Hake M, Heilbronner U, Kalman JL, Reich-Erkelenz D, Klöhn-Saghatolislam F, Schaupp SK, Schulte EC, Juckel G, Dannlowski U, Schmauß M, Zimmermann J, Reimer J, Reininghaus E, Anghelescu IG, Arolt V, Baune BT, Konrad C, Thiel A, Fallgatter AJ, Nieratschker V, Figge C, von Hagen M, Koller M, Becker T, Wigand ME, Jäger M, Dietrich DE, Stierl S, Scherk H, Spitzer C, Folkerts H, Witt SH, Degenhardt F, Forstner AJ, Rietschel M, Nöthen MM, Wiltfang J, Falkai P, Schulze TG, Papiol S. The genetic relationship between educational attainment and cognitive performance in major psychiatric disorders. Transl Psychiatry 2019; 9:210. [PMID: 31462630 PMCID: PMC6713703 DOI: 10.1038/s41398-019-0547-x] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 06/03/2019] [Accepted: 07/17/2019] [Indexed: 11/13/2022] Open
Abstract
Cognitive deficits are a core feature of psychiatric disorders like schizophrenia and bipolar disorder. Evidence supports a genome-wide polygenic score (GPS) for educational attainment (GPSEDU) can be used to explain variability in cognitive performance. We aimed to identify different cognitive domains associated with GPSEDU in a transdiagnostic clinical cohort of chronic psychiatric patients with known cognitive deficits. Bipolar and schizophrenia patients from the PsyCourse cohort (N = 730; 43% female) were used. Likewise, we tested whether GPSs for schizophrenia (GPSSZ) and bipolar disorder (GPSBD) were associated with cognitive outcomes. GPSEDU explained 1.5% of variance in the backward verbal digit span, 1.9% in the number of correctly recalled words of the Verbal Learning and Memory Test, and 1.1% in crystallized intelligence. These effects were robust to the influences of treatment and diagnosis. No significant associations between GPSSZ or GPSBD with cognitive outcomes were found. Furthermore, these risk scores did not confound the effect of GPSEDU on cognitive outcomes. GPSEDU explains a small fraction of cognitive performance in adults with psychiatric disorders, specifically for domains related to linguistic learning and working memory. Investigating such a proxy-phenotype longitudinally, could give intriguing insight into the disease course, highlighting at what time genes play a more influential role on cognitive performance. Better understanding the origin of these deficits might help identify those patients at risk for lower levels of functioning and poor social outcomes. Polygenic estimates may in the future be part of predictive models for more personalized interventions.
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Affiliation(s)
- Ashley L Comes
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany.
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, 80804, Germany.
| | - Fanny Senner
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Monika Budde
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Kristina Adorjan
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Heike Anderson-Schmidt
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, 37075, Germany
| | - Till F M Andlauer
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, 81675, Germany
| | - Katrin Gade
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, 37075, Germany
| | - Maria Hake
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Urs Heilbronner
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Janos L Kalman
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, 80804, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Daniela Reich-Erkelenz
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Farah Klöhn-Saghatolislam
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Sabrina K Schaupp
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Eva C Schulte
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Georg Juckel
- Department of Psychiatry, Ruhr University Bochum, LWL University Hospital, Bochum, 44791, Germany
| | - Udo Dannlowski
- Department of Psychiatry, University of Münster, Münster, 48149, Germany
| | - Max Schmauß
- Department of Psychiatry and Psychotherapy, Bezirkskrankenhaus Augsburg, Augsburg, 86156, Germany
| | - Jörg Zimmermann
- Psychiatrieverbund Oldenburger Land gGmbH, Karl-Jaspers-Klinik, Bad Zwischenahn, 26160, Germany
| | - Jens Reimer
- Department of Psychiatry and Psychotherapy, University Medical Centre Hamburg-Eppendorf, Martinistr. 52, Hamburg, 20246, Germany
| | - Eva Reininghaus
- Department of Psychiatry and Psychotherapeutic Medicine, Research Unit for Bipolar Affective Disorder, Medical University of Graz, Graz, 8036, Austria
| | | | - Volker Arolt
- Department of Psychiatry, University of Münster, Münster, 48149, Germany
| | - Bernhard T Baune
- Department of Psychiatry, University of Münster, Münster, 48149, Germany
- Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Carsten Konrad
- Department of Psychiatry and Psychotherapy, Agaplesion Diakonieklinikum, Rotenburg, 27356, Germany
| | - Andreas Thiel
- Department of Psychiatry and Psychotherapy, Agaplesion Diakonieklinikum, Rotenburg, 27356, Germany
| | - Andreas J Fallgatter
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, 72076, Germany
| | - Vanessa Nieratschker
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, 72076, Germany
| | - Christian Figge
- Karl-Jaspers Clinic, European Medical School Oldenburg-Groningen, Oldenburg, 26160, Germany
| | - Martin von Hagen
- Clinic for Psychiatry and Psychotherapy, Clinical Center Werra-Meißner, Eschwege, 37269, Germany
| | - Manfred Koller
- Asklepios Specialized Hospital, Göttingen, 37081, Germany
| | - Thomas Becker
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, 89312, Germany
| | - Moritz E Wigand
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, 89312, Germany
| | - Markus Jäger
- Department of Psychiatry II, Ulm University, Bezirkskrankenhaus Günzburg, Günzburg, 89312, Germany
| | - Detlef E Dietrich
- AMEOS Clinical Center Hildesheim, Hildesheim, 31135, Germany
- Center für Systems Neuroscience (ZSN) Hannover, Hannover, 30559, Germany
- Dept. of Psychiatry, Medical School of Hannover, Hannover, 30625, Germany
| | | | - Harald Scherk
- AMEOS Clinical Center Osnabrück, Osnabrück, 49088, Germany
| | - Carsten Spitzer
- ASKLEPIOS Specialized Hospital Tiefenbrunn, Rosdorf, 37124, Germany
- Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, 18051, Germany
| | - Here Folkerts
- Department of Psychiatry, Psychotherapy and Psychosomatics, Clinical Center Wilhelmshaven, Wilhelmshaven, 26389, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, 68159, Germany
| | - Franziska Degenhardt
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, 53127, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, 53127, Germany
- Center for Human Genetics, University of Marburg, Marburg, 35033, Germany
- Department of Biomedicine, University of Basel, Basel, 4031, Switzerland
- Department of Psychiatry (UPK), University of Basel, Basel, 4002, Switzerland
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, 68159, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, 53127, Germany
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, 37075, Germany
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, 37075, Germany
- iBiMED, Medical Sciences Department, University of Aveiro, Aveiro, 3810-193, Portugal
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Thomas G Schulze
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Sergi Papiol
- Institute of Psychiatric Phenomics and Genomics, University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
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