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Su YY, D'Arcy C, Li M, O'Donnell KJ, Caron J, Meaney MJ, Meng X. Specific and cumulative lifetime stressors in the aetiology of major depression: A longitudinal community-based population study. Epidemiol Psychiatr Sci 2022; 31:e3. [PMID: 35078547 PMCID: PMC8851045 DOI: 10.1017/s2045796021000779] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 10/12/2021] [Accepted: 12/04/2021] [Indexed: 01/25/2023] Open
Abstract
AIMS Early-life stressful circumstances (i.e. childhood maltreatment) coupled with stressful events later in life increase the likelihood of subsequent depression. However, very few studies have been conducted to examine the specific and cumulative effects of these stressors in the development of depression. There is also a paucity of research that simultaneously considers the role of biological factors combined with psychosocial stressors in the aetiology of depression. Guided by the biopsychosocial model proposed by Engel, the present study aims to examine to what extent the experience of stressors across the lifespan is associated with depression while taking into account the role of genetic predispositions. METHODS Data analysed were from the Social and Psychiatric Epidemiology Catchment Area of the Southwest of Montreal (ZEPSOM), a large-scale, longitudinal community-based cohort study. A total of 1351 participants with complete information on the lifetime diagnoses of depression over a 10-year follow-up period were included in the study. Stressful events across the lifespan were operationalised as specific, cumulative and latent profiles of stressful experiences. Latent profile analysis (LPA) was used to explore the clustering of studied stressors including childhood maltreatment, poor parent-child relationship, and stressful life events. A polygenetic risk score was calculated for each participant to provide information on genetic liability. Multivariate logistic regression was used to examine the association between specific, cumulative and latent profiles of stressors and subsequent depression. RESULTS We found that different subtypes of childhood maltreatment, child-parent bonding and stressful life events predicted subsequent depression. Furthermore, a significant association between combined effects of cumulative stressful experiences and depression was found [odds ratio (OR) = 1.20, 95% confidence interval (CI): 1.12-1.28]. Three latent profiles of lifetime stressors were identified in the present study and named as 'low-level of stress' (75.1%), 'moderate-level of stress' (6.8%) and 'high-level of stress' (18.1%). Individuals with a 'high-level of stress' had a substantially higher risk of depression (OR = 1.80, 95% CI: 1.08-3.00) than the other two profiles after adjusting for genetic predispositions, socio-demographic characteristics, and health-related factors. CONCLUSIONS While controlling for genetic predispositions, the present study provides robust evidence to support the independent and cumulative as well as compositional effects of early- and later-on lifetime psychosocial stressors in the subsequent development of depression. Consequently, mental illness prevention and mental health promotion should target the occurrence of stressful events as well as build resilience in people so they can better cope with stress when it inevitably occurs.
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Affiliation(s)
- Y. Y. Su
- School of Public Health, University of Saskatchewan, Saskatoon, SK, Canada
- Department of Psychiatry, College of Medicine, University of Saskatchewan, Saskatoon, SK, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Research Centre, Montreal, QC, Canada
| | - C. D'Arcy
- School of Public Health, University of Saskatchewan, Saskatoon, SK, Canada
- Department of Psychiatry, College of Medicine, University of Saskatchewan, Saskatoon, SK, Canada
| | - M. Li
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Research Centre, Montreal, QC, Canada
| | - K. J. O'Donnell
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Research Centre, Montreal, QC, Canada
- Yale Child Study Center & Department of Obstetrics Gynecology & Reproductive Sciences, Yale School of Medicine, Yale University, New Haven, CT, USA
- Child & Brain Development Program, CIFAR, Toronto, ON, Canada
| | - J. Caron
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Research Centre, Montreal, QC, Canada
| | - M. J. Meaney
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Research Centre, Montreal, QC, Canada
| | - X. Meng
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Research Centre, Montreal, QC, Canada
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Ocklenburg S, Metzen D, Schlüter C, Fraenz C, Arning L, Streit F, Güntürkün O, Kumsta R, Genç E. Polygenic scores for handedness and their association with asymmetries in brain structure. Brain Struct Funct 2021; 227:515-527. [PMID: 34235564 PMCID: PMC8844179 DOI: 10.1007/s00429-021-02335-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 07/01/2021] [Indexed: 11/28/2022]
Abstract
Handedness is the most widely investigated motor preference in humans. The genetics of handedness and especially the link between genetic variation, brain structure, and right-left preference have not been investigated in detail. Recently, several well-powered genome-wide association studies (GWAS) on handedness have been published, significantly advancing the understanding of the genetic determinants of left and right-handedness. In the present study, we estimated polygenic scores (PGS) of handedness-based on the GWAS by de Kovel and Francks (Sci Rep 9: 5986, 2019) in an independent validation cohort (n = 296). PGS reflect the sum effect of trait-associated alleles across many genetic loci. For the first time, we could show that these GWAS-based PGS are significantly associated with individual handedness lateralization quotients in an independent validation cohort. Additionally, we investigated whether handedness-derived polygenic scores are associated with asymmetries in gray matter macrostructure across the whole brain determined using magnetic resonance imaging. None of these associations reached significance after correction for multiple comparisons. Our results implicate that PGS obtained from large-scale handedness GWAS are significantly associated with individual handedness in smaller validation samples with more detailed phenotypic assessment.
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Affiliation(s)
- Sebastian Ocklenburg
- Department of Biopsychology, Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany.
| | - Dorothea Metzen
- Department of Biopsychology, Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Caroline Schlüter
- Department of Biopsychology, Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Christoph Fraenz
- Leibniz Research Centre for Working Environment and Human Factors (IfADo), Department of Psychology and Neurosciences, Dortmund, Germany
| | - Larissa Arning
- Department of Human Genetics, Faculty of Medicine, Ruhr University Bochum, Bochum, Germany
| | - Fabian Streit
- Medical Faculty Mannheim, Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Onur Güntürkün
- Department of Biopsychology, Faculty of Psychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany
| | - Robert Kumsta
- Department of Genetic Psychology, Faculty of Psychology, Ruhr University Bochum, Bochum, Germany
| | - Erhan Genç
- Leibniz Research Centre for Working Environment and Human Factors (IfADo), Department of Psychology and Neurosciences, Dortmund, Germany
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Mooney MA, Bhatt P, Hermosillo RJM, Ryabinin P, Nikolas M, Faraone SV, Fair DA, Wilmot B, Nigg JT. Smaller total brain volume but not subcortical structure volume related to common genetic risk for ADHD. Psychol Med 2021; 51:1279-1288. [PMID: 31973781 PMCID: PMC7461955 DOI: 10.1017/s0033291719004148] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Mechanistic endophenotypes can inform process models of psychopathology and aid interpretation of genetic risk factors. Smaller total brain and subcortical volumes are associated with attention-deficit hyperactivity disorder (ADHD) and provide clues to its development. This study evaluates whether common genetic risk for ADHD is associated with total brain volume (TBV) and hypothesized subcortical structures in children. METHODS Children 7-15 years old were recruited for a case-control study (N = 312, N = 199 ADHD). Children were assessed with a multi-informant, best-estimate diagnostic procedure and motion-corrected MRI measured brain volumes. Polygenic scores were computed based on discovery data from the Psychiatric Genomics Consortium (N = 19 099 ADHD, N = 34 194 controls) and the ENIGMA + CHARGE consortium (N = 26 577). RESULTS ADHD was associated with smaller TBV, and altered volumes of caudate, cerebellum, putamen, and thalamus after adjustment for TBV; however, effects were larger and statistically reliable only in boys. TBV was associated with an ADHD polygenic score [β = -0.147 (-0.27 to -0.03)], and mediated a small proportion of the effect of polygenic risk on ADHD diagnosis (average ACME = 0.0087, p = 0.012). This finding was stronger in boys (average ACME = 0.019, p = 0.008). In addition, we confirm genetic variation associated with whole brain volume, via an intracranial volume polygenic score. CONCLUSION Common genetic risk for ADHD is not expressed primarily as developmental alterations in subcortical brain volumes, but appears to alter brain development in other ways, as evidenced by TBV differences. This is among the first demonstrations of this effect using molecular genetic data. Potential sex differences in these effects warrant further examination.
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Affiliation(s)
- Michael A Mooney
- Division of Bioinformatics & Computational Biology, Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, USA
- OHSU Knight Cancer Institute, Portland, Oregon, USA
| | - Priya Bhatt
- Department of Psychiatry, Oregon Health & Science University, Portland, Oregon, USA
| | - Robert J M Hermosillo
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA
| | - Peter Ryabinin
- Oregon Clinical and Translational Research Institute, Portland, Oregon, USA
| | - Molly Nikolas
- Department of Psychological and Brain Sciences, The University of Iowa, Iowa City, Iowa, USA
| | - Stephen V Faraone
- Departments of Psychiatry and Neuroscience & Physiology, State University of New York Upstate Medical University, Syracuse, New York, USA
| | - Damien A Fair
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA
- Advanced Imaging Research Center, OHSU, Portland, Oregon, USA
| | - Beth Wilmot
- Division of Bioinformatics & Computational Biology, Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, USA
- Oregon Clinical and Translational Research Institute, Portland, Oregon, USA
| | - Joel T Nigg
- Department of Psychiatry, Oregon Health & Science University, Portland, Oregon, USA
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA
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Ali F, Sreeraj VS, Nadella RK, Holla B, Mahadevan J, Ithal D, Balachander S, Viswanath B, Venkatasubramanian G, John JP, Reddy YCJ, Jain S. Estimating the familial risk of psychiatric illnesses: A review of family history scores. Asian J Psychiatr 2021; 56:102551. [PMID: 33453492 DOI: 10.1016/j.ajp.2021.102551] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 12/17/2020] [Accepted: 01/05/2021] [Indexed: 11/26/2022]
Abstract
A history of psychiatric illnesses in family members of those diagnosed to have an illness has been of significant interest both in research and in clinical practice. Almost all of the major psychiatric illnesses have a familial component to them, perhaps influenced by genetics and a shared environment or their combination. Systematic attempts have been made to quantify these familial risks, as obtained from family history (FH) of psychiatric illnesses. The methods range from a simple dichotomous or count scores to those quantifying as weighted risks such as the Family history density (FHD) measures. This article reviews the available literature on such FH methods and discusses their advantages and limitations. Validation studies have shown that FHD measures may be preferred over dichotomous measures as indicators of familial risk. However, the FHD method has certain limitations, like mostly relying on categorical diagnosis and ignoring other familial risk factors. By critically analysing various existing density measures based on 'ideal characteristics', we suggest a modified version of FHD that would benefit psychiatric research.
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Affiliation(s)
- Furkhan Ali
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru
| | - Vanteemar S Sreeraj
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru.
| | - Ravi Kumar Nadella
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru
| | - Bharath Holla
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru
| | - Jayant Mahadevan
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru
| | - Dhruva Ithal
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru
| | - Srinivas Balachander
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru
| | - Biju Viswanath
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru
| | | | - John P John
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru
| | - Y C Janardhan Reddy
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru
| | - Sanjeev Jain
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru
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Proof-of-concept study of a multi-gene risk score in adolescent bipolar disorder. J Affect Disord 2020; 262:211-222. [PMID: 31727397 DOI: 10.1016/j.jad.2019.11.009] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 10/07/2019] [Accepted: 11/02/2019] [Indexed: 11/21/2022]
Abstract
BACKGROUND Few studies have examined multiple genetic variants concurrently for the purpose of classifying bipolar disorder (BD); the literature among youth is particularly sparse. We selected 35 genetic variants, previously implicated in BD or associated characteristics, from which to identify the most robustly predictive group of genes. METHODS 215 Caucasian adolescents (114 BD and 101 healthy controls (HC), ages 13-20 years) were included. Psychiatric diagnoses were determined based on semi-structured diagnostic interviews. Genomic DNA was extracted from saliva for genotyping. Two models were used to calculate a multi-gene risk score (MGRS). Model 1 used forward and backward regressions, and model 2 used a PLINK generated method. RESULTS In model 1, GPX3 rs3792797 was significant in the forward regression, DRD4 exonIII was significant in the backward regression; IL1β rs16944 and DISC1 rs821577 were significant in both the forward and backward regressions. These variants are involved in dopamine neurotransmission; inflammation and oxidative stress; and neuronal development. Model 1 MGRS did not significantly discriminate between BD and HC. In model 2, ZNF804A rs1344706 was significantly associated with BD; however, this association did not predict diagnosis when entered into the weighted model. LIMITATIONS This study was limited by the number of genetic variants examined and the modest sample size. CONCLUSIONS Whereas regression approaches identified four genetic variants that significantly discriminated between BD and HC, those same variants no longer discriminated between BD and HC when computed as a MGRS. Future larger studies are needed evaluating intermediate phenotypes such as neuroimaging and blood-based biomarkers.
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Alemany S, Jansen PR, Muetzel RL, Marques N, El Marroun H, Jaddoe VWV, Polderman TJC, Tiemeier H, Posthuma D, White T. Common Polygenic Variations for Psychiatric Disorders and Cognition in Relation to Brain Morphology in the General Pediatric Population. J Am Acad Child Adolesc Psychiatry 2019; 58:600-607. [PMID: 30768412 DOI: 10.1016/j.jaac.2018.09.443] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Revised: 08/30/2018] [Accepted: 01/02/2019] [Indexed: 10/27/2022]
Abstract
OBJECTIVE This study examined the relation between polygenic scores (PGSs) for 5 major psychiatric disorders and 2 cognitive traits with brain magnetic resonance imaging morphologic measurements in a large population-based sample of children. In addition, this study tested for differences in brain morphology-mediated associations between PGSs for psychiatric disorders and PGSs for related behavioral phenotypes. METHOD Participants included 1,139 children from the Generation R Study assessed at 10 years of age with genotype and neuroimaging data available. PGSs were calculated for schizophrenia, bipolar disorder, major depression disorder, attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, intelligence, and educational attainment using results from the most recent genome-wide association studies. Image processing was performed using FreeSurfer to extract cortical and subcortical brain volumes. RESULTS Greater genetic susceptibility for ADHD was associated with smaller caudate volume (strongest prior = 0.01: β = -0.07, p = .006). In boys, mediation analysis estimates showed that 11% of the association between the PGS for ADHD and the PGS attention problems was mediated by differences in caudate volume (n = 535), whereas mediation was not significant in girls or the entire sample. PGSs for educational attainment and intelligence showed positive associations with total brain volume (strongest prior = 0.5: β = 0.14, p = 7.12 × 10-8; and β = 0.12, p = 6.87 × 10-7, respectively). CONCLUSION The present findings indicate that the neurobiological manifestation of polygenic susceptibility for ADHD, educational attainment, and intelligence involve early morphologic differences in caudate and total brain volumes in childhood. Furthermore, the genetic risk for ADHD might influence attention problems through the caudate nucleus in boys.
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Affiliation(s)
- Silvia Alemany
- Barcelona Institute for Global Health and the Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
| | - Philip R Jansen
- Erasmus University Medical Center, Rotterdam, the Netherlands; Generation R Study Group, Erasmus University Medical Center; Amsterdam Neuroscience, VU University, Amsterdam, the Netherlands; Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, the Netherlands
| | - Ryan L Muetzel
- Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Natália Marques
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, Portugal
| | - Hanan El Marroun
- Erasmus University Medical Center, Rotterdam, the Netherlands; Generation R Study Group, Erasmus University Medical Center
| | - Vincent W V Jaddoe
- Erasmus University Medical Center, Rotterdam, the Netherlands; Generation R Study Group, Erasmus University Medical Center
| | - Tinca J C Polderman
- Amsterdam Neuroscience, VU University, Amsterdam, the Netherlands; Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, the Netherlands
| | - Henning Tiemeier
- Erasmus University Medical Center, Rotterdam, the Netherlands; Harvard TH Chan School of Public Health, Boston, MA
| | - Danielle Posthuma
- Amsterdam Neuroscience, VU University, Amsterdam, the Netherlands; Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, the Netherlands; VU University Medical Center (VUMC), Amsterdam
| | - Tonya White
- Erasmus University Medical Center, Rotterdam, the Netherlands
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Dezhina Z, Ranlund S, Kyriakopoulos M, Williams SCR, Dima D. A systematic review of associations between functional MRI activity and polygenic risk for schizophrenia and bipolar disorder. Brain Imaging Behav 2019; 13:862-877. [PMID: 29748770 PMCID: PMC6538577 DOI: 10.1007/s11682-018-9879-z] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Genetic factors account for up to 80% of the liability for schizophrenia (SCZ) and bipolar disorder (BD). Genome-wide association studies have successfully identified several genes associated with increased risk for both disorders. This has allowed researchers to model the aggregate effect of genes associated with disease status and create a polygenic risk score (PGRS) for each individual. The interest in imaging genetics using PGRS has grown in recent years, with several studies now published. We have conducted a systematic review to examine the effects of PGRS of SCZ, BD and cross psychiatric disorders on brain function and connectivity using fMRI data. Results indicate that the effect of genetic load for SCZ and BD on brain function affects task-related recruitment, with frontal areas having a more prominent role, independent of task. Additionally, the results suggest that the polygenic architecture of psychotic disorders is not regionally confined but impacts on the task-dependent recruitment of multiple brain regions. Future imaging genetics studies with large samples, especially population studies, would be uniquely informative in mapping the spatial distribution of the genetic risk to psychiatric disorders on brain processes during various cognitive tasks and may lead to the discovery of biological pathways that could be crucial in mediating the link between genetic factors and alterations in brain networks.
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Affiliation(s)
- Zalina Dezhina
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Siri Ranlund
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Marinos Kyriakopoulos
- National and Specialist Acorn Lodge Inpatient Children Unit, South London and Maudsley NHS Foundation Trust, London, UK
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Steve C R Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Danai Dima
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
- Department of Psychology, School of Arts and Social Sciences, City, University of London, 10 Northampton Square, London, EC1V 0HB, UK.
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Polygenic Scores for Neuropsychiatric Traits and White Matter Microstructure in the Pediatric Population. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2019; 4:243-250. [DOI: 10.1016/j.bpsc.2018.07.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Revised: 07/08/2018] [Accepted: 07/09/2018] [Indexed: 12/31/2022]
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Alloza C, Cox SR, Blesa Cábez M, Redmond P, Whalley HC, Ritchie SJ, Muñoz Maniega S, Valdés Hernández MDC, Tucker-Drob EM, Lawrie SM, Wardlaw JM, Deary IJ, Bastin ME. Polygenic risk score for schizophrenia and structural brain connectivity in older age: A longitudinal connectome and tractography study. Neuroimage 2018; 183:884-896. [PMID: 30179718 PMCID: PMC6215331 DOI: 10.1016/j.neuroimage.2018.08.075] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Revised: 08/28/2018] [Accepted: 08/31/2018] [Indexed: 12/14/2022] Open
Abstract
Higher polygenic risk score for schizophrenia (szPGRS) has been associated with lower cognitive function and might be a predictor of decline in brain structure in apparently healthy populations. Age-related declines in structural brain connectivity-measured using white matter diffusion MRI -are evident from cross-sectional data. Yet, it remains unclear how graph theoretical metrics of the structural connectome change over time, and whether szPGRS is associated with differences in ageing-related changes in human brain connectivity. Here, we studied a large, relatively healthy, same-year-of-birth, older age cohort over a period of 3 years (age ∼ 73 years, N = 731; age ∼76 years, N = 488). From their brain scans we derived tract-averaged fractional anisotropy (FA) and mean diffusivity (MD), and network topology properties. We investigated the cross-sectional and longitudinal associations between these structural brain variables and szPGRS. Higher szPGRS showed significant associations with longitudinal increases in MD in the splenium (β = 0.132, pFDR = 0.040), arcuate (β = 0.291, pFDR = 0.040), anterior thalamic radiations (β = 0.215, pFDR = 0.040) and cingulum (β = 0.165, pFDR = 0.040). Significant declines over time were observed in graph theory metrics for FA-weighted networks, such as mean edge weight (β = -0.039, pFDR = 0.048) and strength (β = -0.027, pFDR = 0.048). No significant associations were found between szPGRS and graph theory metrics. These results are consistent with the hypothesis that szPGRS confers risk for ageing-related degradation of some aspects of structural connectivity.
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Affiliation(s)
- C Alloza
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK.
| | - S R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, University of Edinburgh, Edinburgh, UK
| | - M Blesa Cábez
- MRC Centre for Reproductive Health, University of Edinburgh, UK
| | - P Redmond
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - H C Whalley
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - S J Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - S Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - M Del C Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - E M Tucker-Drob
- Department of Psychology, University of Texas, Austin, TX, USA
| | - S M Lawrie
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - J M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - I J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - M E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK; Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
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Krug A, Dietsche B, Zöllner R, Yüksel D, Nöthen MM, Forstner AJ, Rietschel M, Dannlowski U, Baune BT, Maier R, Witt SH, Kircher T. Polygenic risk for schizophrenia affects working memory and its neural correlates in healthy subjects. Schizophr Res 2018; 197:315-320. [PMID: 29409757 DOI: 10.1016/j.schres.2018.01.013] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2017] [Revised: 11/14/2017] [Accepted: 01/17/2018] [Indexed: 12/27/2022]
Abstract
Schizophrenia is a disorder with a high heritability. Patients as well as their first degree relatives display lower levels of performance in a number of cognitive domains compared to subjects without genetic risk. Several studies could link these aberrations to single genetic variants, however, only recently, polygenic risk scores as proxies for genetic risk have been associated with cognitive domains and their neural correlates. In the present study, a sample of healthy subjects (n=137) performed a letter version of the n-back task while scanned with 3-T fMRI. All subjects were genotyped with the PsychChip and polygenic risk scores were calculated based on the PGC2 schizophrenia GWAS results. Polygenic risk for schizophrenia was associated with a lower degree of brain activation in prefrontal areas during the 3-back compared to the 0-back baseline condition. Furthermore, polygenic risk was associated with lower levels of brain activation in the right inferior frontal gyrus during the 3-back compared to a 2-back condition. Polygenic risk leads to a shift in the underlying activation pattern to the left side, thus resembling results reported in patients with schizophrenia. The data may point to polygenic risk for schizophrenia being associated with brain function in a cognitive task known to be impaired in patients and their relatives.
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Affiliation(s)
- Axel Krug
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany.
| | - Bruno Dietsche
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Rebecca Zöllner
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Dilara Yüksel
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, Bonn, Germany; Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, Bonn, Germany; Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany; Department of Psychiatry (UPK), University of Basel, Switzerland; Division of Medical Genetics and Department of Biomedicine, University of Basel, Switzerland
| | - Marcella Rietschel
- Department of Genetic Epidemiology, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Udo Dannlowski
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; Department of Psychiatry, University of Münster, Münster, Germany
| | - Bernhard T Baune
- Discipline of Psychiatry, The University of Adelaide, Adelaide, SA, Australia
| | - Robert Maier
- Queensland Brain Institute, The University of Queensland, Australia
| | - Stephanie H Witt
- Department of Genetic Epidemiology, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
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11
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Neilson E, Bois C, Clarke TK, Hall L, Johnstone EC, Owens DGC, Whalley HC, McIntosh AM, Lawrie SM. Polygenic risk for schizophrenia, transition and cortical gyrification: a high-risk study. Psychol Med 2018; 48:1532-1539. [PMID: 29065934 DOI: 10.1017/s0033291717003087] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND Schizophrenia is a highly heritable disorder, linked to several structural abnormalities of the brain. More specifically, previous findings have suggested that increased gyrification in frontal and temporal regions are implicated in the pathogenesis of schizophrenia. METHODS The current study included participants at high familial risk of schizophrenia who remained well (n = 31), who developed sub-diagnostic symptoms (n = 28) and who developed schizophrenia (n = 9) as well as healthy controls (HC) (n = 16). We first tested whether individuals at high familial risk of schizophrenia carried an increased burden of trait-associated alleles using polygenic risk score analysis. We then assessed the extent to which polygenic risk was associated with gyral folding in the frontal and temporal lobes. RESULTS We found that individuals at high familial risk of schizophrenia who developed schizophrenia carried a significantly greater burden of risk-conferring variants for the disorder compared to those at high risk (HR) who developed sub-diagnostic symptoms or remained well and HC. Furthermore, within the HR cohort, there was a significant and positive association between schizophrenia polygenic risk score and bilateral frontal gyrification. CONCLUSIONS These results suggest that polygenic risk for schizophrenia impacts upon early neurodevelopment to confer greater gyral folding in adulthood and an increased risk of developing the disorder.
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Affiliation(s)
- E Neilson
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
| | - C Bois
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
| | - T-K Clarke
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
| | - L Hall
- International Centre for Life,Institute of Genetic Medicine,Newcastle University,Central Parkway,Newcastle upon Tyne,UK
| | - E C Johnstone
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
| | - D G C Owens
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
| | - H C Whalley
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
| | - A M McIntosh
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
| | - S M Lawrie
- Division of Psychiatry,University of Edinburgh,Royal Edinburgh Hospital,Kennedy Tower,Edinburgh,UK
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12
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Miller JA, Scult MA, Conley ED, Chen Q, Weinberger DR, Hariri AR. Effects of Schizophrenia Polygenic Risk Scores on Brain Activity and Performance During Working Memory Subprocesses in Healthy Young Adults. Schizophr Bull 2018; 44:844-853. [PMID: 29040762 PMCID: PMC6007653 DOI: 10.1093/schbul/sbx140] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Recent work has begun to shed light on the neural correlates and possible mechanisms of polygenic risk for schizophrenia. Here, we map a schizophrenia polygenic risk profile score (PRS) based on genome-wide association study significant loci onto variability in the activity and functional connectivity of a frontoparietal network supporting the manipulation versus maintenance of information during a numerical working memory (WM) task in healthy young adults (n = 99, mean age = 19.8). Our analyses revealed that higher PRS was associated with hypoactivity of the dorsolateral prefrontal cortex (dlPFC) during the manipulation but not maintenance of information in WM (r2 = .0576, P = .018). Post hoc analyses revealed that PRS-modulated dlPFC hypoactivity correlated with faster reaction times during WM manipulation (r2 = .0967, P = .002), and faster processing speed (r2 = .0967, P = .003) on a separate behavioral task. These PRS-associated patterns recapitulate dlPFC hypoactivity observed in patients with schizophrenia during central executive manipulation of information in WM on this task.
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Affiliation(s)
- Jacob A Miller
- UC Berkeley Graduate Neuroscience Program, Helen Wills Neuroscience Institute, Berkeley, CA
| | - Matthew A Scult
- Laboratory of NeuroGenetics, Department of Psychology & Neuroscience, Duke University, Durham, NC,To whom correspondence should be addressed; tel: 919-684-1039, fax: 919-660-5726, e-mail:
| | | | - Qiang Chen
- Lieber Institute for Brain Development, Baltimore, MD,Department of Psychiatry, Johns Hopkins School of Medicine, Baltimore, MD,Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD,Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD,Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Baltimore, MD,Department of Psychiatry, Johns Hopkins School of Medicine, Baltimore, MD,Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD,Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD,Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD
| | - Ahmad R Hariri
- Laboratory of NeuroGenetics, Department of Psychology & Neuroscience, Duke University, Durham, NC
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13
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Chalmer MA, Esserlind AL, Olesen J, Hansen TF. Polygenic risk score: use in migraine research. J Headache Pain 2018; 19:29. [PMID: 29623444 PMCID: PMC5887014 DOI: 10.1186/s10194-018-0856-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Accepted: 03/21/2018] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The latest Genome-Wide Association Study identified 38 genetic variants associated with migraine. In this type of studies the significance level is very difficult to achieve (5 × 10- 8) due to multiple testing. Thus, the identified variants only explain a small fraction of the genetic risk. It is expected that hundreds of thousands of variants also confer an increased risk but do not reach significance levels. One way to capture this information is by constructing a Polygenic Risk Score. Polygenic Risk Score has been widely used with success in genetics studies within neuropsychiatric disorders. The use of polygenic scores is highly relevant as data from a large migraine Genome-Wide Association Study are now available, which will form an excellent basis for Polygenic Risk Score in migraine studies. RESULTS Polygenic Risk Score has been used in studies of neuropsychiatric disorders to assess prediction of disease status in case-control studies, shared genetic correlation between co-morbid diseases, and shared genetic correlation between a disease and specific endophenotypes. CONCLUSION Polygenic Risk Score provides an opportunity to investigate the shared genetic risk between known and previously unestablished co-morbidities in migraine research, and may lead to better and personalized treatment of migraine if used as a clinical assistant when identifying responders to specific drugs. Polygenic Risk Score can be used to analyze the genetic relationship between different headache types and migraine endophenotypes. Finally, Polygenic Risk Score can be used to assess pharmacogenetic effects, and perhaps help to predict efficacy of the Calcitonin Gene-Related Peptide monoclonal antibodies that soon become available as migraine treatment.
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Affiliation(s)
- Mona Ameri Chalmer
- Department of Neurology, Danish Headache Center, Copenhagen University Hospital, DK-2600, Glostrup, Denmark.
| | - Ann-Louise Esserlind
- Department of Neurology, Danish Headache Center, Copenhagen University Hospital, DK-2600, Glostrup, Denmark
| | - Jes Olesen
- Department of Neurology, Danish Headache Center, Copenhagen University Hospital, DK-2600, Glostrup, Denmark
| | - Thomas Folkmann Hansen
- Department of Neurology, Danish Headache Center, Copenhagen University Hospital, DK-2600, Glostrup, Denmark
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14
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A Homer 1 gene variant influences brain structure and function, lithium effects on white matter, and antidepressant response in bipolar disorder: A multimodal genetic imaging study. Prog Neuropsychopharmacol Biol Psychiatry 2018; 81:88-95. [PMID: 29079138 DOI: 10.1016/j.pnpbp.2017.10.011] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2017] [Revised: 09/28/2017] [Accepted: 10/21/2017] [Indexed: 11/24/2022]
Abstract
BACKGROUND The Homer family of postsynaptic scaffolding proteins plays a crucial role in glutamate-mediated synaptic plasticity, a phenotype associated with Bipolar Disorder (BD). Homer is a target for antidepressants and mood stabilizers. The AA risk genotype of the Homer rs7713917 A>G SNP has been associated with mood disorders and suicide, and in healthy humans with brain function. Despite the evidence linking Homer 1 gene and function to mood disorder, as well as its involvement in animal models of depression, no study has yet investigated the role of Homer in bipolar depression and treatment response. METHODS We studied 199 inpatients, affected by a major depressive episode in course of BD. 147 patients were studied with structural MRI of grey and white matter, and 50 with BOLD functional MRI of emotional processing. 158 patients were treated with combined total sleep deprivation and light therapy. RESULTS At neuroimaging, patients with the AA genotype showed lower grey matter volumes in medial prefrontal cortex, higher BOLD fMRI neural responses to emotional stimuli in anterior cingulate cortex, and lower fractional anisotropy in bilateral frontal WM tracts. Lithium treatment increased axial diffusivity more in AA patients than in G*carriers. At clinical evaluation, the same AA homozygotes showed a worse antidepressant response to combined SD and LT. CONCLUSIONS rs7713917 influenced brain grey and white matter structure and function in BD, long term effects of lithium on white matter structure, and antidepressant response to chronotherapeutics, thus suggesting that glutamatergic neuroplasticity and Homer 1 function might play a role in BD psychopathology and response to treatment.
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15
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Abstract
Recent large-scale genomic studies have confirmed that schizophrenia is a polygenic syndrome and have implicated a number of biological pathways in its aetiology. Both common variants individually of small effect and rarer but more penetrant genetic variants have been shown to play a role in the pathogenesis of the disorder. No simple Mendelian forms of the condition have been identified, but progress has been made in stratifying risk on the basis of the polygenic burden of common variants individually of small effect, and the contribution of rarer variants of larger effect such as Copy Number Variants (CNVs). Pathway analysis of risk-associated variants has begun to identify specific biological processes implicated in risk for the disorder, including elements of the glutamatergic NMDA receptor complex and post synaptic density, voltage-gated calcium channels, targets of the Fragile X Mental Retardation Protein (FMRP targets) and immune pathways. Genetic studies have also been used to drive genomic imaging approaches to the investigation of brain markers associated with risk for the disorder. Genomic imaging approaches have been applied both to investigate the effect of polygenic risk and to study the impact of individual higher-penetrance variants such as CNVs. Both genomic and genomic imaging approaches offer potential for the stratification of patients and at-risk groups and the development of better biomarkers of risk and treatment response; however, further research is needed to integrate this work and realise the full potential of these approaches.
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16
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Ranlund S, Calafato S, Thygesen JH, Lin K, Cahn W, Crespo‐Facorro B, de Zwarte SM, Díez Á, Di Forti M, Iyegbe C, Jablensky A, Jones R, Hall M, Kahn R, Kalaydjieva L, Kravariti E, McDonald C, McIntosh AM, McQuillin A, Picchioni M, Prata DP, Rujescu D, Schulze K, Shaikh M, Toulopoulou T, van Haren N, van Os J, Vassos E, Walshe M, Lewis C, Murray RM, Powell J, Bramon E. A polygenic risk score analysis of psychosis endophenotypes across brain functional, structural, and cognitive domains. Am J Med Genet B Neuropsychiatr Genet 2018; 177:21-34. [PMID: 28851104 PMCID: PMC5763362 DOI: 10.1002/ajmg.b.32581] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Accepted: 07/24/2017] [Indexed: 12/26/2022]
Abstract
This large multi-center study investigates the relationships between genetic risk for schizophrenia and bipolar disorder, and multi-modal endophenotypes for psychosis. The sample included 4,242 individuals; 1,087 patients with psychosis, 822 unaffected first-degree relatives of patients, and 2,333 controls. Endophenotypes included the P300 event-related potential (N = 515), lateral ventricular volume (N = 798), and the cognitive measures block design (N = 3,089), digit span (N = 1,437), and the Ray Auditory Verbal Learning Task (N = 2,406). Data were collected across 11 sites in Europe and Australia; all genotyping and genetic analyses were done at the same laboratory in the United Kingdom. We calculated polygenic risk scores for schizophrenia and bipolar disorder separately, and used linear regression to test whether polygenic scores influenced the endophenotypes. Results showed that higher polygenic scores for schizophrenia were associated with poorer performance on the block design task and explained 0.2% (p = 0.009) of the variance. Associations in the same direction were found for bipolar disorder scores, but this was not statistically significant at the 1% level (p = 0.02). The schizophrenia score explained 0.4% of variance in lateral ventricular volumes, the largest across all phenotypes examined, although this was not significant (p = 0.063). None of the remaining associations reached significance after correction for multiple testing (with alpha at 1%). These results indicate that common genetic variants associated with schizophrenia predict performance in spatial visualization, providing additional evidence that this measure is an endophenotype for the disorder with shared genetic risk variants. The use of endophenotypes such as this will help to characterize the effects of common genetic variation in psychosis.
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Affiliation(s)
- Siri Ranlund
- Division of PsychiatryUniversity College LondonLondonUK
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | | | | | - Kuang Lin
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Nuffield Department of Population HealthUniversity of OxfordOxfordUK
| | - Wiepke Cahn
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Benedicto Crespo‐Facorro
- CIBERSAMCentro Investigación Biomédica en Red Salud MentalMadridSpain
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of MedicineUniversity of Cantabria–IDIVALSantanderSpain
| | - Sonja M.C. de Zwarte
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Álvaro Díez
- Division of PsychiatryUniversity College LondonLondonUK
- Laboratory of Cognitive and Computational Neuroscience—Centre for Biomedical Technology (CTB)Complutense University and Technical University of MadridMadridSpain
| | - Marta Di Forti
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | | | - Conrad Iyegbe
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Assen Jablensky
- Centre for Clinical Research in NeuropsychiatryThe University of Western AustraliaPerth, Western AustraliaAustralia
| | - Rebecca Jones
- Division of PsychiatryUniversity College LondonLondonUK
| | - Mei‐Hua Hall
- Psychosis Neurobiology Laboratory, Harvard Medical SchoolMcLean HospitalBelmontMassachusetts
| | - Rene Kahn
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Luba Kalaydjieva
- Harry Perkins Institute of Medical Research and Centre for Medical ResearchThe University of Western AustraliaPerthAustralia
| | - Eugenia Kravariti
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Colm McDonald
- The Centre for Neuroimaging & Cognitive Genomics (NICOG) and NCBES Galway Neuroscience CentreNational University of Ireland GalwayGalwayIreland
| | - Andrew M. McIntosh
- Division of Psychiatry, University of EdinburghRoyal Edinburgh HospitalEdinburghUK
- Centre for Cognitive Ageing and Cognitive EpidemiologyUniversity of EdinburghEdinburghUK
| | | | | | - Marco Picchioni
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Diana P. Prata
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Faculdade de Medicina, Instituto de Medicina MolecularUniversidade de LisboaPortugal
| | - Dan Rujescu
- Department of PsychiatryLudwig‐Maximilians University of MunichMunichGermany
- Department of Psychiatry, Psychotherapy and PsychosomaticsUniversity of Halle WittenbergHalleGermany
| | - Katja Schulze
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Madiha Shaikh
- North East London Foundation TrustLondonUK
- Research Department of Clinical, Educational and Health PsychologyUniversity College LondonLondonUK
| | - Timothea Toulopoulou
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Department of Psychology, Bilkent UniversityMain CampusBilkent, AnkaraTurkey
- Department of PsychologyThe University of Hong Kong, Pokfulam RdHong Kong SARChina
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong KongThe Hong Kong Jockey Club Building for Interdisciplinary ResearchHong Kong SARChina
| | - Neeltje van Haren
- Department of Psychiatry, Brain Centre Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Jim van Os
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Department of Psychiatry and Psychology, Maastricht University Medical CentreEURONMaastrichtThe Netherlands
| | - Evangelos Vassos
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Muriel Walshe
- Division of PsychiatryUniversity College LondonLondonUK
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | | | - Cathryn Lewis
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Robin M. Murray
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - John Powell
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
| | - Elvira Bramon
- Division of PsychiatryUniversity College LondonLondonUK
- Institute of Psychiatry Psychology and Neuroscience at King's College London and South LondonMaudsley NHS Foundation TrustLondonUK
- Institute of Cognitive NeuroscienceUniversity College LondonLondonUK
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17
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Yüksel D, Dietsche B, Forstner AJ, Witt SH, Maier R, Rietschel M, Konrad C, Nöthen MM, Dannlowski U, Baune BT, Kircher T, Krug A. Polygenic risk for depression and the neural correlates of working memory in healthy subjects. Prog Neuropsychopharmacol Biol Psychiatry 2017. [PMID: 28624581 DOI: 10.1016/j.pnpbp.2017.06.010] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
INTRODUCTION Major depressive disorder (MDD) patients show impairments of cognitive functioning such as working memory (WM), and furthermore alterations during WM-fMRI tasks especially in frontal and parietal brain regions. The calculation of a polygenic risk score (PRS) can be used to describe the genetic influence on MDD, hence imaging genetic studies aspire to combine both genetics and neuroimaging data to identify the influence of genetic factors on brain functioning. We aimed to detect the effect of MDD-PRS on brain activation during a WM task measured with fMRI and expect healthy individuals with a higher PRS to be more resembling to MDD patients. METHOD In total, n=137 (80 men, 57 women, aged 34.5, SD=10.4years) healthy subjects performed a WM n-back task [0-back (baseline), 2-back and 3-back condition] in a 3T-MRI-tomograph. The sample was genotyped using the Infinium PsychArray BeadChip and a polygenic risk score was calculated for MDD using PGC MDD GWAS results. RESULTS A lower MDD risk score was associated with increased activation in the bilateral middle occipital gyri (MOG), the bilateral middle frontal gyri (MFG) and the right precentral gyrus (PCG) during the 2-back vs. baseline condition. Moreover, a lower PRS was associated with increased brain activation during the 3-back vs. baseline condition in the bilateral cerebellum, the right MFG and the left inferior parietal lobule. A higher polygenic risk score was associated with hyperactivation in brain regions comprising the right MFG and the right supplementary motor area during the 3-back vs. 2-back condition. DISCUSSION The results suggest that part of the WM-related brain activation patterns might be explained by genetic variants captured by the MDD-PRS. Furthermore we were able to detect MDD-associated activation patterns in healthy individuals depending on the MDD-PRS and the task complexity. Additional gene loci could contribute to these task-dependent brain activation patterns.
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Affiliation(s)
- Dilara Yüksel
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany.
| | - Bruno Dietsche
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Andreas J Forstner
- Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany; Institute of Human Genetics, University of Bonn, Bonn, Germany; Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland; Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - Stephanie H Witt
- Discipline Department of Genetic Epidemiology, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Robert Maier
- Discipline Queensland Brain Institute, The University of Queensland, Australia
| | - Marcella Rietschel
- Discipline Department of Genetic Epidemiology, Central Institute of Mental Health, University of Heidelberg, Mannheim, Germany
| | - Carsten Konrad
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; Agaplesion Diakonieklinikum Rotenberg, Centre for Psychosocial Medicine, Elise-Averdieck-Straße 17, 27356 Rotenburg (Wümme), Germany
| | - Markus M Nöthen
- Department of Genomics, Life & Brain Center, University of Bonn, Bonn, Germany; Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Udo Dannlowski
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; Department of Psychiatry, University of Münster, Münster, Germany
| | - Bernhard T Baune
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, Australia
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany
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18
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Alloza C, Bastin ME, Cox SR, Gibson J, Duff B, Semple SI, Whalley HC, Lawrie SM. Central and non-central networks, cognition, clinical symptoms, and polygenic risk scores in schizophrenia. Hum Brain Mapp 2017; 38:5919-5930. [PMID: 28881417 DOI: 10.1002/hbm.23798] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Revised: 08/02/2017] [Accepted: 08/24/2017] [Indexed: 12/25/2022] Open
Abstract
Schizophrenia is a complex disorder that may be the result of aberrant connections between specific brain regions rather than focal brain abnormalities. Here, we investigate the relationships between brain structural connectivity as described by network analysis, intelligence, symptoms, and polygenic risk scores (PGRS) for schizophrenia in a group of patients with schizophrenia and a group of healthy controls. Recently, researchers have shown an interest in the role of high centrality networks in the disorder. However, the importance of non-central networks still remains unclear. Thus, we specifically examined network-averaged fractional anisotropy (mean edge weight) in central and non-central subnetworks. Connections with the highest betweenness centrality within the average network (>75% of centrality values) were selected to represent the central subnetwork. The remaining connections were assigned to the non-central subnetwork. Additionally, we calculated graph theory measures from the average network (connections that occur in at least 2/3 of participants). Density, strength, global efficiency, and clustering coefficient were significantly lower in patients compared with healthy controls for the average network (pFDR < 0.05). All metrics across networks were significantly associated with intelligence (pFDR < 0.05). There was a tendency towards significance for a correlation between intelligence and PGRS for schizophrenia (r = -0.508, p = 0.052) that was significantly mediated by central and non-central mean edge weight and every graph metric from the average network. These results are consistent with the hypothesis that intelligence deficits are associated with a genetic risk for schizophrenia, which is mediated via the disruption of distributed brain networks. Hum Brain Mapp 38:5919-5930, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Clara Alloza
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom.,Centre for Clinical Brain Sciences, Western General Hospital, University of Edinburgh, Edinburgh, United Kingdom.,Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, United Kingdom
| | - Simon R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom.,Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom.,Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, United Kingdom
| | - Jude Gibson
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Barbara Duff
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Scott I Semple
- Clinical Research Imaging Centre, University of Edinburgh, Edinburgh, United Kingdom
| | - Heather C Whalley
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Stephen M Lawrie
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
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19
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Effects of environmental risks and polygenic loading for schizophrenia on cortical thickness. Schizophr Res 2017; 184:128-136. [PMID: 27989645 DOI: 10.1016/j.schres.2016.12.011] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Revised: 12/09/2016] [Accepted: 12/11/2016] [Indexed: 01/21/2023]
Abstract
There are established differences in cortical thickness (CT) in schizophrenia (SCZ) and bipolar (BD) patients when compared to healthy controls (HC). However, it is unknown to what extent environmental or genetic risk factors impact on CT in these populations. We have investigated the effect of Environmental Risk Scores (ERS) and Polygenic Risk Scores for SCZ (PGRS-SCZ) on CT. Structural MRI scans were acquired at 3T for patients with SCZ or BD (n=57) and controls (n=41). Cortical reconstructions were generated in FreeSurfer (v5.3). The ERS was created by determining exposure to cannabis use, childhood adverse events, migration, urbanicity and obstetric complications. The PGRS-SCZ were generated, for a subset of the sample (Patients=43, HC=32), based on the latest PGC GWAS findings. ANCOVAs were used to test the hypotheses that ERS and PGRS-SCZ relate to CT globally, and in frontal and temporal lobes. An increase in ERS was negatively associated with CT within temporal lobe for patients. A higher PGRS-SCZ was also related to global cortical thinning for patients. ERS effects remained significant when including PGRS-SCZ as a fixed effect. No relationship which survived FDR correction was found for ERS and PGRS-SCZ in controls. Environmental risk for SCZ was related to localised cortical thinning in patients with SCZ and BD, while increased PGRS-SCZ was associated with global cortical thinning. Genetic and environmental risk factors for SCZ appear therefore to have differential effects. This provides a mechanistic means by which different risk factors may contribute to the development of SCZ and BD.
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Impact of Familial Loading on Prefrontal Activation in Major Psychiatric Disorders: A Near-Infrared Spectroscopy (NIRS) Study. Sci Rep 2017; 7:44268. [PMID: 28295013 PMCID: PMC5353718 DOI: 10.1038/srep44268] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2016] [Accepted: 02/07/2017] [Indexed: 11/08/2022] Open
Abstract
Family history (FH) is predictive of the development of major psychiatric disorders (PSY). Familial psychiatric disorders are largely a consequence of genetic factors and typically exhibit more severe impairments. Decreased prefrontal activity during verbal fluency testing (VFT) may constitute an intermediate phenotype for PSY. We investigated whether familial PSY were associated with a greater severity of prefrontal dysfunction in accordance with genetic loading. We measured prefrontal activity during VFT using near-infrared spectroscopy (NIRS) in patients with schizophrenia (SCZ, n = 45), major depressive disorder (MDD, n = 26) or bipolar disorder (BIP, n = 22) and healthy controls (HC, n = 51). We compared prefrontal activity among patients with or without FH and HC. Patients in the SCZ, MDD and BIP patient groups had lower prefrontal activity than HC subjects. Patients with and without FH in all diagnostic groups had lower prefrontal activity than HC subjects. Moreover, SCZ patients with FH had lower prefrontal activity than SCZ patients without FH. When we included patients with SCZ, MDD or BIP in the group of patients with PSY, the effects of psychiatric FH on prefrontal activity were enhanced. These findings demonstrate the association of substantially more severe prefrontal dysfunction with higher genetic loading in major psychiatric disorders.
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Polygenic risk for five psychiatric disorders and cross-disorder and disorder-specific neural connectivity in two independent populations. NEUROIMAGE-CLINICAL 2017; 14:441-449. [PMID: 28275544 PMCID: PMC5328751 DOI: 10.1016/j.nicl.2017.02.011] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2016] [Revised: 02/10/2017] [Accepted: 02/11/2017] [Indexed: 12/21/2022]
Abstract
Major psychiatric disorders, including attention deficit hyperactivity disorder (ADHD), autism (AUT), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SZ), are highly heritable and polygenic. Evidence suggests that these five disorders have both shared and distinct genetic risks and neural connectivity abnormalities. To measure aggregate genetic risks, the polygenic risk score (PGRS) was computed. Two independent general populations (N = 360 and N = 323) were separately examined to investigate whether the cross-disorder PGRS and PGRS for a specific disorder were associated with individual variability in functional connectivity. Consistent altered functional connectivity was found with the bilateral insula: for the left supplementary motor area and the left superior temporal gyrus with the cross-disorder PGRS, for the left insula and right middle and superior temporal lobe associated with the PGRS for autism, for the bilateral midbrain, posterior cingulate, cuneus, and precuneus associated with the PGRS for BD, and for the left angular gyrus and the left dorsolateral prefrontal cortex associated with the PGRS for schizophrenia. No significant functional connectivity was found associated with the PGRS for ADHD and MDD. Our findings indicated that genetic effects on the cross-disorder and disorder-specific neural connectivity of common genetic risk loci are detectable in the general population. Our findings also indicated that polygenic risk contributes to the main neurobiological phenotypes of psychiatric disorders and that identifying cross-disorder and specific functional connectivity related to polygenic risks may elucidate the neural pathways for these disorders. Altered cross-disorder functional connectivity related to PGRSs is detected. Altered disorder-specific functional connectivity related to PGRSs is detected. Altered functional connectivity related to PGRSs is involved in brain networks. Polygenic risk contributes to neurobiological phenotypes of psychiatric disorders.
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Sutcliffe G, Harneit A, Tost H, Meyer-Lindenberg A. Neuroimaging Intermediate Phenotypes of Executive Control Dysfunction in Schizophrenia. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2016; 1:218-229. [DOI: 10.1016/j.bpsc.2016.03.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2015] [Revised: 03/11/2016] [Accepted: 03/14/2016] [Indexed: 01/10/2023]
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Lancaster TM, Ihssen N, Brindley LM, Tansey KE, Mantripragada K, O'Donovan MC, Owen MJ, Linden DEJ. Associations between polygenic risk for schizophrenia and brain function during probabilistic learning in healthy individuals. Hum Brain Mapp 2015; 37:491-500. [PMID: 26510167 PMCID: PMC4949629 DOI: 10.1002/hbm.23044] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2015] [Revised: 10/14/2015] [Accepted: 10/19/2015] [Indexed: 12/18/2022] Open
Abstract
A substantial proportion of schizophrenia liability can be explained by additive genetic factors. Risk profile scores (RPS) directly index risk using a summated total of common risk variants weighted by their effect. Previous studies suggest that schizophrenia RPS predict alterations to neural networks that support working memory and verbal fluency. In this study, we apply schizophrenia RPS to fMRI data to elucidate the effects of polygenic risk on functional brain networks during a probabilistic‐learning neuroimaging paradigm. The neural networks recruited during this paradigm have previously been shown to be altered to unmedicated schizophrenia patients and relatives of schizophrenia patients, which may reflect genetic susceptibility. We created schizophrenia RPS using summary data from the Psychiatric Genetic Consortium (Schizophrenia Working Group) for 83 healthy individuals and explore associations between schizophrenia RPS and blood oxygen level dependency (BOLD) during periods of choice behavior (switch–stay) and reflection upon choice outcome (reward–punishment). We show that schizophrenia RPS is associated with alterations in the frontal pole (PWHOLE‐BRAIN‐CORRECTED = 0.048) and the ventral striatum (PROI‐CORRECTED = 0.036), during choice behavior, but not choice outcome. We suggest that the common risk variants that increase susceptibility to schizophrenia can be associated with alterations in the neural circuitry that support the processing of changing reward contingencies. Hum Brain Mapp 37:491–500, 2016. © 2015 Wiley Periodicals, Inc.
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Affiliation(s)
- Thomas M Lancaster
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom.,School of Psychology, Cardiff University, Cardiff University Brain Research Imaging Centre (CUBRIC), 70 Park Place, Cardiff, CF10 3AT, Wales, United Kingdom.,Cardiff School of Medicine, Cardiff University, MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff, United Kingdom
| | - Niklas Ihssen
- School of Psychology, Cardiff University, Cardiff University Brain Research Imaging Centre (CUBRIC), 70 Park Place, Cardiff, CF10 3AT, Wales, United Kingdom.,Cardiff School of Medicine, Cardiff University, MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff, United Kingdom
| | - Lisa M Brindley
- School of Psychology, Cardiff University, Cardiff University Brain Research Imaging Centre (CUBRIC), 70 Park Place, Cardiff, CF10 3AT, Wales, United Kingdom.,Cardiff School of Medicine, Cardiff University, MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff, United Kingdom
| | - Katherine E Tansey
- Cardiff School of Medicine, Cardiff University, MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff, United Kingdom
| | - Kiran Mantripragada
- Cardiff School of Medicine, Cardiff University, MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff, United Kingdom
| | - Michael C O'Donovan
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom.,Cardiff School of Medicine, Cardiff University, MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff, United Kingdom
| | - Michael J Owen
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom.,Cardiff School of Medicine, Cardiff University, MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff, United Kingdom
| | - David E J Linden
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom.,School of Psychology, Cardiff University, Cardiff University Brain Research Imaging Centre (CUBRIC), 70 Park Place, Cardiff, CF10 3AT, Wales, United Kingdom.,Cardiff School of Medicine, Cardiff University, MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff, United Kingdom
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Scarr E, Millan MJ, Bahn S, Bertolino A, Turck CW, Kapur S, Möller HJ, Dean B. Biomarkers for Psychiatry: The Journey from Fantasy to Fact, a Report of the 2013 CINP Think Tank. Int J Neuropsychopharmacol 2015; 18:pyv042. [PMID: 25899066 PMCID: PMC4648162 DOI: 10.1093/ijnp/pyv042] [Citation(s) in RCA: 70] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND A think tank sponsored by the Collegium Internationale Neuropsychopharmacologium (CINP) debated the status and prospects of biological markers for psychiatric disorders, focusing on schizophrenia and major depressive disorder. METHODS Discussions covered markers defining and predicting specific disorders or domains of dysfunction, as well as predicting and monitoring medication efficacy. Deliberations included clinically useful and viable biomarkers, why suitable markers are not available, and the need for tightly-controlled sample collection. RESULTS Different types of biomarkers, appropriate sensitivity, specificity, and broad-based exploitability were discussed. Whilst a number of candidates are in the discovery phases, all will require replication in larger, real-life cohorts. Clinical cost-effectiveness also needs to be established. CONCLUSIONS Since a single measure is unlikely to suffice, multi-modal strategies look more promising, although they bring greater technical and implementation complexities. Identifying reproducible, robust biomarkers will probably require pre-competitive consortia to provide the resources needed to identify, validate, and develop the relevant clinical tests.
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Affiliation(s)
- Elizabeth Scarr
- Department of Psychiatry, University of Melbourne, Victoria, Australia (Drs Scarr and Dean); The Molecular Psychiatry Laboratory, Florey Institute for Neuroscience and Mental Health, Victoria, Australia (Drs Scarr and Dean); Pole d'Innovation Thérapeutique en Neuropsychiatrie, Institut de Recherches Servier, Paris, France (Dr Millan); Cambridge Centre for Neuropsychiatric Research, University of Cambridge, UK (Dr Bahn); Pharma Research & Early Development, NORD, DTA, Hoffman - La Roche, Ltd., Basel, Switzerland (Dr Bertolino); School of Medicine, Basic Medical Sciences, Neuroscience and Sense Organs (DMBNOS), University of Bari, Italy (Dr Bertolino); Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany (Dr Turck); Institute of Psychiatry, Kings College London, London, UK (Dr Kapur); Department of Psychiatry, Ludwig-Maximilians-University, Munich, Germany (Dr Möller)
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