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Tucci AA, Schroeder A, Noël C, Shvetz C, Yee J, Howard AL, Keshavan MS, Guimond S. Social cognition in youth with a first-degree relative with schizophrenia: A systematic scoping review. Psychiatry Res 2023; 323:115173. [PMID: 36989908 DOI: 10.1016/j.psychres.2023.115173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 03/14/2023] [Accepted: 03/18/2023] [Indexed: 03/31/2023]
Abstract
Social-cognitive deficits are present in individuals at familial high-risk (FHR) for schizophrenia and may play a role in the onset of the illness. No literature review has examined the social-cognitive profiles of youth at FHR who are within the peak window of risk for developing schizophrenia, which could provide insight on the endophenotypic role of social cognition. This systematic scoping review (1) summarizes the evidence on social-cognitive deficits in youth at FHR, (2) explores brain correlates, and (3) describes social-cognitive deficits and prodromal symptom associations. We searched PsycInfo and PubMed for studies investigating social cognition in FHR youth aged 35 or younger and included 19 studies (FHR=639; controls=689). Studies report that youth at FHR have difficulty recognizing negative emotions, particularly fear. Youth at FHR also have difficulty performing complex theory of mind tasks. Abnormality in corticolimbic and temporoparietal regions are observed in youth at FHR during social-cognitive tasks, but results are inconsistent. Finally, there is evidence for negative associations between prodromal symptoms and performance on emotion regulation and theory of mind tasks, but the research is scarce. This review highlights the need for studies on youth at FHR using longitudinal designs and extensive social-cognitive, brain imaging and clinical measures.
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Affiliation(s)
- Alexandra A Tucci
- Institute of Mental Health Research, Royal Ottawa Mental Health Centre, Ottawa, ON, Canada; Department of Psychology, Carleton University, Ottawa, ON, Canada
| | - Alexandra Schroeder
- Institute of Mental Health Research, Royal Ottawa Mental Health Centre, Ottawa, ON, Canada; Department of Neuroscience, Carleton University, Ottawa, ON, Canada
| | - Chelsea Noël
- Institute of Mental Health Research, Royal Ottawa Mental Health Centre, Ottawa, ON, Canada
| | - Cecelia Shvetz
- Institute of Mental Health Research, Royal Ottawa Mental Health Centre, Ottawa, ON, Canada; Department of Neuroscience, Carleton University, Ottawa, ON, Canada
| | - Jasmin Yee
- Institute of Mental Health Research, Royal Ottawa Mental Health Centre, Ottawa, ON, Canada
| | - Andrea L Howard
- Department of Psychology, Carleton University, Ottawa, ON, Canada
| | - Matcheri S Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Massachusetts Mental Health Center Division of Public Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Synthia Guimond
- Institute of Mental Health Research, Royal Ottawa Mental Health Centre, Ottawa, ON, Canada; Department of Psychology, Carleton University, Ottawa, ON, Canada; Department of Neuroscience, Carleton University, Ottawa, ON, Canada; Department of Psychoeducation and Psychology, University of Quebec in Outaouais, Gatineau, QC, Canada; Department of Psychiatry, University of Ottawa, Ottawa, ON, Canada.
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Alkan E, Evans SL. Clustering of cognitive subtypes in schizophrenia patients and their siblings: relationship with regional brain volumes. NPJ SCHIZOPHRENIA 2022; 8:50. [PMID: 35853888 PMCID: PMC9261107 DOI: 10.1038/s41537-022-00242-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Accepted: 02/23/2022] [Indexed: 11/09/2022]
Abstract
AbstractSchizophrenia patients (SZH) often show impaired cognition and reduced brain structural volumes; these deficits are also detectable in healthy relatives of SZH. However, there is considerable heterogeneity: a sizable percentage of SZH are relatively cognitively intact; clustering strategies have proved useful for categorising into cognitive subgroups. We used a clustering strategy to investigate relationships between subgroup assignment and brain volumes, in 102 SZH (N = 102) and 32 siblings of SZH (SZH-SIB), alongside 92 controls (CON) and 48 of their siblings. SZH had poorer performance in all cognitive domains, and smaller brain volumes within prefrontal and temporal regions compared to controls. We identified three distinct cognitive clusters (‘neuropsychologically normal’, ‘intermediate’, ‘cognitively impaired’) based on age- and gender-adjusted cognitive domain scores. The majority of SZH (60.8%) were assigned to the cognitively impaired cluster, while the majority of SZH-SIB (65.6%) were placed in the intermediate cluster. Greater right middle temporal volume distinguished the normal cluster from the more impaired clusters. Importantly, the observed brain volume differences between SZH and controls disappeared after adjustment for cluster assignment. This suggests an intimate link between cognitive performance levels and regional brain volume differences in SZH. This highlights the importance of accounting for heterogeneity in cognitive performance within SZH populations when attempting to characterise the brain structural abnormalities associated with the disease.
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Baliga SP, Kedare JS, Mankar UJ, Kamath RM. Subjective Cognitive Complaints in Unaffected First-Degree Relatives of Schizophrenia Patients: Relation to Cognitive Performance, Psychotic Experiences, and Social Functioning. Indian J Psychol Med 2022; 44:129-136. [PMID: 35655986 PMCID: PMC9120994 DOI: 10.1177/02537176211010504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Neurocognitive deficits are well-documented in patients of schizophrenia and their first-degree relatives (FDRs). Metacognitive awareness of these deficits, called neurocognitive insight (NI), has been found to be poor in schizophrenia patients but has not been assessed in their FDRs. This study evaluated NI and its relationship with objective cognitive performance, a history of psychotic experiences (PEs), and social functioning in unaffected FDRs. METHODS This cross-sectional study was conducted at the outpatient department of a tertiary care teaching hospital. A total of 100 FDRs were assessed for PEs and evaluated for subjective cognitive complaints (SCC), objective cognitive performance, and social functioning using the Subjective Scale to Investigate Cognition in Schizophrenia, neurocognitive tests from the National Institute of Mental Health and Neurosciences battery, and SCARF Social Functioning Index, respectively. RESULTS Compared to normative data, episodic memory was the most commonly impaired domain (up to 72% of participants), followed by working memory, attention, and executive function. There was no correlation between SCC and neuropsychological test scores in the corresponding cognitive domains, implying poor NI. 15% of participants had a lifetime history of PEs. This group had significantly higher SCC as compared to those without PEs (U = 0.366, P = 0.009, r = 0.26). A regression analysis showed that the FDRs' social functioning reduced by 0.178 units for each unit increase in SCC [F (1,98) = 5.198, P = 0.025]. CONCLUSION Similar to schizophrenia patients, FDRs also have poor NI. The severity and progression of SCC could be explored as a possible marker for screening and monitoring FDRs at an ultrahigh risk for psychosis. Importantly, even in unaffected FDRs, SCC could affect socio-occupational functioning and need further research.
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Affiliation(s)
- Sachin P Baliga
- Dept. of Psychiatry, BYL Nair Charitable Hospital and Topiwala National Medical College, Mumbai, Maharashtra, India
| | - Jahnavi S Kedare
- Dept. of Psychiatry, BYL Nair Charitable Hospital and Topiwala National Medical College, Mumbai, Maharashtra, India
| | - Utkarsh J Mankar
- Dept. of Psychiatry, Sion Hospital and Lokmanya Tilak Memorial Medical College, Mumbai, Maharashtra, India
| | - Ravindra M Kamath
- Dept. of Psychiatry, BYL Nair Charitable Hospital and Topiwala National Medical College, Mumbai, Maharashtra, India
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Andrade C. The Limitations of Quasi-Experimental Studies, and Methods for Data Analysis When a Quasi-Experimental Research Design Is Unavoidable. Indian J Psychol Med 2021; 43:451-452. [PMID: 34584313 PMCID: PMC8450731 DOI: 10.1177/02537176211034707] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
A quasi-experimental (QE) study is one that compares outcomes between intervention groups where, for reasons related to ethics or feasibility, participants are not randomized to their respective interventions; an example is the historical comparison of pregnancy outcomes in women who did versus did not receive antidepressant medication during pregnancy. QE designs are sometimes used in noninterventional research, as well; an example is the comparison of neuropsychological test performance between first degree relatives of schizophrenia patients and healthy controls. In QE studies, groups may differ systematically in several ways at baseline, itself; when these differences influence the outcome of interest, comparing outcomes between groups using univariable methods can generate misleading results. Multivariable regression is therefore suggested as a better approach to data analysis; because the effects of confounding variables can be adjusted for in multivariable regression, the unique effect of the grouping variable can be better understood. However, although multivariable regression is better than univariable analyses, there are inevitably inadequately measured, unmeasured, and unknown confounds that may limit the validity of the conclusions drawn. Investigators should therefore employ QE designs sparingly, and only if no other option is available to answer an important research question.
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Affiliation(s)
- Chittaranjan Andrade
- Dept. of Clinical Psychopharmacology and Neurotoxicology, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India
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Wijtenburg SA, Wang M, Korenic SA, Chen S, Barker PB, Rowland LM. Metabolite Alterations in Adults With Schizophrenia, First Degree Relatives, and Healthy Controls: A Multi-Region 7T MRS Study. Front Psychiatry 2021; 12:656459. [PMID: 34093272 PMCID: PMC8170030 DOI: 10.3389/fpsyt.2021.656459] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 04/06/2021] [Indexed: 11/13/2022] Open
Abstract
Proton magnetic resonance spectroscopy (MRS) studies in schizophrenia have shown altered GABAergic, glutamatergic, and bioenergetic pathways, but if these abnormalities are brain region or illness-stage specific is largely unknown. MRS at 7T MR enables reliable quantification of multiple metabolites, including GABA, glutamate (Glu) and glutamine (Gln), from multiple brain regions within the time constraints of a clinical examination. In this study, GABA, Glu, Gln, the ratio Gln/Glu, and lactate (Lac) were quantified using 7T MRS in five brain regions in adults with schizophrenia (N = 40), first-degree relatives (N = 11), and healthy controls (N = 38). Metabolites were analyzed for differences between groups, as well as between subjects with schizophrenia with either short (<5 years, N = 19 or long (>5 years, N = 21) illness duration. For analyses between the three groups, there were significant glutamatergic and GABAergic differences observed in the anterior cingulate, centrum semiovale, and dorsolateral prefrontal cortex. There were also significant relationships between anterior cingulate cortex, centrum semiovale, and dorsolateral prefrontal cortex and cognitive measures. There were also significant glutamatergic, GABAergic, and lactate differences between subjects with long and short illness duration in the anterior cingulate, centrum semiovale, dorsolateral prefrontal cortex, and hippocampus. Finally, negative symptom severity ratings were significantly correlated with both anterior cingulate and centrum semiovale metabolite levels. In summary, 7T MRS shows multi-region differences in GABAergic and glutamatergic metabolites between subjects with schizophrenia, first-degree relatives and healthy controls, suggesting relatively diffuse involvement that evolves with illness duration. Unmedicated first-degree relatives share some of the same metabolic characteristics as patients with a diagnosis of schizophrenia, suggesting that these differences may reflect a genetic vulnerability and are not solely due to the effects of antipsychotic interventions.
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Affiliation(s)
- S Andrea Wijtenburg
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Min Wang
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Stephanie A Korenic
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Shuo Chen
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Peter B Barker
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,FM Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Laura M Rowland
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, MD, United States
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Xi C, Liu ZN, Yang J, Zhang W, Deng MJ, Pan YZ, Cheng YQ, Pu WD. Schizophrenia patients and their healthy siblings share decreased prefronto-thalamic connectivity but not increased sensorimotor-thalamic connectivity. Schizophr Res 2020; 222:354-361. [PMID: 32507372 DOI: 10.1016/j.schres.2020.04.033] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 04/12/2020] [Accepted: 04/26/2020] [Indexed: 12/12/2022]
Abstract
The pattern of decreased prefronto-thalamic connectivity and increased sensorimotor-thalamic connectivity has been consistently documented in schizophrenia. However, whether this thalamo-cortical abnormality pattern is of genetic predisposition remains unknown. The present study for the first time aimed to investigate the common and distinct characteristics of this circuit in schizophrenia patients and their unaffected siblings who share half of the patient's genotype. Totally 293 participants were recruited into this study including 94 patients with schizophrenia, 96 their healthy siblings, and 103 healthy controls scanned using gradient-echo echo-planar imaging at rest. By using a fine-grained atlas of thalamus with 16 sub-regions, we mapped the thalamocortical network in three groups. Decreased thalamo-prefronto-cerebellar connectivity was shared between schizophrenia and their healthy siblings, but increased sensorimotor-thalamic connectivity was only found in schizophrenia. The shared thalamo-prefronto-cerebellar dysconnectivity showed an impressively gradient reduction pattern in patients and siblings comparing to controls: higher in the controls, lower in the patients and intermediate in the siblings. Anatomically, the decreased thalamic connectivity mostly centered on the pre-frontal thalamic subregions locating at the mediodorsal nucleus, while the increased functional connectivity with sensorimotor cortices was only observed in the caudal temporal thalamic subregion anchoring at the dorsal and ventral lateral nuclei. Moreover, both decreased thalamo-prefronto-cerebellar connectivity and increased sensorimotor-thalamic connectivity were related to clinical symptoms in patients. Our findings extend the evidence that the decreased thalamo-prefronto-cerebellar connectivity may be related to the high genetic risk in schizophrenia, while increased sensorimotor-thalamic connectivity potentially represents a neural biomarker for this severe mental disorder.
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Affiliation(s)
- Chang Xi
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha 410011, China; Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, China; The China National Clinical Research Center for Mental Health Disorders, Changsha, China
| | - Zhe-Ning Liu
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, China; The China National Clinical Research Center for Mental Health Disorders, Changsha, China
| | - Jie Yang
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, China; The China National Clinical Research Center for Mental Health Disorders, Changsha, China
| | - Wen Zhang
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, China; The China National Clinical Research Center for Mental Health Disorders, Changsha, China
| | - Meng-Jie Deng
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, China; The China National Clinical Research Center for Mental Health Disorders, Changsha, China
| | - Yun-Zhi Pan
- Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, China; Mental Health Institute of the Second Xiangya Hospital, Central South University, Changsha, China; The China National Clinical Research Center for Mental Health Disorders, Changsha, China
| | - Yu-Qi Cheng
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Wei-Dan Pu
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha 410011, China; The China National Clinical Research Center for Mental Health Disorders, Changsha, China.
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Fiksinski AM, Breetvelt EJ, Lee YJ, Boot E, Butcher N, Palmer L, Chow EWC, Kahn RS, Vorstman JAS, Bassett AS. Neurocognition and adaptive functioning in a genetic high risk model of schizophrenia. Psychol Med 2019; 49:1047-1054. [PMID: 30064532 DOI: 10.1017/s0033291718001824] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND Identifying factors that influence the functional outcome is an important goal in schizophrenia research. The 22q11.2 deletion syndrome (22q11DS) is a unique genetic model with high risk (20-25%) for schizophrenia. This study aimed to identify potentially targetable domains of neurocognitive functioning associated with functional outcome in adults with 22q11DS. METHODS We used comprehensive neurocognitive test data available for 99 adults with 22q11DS (n = 43 with schizophrenia) and principal component analysis to derive four domains of neurocognition (Verbal Memory, Visual and Logical Memory, Motor Performance, and Executive Performance). We then investigated the association of these neurocognitive domains with adaptive functioning using Vineland Adaptive Behavior Scales data and a linear regression model that accounted for the effects of schizophrenia status and overall intellectual level. RESULTS The regression model explained 46.8% of the variance in functional outcome (p < 0.0001). Executive Performance was significantly associated with functional outcome (p = 0.048). Age and schizophrenia were also significant factors. The effects of Executive Performance on functioning did not significantly differ between those with and without psychotic illness. CONCLUSION The findings provide the impetus for further studies to examine the potential of directed (early) interventions targeting Executive Performance to improve long-term adaptive functional outcome in individuals with, or at high risk for, schizophrenia. Moreover, the neurocognitive test profiles may benefit caregivers and clinicians by providing insight into the relative strengths and weaknesses of individuals with 22q11DS, with and without psychotic illness.
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Affiliation(s)
- A M Fiksinski
- Department of Psychiatry,Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht,Utrecht,The Netherlands
| | - E J Breetvelt
- Clinical Genetics Research Program, Centre for Addiction and Mental Health,Toronto, Ontario,Canada
| | - Y J Lee
- Clinical Genetics Research Program, Centre for Addiction and Mental Health,Toronto, Ontario,Canada
| | - E Boot
- Clinical Genetics Research Program, Centre for Addiction and Mental Health,Toronto, Ontario,Canada
| | - N Butcher
- Clinical Genetics Research Program, Centre for Addiction and Mental Health,Toronto, Ontario,Canada
| | - L Palmer
- The Dalglish Family 22q Clinic for 22q11.2 Deletion Syndrome,Toronto General Hospital,University Health Network,Toronto, Ontario,Canada
| | - E W C Chow
- Clinical Genetics Research Program, Centre for Addiction and Mental Health,Toronto, Ontario,Canada
| | - R S Kahn
- Department of Psychiatry,Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht,Utrecht,The Netherlands
| | - J A S Vorstman
- Department of Psychiatry,Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht,Utrecht,The Netherlands
| | - A S Bassett
- Clinical Genetics Research Program, Centre for Addiction and Mental Health,Toronto, Ontario,Canada
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Viswanath B, Rao NP, Narayanaswamy JC, Sivakumar PT, Kandasamy A, Kesavan M, Mehta UM, Venkatasubramanian G, John JP, Mukherjee O, Purushottam M, Kannan R, Mehta B, Kandavel T, Binukumar B, Saini J, Jayarajan D, Shyamsundar A, Moirangthem S, Vijay Kumar KG, Thirthalli J, Chandra PS, Gangadhar BN, Murthy P, Panicker MM, Bhalla US, Chattarji S, Benegal V, Varghese M, Reddy JYC, Raghu P, Rao M, Jain S. Discovery biology of neuropsychiatric syndromes (DBNS): a center for integrating clinical medicine and basic science. BMC Psychiatry 2018; 18:106. [PMID: 29669557 PMCID: PMC5907468 DOI: 10.1186/s12888-018-1674-2] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Accepted: 03/21/2018] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND There is emerging evidence that there are shared genetic, environmental and developmental risk factors in psychiatry, that cut across traditional diagnostic boundaries. With this background, the Discovery biology of neuropsychiatric syndromes (DBNS) proposes to recruit patients from five different syndromes (schizophrenia, bipolar disorder, obsessive compulsive disorder, Alzheimer's dementia and substance use disorders), identify those with multiple affected relatives, and invite these families to participate in this study. The families will be assessed: 1) To compare neuro-endophenotype measures between patients, first degree relatives (FDR) and healthy controls., 2) To identify cellular phenotypes which differentiate the groups., 3) To examine the longitudinal course of neuro-endophenotype measures., 4) To identify measures which correlate with outcome, and 5) To create a unified digital database and biorepository. METHODS The identification of the index participants will occur at well-established specialty clinics. The selected individuals will have a strong family history (with at least another affected FDR) of mental illness. We will also recruit healthy controls without family history of such illness. All recruited individuals (N = 4500) will undergo brief clinical assessments and a blood sample will be drawn for isolation of DNA and peripheral blood mononuclear cells (PBMCs). From among this set, a subset of 1500 individuals (300 families and 300 controls) will be assessed on several additional assessments [detailed clinical assessments, endophenotype measures (neuroimaging- structural and functional, neuropsychology, psychophysics-electroencephalography, functional near infrared spectroscopy, eye movement tracking)], with the intention of conducting repeated measurements every alternate year. PBMCs from this set will be used to generate lymphoblastoid cell lines, and a subset of these would be converted to induced pluripotent stem cell lines and also undergo whole exome sequencing. DISCUSSION We hope to identify unique and overlapping brain endophenotypes for major psychiatric syndromes. In a proportion of subjects, we expect these neuro-endophenotypes to progress over time and to predict treatment outcome. Similarly, cellular assays could differentiate cell lines derived from such groups. The repository of biomaterials as well as digital datasets of clinical parameters, will serve as a valuable resource for the broader scientific community who wish to address research questions in the area.
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Affiliation(s)
- Biju Viswanath
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - Naren P. Rao
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | | | | | - Arun Kandasamy
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - Muralidharan Kesavan
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | | | | | - John P. John
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - Odity Mukherjee
- Institute for Stem Cell Biology and Regenerative Medicine (InStem), Bangalore, India
| | - Meera Purushottam
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - Ramakrishnan Kannan
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - Bhupesh Mehta
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - Thennarasu Kandavel
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - B. Binukumar
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - Jitender Saini
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - Deepak Jayarajan
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - A. Shyamsundar
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - Sydney Moirangthem
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - K. G. Vijay Kumar
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - Jagadisha Thirthalli
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - Prabha S. Chandra
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | | | - Pratima Murthy
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - Mitradas M. Panicker
- National Centre for Biological Sciences, Tata Institute of Fundamental Research (NCBS-TIFR), Bangalore, India
| | - Upinder S. Bhalla
- National Centre for Biological Sciences, Tata Institute of Fundamental Research (NCBS-TIFR), Bangalore, India
| | - Sumantra Chattarji
- Institute for Stem Cell Biology and Regenerative Medicine (InStem), Bangalore, India
- National Centre for Biological Sciences, Tata Institute of Fundamental Research (NCBS-TIFR), Bangalore, India
| | - Vivek Benegal
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | - Mathew Varghese
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
| | | | - Padinjat Raghu
- National Centre for Biological Sciences, Tata Institute of Fundamental Research (NCBS-TIFR), Bangalore, India
| | - Mahendra Rao
- Institute for Stem Cell Biology and Regenerative Medicine (InStem), Bangalore, India
| | - Sanjeev Jain
- National Institute of Mental Health and Neuro Sciences (NIMHANS), Bangalore, India
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