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Dive into the research topics where Jaya Padmanabhan is active.

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Featured researches published by Jaya Padmanabhan.


Schizophrenia Bulletin | 2015

Correlations Between Brain Structure and Symptom Dimensions of Psychosis in Schizophrenia, Schizoaffective, and Psychotic Bipolar I Disorders

Jaya Padmanabhan; Neeraj Tandon; Chiara S. Haller; Ian T. Mathew; Shaun M. Eack; Brett A. Clementz; Godfrey D. Pearlson; John A. Sweeney; Carol A. Tamminga; Matcheri S. Keshavan

INTRODUCTION Structural alterations may correlate with symptom severity in psychotic disorders, but the existing literature on this issue is heterogeneous. In addition, it is not known how cortical thickness and cortical surface area correlate with symptom dimensions of psychosis. METHODS Subjects included 455 individuals with schizophrenia, schizoaffective, or bipolar I disorders. Data were obtained as part of the Bipolar Schizophrenia Network for Intermediate Phenotypes study. Diagnosis was made through the Structured Clinical Interview for DSM-IV. Positive and negative symptom subscales were assessed using the Positive and Negative Syndrome Scale. Structural brain measurements were extracted from T1-weight structural MRIs using FreeSurfer v5.1 and were correlated with symptom subscales using partial correlations. Exploratory factor analysis was also used to identify factors among those regions correlating with symptom subscales. RESULTS The positive symptom subscale correlated inversely with gray matter volume (GMV) and cortical thickness in frontal and temporal regions, whereas the negative symptom subscale correlated inversely with right frontal cortical surface area. Among regions correlating with the positive subscale, factor analysis identified four factors, including a temporal cortical thickness factor and frontal GMV factor. Among regions correlating with the negative subscale, factor analysis identified a frontal GMV-cortical surface area factor. There was no significant diagnosis by structure interactions with symptom severity. CONCLUSIONS Structural measures correlate with positive and negative symptom severity in psychotic disorders. Cortical thickness demonstrated more associations with psychopathology than cortical surface area.


F1000 Medicine Reports | 2014

Recent advances in understanding schizophrenia.

Chiara S. Haller; Jaya Padmanabhan; Paulo Lizano; John Torous; Matcheri S. Keshavan

Schizophrenia is a highly disabling disorder whose causes remain to be better understood, and treatments have to be improved. However, several recent advances have been made in diagnosis, etiopathology, and treatment. Whereas reliability of diagnosis has improved with operational criteria, including Diagnostic and Statistical Manual of Mental Disorders, (DSM) Fifth Edition, validity of the disease boundaries remains unclear because of substantive overlaps with other psychotic disorders. Recent emphasis on dimensional approaches and translational bio-behavioral research domain criteria may eventually help move toward a neuroscience-based definition of schizophrenia. The etiology of schizophrenia is now thought to be multifactorial, with multiple small-effect and fewer large-effect susceptibility genes interacting with several environmental factors. These factors may lead to developmentally mediated alterations in neuroplasticity, manifesting in a cascade of neurotransmitter and circuit dysfunctions and impaired connectivity with an onset around early adolescence. Such etiopathological understanding has motivated a renewed search for novel pharmacological as well as psychotherapeutic targets. Addressing the core features of the illness, such as cognitive deficits and negative symptoms, and developing hypothesis-driven early interventions and preventive strategies are high-priority goals for the field. Schizophrenia is a severe, chronic mental disorder and is among the most disabling disorders in all of medicine. It is estimated by the National Institute of Mental Health (NIMH) that 2.4 million people over the age of 18 in the US suffer from schizophrenia. This illness typically begins in adolescence and derails the formative goals of school, family, and work, leading to considerable suffering and disability and reduced life expectancy by about 20 years. Treatment outcomes are variable, and some people are successfully treated and reintegrated (i.e. go back to work). Despite the effort of many experts in the field, however, schizophrenia remains a chronic relapsing and remitting disorder associated with significant impairments in social and vocational functioning and a shortened lifespan. Comprehensive treatment entails a multi-modal approach, including psychopharmacology, psychosocial interventions, and assistance with housing and financial sustenance. Research to date suggests a network of genetic, neural, behavioral, and environmental factors to be responsible for its development and course. This article aims to summarize and explain recent advancements in research on schizophrenia, to suggest how these recent discoveries may lead to a better understanding and possible further development of effective therapies, and to highlight the paradigm shifts that have taken place in our understanding of the diagnosis, etiopathology, and treatment.


Schizophrenia Research | 2015

Increased cardiometabolic dysfunction in first-degree relatives of patients with psychotic disorders

Suraj Sarvode Mothi; Neeraj Tandon; Jaya Padmanabhan; Ian T. Mathew; Brett A. Clementz; Carol A. Tamminga; Godfrey D. Pearlson; John A. Sweeney; Matcheri S. Keshavan

INTRODUCTION Elevated prevalence of comorbid cardio-vascular and metabolic dysfunction (CMD) is consistently reported in patients with severe psychotic disorders such as schizophrenia (SZ), schizoaffective (SZA) and bipolar disorder (BP-P). Since both psychosis and CMD are substantively heritable in nature, we attempted to investigate the occurrence of CMD disorders in first-degree relatives of probands with psychosis. METHODS Our sample included 861 probands with a diagnosis of SZ (n=354), SZA (n=212) and BP-P (n=295), 776 first-degree relatives of probands and 416 healthy controls. Logistic regression was used to compare prevalence of any CMD disorders (diabetes, hypertension, hyperlipidemia or coronary artery disease) across groups. Post hoc tests of independence checked for CMD prevalence across psychosis diagnosis (SZ, SZA and BP-P), both in relatives of probands and within probands themselves. RESULTS After controlling for potential confounders, first-degree relatives with (p<0.001) and without (p=0.03) Axis I non-psychotic or Axis- II cluster disorders were at a significant risk for CMD compared to controls. No significant difference (p=0.42) was observed in prevalence of CMD between relatives of SZ, SZA and BP-P, or between psychosis diagnoses for probands (p=0.25). DISCUSSION Prevalence of CMD was increased in the first-degree relatives of psychosis subjects. This finding suggests the possibility of overlapping genetic contributions to CMD and psychosis. Increased somatic disease burden in relatives of psychotic disorder probands points to need for early detection and preventive efforts in this population.


Biological Psychiatry: Cognitive Neuroscience and Neuroimaging | 2017

Strategies for Advancing Disease Definition Using Biomarkers and Genetics: The Bipolar and Schizophrenia Network for Intermediate Phenotypes

Carol A. Tamminga; Godfrey D. Pearlson; Ana D. Stan; Robert D. Gibbons; Jaya Padmanabhan; Matcheri S. Keshavan; Brett A. Clementz

It is critical for psychiatry as a field to develop approaches to define the molecular, cellular, and circuit basis of its brain diseases, especially for serious mental illnesses, and then to use these definitions to generate biologically based disease categories, as well as to explore disease mechanisms and illness etiologies. Our current reliance on phenomenology is inadequate to support exploration of molecular treatment targets and disease formulations, and the leap directly from phenomenology to disease biology has been limiting because of broad heterogeneity within conventional diagnoses. The questions addressed in this review are formulated around how we can use brain biomarkers to achieve disease categories that are biologically based. We have grouped together a series of vignettes as examples of early approaches, all using the Bipolar and Schizophrenia Network on Intermediate Phenotypes (BSNIP) biomarker database and collaborators, starting off with describing the foundational statistical methods for these goals. We use primarily criterion-free statistics to identify pertinent groups of involved genes related to psychosis as well as symptoms, and finally, to create new biologically based disease cohorts within the psychopathological dimension of psychosis. Although we do not put these results forward as final formulations, they represent a novel effort to rely minimally on phenomenology as a diagnostic tool and to fully embrace brain characteristics of structure, as well as molecular and cellular characteristics and function, to support disease definition in psychosis.


Journal of Psychiatric Research | 2016

Polygenic risk for type 2 diabetes mellitus among individuals with psychosis and their relatives

Jaya Padmanabhan; Pranav Nanda; Neeraj Tandon; Suraj Sarvode Mothi; Nicolas R. Bolo; Steven A. McCarroll; Brett A. Clementz; Elliot S. Gershon; Godfrey D. Pearlson; John A. Sweeney; Carol A. Tamminga; Matcheri S. Keshavan

BACKGROUND An elevated prevalence of Type 2 diabetes (T2D) has been observed in people with psychotic disorders and their relatives compared to the general population. It is not known whether this population also has increased genetic risk for T2D. METHODS Subjects included probands with schizophrenia, schizoaffective disorder, or psychotic bipolar I disorder, their first-degree relatives without psychotic disorders, and healthy controls, who participated in the Bipolar Schizophrenia Network for Intermediate Phenotypes study. We constructed sets of polygenic risk scores for T2D (PGRST2D) and schizophrenia (PGRSSCHIZ) using publicly available data from genome-wide association studies. We then explored the correlation of PGRST2D with psychiatric proband or relative status, and with self-reported diabetes. Caucasians and African-Americans were analyzed separately. We also evaluated correlations between PGRSSCHIZ and diabetes mellitus among Caucasian probands and their relatives. RESULTS In Caucasians, PGRST2D was correlated with self-reported diabetes mellitus within probands, but was not correlated with proband or relative status in the whole sample. In African-Americans, a PGRST2D based on selected risk alleles for T2D in this population did not correlate with proband or relative status. PGRSSCHIZ was not correlated with self-reported diabetes within Caucasian probands. CONCLUSION Differences in polygenic risk for T2D do not explain the increased prevalence of diabetes mellitus observed in psychosis probands and their relatives.


Schizophrenia Research | 2017

Novel gene-brain structure relationships in psychotic disorder revealed using parallel independent component analyses

Neeraj Tandon; Pranav Nanda; Jaya Padmanabhan; Ian T. Mathew; Shaun M. Eack; Balaji Narayanan; Shashwath A. Meda; Sarah E. Bergen; Gualbert Ruaño; Andreas Windemuth; Mohan Kocherla; Tracey L. Petryshen; Brett A. Clementz; John A. Sweeney; Carol A. Tamminga; Godfrey D. Pearlson; Matcheri S. Keshavan

BACKGROUND Schizophrenia, schizoaffective disorder, and psychotic bipolar disorder overlap with regard to symptoms, structural and functional brain abnormalities, and genetic risk factors. Neurobiological pathways connecting genes to clinical phenotypes across the spectrum from schizophrenia to psychotic bipolar disorder remain largely unknown. METHODS We examined the relationship between structural brain changes and risk alleles across the psychosis spectrum in the multi-site Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) cohort. Regional MRI brain volumes were examined in 389 subjects with a psychotic disorder (139 schizophrenia, 90 schizoaffective disorder, and 160 psychotic bipolar disorder) and 123 healthy controls. 451,701 single-nucleotide polymorphisms were screened and processed using parallel independent component analysis (para-ICA) to assess associations between genes and structural brain abnormalities in probands. RESULTS 482 subjects were included after quality control (364 individuals with psychotic disorder and 118 healthy controls). Para-ICA identified four genetic components including several risk genes already known to contribute to schizophrenia and bipolar disorder and revealed three structural components that showed overlapping relationships with the disease risk genes across the three psychotic disorders. Functional ontologies representing these gene clusters included physiological pathways involved in brain development, synaptic transmission, and ion channel activity. CONCLUSIONS Heritable brain structural findings such as reduced cortical thickness and surface area in probands across the psychosis spectrum were associated with somewhat distinct genes related to putative disease pathways implicated in psychotic disorders. This suggests that brain structural alterations might represent discrete psychosis intermediate phenotypes along common neurobiological pathways underlying disease expression across the psychosis spectrum.


bioRxiv | 2017

Higher genetic risk of schizophrenia is associated with lower cognitive performance in healthy individuals

Rebecca Shafee; Pranav Nanda; Jaya Padmanabhan; Neeraj Tandon; Ney Alliey-Rodriguez; Richard S.E. Keefe; Scot K. Hill; Jeffrey R. Bishop; Brett A. Clementz; Carol A. Tamminga; Elliot S. Gershon; Godfrey D. Pearlson; Matcheri S. Keshavan; John A. Sweeney; Elise B. Robinson; Steven A. McCarroll

Psychotic disorders including schizophrenia are commonly accompanied by cognitive deficits. Recent studies have reported negative genetic correlations between schizophrenia and indicators of cognitive ability such as general intelligence and processing speed. Here we compare the effect of the genetic risk of schizophrenia (PRSSCZ) on measures that differ in their relationships with psychosis onset: a measure of current cognitive abilities (the Brief Assessment of Cognition in Schizophrenia, BACS) that is greatly reduced in psychosis patients; a measure of premorbid intelligence that is minimally affected by psychosis (the Wide-Range Achievement Test, WRAT); and educational attainment (EY), which covaries with both BACS and WRAT. Using genome-wide SNP data from 314 psychotic and 423 healthy research participants in the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) Consortium, we investigated the association of PRSSCZ with BACS, WRAT and EY. Among apparently healthy individuals, greater genetic risk for schizophrenia (PRSSCZ) was associated with lower BACS scores (r = −0.19, p = 1 × 10−4 at PT = 1 × 10−4) but did not associate with WRAT or EY, suggesting that these areas of cognition vary in their etiologic relationships with schizophrenia. Among individuals with psychosis, PRSSCZ did not associate with variation in cognitive performance. These findings suggest that the same cognitive abilities that are disrupted in psychotic disorders are also associated with schizophrenia genetic risk in the general population. Specific cognitive phenotypes, independent of education or general intelligence, could be more deeply studied for insight into the specific processes affected by the genetic influences on psychosis. Significance Psychotic disorders such as schizophrenia often involve profound cognitive deficits, the genetic underpinnings of which remain to be elucidated. Poor educational performance early in life is a well-known risk factor for future psychotic illness, potentially reflecting either shared genetic influences or other risk factors that are epidemiologically correlated. Here we show that, in apparently healthy individuals, common genetic risk factors for schizophrenia associate with lower performance in areas of cognition that are impaired in psychotic disorders but do not associate independently with educational attainment or more general measures of intelligence. These results suggest that specific cognitive phenotypes – independent of education or general intelligence – could be more deeply studied for insight into the processes affected by the genetic influences on psychosis.


Translational Psychiatry | 2018

Polygenic risk for schizophrenia and measured domains of cognition in individuals with psychosis and controls.

Rebecca Shafee; Pranav Nanda; Jaya Padmanabhan; Neeraj Tandon; Ney Alliey-Rodriguez; Sreeja Kalapurakkel; Daniel J. Weiner; Raquel E. Gur; Richard S.E. Keefe; Scot K. Hill; Jeffrey R. Bishop; Brett A. Clementz; Carol A. Tamminga; Elliot S. Gershon; Godfrey D. Pearlson; Matcheri S. Keshavan; John A. Sweeney; Steven A. McCarroll; Elise B. Robinson

Psychotic disorders including schizophrenia are commonly accompanied by cognitive deficits. Recent studies have reported negative genetic correlations between schizophrenia and indicators of cognitive ability such as general intelligence and processing speed. Here we compare the effect of polygenetic risk for schizophrenia (PRSSCZ) on measures that differ in their relationships with psychosis onset: a measure of current cognitive abilities (the Brief Assessment of Cognition in Schizophrenia, BACS) that is greatly reduced in psychotic disorder patients, a measure of premorbid intelligence that is minimally affected by psychosis onset (the Wide-Range Achievement Test, WRAT); and educational attainment (EY), which covaries with both BACS and WRAT. Using genome-wide single nucleotide polymorphism (SNP) data from 314 psychotic and 423 healthy research participants in the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) Consortium, we investigated the association of PRSSCZ with BACS, WRAT, and EY. Among apparently healthy individuals, greater genetic risk for schizophrenia (PRSSCZ) was significantly associated with lower BACS scores (r = −0.17, p = 6.6 × 10−4 at PT = 1 × 10−4), but not with WRAT or EY. Among individuals with psychosis, PRSSCZ did not associate with variations in any of these three phenotypes. We further investigated the association between PRSSCZ and WRAT in more than 4500 healthy subjects from the Philadelphia Neurodevelopmental Cohort. The association was again null (p > 0.3, N = 4511), suggesting that different cognitive phenotypes vary in their etiologic relationship with schizophrenia.


Translational Psychiatry | 2018

VEGFA GENE variation influences hallucinations and frontotemporal morphology in psychotic disorders: a B-SNIP study

Paulo Lizano; Olivia Lutz; George Ling; Jaya Padmanabhan; Neeraj Tandon; John A. Sweeney; Carol A. Tamminga; Godfrey D. Pearlson; Gualberto Ruaño; Mohan Kocherla; Andreas Windemuth; Brett A. Clementz; Elliot S. Gershon; Matcheri S. Keshavan

Vascular endothelial growth factor A (VEGFA) dysfunction may contribute to a number of pathological processes that characterize psychotic disorders. However, the influence of VEGFA gene variants on clinical and neuroimaging phenotypes in psychotic disorders has yet to be shown. In the present study, we examined whether different VEGFA gene variants influence psychosis risk, symptom severity, cognition, and brain volume. The study group included 480 probands (Bipolar I disorder with psychosis, n = 205; Schizoaffective disorder, n = 112; Schizophrenia, n = 163) and 126 healthy controls that were recruited across six sites in the B-SNIP consortium. VEGFA variants identified for analysis (rs699947, rs833070, and rs2146323) were quantified via SNP chip array. We assessed symptoms and cognition using standardized clinical and neuropsychological batteries. The dorsolateral prefrontal cortex (DLPFC), medial temporal lobe, and hippocampal volumes were quantified using FreeSurfer. In our sample, VEGFA rs2146323 A- carriers showed reduced odds of being a proband (p = 0.037, OR = 0.65, 95% CI = 0.43–0.98) compared to noncarriers, but not for rs699947 or rs833070. In probands, rs2146323 A- carriers demonstrated fewer hallucinations (p = 0.035, Cohen’s d = 0.194), as well as significantly greater DLPFC (p < 0.05, Cohen’s d = −0.21) and parahippocampal volumes (p < 0.01, Cohen’s d = −0.27). No clinical or neuroimaging associations were identified for rs699947 or rs833070. In general, we found that the three SNPs exhibited several significant negative relationships between psychosis symptoms and brain structure. In the probands and control groups, positive relationships were identified between several cognitive and brain volume measures. The findings suggest VEGFA effects in the DLPFC and hippocampus found in animals may also extend to humans. VEGFA variations may have important implications in identifying dimensional moderators of function that could be targeted through VEGFA-mediated interventions.


bioRxiv | 2017

Common variants of NRXN1, LRP1B and RORA are associated with increased ventricular volumes in psychosis - GWAS findings from the B-SNIP deep phenotyping study

Ney Alliey-Rodriguez; Tamar A. Grey; Rebecca Shafee; Jaya Padmanabhan; Neeraj Tandon; Madeline Klinger; Jonathan Spring; Lucas Coppes; Katherine Reis; Matcheri S. Keshavan; Diane Gage; Steven A. McCarroll; Jeffrey R. Bishop; Scot K. Hill; James L. Reilly; Rebekka Lencer; Brett A. Clementz; Peter F. Buckley; Shashwath A. Meda; Balaji Narayanan; David C. Glahn; Godfrey D. Pearlson; Elena I. Ivleva; Carol A. Tamminga; John A. Sweeney; David Curtis; Sarah K. Keedy; Judith Badner; Chunyu Liu; Elliot S. Gershon

Schizophrenia, Schizoaffective, and Bipolar Disorders share common illness traits, intermediate phenotypes and a partially overlapping polygenic basis. We performed GWAS on deep phenotyping data, including structural MRI and DTI, clinical, and behavioral scales from 1,115 cases and controls. Significant associations were observed with two cerebrospinal fluid volumes: the temporal horn of left lateral ventricle was associated with NRXN1, and the volume of the cavum septum pellucidum was associated with LRP1B and RORA. Both volumes were associated with illness. Suggestive associations were observed with local gyrification indices, fractional anisotropy and age at onset. The deep phenotyping approach allowed unexpected genetic sharing to be found between phenotypes, including temporal horn of left lateral ventricle and age at onset.

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Matcheri S. Keshavan

Beth Israel Deaconess Medical Center

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Carol A. Tamminga

University of Texas Southwestern Medical Center

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Neeraj Tandon

Beth Israel Deaconess Medical Center

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Ian T. Mathew

Beth Israel Deaconess Medical Center

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Pranav Nanda

Columbia University Medical Center

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