Publications

2026 Asian J Psychiatr

The competency-control paradox in parenting adolescents: Evidence from an Indian mixed-methods study

Sharma, E.; Jacob, P.; Binu, V. S.; Venkataramanan, S.; Benegal, V.; cVEDA consortium

Asian J Psychiatr, 120, 104965, doi: 10.1016/j.ajp.2026.104965

2025 BMC Psychiatry

The PAthways to Resilience And Mental health (PARAM) project: protocol for a multi-site developmental cohort in India

Holla, B.; Sharma, E.; Venkataramanan, S.; Zoya, S.; Shankar, K.; Kumar, A.; Basavaraj, A.; Shankarappa, B.; Mahadevan, J.; Sreeraj, V. S.; Meera, S. S.; Desai, G.; Chakrabarti, A.; Ghosh, A.; Naik, S.; Basu, D.; Kartik, K.; Kalyanram, K.; Venkatram, P.; Raman, S.; Authreya, A. J.; Singh, S. G.; Basu, A.; Setty, N. K. H.; Nebhinani, N.; Khandwal, O. P.; Singh, N.; Binu, V. S.; Viswanath, B.; Purushottam, M.; Venkatasubramanian, G.; Bharath, R. D.; Laveti, R. N.; Sudarsan, S. D.; Srikanth, T. K.; Dinakaran, D.; Kumar, K.; Shouche, Y.; Mamidi, R. S.; Dahiya, N.; Grover, A.; Chandra, P. S.; Murthy, P.; Benegal, V.

BMC Psychiatry, 25(1), 1051, doi: 10.1186/s12888-025-07492-x

Abstract

BACKGROUND: Psychiatric disorders are increasingly conceptualised within a neurodevelopmental framework, in which genetic liability interacts with environmental exposures across the lifespan to shape brain and behavioural trajectories. Deviations in these trajectories may confer vulnerability or resilience to later psychopathology. Longitudinal cohorts spanning critical developmental windows are required to map these pathways and their associated risk and protective factors. METHODS: The PAthways to Resilience And Mental health (PARAM) project is a multi-site longitudinal cohort in India, enrolling approximately 9,000 participants from the antenatal period to 30 years of age. PARAM extends the Consortium on the Vulnerability to Externalizing Disorders and Addictions (cVEDA) cohort, which recruited more than 9,000 individuals aged 6-23 years, by adding intensive follow-up from the fetal period to early childhood. Eight sites across India participate, with five recontacting their original cVEDA participants for repeated assessments. Repeated measures include questionnaires on development, temperament, and mental health; family medical and psychiatric history; assessments of environmental exposures such as adverse experiences, diet, maternal stress, toxic exposures, and screen use; and satellite-derived indicators of urbanisation and air pollution over time. Detailed examinations comprise anthropometry and body composition, neurocognitive testing, neurophysiological measures including heart rate variability and body sway, neuroimaging with 3T MRI and fNIRS, and biospecimen collection (blood, buccal swabs, hair, nails, urine, stool) for genomic, toxicological, and metabolic assays. Data are stored in a harmonised digital archive linked to a barcoded biorepository. Follow-up employs a closed cohort design for children younger than two years and an accelerated longitudinal design for older participants. Planned analyses include mixed-effects and generalized additive models for trajectories, multi-site imaging harmonisation and normative modelling, multivariate integration of multi-omic and imaging features, and predictive modelling with nested cross-validation and external validation where feasible. Missing data and attrition will be addressed using multiple imputation and inverse probability weighting. DISCUSSION: PARAM will offer insights into population-based developmental trajectories, identify modifiable risk and protective factors, and support predictive models for psychopathology. The findings are expected to inform precision interventions and public health strategies, while contributing a socio-culturally diverse resource to global mental health research.

2025 Biol Psychiatry

Shared and distinct alterations in brain structure of youth with internalizing or externalizing disorders: Findings from the ENIGMA Antisocial Behavior, ADHD, MDD, and Anxiety Working Groups

Townend, S.; Staginnus, M.; Gao, Y.; Alexander, N.; Arolt, V.; Banaschewski, T.; Bellgrove, M. A.; Benegal, V.; Blair, R. J.; Blanco-Hinojo, L.; Boeken, O. J.; Bohnlein, J.; Bolte, S.; Bonnekoh, L. M.; Brandeis, D.; Bressan, R. A.; Breuer, F.; Bruin, W. B.; Buitelaar, J. K.; Burkhouse, K. L.; Calkins, M. E.; Cano, M.; Cardoner, N.; Chen, H.; Chen, X.; Coghill, D. R.; Colins, O. F.; Connolly, C. G.; Craig, M. C.; Cullen, K. R.; Dannlowski, U.; Davey, C. G.; Dietrich, A.; Dong, D.; Freitag, C. M.; Frodl, T.; Goossens, L.; Grotegerd, D.; Gur, R. E.; Gur, R. C.; Haavik, J.; Hagan, C. C.; Hahn, T.; Hamm, A. O.; Harrison, B. J.; Hartman, C. A.; Herrmann, M. J.; Ho, T. C.; Hoekstra, P. J.; Holla, B.; Ibrahim, K.; Jackowski, A.; Jamalabadi, H.; Jiang, Y.; Kircher, T.; Konrad, K.; Kraus, A.; Kuntsi, J.; Langhammer, T.; Lazaro, L.; Leehr, E. J.; Lueken, U.; Ma, R.; MacMaster, F. P.; Manfro, G. G.; Martinelli, A.; Meinert, H.; Meinert, S.; Michalowski, J. M.; Ming, Q.; Moeck, R.; Mujica-Parodi, L. R.; Mwangi, B.; Neufeld, J.; Nigg, J. T.; O'Gorman Tuura, R. L.; Oh, H.; Oosterlaan, J.; Paloyelis, Y.; Pan, P. M.; Passamonti, L.; Penate, W.; Phan, K. L.; Plessen, K. J.; Pujol, J.; Remnelius, K. L.; Rivero, F.; Rubia, K.; Salas, R.; Salum, G. A.; Satterthwaite, T. D.; Schienle, A.; Schrammen, E.; Schruers, K. R. J.; Schumann, G.; Sethi, A.; Silk, T.; Skokauskas, N.; Smoller, J.; Soares, J. C.; et al.

Biol Psychiatry, doi: 10.1016/j.biopsych.2025.08.003

2025 Eur Psychiatry

Human development, inequality, and their associations with brain structure across 29 countries

Medel, V.; Alliende, L. M.; Bethlehem, R.; Seidlitz, J.; Ringlein, G.; Arango, C.; Arnatkevičiūtė, A.; Asmal, L.; Bellgrove, M.; Benegal, V.; Bernardo, M.; Billeke, P.; Bosch-Bayard, J.; Bressan, R.; Busatto, G.; Castro, M.; Chaim-Avancini, T.; Costanzi, M.; Czepielewski, L.; Dazzan, P.; de la Fuente-Sandoval, C.; Diaz-Caneja, C. M.; Di Forti, M.; Diaz-Zuluaga, A. M.; Du Plessis, S.; Duran, F.; Fittipaldi, S.; Fornito, A.; Freimer, N.; Gadelha, A.; Gama, C.; Garani, R.; Garcia-Rizo, C.; Gonzalez Campo, C.; Gonzalez-Valderrama, A.; Guinjoan, S.; Holla, B.; Ibañez, A.; Ivanovic, D.; Jackowski, A.; Leon-Ortiz, P.; Lochner, C.; Lopez-Jaramillo, C.; Luckhoff, H.; Massuda, R.; McGuire, P.; Miyata, J.; Mizrahi, R.; Murray, R.; Ozerdem, A.; Pan, P.; Parellada, M.; Phahladira, L.; Ramirez-Mahaluf, J. P.; Reckziegel, R.; Marques, T. R.; Reyes-Madrigal, F.; Roos, A.; Rosa, P.; Salum, G.; Scheffler, F.; Schumann, G.; Serpa, M.; Stein, D. J.; Tepper, A.; Tiego, J.; Ueno, T.; Undurraga, J.; Undurraga, E. A.; Valdes-Sosa, P.; Valli, I.; Villarreal, M.; Winton-Brown, T. T.; Yalin, N.; Zamorano, F.; Zanetti, M.; Winkler, A. M.; Evans-Lacko, S.; Crossley, N. A.

Eur Psychiatry, 68(1), e100, doi: 10.1192/j.eurpsy.2025.10060

2025 PLoS One

Examining the impact of maternal experiences of domestic violence on the mental health of their adolescent children in India

Gourisankar, A.; Ravi, P.; Kalokhe, A.; Waford Hall, R.; Vaidya, N.; Sharma, E.; Holla, B.; Basu, D.; Bharath, R. D.; Chakrabarti, A.; Desrivieres, S.; Hickman, M.; Kartik, K.; Ghattu, K.; Kalyanaraman, K.; Krishna, M.; Kuriyan, R.; Murthy, P.; Papadopoulos Orfanos, D.; Purushottam, M.; Kurpad, S. S.; Lenin Singh, R.; Lourembam Singh, R.; Nanjayya Subodh, B.; Toledano, M. B.; Benegal, V.; Schumann, G.; Kalyanram, K.

PLoS One, 20(5), e0304936, doi: 10.1371/journal.pone.0304936

2025 Scientific Data

DICOM datasets for reproducible neuroimaging research across manufacturers and software versions

Rorden, C.; Béranger, B.; Cheng, H.; Clemence, M.; Debacker, C.; Fernandez, B.; Halchenko, Y. O.; Harms, M. P.; Holla, B.; Innis, I.; Kuijer, J. P. A.; Levitas, D.; Litinas, K.; Luci, J.; Newman-Norlund, R.; Peltier, S.; Rehwald, W.; Reid, R. I.; Rogers, B.; Schwarz, C. G.; Shin, J.; Ganesan, V.; Ganji, S.; Morgan, P. S.

Scientific Data, 12(1), 1168, doi: 10.1038/s41597-025-05503-w

2025 INDIAN JOURNAL OF PSYCHIATRY

Conducting Large Scale Psychiatric Genetic Studies in India-Opportunities and Challenges

Mahadevan, J.; Ganesh, S.; Purushottam, M.; Shankarappa, B.; Holla, B.

INDIAN JOURNAL OF PSYCHIATRY, 67(SUPPL 1), S127-S127

2025 medRxiv

A transdiagnostic evaluation of adult temperamental profiles and their interactions with childhood adversities across major psychiatric disorders

Dayalamurthy, P.; Balachander, S.; Lakkireddy, S. P.; Bhattacharya, M.; Joseph, M. S.; Kumar, P.; Kannampuzha, A. J.; Mallappagari, S.; Narayana, S.; Alexander, A. C.; Muthukumaran, M.; Puzhakkal, J. C.; Thatikonda, N. S.; Sheth, S.; Ali, F.; Selvaraj, S.; Sreeraj, V. S.; Holla, B.; Venkatasubramanian, G.; John, J. P.; Viswanath, B.; Consortium, C.; Consortium, A. D. B. S. C. B. M.; Benegal, V.; Reddy, Y. C. J.; Jain, S.

medRxiv, 2025.11.12.25340048, doi: 10.1101/2025.11.12.25340048

Abstract

Background Temperamental profiles and adverse childhood experiences (ACEs) have been reported in most major psychiatric disorders. However, the nature of this relationship is complex and under-studied.Methods A total of 1162 individuals (N=532 affected; N=457 unaffected first-degree relatives (FDRs) and N=173 healthy controls) were included. Affected individuals and their FDRs were from 393 multiplex families of schizophrenia, bipolar disorder, obsessive-compulsive disorder, or alcohol use disorder. They were assessed using the self-reported Adult Temperament Questionnaire (ATQ), and the ACEs International Questionnaire. We performed frequentist and Bayesian mixed-effects regression models, to look for associations between the ATQ domains, ACEs score and their interaction with each diagnosis/familial risk. External validity of our final model was tested to predict diagnosis in an independent cohort. Receiver operator characteristic plots and the area under the curve (AUC) were used to evaluate its prediction accuracy.Results All temperamental domains: negative affectivity (NA), extraversion (EV), effortful control (EC) and orienting sensitivity (OS) had significant associations in a unique configuration within each of the four diagnoses and their familial risk. ACEs, and its interactions were significantly associated with alcohol use disorder only. In the external validation dataset, the final model was found to successfully predict AUD (AUC=0.82), BD (AUC=0.75) and OCD (AUC=0.74), but not SCZ (AUC=0.53).Conclusions These findings provide unique insights into the complexities of temperament in major psychiatric disorders, and emphasize the importance of evaluating temperament in conjunction with childhood adversity to characterize risk.Graphical Abstract (Study Methodology):Competing Interest StatementThe authors have declared no competing interest.Funding StatementThis research is funded by the Accelerator program for Discovery in Brain disorders using Stem cells (ADBS) (jointly funded by the Department of Biotechnology, Government of India, and the Pratiksha trust; Grant BT/PR17316/MED/31/326/2015) and), and the Centre for Brain and Mind (CBM) grant of the Rohini Nilekani Philanthropies. BV is funded by the Intermediate (Clinical and Public Health) Fellowship (IA/CPHI/20/1/505266) of the DBT/Wellcome Trust India Alliance. The validation dataset was derived from the Consortium for Vulnerability to Externalizing Disorders and Addictions (c-VEDA), which is jointly funded by the Indian Council for Medical Research (ICMR/MRC/3/M/2015-NCD-I) and the Newton Grant from the Medical Research Council (MR/N000390/1), United KingdomAuthor DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:The project was reviewed and approved by the Institutional Ethics Review Board of the National Institute of Mental Health and Neuro Sciences, Bengaluru, Karnataka, IndiaI confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.YesThe study datasets will be made available upon request to the Principal Investigators of the ongoing ADBS (adbsnimhans.org) and c-VEDA (cveda-project.org) studies. The R codes used for statistical analysis can be provided upon request to the corresponding author (SB).

2024 Nature

Study design features increase replicability in brain-wide association studies

Kang, K.; Seidlitz, J.; Bethlehem, R. A. I.; Xiong, J.; Jones, M. T.; Mehta, K.; Keller, A. S.; Tao, R.; Randolph, A.; Larsen, B.; Tervo-Clemmens, B.; Feczko, E.; Dominguez, O. M.; Nelson, S.; Lifespan Brain Chart, C.; R, B.; Aibl; Alzheimer’s Disease Neuroimaging, I.; Alzheimer’s Disease Repository Without Borders, I.; Team, C.; Ccnp; Cobre; cVEDA; Harvard Aging Brain, S.; Imagen; Pond; The, P. A. D. R. G.; Schildcrout, J.; Fair, D.; Satterthwaite, T. D.; Alexander-Bloch, A.; Vandekar, S.

Nature, 636(8043), 719-727, doi: 10.1038/s41586-024-08260-9

2024 European Neuropsychopharmacology

F98. EFFECT OF CHILDHOOD ADVERSITY ON DNA METHYLATION AT THE GLUCOCORTICOID RECEPTOR (NR3C1) LOCUS

Shankarappa, B.; Janardhanan, M.; Parthaje, S.; Mahadevan, J.; Paul, P.; Viswanath, B.; Purushottam, M.; Jain, S.; Sharma, E.; Holla, B.; Benegal, V.

European Neuropsychopharmacology, 87, 257-258, doi: https://doi.org/10.1016/j.euroneuro.2024.08.509

2024 Front Psychiatry

Cross-continental environmental and genome-wide association study on children and adolescent anxiety and depression

Thapaliya, B.; Ray, B.; Farahdel, B.; Suresh, P.; Sapkota, R.; Holla, B.; Mahadevan, J.; Chen, J.; Vaidya, N.; Perrone-Bizzozero, N. I.; Benegal, V.; Schumann, G.; Calhoun, V. D.; Liu, J.

Front Psychiatry, 15, 1384298, doi: 10.3389/fpsyt.2024.1384298

Abstract

Anxiety and depression in children and adolescents warrant special attention as a public health concern given their devastating and long-term effects on development and mental health. Multiple factors, ranging from genetic vulnerabilities to environmental stressors, influence the risk for the disorders. This study aimed to understand how environmental factors and genomics affect children and adolescents anxiety and depression across three cohorts: Adolescent Brain and Cognitive Development Study (US, age of 9-10; N=11,875), Consortium on Vulnerability to Externalizing Disorders and Addictions (INDIA, age of 6-17; N=4,326) and IMAGEN (EUROPE, age of 14; N=1888). We performed data harmonization and identified the environmental impact on anxiety/depression using a linear mixed-effect model, recursive feature elimination regression, and the LASSO regression model. Subsequently, genome-wide association analyses with consideration of significant environmental factors were performed for all three cohorts by mega-analysis and meta-analysis, followed by functional annotations. The results showed that multiple environmental factors contributed to the risk of anxiety and depression during development, where early life stress and school support index had the most significant and consistent impact across all three cohorts. In both meta, and mega-analysis, SNP rs79878474 in chr11p15 emerged as a particularly promising candidate associated with anxiety and depression, despite not reaching genomic significance. Gene set analysis on the common genes mapped from top promising SNPs of both meta and mega analyses found significant enrichment in regions of chr11p15 and chr3q26, in the function of potassium channels and insulin secretion, in particular Kv3, Kir-6.2, SUR potassium channels encoded by the KCNC1, KCNJ11, and ABCCC8 genes respectively, in chr11p15. Tissue enrichment analysis showed significant enrichment in the small intestine, and a trend of enrichment in the cerebellum. Our findings provide evidences of consistent environmental impact from early life stress and school support index on anxiety and depression during development and also highlight the genetic association between mutations in potassium channels, which support the stress-depression connection via hypothalamic-pituitary-adrenal axis, along with the potential modulating role of potassium channels.

2024 Lancet Psychiatry

Cortical structure and subcortical volumes in conduct disorder: a coordinated analysis of 15 international cohorts from the ENIGMA-Antisocial Behavior Working Group

Gao, Y.; Staginnus, M.; Group, E. N. I. G. M. A. A. B. W.

Lancet Psychiatry, 11(8), 620-632, doi: 10.1016/S2215-0366(24)00187-1

Abstract

BACKGROUND: Conduct disorder is associated with the highest burden of any mental disorder in childhood, yet its neurobiology remains unclear. Inconsistent findings limit our understanding of the role of brain structure alterations in conduct disorder. This study aims to identify the most robust and replicable brain structural correlates of conduct disorder. METHODS: The ENIGMA-Antisocial Behavior Working Group performed a coordinated analysis of structural MRI data from 15 international cohorts. Eligibility criteria were a mean sample age of 18 years or less, with data available on sex, age, and diagnosis of conduct disorder, and at least ten participants with conduct disorder and ten typically developing participants. 3D T1-weighted MRI brain scans of all participants were pre-processed using ENIGMA-standardised protocols. We assessed group differences in cortical thickness, surface area, and subcortical volumes using general linear models, adjusting for age, sex, and total intracranial volume. Group-by-sex and group-by-age interactions, and DSM-subtype comparisons (childhood-onset vs adolescent-onset, and low vs high levels of callous-unemotional traits) were investigated. People with lived experience of conduct disorder were not involved in this study. FINDINGS: We collated individual participant data from 1185 young people with conduct disorder (339 [28.6%] female and 846 [71.4%] male) and 1253 typically developing young people (446 [35.6%] female and 807 [64.4%] male), with a mean age of 13.5 years (SD 3.0; range 7-21). Information on race and ethnicity was not available. Relative to typically developing young people, the conduct disorder group had lower surface area in 26 cortical regions and lower total surface area (Cohen's d 0.09-0.26). Cortical thickness differed in the caudal anterior cingulate cortex (d 0.16) and the banks of the superior temporal sulcus (d -0.13). The conduct disorder group also had smaller amygdala (d 0.13), nucleus accumbens (d 0.11), thalamus (d 0.14), and hippocampus (d 0.12) volumes. Most differences remained significant after adjusting for ADHD comorbidity or intelligence quotient. No group-by-sex or group-by-age interactions were detected. Few differences were found between DSM-defined conduct disorder subtypes. However, individuals with high callous-unemotional traits showed more widespread differences compared with controls than those with low callous-unemotional traits. INTERPRETATION: Our findings provide robust evidence of subtle yet widespread brain structural alterations in conduct disorder across subtypes and sexes, mostly in surface area. These findings provide further evidence that brain alterations might contribute to conduct disorder. Greater consideration of this under-recognised disorder is needed in research and clinical practice. FUNDING: Academy of Medical Sciences and Economic and Social Research Council.

2024 Psychol Med

Childhood adversities characterize the heterogeneity in the brain pattern of individuals during neurodevelopment

Kashyap, R.; Holla, B.; Bhattacharjee, S.; Sharma, E.; Mehta, U. M.; Vaidya, N.; Bharath, R. D.; Murthy, P.; Basu, D.; Nanjayya, S. B.; Singh, R. L.; Lourembam, R.; Chakrabarti, A.; Kartik, K.; Kalyanram, K.; Kumaran, K.; Krishnaveni, G.; Krishna, M.; Kuriyan, R.; Kurpad, S. S.; Desrivieres, S.; Purushottam, M.; Barker, G.; Orfanos, D. P.; Hickman, M.; Heron, J.; Toledano, M.; Schumann, G.; Benegal, V.

Psychol Med, 54(10), 2599-2611, doi: 10.1017/s0033291724000710

2024 medRxiv

A cross ancestry genetic study of psychiatric disorders from India

Holla, B.; Mahadevan, J.; Ganesh, S.; Sud, R.; Janardhanan, M.; Balachander, S.; Strom, N.; Mattheisen, M.; Sullivan, P. F.; Huang, H.; Zandi, P.; Benegal, V.; Reddy, Y. J.; Jain, S.; Purushottam, M.; Viswanath, B.

medRxiv, doi: 10.1101/2024.04.25.24306377

2023 Dev Psychopathol

Risk clustering and psychopathology from a multi-center cohort of Indian children, adolescents, and young adults

Basu, D.; Ghosh, A.; Naskar, C.; Balachander, S.; Fernandes, G.; Vaidya, N.; Kumaran, K.; Krishna, M.; Barker, G. J.; Sharma, E.; Murthy, P.; Holla, B.; Jain, S.; Orfanos, D. P.; Kalyanram, K.; Purushottam, M.; Bharath, R. D.; Varghese, M.; Thennarasu, K.; Chakrabarti, A.; Singh, R. L.; Singh, R. L.; Nanjayya, S. B.; Ahuja, C. K.; Kartik, K.; Krishnaveni, G.; Kuriyan, R.; Kurpad, S. S.; Desrivieres, S.; Iyengar, U.; Zhang, Y.; Hickman, M.; Spiers, A.; Toledano, M.; Schumann, G.; Benegal, V.

Dev Psychopathol, 35(2), 800-808, doi: 10.1017/S0954579422000050

2023 JAMA Netw Open

Neurocognitive Analysis of Low-level Arsenic Exposure and Executive Function Mediated by Brain Anomalies Among Children, Adolescents, and Young Adults in India

Vaidya, N.; Holla, B.; Heron, J.; Sharma, E.; Zhang, Y.; Fernandes, G.; Iyengar, U.; Spiers, A.; Yadav, A.; Das, S.; Roy, S.; Ahuja, C. K.; Barker, G. J.; Basu, D.; Bharath, R. D.; Hickman, M.; Jain, S.; Kalyanram, K.; Kartik, K.; Krishna, M.; Krishnaveni, G.; Kumaran, K.; Kuriyan, R.; Murthy, P.; Papadopoulos Orfanos, D.; Purushottam, M.; Kurpad, S. S.; Singh, L.; Singh, R.; Subodh, B. N.; Toledano, M.; Walter, H.; Desrivières, S.; Chakrabarti, A.; Benegal, V.; Schumann, G.

JAMA Netw Open, 6(5), e2312810, doi: 10.1001/jamanetworkopen.2023.12810

Abstract

IMPORTANCE: Arsenic, a contaminant of groundwater and irrigated crops, is a global public health hazard. Exposure to low levels of arsenic through food extends well beyond the areas with high arsenic content in water. OBJECTIVE: To identify cognitive impairments following commonly prevalent low-level arsenic exposure and characterize their underlying brain mechanisms. DESIGN, SETTING, AND PARTICIPANTS: This multicenter population-based cohort study analyzed cross-sectional data of the Indian Consortium on Vulnerability to Externalizing Disorders and Addictions (cVEDA) cohort, recruited between November 4, 2016, and May 4, 2019. Participants aged 6 to 23 years were characterized using deep phenotyping measures of behavior, neuropsychology, psychopathology, brain neuroimaging, and exposure to developmental adversities and environmental neurotoxins. All analyses were performed between June 1, 2020, and December 31, 2021. EXPOSURE: Arsenic levels were measured in urine as an index of exposure. MAIN OUTCOMES AND MEASURES: Executive function measured using the cVEDA neuropsychological battery, gray matter volume (GMV) from T1-weighted magnetic resonance imaging, and functional network connectivity measures from resting state functional magnetic resonance imaging. RESULTS: A total of 1014 participants aged 6 to 23 years (589 male [58.1%]; mean [SD] age, 14.86 [4.79] years) were included from 5 geographic locations. Sparse-partial least squares analysis was used to describe a negative association of arsenic exposure with executive function (r = -0.12 [P = 5.4 × 10-4]), brain structure (r = -0.20 [P = 1.8 × 10-8]), and functional connectivity (within network, r = -0.12 [P = 7.5 × 10-4]; between network, r = -0.23 [P = 1.8 × 10-10]). Alterations in executive function were partially mediated by GMV (b = -0.004 [95% CI, -0.007 to -0.002]) and within-network functional connectivity (b = -0.004 [95% CI, -0.008 to -0.002]). Socioeconomic status and body mass index moderated the association between arsenic and GMV, such that the association was strongest in participants with lower socioeconomic status and body mass index. CONCLUSIONS AND RELEVANCE: The findings of this cross-sectional study suggest that low-level arsenic exposure was associated with alterations in executive functioning and underlying brain correlates. These results indicate potential detrimental consequences of arsenic exposure that are below the currently recommended guidelines and may extend beyond endemic risk areas. Precision medicine approaches to study global mental health vulnerabilities highlight widespread but potentially modifiable risk factors and a mechanistic understanding of the impact of low-level arsenic exposure on brain development.

2023 Asian J Psychiatr

Growth trajectories for executive and social cognitive abilities in an Indian population sample: Impact of demographic and psychosocial determinants

Sharma, E.; Ravi, G. S.; Kumar, K.; Thennarasu, K.; Heron, J.; Hickman, M.; Vaidya, N.; Holla, B.; Rangaswamy, M.; Mehta, U. M.; Krishna, M.; Chakrabarti, A.; Basu, D.; Nanjayya, S. B.; Singh, R. L.; Lourembam, R.; Kumaran, K.; Kuriyan, R.; Kurpad, S. S.; Kartik, K.; Kalyanram, K.; Desrivieres, S.; Barker, G.; Orfanos, D. P.; Toledano, M.; Purushottam, M.; Bharath, R. D.; Murthy, P.; Jain, S.; Schumann, G.; Benegal, V.

Asian J Psychiatr, 82, 103475, doi: 10.1016/j.ajp.2023.103475

2023 Neuroinformatics

Federated Analysis in COINSTAC Reveals Functional Network Connectivity and Spectral Links to Smoking and Alcohol Consumption in Nearly 2,000 Adolescent Brains

Gazula, H.; Rootes-Murdy, K.; Holla, B.; Basodi, S.; Zhang, Z.; Verner, E.; Kelly, R.; Murthy, P.; Chakrabarti, A.; Basu, D.; Bhagyalakshmi Nanjayya, S.; Lenin Singh, R.; Lourembam Singh, R.; Kalyanram, K.; Kartik, K.; Kalyanaraman, K.; Ghattu, K.; Kuriyan, R.; Kurpad, S. S.; Barker, G. J.; Bharath, R. D.; Desrivieres, S.; Purushottam, M.; Orfanos, D. P.; Sharma, E.; Hickman, M.; Toledano, M.; Vaidya, N.; Banaschewski, T.; Bokde, A. L. W.; Flor, H.; Grigis, A.; Garavan, H.; Gowland, P.; Heinz, A.; Brühl, R.; Martinot, J. L.; Paillére Martinot, M. L.; Artiges, E.; Nees, F.; Paus, T.; Poustka, L.; Fröhner, J. H.; Robinson, L.; Smolka, M. N.; Walter, H.; Winterer, J.; Whelan, R.; Turner, J. A.; Sarwate, A. D.; Plis, S. M.; Benegal, V.; Schumann, G.; Calhoun, V. D.

Neuroinformatics, 21(2), 287-301, doi: 10.1007/s12021-022-09604-4

2023 European Neuropsychopharmacology

F31. CROSS-ANCESTRY POLYGENIC RISK SCORES FOR PSYCHIATRIC DISORDERS IN INDIAN POPULATIONS

Holla, B.; Ganesh, S.; Janardhanan, M.; Mahadevan, J.; Jain, S.; Reddy, Y. C. J.; Benegal, V.; Consortium, C.; Purushottam, M.; Viswanath, B.

European Neuropsychopharmacology, 75, S236-S237, doi: https://doi.org/10.1016/j.euroneuro.2023.08.419

Abstract

Background Psychiatric disorders, while globally prevalent, exhibit heterogeneity in manifestation and risk across diverse populations. This variability can be attributed to a complex interplay of genetic and environmental factors. India's genetic diversity, due to unique demographic events and population substructure, presents a rich but under-explored backdrop for psychiatric genetics research. To bridge this gap, we analyzed approx. 3000 samples from two cohorts from India: cVEDA, a multi-centric pan-India neurodevelopmental cohort; and a clinic-based sample of Bipolar Affective Disorder (BPAD) and Obsessive-Compulsive Disorder (OCD) patients from NIMHANS, India. Methods We utilized Illumina's Global Screening Array (GSA) for genotyping and performed quality control (QC) procedures to maintain dataset integrity. Post-QC, imputation accuracy of our data was assessed against three reference panels: 1000 Genomes (1000G), Genome Asia, and Haplotype Reference Consortium (HRC), with HRC showing superior INFO scores. Principal Component Analysis (PCA) addressed genetic structure and population stratification at global, continental, and regional levels. Ancestry of our samples was further delineated using a Support Vector Machines (SVM) model trained on labeled data from the reference panels (1000 Genome Phase 3, Human Genome Diversity Project and Genome Asia Pilot data.). We conducted unsupervised admixture analysis to explore potential substructure within our Indian samples and estimated the fixation index (Fst) to gauge genetic diversity. The main goal of our analysis was testing the cross-ancestry predictive accuracy of Polygenic Risk Scores (PRS) for Bipolar Disorder (BPAD) and Obsessive-Compulsive Disorder (OCD) derived from European GWAS summary statistics on Indian samples. We employed the Bayesian PRS-CS-auto method with a European LD reference panel and applied continuous shrinkage to refine the estimation of SNP effect sizes, thus enhancing the predictive power of the PRS. The PRS were computed using summary statistics from the PGC's 2017 meta-analysis for OCD and a 2021 meta-analysis for BPAD. Results The global PCA depicted our Indian samples overlapping with South Asian (SAS) samples from the 1000 Genomes Project. A more detailed sub-continental PCA, leveraging the GenomeAsia dataset, highlighted the extension of the Indian peninsula from SAS towards Oceania, South-East Asia, and North-East Asia. The SVM models predicted the continental labels better than the sub-continental labels. Admixture analysis suggested a 2-ancestry solution, reflecting genetic diversity within Indian populations, comparable to the genomic diversity observed across Europe. The BPAD PRS demonstrated significant predictive power for the disorder [Nagelkerke R2=0.0314, 10th decile OR (95%CI)= 3.08 (1.8, 5.0), N=1993 (Cases: 472, Controls: 1,521)], whereas the OCD PRS did not [N=2078 (Cases: 557, Controls: 1,521)]. Discussion The differential PRS prediction accuracy could be due to the smaller sample size of the OCD discovery GWAS and variations in allele frequencies and effect estimates across ancestries. Our results underscore the need for a comprehensive understanding of ancestry's role in psychiatric risk prediction, especially in genetically diverse populations like India. Future genetic research should aim to involve larger and more diverse samples to improve the accuracy and inclusivity of genetic risk predictions for psychiatric disorders across various ancestries.

2023 medRxiv

Cross-continental environmental and genome-wide association study on children and adolescent anxiety and depression

Thapaliya, B.; Ray, B.; Farahdel, B.; Suresh, P.; Sapkota, R.; Holla, B.; Mahadevan, J.; Chen, J.; Vaidya, N.; Perrone-Bizzozero, N.; Benegal, V.; Schumann, G.; Calhoun, V. D.; Liu, J.

medRxiv, doi: 10.1101/2023.02.06.23285530

Abstract

Anxiety and depression in children and adolescents warrant special attention as a public health issue given their devastating and long-term effects on development and mental health. Multiple factors, ranging from genetic vulnerabilities to environmental stressors, influence the risk for the disorders. This study aimed to understand how environmental factors and genomics affect children and adolescents anxiety and depression across three cohorts: Adolescent Brain and Cognitive Development Study (US, age of 9-10), Consortium on Vulnerability to Externalizing Disorders and Addictions (INDIA, age of 6-17) and IMAGEN (EUROPE, age of 14). We performed data harmonization and identified the environmental impact on anxiety/depression using a linear mixed-effect model, recursive feature elimination regression, and the LASSO regression model. Subsequently, genome-wide association analyses with consideration of significant environmental factors were performed for all three cohorts by mega-analysis and meta-analysis, followed by functional annotations. The results showed that multiple environmental factors contributed to the risk of anxiety and depression during development, where early life stress and school risk had the most significant and consistent impact across all three cohorts. Both meta and mega-analysis identified a novel SNP rs79878474 in chr11p15 to be the most promising SNP associated with anxiety and depression. Gene set analysis on the common genes mapped from top promising SNPs of both meta and mega analyses found significant enrichment in regions of chr11p15 and chr3q26, in the function of potassium channels and insulin secretion, in particular Kv3, Kir-6.2, SUR potassium channels encoded by the KCNC1, KCNJ11, and ABCCC8 genes respectively, in chr11p15. Tissue enrichment analysis showed significant enrichment in the small intestine and a trend of enrichment in the cerebellum. Our findings provide evidence of consistent environmental impact from early life stress and school risks on anxiety and depression during development and also highlight the genetic association between mutations in potassium channels along with the potential role of the cerebellum region, which are worthy of further investigation.

2023 Proc Natl Acad Sci U S A

Country-level gender inequality is associated with structural differences in the brains of women and men

Zugman, A.; Alliende, L. M.; Medel, V.; Bethlehem, R. A. I.; Seidlitz, J.; Ringlein, G.; Arango, C.; Arnatkevičiūtė, A.; Asmal, L.; Bellgrove, M.; Benegal, V.; Bernardo, M.; Billeke, P.; Bosch-Bayard, J.; Bressan, R.; Busatto, G. F.; Castro, M. N.; Chaim-Avancini, T.; Compte, A.; Costanzi, M.; Czepielewski, L.; Dazzan, P.; de la Fuente-Sandoval, C.; Di Forti, M.; Díaz-Caneja, C. M.; María Díaz-Zuluaga, A.; Du Plessis, S.; Duran, F. L. S.; Fittipaldi, S.; Fornito, A.; Freimer, N. B.; Gadelha, A.; Gama, C. S.; Garani, R.; Garcia-Rizo, C.; Gonzalez Campo, C.; Gonzalez-Valderrama, A.; Guinjoan, S.; Holla, B.; Ibañez, A.; Ivanovic, D.; Jackowski, A.; Leon-Ortiz, P.; Lochner, C.; López-Jaramillo, C.; Luckhoff, H.; Massuda, R.; McGuire, P.; Miyata, J.; Mizrahi, R.; Murray, R.; Ozerdem, A.; Pan, P. M.; Parellada, M.; Phahladira, L.; Ramirez-Mahaluf, J. P.; Reckziegel, R.; Reis Marques, T.; Reyes-Madrigal, F.; Roos, A.; Rosa, P.; Salum, G.; Scheffler, F.; Schumann, G.; Serpa, M.; Stein, D. J.; Tepper, A.; Tiego, J.; Ueno, T.; Undurraga, J.; Undurraga, E. A.; Valdes-Sosa, P.; Valli, I.; Villarreal, M.; Winton-Brown, T. T.; Yalin, N.; Zamorano, F.; Zanetti, M. V.; Winkler, A. M.; Pine, D. S.; Evans-Lacko, S.; Crossley, N. A.

Proc Natl Acad Sci U S A, 120(20), e2218782120, doi: 10.1073/pnas.2218782120

2022 Nature

Brain charts for the human lifespan

Bethlehem, R. A. I.; Seidlitz, J.; White, S. R.; Vogel, J. W.; Anderson, K. M.; Adamson, C.; Adler, S.; Alexopoulos, G. S.; Anagnostou, E.; Areces-Gonzalez, A.; Astle, D. E.; Auyeung, B.; Ayub, M.; Bae, J.; Ball, G.; Baron-Cohen, S.; Beare, R.; Bedford, S. A.; Benegal, V.; Beyer, F.; Blangero, J.; Blesa Cábez, M.; Boardman, J. P.; Borzage, M.; Bosch-Bayard, J. F.; Bourke, N.; Calhoun, V. D.; Chakravarty, M. M.; Chen, C.; Chertavian, C.; Chetelat, G.; Chong, Y. S.; Cole, J. H.; Corvin, A.; Costantino, M.; Courchesne, E.; Crivello, F.; Cropley, V. L.; Crosbie, J.; Crossley, N.; Delarue, M.; Delorme, R.; Desrivieres, S.; Devenyi, G. A.; Di Biase, M. A.; Dolan, R.; Donald, K. A.; Donohoe, G.; Dunlop, K.; Edwards, A. D.; Elison, J. T.; Ellis, C. T.; Elman, J. A.; Eyler, L.; Fair, D. A.; Feczko, E.; Fletcher, P. C.; Fonagy, P.; Franz, C. E.; Galan-Garcia, L.; Gholipour, A.; Giedd, J.; Gilmore, J. H.; Glahn, D. C.; Goodyer, I. M.; Grant, P. E.; Groenewold, N. A.; Gunning, F. M.; Gur, R. E.; Gur, R. C.; Hammill, C. F.; Hansson, O.; Hedden, T.; Heinz, A.; Henson, R. N.; Heuer, K.; Hoare, J.; Holla, B.; Holmes, A. J.; Holt, R.; Huang, H.; Im, K.; Ipser, J.; Jack, C. R. J.; Jackowski, A. P.; Jia, T.; Johnson, K. A.; Jones, P. B.; Jones, D. T.; Kahn, R. S.; Karlsson, H.; Karlsson, L.; Kawashima, R.; Kelley, E. A.; Kern, S.; Kim, K. W.; Kitzbichler, M. G.; Kremen, W. S.; Lalonde, F.; Landeau, B.; et al.

Nature, 604(7906), 525-533, doi: 10.1038/s41586-022-04554-y

2021 European Neuropsychopharmacology

W91. GENE-ENVIRONMENT INTERACTION AND BRAIN NETWORKS IN THE PATHOPHYSIOLOGY OF EXTERNALIZING BEHAVIORS AND SUBSTANCE USE RISK

Holla, B.; Viswanath, B.; Venkatasubramanian, G.; Muddashetty, R.; Purushottam, M.; Jain, S.; Schumann, G.; Bogdan, R.; Mattheisen, M.; Sullivan, P.; Agrawal, A.; Benegal, V.

European Neuropsychopharmacology, 51, e192-e193, doi: https://doi.org/10.1016/j.euroneuro.2021.08.174

2021 BMC Public Health

Adverse childhood experiences and substance misuse in young people in India: results from the multisite cVEDA cohort

Fernandes, G. S.; Spiers, A.; Vaidya, N.; Zhang, Y.; Sharma, E.; Holla, B.; Heron, J.; Hickman, M.; Murthy, P.; Chakrabarti, A.; Basu, D.; Subodh, B. N.; Singh, L.; Singh, R.; Kalyanram, K.; Kartik, K.; Kumaran, K.; Krishnaveni, G.; Kuriyan, R.; Kurpad, S.; Barker, G. J.; Bharath, R. D.; Desrivieres, S.; Purushottam, M.; Orfanos, D. P.; Toledano, M. B.; Schumann, G.; Benegal, V.

BMC Public Health, 21(1), 1920, doi: 10.1186/s12889-021-11892-5

2020 Mol Psychiatry

The Consortium on Vulnerability to Externalizing Disorders and Addictions (c-VEDA): an accelerated longitudinal cohort of children and adolescents in India

Zhang, Y.; Vaidya, N.; Iyengar, U.; Sharma, E.; Holla, B.; Ahuja, C. K.; Barker, G. J.; Basu, D.; Bharath, R. D.; Chakrabarti, A.; Desrivieres, S.; Elliott, P.; Fernandes, G.; Gourisankar, A.; Heron, J.; Hickman, M.; Jacob, P.; Jain, S.; Jayarajan, D.; Kalyanram, K.; Kartik, K.; Krishna, M.; Krishnaveni, G.; Kumar, K.; Kumaran, K.; Kuriyan, R.; Murthy, P.; Orfanos, D. P.; Purushottam, M.; Rangaswamy, M.; Kupard, S. S.; Singh, L.; Singh, R.; Subodh, B. N.; Thennarasu, K.; Toledano, M.; Varghese, M.; Benegal, V.; Schumann, G.

Mol Psychiatry, 25(8), 1618-1630, doi: 10.1038/s41380-020-0656-1

2020 Sci Bull (Beijing)

Population normative models of human brain growth across development

Holla, B.; Seidlitz, J.; Bethlehem, R. A. I.; Schumann, G.

Sci Bull (Beijing), 65(22), 1872-1873, doi: 10.1016/j.scib.2020.08.040

2020 BMC Psychiatry

Consortium on Vulnerability to Externalizing Disorders and Addictions (cVEDA): A developmental cohort study protocol

Sharma, E.; Vaidya, N.; Iyengar, U.; Zhang, Y.; Holla, B.; Purushottam, M.; Chakrabarti, A.; Fernandes, G. S.; Heron, J.; Hickman, M.; Desrivieres, S.; Kartik, K.; Jacob, P.; Rangaswamy, M.; Bharath, R. D.; Barker, G.; Orfanos, D. P.; Ahuja, C.; Murthy, P.; Jain, S.; Varghese, M.; Jayarajan, D.; Kumar, K.; Thennarasu, K.; Basu, D.; Subodh, B. N.; Kuriyan, R.; Kurpad, S. S.; Kalyanram, K.; Krishnaveni, G.; Krishna, M.; Singh, R. L.; Singh, L. R.; Kalyanram, K.; Toledano, M.; Schumann, G.; Benegal, V.

BMC Psychiatry, 20(1), 2, doi: 10.1186/s12888-019-2373-3

Abstract

BACKGROUND: Low and middle-income countries like India with a large youth population experience a different environment from that of high-income countries. The Consortium on Vulnerability to Externalizing Disorders and Addictions (cVEDA), based in India, aims to examine environmental influences on genomic variations, neurodevelopmental trajectories and vulnerability to psychopathology, with a focus on externalizing disorders. METHODS: cVEDA is a longitudinal cohort study, with planned missingness design for yearly follow-up. Participants have been recruited from multi-site tertiary care mental health settings, local communities, schools and colleges. 10,000 individuals between 6 and 23 years of age, of all genders, representing five geographically, ethnically, and socio-culturally distinct regions in India, and exposures to variations in early life adversity (psychosocial, nutritional, toxic exposures, slum-habitats, socio-political conflicts, urban/rural living, mental illness in the family) have been assessed using age-appropriate instruments to capture socio-demographic information, temperament, environmental exposures, parenting, psychiatric morbidity, and neuropsychological functioning. Blood/saliva and urine samples have been collected for genetic, epigenetic and toxicological (heavy metals, volatile organic compounds) studies. Structural (T1, T2, DTI) and functional (resting state fMRI) MRI brain scans have been performed on approximately 15% of the individuals. All data and biological samples are maintained in a databank and biobank, respectively. DISCUSSION: The cVEDA has established the largest neurodevelopmental database in India, comparable to global datasets, with detailed environmental characterization. This should permit identification of environmental and genetic vulnerabilities to psychopathology within a developmental framework. Neuroimaging and neuropsychological data from this study are already yielding insights on brain growth and maturation patterns.

2020 Hum Brain Mapp

A series of five population-specific Indian brain templates and atlases spanning ages 6-60 years

Holla, B.; Taylor, P. A.; Glen, D. R.; Lee, J. A.; Vaidya, N.; Mehta, U. M.; Venkatasubramanian, G.; Pal, P. K.; Saini, J.; Rao, N. P.; Ahuja, C. K.; Kuriyan, R.; Krishna, M.; Basu, D.; Kalyanram, K.; Chakrabarti, A.; Orfanos, D. P.; Barker, G. J.; Cox, R. W.; Schumann, G.; Bharath, R. D.; Benegal, V.

Hum Brain Mapp, 41(18), 5164-5175, doi: 10.1002/hbm.25182

2019 INDIAN JOURNAL OF PSYCHIATRY

Tracking Deviations in Neurodevelopmental Trajectories to Predict Adult Psychopathology

Benegal, V.; Vaidya, N.; Sharma, E.; Holla, B.

INDIAN JOURNAL OF PSYCHIATRY, 61(9), S395-S395

2019 Lancet Glob Health

Precision medicine and global mental health

Schumann, G.; Benegal, V.; Yu, C.; Tao, S.; Jernigan, T.; Heinz, A.; Araya, R.; Yu, L.; Calhoun, V.; Global Imaging Genetics in Adolescents, C.

Lancet Glob Health, 7(1), e32, doi: 10.1016/S2214-109X(18)30406-6