@article {2292, title = {Cross-diagnostic evaluation of minor physical anomalies in psychiatric disorders.}, journal = {J Psychiatr Res}, volume = {142}, year = {2021}, month = {2021 Jul 20}, pages = {54-62}, abstract = {

BACKGROUND: Minor physical anomalies (MPA) are markers of impaired neurodevelopment during the prenatal stage. Assessing MPA across psychiatric disorders may help understand their shared nature. In addition, MPA in family members would indicate a shared liability and endophenotype potential. We examined familial aggregation of MPA and their role as transdiagnostic and disorder-specific markers of 5 major psychiatric/neuropsychiatric conditions (schizophrenia, bipolar disorder, substance dependence, obsessive-compulsive disorder, and Alzheimer{\textquoteright}s dementia).

METHODS: Modified Waldrop{\textquoteright}s MPA scale was applied on 1321 individuals from 439 transdiagnostic multiplex families and 125 healthy population controls (HC). Stage of fetal development (morphogenetic/phenogenetic)- and anatomical location (craniofacial/peripheral)-based sub-scores were calculated. Familiality and endophenotypic potential of MPA were analyzed with serial negative binomial mixed-effect regression. Cross-diagnostic differences and the effect of family history density (FHD) of each diagnosis on MPA were assessed. Mixed-effects Cox models estimated the influence of MPA on age-at-onset of illness (AAO).

RESULTS: MPA were found to be heritable in families with psychiatric disorders, with a familiality of 0.52. MPA were higher in psychotic disorders after controlling for effects of sex and intrafamilial correlation. Morphogenetic variant MPA was noted to be lower in dementia in comparison to HC. FHD of schizophrenia and bipolar disorder predicted higher, and that of dementia and substance dependence predicted lower MPA. MPA brought forward the AAO [HR:1.07 (1.03-1.11)], and this was more apparent in psychotic disorders.

CONCLUSION: MPA are transmissible in families, are specifically related to the risk of developing psychoses, and predict an earlier age at onset. Neurodevelopmentally informed classification of MPA has the potential to enhance the etiopathogenic and translational understanding of psychiatric disorders.

}, issn = {1879-1379}, doi = {10.1016/j.jpsychires.2021.07.028}, author = {Sreeraj, Vanteemar S and Puzhakkal, Joan C and Holla, Bharath and Nadella, Ravi Kumar and Sheth, Sweta and Balachander, Srinivas and Ithal, Dhruva and Ali, Furkhan and Viswanath, Biju and Muralidharan, Kesavan and Venkatasubramanian, Ganesan and John, John P and Benegal, Vivek and Murthy, Pratima and Varghese, Mathew and Reddy, Yc Janardhan and Jain, Sanjeev} } @article {2202, title = {Psychiatric symptoms and syndromes transcending diagnostic boundaries in Indian multiplex families: The cohort of ADBS study.}, journal = {Psychiatry Res}, volume = {296}, year = {2021}, month = {2021 Feb}, pages = {113647}, abstract = {

Syndromes of schizophrenia, bipolar disorder, obsessive-compulsive disorder, substance use disorders and Alzheimer{\textquoteright}s dementia are highly heritable. About 10-20\% of subjects have another affected first degree relative (FDR), and thus represent a {\textquoteright}greater{\textquoteright} genetic susceptibility. We screened 3583 families to identify 481 families with multiple affected members, assessed 1406 individuals in person, and collected information systematically about other relatives. Within the selected families, a third of all FDRs were affected with serious mental illness. Although similar diagnoses aggregated within families, 62\% of the families also had members with other syndromes. Moreover, 15\% of affected individuals met criteria for co-occurrence of two or more syndromes, across their lifetime. Using dimensional assessments, we detected a range of symptom clusters in both affected and unaffected individuals, and across diagnostic categories. Our findings suggest that in multiplex families, there is considerable heterogeneity of clinical syndromes, as well as sub-threshold symptoms. These families would help provide an opportunity for further research using both genetic analyses and biomarkers.

}, issn = {1872-7123}, doi = {10.1016/j.psychres.2020.113647}, author = {Sreeraj, Vanteemar S and Holla, Bharath and Ithal, Dhruva and Nadella, Ravi Kumar and Mahadevan, Jayant and Balachander, Srinivas and Ali, Furkhan and Sheth, Sweta and Narayanaswamy, Janardhanan C and Venkatasubramanian, Ganesan and John, John P and Varghese, Mathew and Benegal, Vivek and Jain, Sanjeev and Reddy, Yc Janardhan and Viswanath, Biju} } @article {2245, title = {Systematic evaluation of the impact of defacing on quality and volumetric assessments on T1-weighted MR-images.}, journal = {J Neuroradiol}, year = {2021}, month = {2021 Mar 13}, abstract = {

BACKGROUND AND PURPOSE: Facial features can be potentially reconstructed from structural magnetic resonance images, thereby compromising the confidentiality of study participants. Defacing methods can be applied to MRI images to ensure privacy of study participants. These methods remove facial features, thereby rendering the image unidentifiable. It is commonly assumed that defacing would not have any impact on quantitative assessments of the brain. In this study, we have assessed the impact of different defacing methods on quality and volumetric estimates.

MATERIALS AND METHODS: We performed SPM-, Freesurfer-, pydeface, and FSL-based defacing on 30 T1-weighted images. We statistically compared the change in quality measurements (from MRIQC) and volumes (from SPM, CAT, and Freesurfer) between non-defaced and defaced images. We also calculated the Dice coefficient of each tissue class between non-defaced and defaced images.

RESULTS: Almost all quality measurements and tissue volumes changed after defacing, irrespective of the method used. All tissue volumes decreased post-defacing for CAT, but no such consistent trend was seen for SPM and Freesurfer. Dice coefficients indicated that segmentations are relatively robust; however, partial volumes might be affected leading to changed volumetric estimates.

CONCLUSION: In this study, we demonstrated that volumes and quality measurements get affected differently by defacing methods. It is likely that this will have a significant impact on the reproducibility of experiments. We provide suggestions on ways to minimize the impact of defacing on outcome measurements. Our results warrant the need for robust handling of defaced images at different steps of image processing.

}, issn = {0150-9861}, doi = {10.1016/j.neurad.2021.03.001}, author = {Bhalerao, Gaurav Vivek and Parekh, Pravesh and Saini, Jitender and Venkatasubramanian, Ganesan and John, John P} } @article {1149, title = {Discovery biology of neuropsychiatric syndromes (DBNS): a center for integrating clinical medicine and basic science.}, journal = {BMC Psychiatry}, volume = {18}, year = {2018}, month = {2018 Apr 18}, pages = {106}, 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{\textquoteright}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.

}, issn = {1471-244X}, doi = {10.1186/s12888-018-1674-2}, author = {Viswanath, Biju and Rao, Naren P and Narayanaswamy, Janardhanan C and Sivakumar, Palanimuthu T and Kandasamy, Arun and Kesavan, Muralidharan and Mehta, Urvakhsh Meherwan and Venkatasubramanian, Ganesan and John, John P and Mukherjee, Odity and Purushottam, Meera and Kannan, Ramakrishnan and Mehta, Bhupesh and Kandavel, Thennarasu and Binukumar, B and Saini, Jitender and Jayarajan, Deepak and Shyamsundar, A and Moirangthem, Sydney and Vijay Kumar, K G and Thirthalli, Jagadisha and Chandra, Prabha S and Gangadhar, Bangalore N and Murthy, Pratima and Panicker, Mitradas M and Bhalla, Upinder S and Chattarji, Sumantra and Benegal, Vivek and Varghese, Mathew and Reddy, Janardhan Y C and Raghu, Padinjat and Rao, Mahendra and Jain, Sanjeev} }