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BACKGROUND: Several factors shape the neurodevelopmental trajectory. A key area of focus in neurodevelopmental research is to estimate the factors that have maximal influence on the brain and can tip the balance from typical to atypical development. METHODS: Utilizing a dissimilarity maximization algorithm on the dynamic mode decomposition (DMD) of the resting state functional MRI data, we classified subjects from the cVEDA neurodevelopmental cohort (n = 987, aged 6-23 years) into homogeneously patterned DMD (representing typical development in 809 subjects) and heterogeneously patterned DMD (indicative of atypical development in 178 subjects). RESULTS: Significant DMD differences were primarily identified in the default mode network (DMN) regions across these groups (p < 0.05, Bonferroni corrected). While the groups were comparable in cognitive performance, the atypical group had more frequent exposure to adversities and faced higher abuses (p < 0.05, Bonferroni corrected). Upon evaluating brain-behavior correlations, we found that correlation patterns between adversity and DMN dynamic modes exhibited age-dependent variations for atypical subjects, hinting at differential utilization of the DMN due to chronic adversities. CONCLUSION: Adversities (particularly abuse) maximally influence the DMN during neurodevelopment and lead to the failure in the development of a coherent DMN system. While DMN's integrity is preserved in typical development, the age-dependent variability in atypically developing individuals is contrasting. The flexibility of DMN might be a compensatory mechanism to protect an individual in an abusive environment. However, such adaptability might deprive the neural system of the faculties of normal functioning and may incur long-term effects on the psyche.
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Background and Aim: Friedreich's ataxia (FRDA) is a common cause of autosomal recessive cerebellar ataxia. The phenotype is dependent on the repeat size and duration of the disease. We aimed to study the clinical, electrophysiologic, and radiologic profiles in a large Indian cohort of genetically proven FRDA patients. Subjects and Methods: A retrospective cross-sectional, descriptive analysis of genetically proven FRDA patients was performed. A detailed review of all the hospital case records was done to analyze the clinical, radiologic, and electrophysiologic details. Results: A total of 100 FRDA patients were selected for the analysis. Eighty-six patients had an age at onset between 5 and 25 years. Eight patients (8%) were classified as late-onset FRDA and six patients (6%) as early-onset FRDA. The median age at presentation was 19 years. The median age at onset was 14 years, and the median duration of illness was 4 years. All patients had gait ataxia as the initial symptom. Gait ataxia, loss of proprioception, and areflexia were seen in all patients. Dysarthria, nystagmus, amyotrophy, spasticity, extensor plantars, pes cavus, and scoliosis occurred in one-third of patients. Cardiomyopathy (18%) and diabetes (5%) were less common. Sensory polyneuropathy (87.5%) was the most common nerve conduction abnormality. Cortical somatosensory evoked responses were absent in all 43 tested patients (100%). Brainstem auditory evoked response test was done in 24 patients and it showed absent reactions in six patients (25%). Visual evoked potential was tested in 24 patients and it showed absent P100 responses in five patients (21%). Cerebellar and cord atrophy was seen on magnetic resonance imaging in 50% of patients. Conclusion: Most FRDA patients (86%) had an age at onset of less than 25 years, with typical symptoms of gait ataxia, areflexia, and loss of proprioception found in all patients. Dysarthria, nystagmus, amyotrophy, spasticity, extensor plantars, pes cavus, scoliosis, cardiomyopathy, and diabetes were not seen in all patients. Cerebellar atrophy can occur in FRDA patients. Knowledge regarding the clinical, radiologic, and electrophysiologic profile of FRDA will aid in proper phenotypic characterization.
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Genome-wide association studies across diverse populations may help validate and confirm genetic contributions to risk of disease. We estimated the extent of population stratification as well as the predictive accuracy of polygenic scores (PGS) derived from European samples to a data set from India. We analysed 2685 samples from two data sets, a population neurodevelopmental study (cVEDA) and a hospital-based sample of bipolar affective disorder (BD) and obsessive-compulsive disorder (OCD). Genotyping was conducted using Illumina's Global Screening Array. Population structure was examined with principal component analysis (PCA), uniform manifold approximation and projection (UMAP), support vector machine (SVM) ancestry predictions, and admixture analysis. PGS were calculated from the largest available European discovery GWAS summary statistics for BD, OCD, and externalizing traits using two Bayesian methods that incorporate local linkage disequilibrium structures (PGS-CS-auto) and functional genomic annotations (SBayesRC). Our analyses reveal global and continental PCA overlap with other South Asian populations. Admixture analysis revealed a north-south genetic axis within India (FST 1.6%). The UMAP partially reconstructed the contours of the Indian subcontinent. The Bayesian PGS analyses indicates moderate-to-high predictive power for BD. This was despite the cross-ancestry bias of the discovery GWAS dataset, with the currently available data. However, accuracy for OCD and externalizing traits was much lower. The predictive accuracy was perhaps influenced by the sample size of the discovery GWAS and phenotypic heterogeneity across the syndromes and traits studied. Our study results highlight the accuracy and generalizability of newer PGS models across ancestries. Further research, across diverse populations, would help understand causal mechanisms that contribute to psychiatric syndromes and traits.