Biology subjects

Ghorai, A.

Publications and source records attributed to Ghorai, A..

4 recordsLinked to original sources

bioRxiv2024

Sleep and Activity Patterns in Autism Spectrum Disorder

BackgroundAutism spectrum disorder (ASD) is a highly heritable and heterogeneous neurodevelopmental disorder characterized by impaired social interactions, repetitive behaviors, and a wide range of comorbidities. Between 44-83% of autistic individuals report sleep disturbances, which may share an underlying neurodevelopmental basis with ASD. MethodsWe recruited 382 ASD individuals and 223 of their family members to obtain quantitative ASD-related traits and wearable device-based accelerometer data spanning three consecutive weeks. An unbiased approach identifying traits associated with ASD was achieved by applying the elastic net machine learning algorithm with five-fold cross-validation on 6,878 days of data. The relationship between sleep and physical activity traits was examined through linear mixed-effects regressions using each night of data. ResultsThis analysis yielded 59 out of 242 actimetry measures associated with ASD status in the training set, which were validated in a test set (AUC: 0.777). For several of these traits (e.g. total light physical activity), the day-to-day variability, in addition to the mean, was associated with ASD. Individuals with ASD were found to have a stronger correlation between physical activity and sleep, where less physical activity decreased their sleep more significantly than that of their non-ASD relatives. ConclusionsThe average duration of sleep/physical activity and the variation in the average duration of sleep/physical activity strongly predict ASD status. Physical activity measures were correlated with sleep quality, traits, and regularity, with ASD individuals having stronger correlations. Interventional studies are warranted to investigate whether improvements in both sleep and increased physical activity may improve the core symptoms of ASD.

neuroscience↗

bioRxiv2023

Interaction of SCoV-2 NSP7 or NSP8 alone may cause constriction of the RNA entry channel in NSP12: Implications for novel RdRp inhibitor drug discovery

RNA-dependent RNA polymerase (RdRP) is a critical component of the RNA virus life cycle, including SCoV-2. Among the Coronavirus-encoded proteins, non-structural protein 12 (NSP12) exhibits polymerase activity in collaboration with one unit of NSP7 and two units of NSP8, constituting the RdRp holoenzyme. While there is abundant information on SCoV-2 RdRp-mediated RNA replication, the influence of interplay among NSP12, NSP7, and NSP8 on template RNA binding and primer extension activity remains relatively unexplored and poorly understood. Here, we recreated a functional RdRp holoenzyme in vitro using recombinant SCoV-2 NSP12, NSP7, and NSP8, and established its functional activity. Subsequently, molecular interactions among the NSPs in the presence of a variety of templates and their effects on polymerase activity were studied, wherein we found that NSP12 alone exhibited notable polymerase activity that increased significantly in the presence of NSP7 and NSP8. However, this activity was completely shut down, and the template RNA-primer complex was detached from NSP12 when one of the two cofactors was present. Through computational analysis, we found that the template RNA entry channel was more constricted in the presence of one of the two cofactors, which was relatively more constricted in the presence of NSP8 compared to that in the presence of NSP7. In conclusion, we report that NSP7 and NSP8 together synergise to enhance the activity of NSP12, but antagonise when present alone. Our findings have implications for novel drug development, and compounds that obstruct the binding of NSP7 or NSP8 to NSP12 can have lethal effects on viral RNA replication.

molecular biology↗

bioRxiv2018

PennZzz - an algorithm for estimating behavioral states from wrist-worn accelerometery

Sleep is a heterogeneous behavioral state comprised of different stages and interspersed with episodes of wakefulness. Sleep/wake states can be monitored in the sleep laboratory by polysomnography (PSG). However, sleep studies are intrusive, laborious and expensive, and are usually performed over a single night. In contrast, wrist-worn activity-tracking devices (actimeters) are inexpensive, unobtrusive, and can be used to estimate sleep and wake patterns over multiple nights. We designed the PennZzz algorithm to estimate sleep and wake from actimetry data. Results obtained by actimetry-based monitoring in 26 subjects were compared to stages of sleep and wakefulness detected by simultaneous polysomnography. We found that our algorithm identifies PSG-defined wake episodes with a high accuracy (336/431 - 76% of algorithm wake events correspond to true wakefulness). Furthermore, we find that the algorithm is sensitive enough to detect the majority (258/431 - 59%) of true wake episodes occurring after the first NREM1 to NREM2 transition. With correction, algorithm outputs can be used to estimate the total amount of time awake after sleep onset. We further refined this program for application in a high-throughput manner to assess the total amount of sleep, wake, and non-wear during longer recording periods.

physiology↗

bioRxiv2017

Genetic pleiotropy between mood disorders, metabolic, and endocrine traits in a multigenerational pedigree

Bipolar disorder (BD) is a mental disorder characterized by alternating periods of depression and mania. Individuals with BD have higher levels of early mortality than the general population, and a substantial proportion of this may be due to increased risk for comorbid diseases. Recent evidence suggests that pleiotropy, either in the form of a single risk-allele or the combination of multiple loci genome-wide, may underlie medical comorbidity between traits and diseases. To identify the molecular events that underlie BD and related medical comorbidities, we generated imputed whole genome sequence (WGS) data using a population specific reference panel, for an extended multigenerational Old Order Amish pedigree (400 family members) segregating BD and related disorders. First, we investigated all putative disease-causing variants at known Mendelian disease loci present in this pedigree. Second, we performed genomic profiling using polygenic risk scores to establish each individual's risk for several complex diseases. To explore the contribution of disease genes to BD we performed gene-based and variant-based association tests for BD, and found that Mendelian disease genes are enriched in the top results from both tests (OR=20.3, p=1x10-3; OR=2.2, p=1x10-2). We next identified a set of Mendelian variants that co-occur in individuals with BD more frequently than their unaffected family members, including the R3527Q mutation in APOB associated with hypercholesterolemia. Using polygenic risk scores, we demonstrated that BD individuals from this pedigree were enriched for the same common risk-alleles for BD as in the general population ({beta}=0.416, p=6x10-4). Furthermore, in the extended Amish family we find evidence for a common genetic etiology between BD and clinical autoimmune thyroid disease (p=1x10-4), diabetes (p=1x10-3), and lipid traits such as triglyceride levels (p=3x10-4). We identify genomic regions that contribute to the differences between BD individuals and unaffected family members by calculating local genetic risk for independent LD blocks. Our findings provide evidence for the extensive genetic pleiotropy that can drive epidemiological findings of comorbidities between diseases and other complex traits. Identifying such patterns may enable the subtyping of complex diseases and facilitate our understanding of the genetic mechanisms underlying phenotypic heterogeneity.

genetics↗