Biology subjects

Dhindsa, J.

Publications and source records attributed to Dhindsa, J..

3 recordsLinked to original sources

bioRxiv2024

Systems genetic dissection of Alzheimer's disease brain gene expression networks

In Alzheimers disease (AD), changes in the brain transcriptome are hypothesized to mediate the impact of neuropathology on cognition. Gene expression profiling from postmortem brain tissue is a promising approach to identify causal pathways; however, there are challenges to definitively resolve the upstream pathologic triggers along with the downstream consequences for AD clinical manifestations. We have functionally dissected 30 AD-associated gene coexpression modules using a cross-species strategy in fruit fly (Drosophila melanogaster) models. Integrating longitudinal RNA-sequencing and behavioral phenotyping, we interrogated the unique and shared transcriptional responses to amyloid beta (A{beta}) plaques, tau neurofibrillary tangles, and/or aging, along with potential links to progressive neuronal dysfunction. Our results highlight hundreds of conserved, differentially expressed genes mapping to human AD regulatory networks. To confirm causal modules and pinpoint AD network drivers, we performed systematic in vivo genetic manipulations of 357 conserved, prioritized targets, identifying 141 modifiers of A{beta}- and/or tau-induced neurodegeneration. We discover an up-regulated network that is significantly enriched for both AD risk variants and markers of immunity / inflammation, and which promotes A{beta} and tau-mediated neurodegeneration based on fly genetic manipulations in neurons. By contrast, a synaptic regulatory network is strongly downregulated in human brains with AD and is enriched for loss-of-function suppressors of A{beta}/tau in Drosophila. Additional experiments suggest that this human brain transcriptional module may respond to and modulate A{beta}-induced glutamatergic hyperactivation injury. In sum, our cross-species, systems genetic approach establishes a putative causal chain linking AD pathology, large-scale gene expression perturbations, and ultimately, neurodegeneration.

systems biology↗

bioRxiv2023

Using an ODE model to separate Rest and Task signals in fMRI

Cortical activity results from the interplay between network-connected regions that integrate information and stimulus-driven processes originating from sensory motor networks responding to specific tasks. Separating the information due to each of these components has been challenging, and the relationship as measured by fMRI in each of these cases Rest (network) and Task (stimulus-driven) remains a significant open question in the study of large-scale brain dynamics. In this study, we develop a network ordinary differential equation (ODE) model using advanced system identification tools to analyze fMRI data from both rest and task conditions. We demonstrate that task-specific ODEs are essentially a subset of rest-specific ODEs across four different tasks from the Human Connectome Project. By assuming that task activity is a relative complement of rest activity, our model significantly improves predictions of reaction times on a trial-by-trial basis, leading to a 9 % increase in explanatory power (R2) across the 14 sub-tasks tested. We have additionally shown that these results hold for predicting missing trials and accuracy on a per individual basis as well as classifying Tasks trajectories or resulting dynamic Task functional connectivity. Our findings establish the principle of the Active Cortex Model, which posits that the cortex is always active and that Rest State encompasses all processes, while certain subsets of processes get elevated to perform specific task computations. Thus, this study is an important milestone in the development of the fMRI equation - to causally link large-scale brain activity, brain structural connectivity, and behavioral variables within a single framework.

neuroscience↗

bioRxiv2022

Tau polarizes an aging transcriptional signature to excitatory neurons and glia

Aging is a major risk factor for Alzheimers disease (AD), and cell-type vulnerability underlies its characteristic clinical manifestations. We have performed longitudinal, single-cell RNA-sequencing in Drosophila with pan-neuronal expression of human tau, which forms AD neurofibrillary tangle pathology. Whereas tau- and aging-induced gene expression strongly overlap (93%), they differ in the affected cell types. In contrast to the broad impact of aging, tau-triggered changes are strongly polarized to excitatory neurons and glia. Further, tau can either activate or suppress innate immune gene expression signatures in a cell type-specific manner. Integration of cellular abundance and gene expression pinpoints Nuclear Factor Kappa B signaling as a potential marker for neuronal vulnerability. We also highlight the conservation of cell type-specific transcriptional patterns between Drosophila and human postmortem brain tissue. Overall, our results create a resource for dissection of dynamic, age-dependent gene expression changes at cellular resolution in a genetically tractable model of tauopathy.

genomics↗