Biology subjects

Zaidi, S. S. A.

Publications and source records attributed to Zaidi, S. S. A..

3 recordsLinked to original sources

bioRxiv2026

A generative reference grammar of healthy TCR repertoires reveals cancer-associated immune remodeling

T-cell receptor (TCR) repertoires record how adaptive immunity is organized and how cancer and therapy reshape it, but this signal is hard to read: treatment-associated change is entangled with the V(D)J recombination constraints that shape every repertoire. We present CRAFT (Cancer Repertoire Anomaly Finding Transformer), a conditional sequence-to-sequence transformer that learns a nucleotide-level generative grammar of productive TCR-beta CDR3 sequences from healthy donors, conditioned on germline V(D)J assignments. A dual-head decoder mirrors the independence of V-D and D-J recombination, and curriculum training produces embeddings that define a healthy-reference coordinate system in which cancer-associated change appears as structured, measurable deviation. In proof-of-concept applications to a neoadjuvant checkpoint-blockade cohort sampled longitudinally across blood, and to serial single-cell profiling of T-cell subsets during oncolytic immunotherapy, CRAFT geometric metrics capture response-associated remodeling, including shifts in repertoire organization over time. On antigen-labeled benchmarks, CRAFT organizes specificity classes coherently, recovering structure that reflects shared antigen recognition.

cancer biology↗

bioRxiv2022

Predictive Network Analysis Identifies JMJD6 and Other Novel Key Drivers in Alzheimer Disease

Despite decades of genetic studies on late onset Alzheimers disease (LOAD), the molecular mechanisms of Alzheimers disease (AD) remain unclear. Furthermore, different cell types in the central nervous system (CNS) play distinct roles in the onset and progression of AD pathology. To better comprehend the complex etiology of AD, we used an integrative approach to build robust predictive (causal) network models which were cross-validated over multiple large human multi-omics datasets in AD. We employed a published method to delineate bulk-tissue gene expression into single cell-type gene expression and integrated clinical and pathologic traits of AD, single nucleotide variation, and deconvoluted gene expression for the construction of predictive network models for each cell type in AD. With these predictive causal models, we are able to identify and prioritize robust key drivers of the AD-associated network state. In this study, we focused on neuron-specific network models and prioritized 19 predicted key drivers modulating AD pathology. These targets were validated via shRNA knockdown in human induced pluripotent stem cell (iPSC) derived neurons (iNs), in which 10 out of the 19 neuron-related targets (JMJD6, NSF, NUDT2, YWHAZ, RBM4, DCAF12, NDRG4, STXBP1, ATP1B1, and FIBP) significantly modulated levels of amyloid-beta and/or phosphorylated tau peptides in the postmitotic iNs. Most notably, knockdown of JMJD6 significantly altered the neurotoxic ratios of A{beta}42 to 40 and p231-tau to total tau, indicating its potential therapeutic relevance to both amyloid and tau pathology in AD. Molecular validation by RNA sequencing (RNAseq) in iNs further confirmed the network structure, showing significant enrichment in differentially expressed genes after knockdown of the validated targets. Interestingly, our network model predicts that these 10 key drivers are upstream regulators of REST and VGF, two recently identified key regulators of AD pathogenesis.

neuroscience↗

bioRxiv2022

Novel Master Regulators of Microglial Phagocytosis and Repurposed FDA-approved Drug for Treatment of Alzheimer Disease

Microglia, the innate immune cells of the brain, are essential determinants of late-onset Alzheimers Disease (LOAD) neuropathology. Here, we developed an integrative computational systems biology approach to construct causal network models of genetic regulatory programs for microglia in Alzheimers Disease (AD). This model enabled us to identify novel key driver (KDs) genes for microglial functions that can be targeted for AD pharmacotherapy. We prioritized FCER1G, HCK, LAPTM5, ITGB2, SLC1A2, PAPLN, GSAP, NTRK2, and CIRBP as KDs of microglial phagocytosis promoting neuroprotection and/or neural repair. In vitro, shRNA knockdown of each KD significantly reduced microglial phagocytosis. We repurposed riluzole, an FDA-approved ALS drug that upregulates SLC1A2 activity, and discovered that it stimulated phagocytosis of A{beta}1-42 in human primary microglia and decreased hippocampal amyloid plaque burden/phosphorylated tau levels in the brain of aged 3xTg-AD mice. Taken together, these data emphasize the utlility of our integrative approach for repurposing drugs for AD therapy.

neuroscience↗