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Tukker, A. M.

Publications and source records attributed to Tukker, A. M..

2 recordsLinked to original sources

Neuronal subtype-specific metabolic changes in neurodegenerative and neuropsychiatric diseases predicted via a systems biology-based approach

Understanding how distinct neuronal subtypes contribute to Alzheimers disease (AD) pathology remains a major challenge. Patient-derived induced pluripotent stem cell (iPSC) studies have shown neuronal subtype-specific molecular and pathological signatures, yet the underlying metabolic shifts driving this selective vulnerability are not completely understood. Here we present iNeuron-GEM, the first manually curated, genome-scale metabolic network of human neurons that integrates transcriptomic and metabolic knowledge to resolve subtype-specific metabolic states. By coupling iNeuron-GEM with single nucleus RNA sequencing data from post-mortem human cohort studies, ROSMAP and SEA-AD, we capture neuronal subtype-specific metabolic features and fluxes and identify perturbations in lipid and energy metabolism across excitatory and inhibitory neurons. Integrative analysis with NPS-AD data shows overlapping metabolic disruptions in AD and schizophrenia (SCZ), suggesting shared molecular vulnerabilities between neurodegenerative and neuropsychiatric disorders. We also developed a computational pipeline to infer transcriptional regulation of metabolic pathways and identify NR6A1 and NR3C1 as important regulators of lipid dysregulation in AD neurons. Our study establishes iNeuron-GEM as a framework to identify neuronal subtype-specific metabolic vulnerabilities in complex brain disorders.

systems biology↗

From Correlation to Causation: Cell-Type-Specific Gene Regulatory Networks in Alzheimer's Disease

INTRODUCTIONAlzheimers disease (AD) involves complex regulatory disruptions across multiple brain cell types, yet a comprehensive understanding of the intracellular causal mechanisms remains unclear. METHODSWe presented an integrative analysis framework using single-nucleus transcriptomic with matched subject-level genotype data from 272 human AD in the Religious Orders Study and the Rush Memory and Aging Project (ROSMAP) study, and constructed causality-based, cell-type-specific gene regulatory networks (GRNs). RESULTSOur method identifies regulatory genes from both transcription factors (TFs) and non-TFs, thereby capturing a complete and accurate causal regulatory map across different brain cell types. This work revealed both established and novel regulations, pathways, and cell-type-unique hub genes in AD. Beyond constructing transcriptome-wide GRNs, we quantitatively assessed hub genes and distinguished those with regulatory or responsive roles. DISCUSSIONOur study provides a comprehensive mapping of cell-type-specific causal GRNs in AD, providing a powerful resource for dynamic pathway exploration, hypothesis generation, and functional interpretation.

neuroscience↗