Multi-tissue gene expression profiles of human brain (VC)

The genetics of complex disease produce alterations in molecular interactions of cellular pathways which collective effect may become clear through the organized structure of molecular networks. To characterize molecular systems associated with late-onset Alzheimer´s disease (LOAD), we constructed gene regulatory networks in hundreds of autopsied brain tissues from LOAD patients and non-demented subjects. We demonstrate that LOAD reconfigures specific portions of the molecular interaction structure, and via an integrative network-based approach we rank ordered these sub-networks (modules) for relevance to LOAD pathology, highlighting the immune/microglia module as the top ranking. Through a Bayesian inference approach we identified multiple key causal regulators for LOAD brains. Autopsied tissues from dorsolateral prefrontal cortex (PFC), visual cortex (VC) and cerebellum (CR) in brains of LOAD patients, and non-demented healthy controls, collected through the Harvard Brain Tissue Resource Center (HBTRC), were profiled on a custom-made Agilent 44K array (GPL4372_1). All subjects were diagnosed at intake and each brain underwent extensive LOAD-related pathology examination. Gene expression analyses were adjusted for age and sex, postmortem interval (PMI) in hours, sample pH and RNA integrity number (RIN). In the overall cohort of LOAD and non-demented brains the mean ± SD for sample PMI, pH and RIN were 17.8±8.3, 6.4±0.3 and 6.8±0.8, respectively. 230 samples with all PFC, VC, and CR tissue profiled were included for further multi-tissue analysis.