1647 autopsied brain tissues from hundreds of LOAD patients and non-demented subjects. We identified numerous modules of distinct functional categories and cellular specificity, many showing a massive remodeling effect in the LOAD brain. Next we applied an integrative network-based approach to rank-order these modules for relevance to LOAD pathology and used a Bayesian inference to identify the key causal regulators of these remodeled networks. For instance, we identified, eight causal regulators of the top-ranked immune/microglia module including TYROBP (aka DAP12) as the highest ranking in terms of regulatory strength and differential expression in LOAD brains. We demonstrate through mouse microglia cells over-expressing intact or truncated dominant-negative TYROBP that downstream expression changes significantly overlapped the human TYROBP brain network. This study presents many of the network advantages useful in identifying and prioritizing pathways and gene targets involved in the pathophysiology of LOAD.
