Integrative network analysis of nineteen brain regions identifies molecular signatures and networks underlying selective regional vulnerability to Alzheimer's disease. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Wang, Minghui; Roussos, Panos; McKenzie, Andrew; Zhou, Xianxiao; Kajiwara, Yuji; Brennand, Kristen; De Luca, Gabriele; Crary, John; Casaccia, Patrizia; Buxbaum, Joseph; Ehrlich, Michelle; Gandy, Sam; Goate, Alison; Katsel, Pavel; Schadt, Eric; Haroutunian, Vahram; Zhang, Bin
• Is Part Of: Genome medicine. Volume 8:Issue 1(2016)
• Page Start: 1
• Page End: 21
• Publication Date: 2016-12
• Subjects: Alzheimer's disease -- Dementia -- Differential expression -- Gene co-expression network -- Gene module -- Systems biology -- Selective vulnerability -- Demyelination -- Brain cell types; Genomics -- Periodicals; Medical genetics -- Periodicals; 616.042
• DOI: 10.1186/s13073-016-0355-3
• Languages: English
• ISSNs: 1756-994X

Abstract

Abstract Background Alzheimer's disease (AD) is the most common form of dementia, characterized by progressive cognitive impairment and neurodegeneration. However, despite extensive clinical and genomic studies, the molecular basis of AD development and progression remains elusive. Methods To elucidate molecular systems associated with AD, we developed a large scale gene expression dataset from 1053 postmortem brain samples across 19 cortical regions of 125 individuals with a severity spectrum of dementia and neuropathology of AD. We excluded brain specimens that evidenced neuropathology other than that characteristic of AD. For the first time, we performed a pan-cortical brain region genomic analysis, characterizing the gene expression changes associated with a measure of dementia severity and multiple measures of the severity of neuropathological lesions associated with AD (neuritic plaques and neurofibrillary tangles) and constructing region-specific co-expression networks. We rank-ordered 44, 692 gene probesets, 1558 co-expressed gene modules and 19 brain regions based upon their association with the disease traits. Results The neurobiological pathways identified through these analyses included actin cytoskeleton, axon guidance, and nervous system development. Using public human brain single-cell RNA-sequencing data, we computed brain cell type-specific marker genes for human and determined that many of the abnormally expressed gene signatures and network modules were specific to oligodendrocytes, astrocytes, and neurons. Analysis based on disease severity suggested that: many of the gene expression changes, including those of oligodendrocytes, occurred early in the progression of disease, making them potential translational/treatment development targets and unlikely to be mere bystander result of degeneration; several modules were closely linked to cognitive compromise with lesser association with traditional measures of neuropathology. The brain regional analyses identified temporal lobe gyri as sites associated with the greatest and earliest gene expression abnormalities. Conclusions This transcriptomic network analysis of 19 brain regions provides a comprehensive assessment of the critical molecular pathways associated with AD pathology and offers new insights into molecular mechanisms underlying selective regional vulnerability to AD at different stages of the progression of cognitive compromise and development of the canonical neuropathological lesions of AD.