SUMMARY We present a consensus atlas of the human brain transcriptome in Alzheimer’s disease (AD), based on meta-analysis of differential gene expression in 2,114 postmortem samples. We discover 30 brain coexpression modules from seven regions as the major source of AD transcriptional perturbations. We next examine overlap with 251 brain differentially expressed gene sets from mouse models of AD and other neurodegenerative disorders. Human-mouse overlaps highlight responses to amyloid versus tau pathology and reveal age- and sex-dependent expression signatures for disease progression. Human coexpression modules enriched for neuronal and/or microglial genes broadly overlap with mouse models of AD, Huntington’s disease, amyotrophic lateral sclerosis, and aging. Other human coexpression modules, including those implicated in proteostasis, are not activated in AD models but rather following other, unexpected genetic manipulations. Our results comprise a cross-species resource, highlighting transcriptional networks altered by human brain pathophysiology and identifying correspondences with mouse models for AD preclinical studies.

Classical laboratory strains show limited genetic diversity and do not harness natural genetic variation. Mouse models relevant to Alzheimer’s disease (AD) have largely been developed using these classical laboratory strains, such as C57BL/6J (B6), and this has likely contributed to the failure of translation of findings from mice to the clinic. Therefore, here we test the potential for natural genetic variation to enhance the translatability of AD mouse models. Two widely used AD-relevant transgenes, APP swe and PS1 de9 ( APP/PS1 ), were backcrossed from B6 to three wild-derived strains CAST/EiJ, WSB/EiJ, PWK/PhJ, representative of three Mus musculus subspecies. These new AD strains were characterized using metabolic, functional, neuropathological and transcriptional assays. Strain-, sex- and genotype-specific differences were observed in cognitive ability, neurodegeneration, plaque load, cerebrovascular health and cerebral amyloid angiopathy. Analyses of brain transcriptional data showed strain was the greatest driver of variation. We identified significant variation in myeloid cell numbers in wild type mice of different strains as well as significant differences in plaque-associated myeloid responses in APP/PS1 mice between the strains. Collectively, these data support the use of wild-derived strains to better model the complexity of human AD.

Bicuspid aortic valve (BAV) is a common congenital heart defect (population incidence, 1–2%) 1 – 3 that frequently presents with ascending aortic aneurysm (AscAA) 4 . BAV/AscAA shows autosomal dominant inheritance with incomplete penetrance and male predominance. Causative gene mutations are known for ≤1% of nonsyndromic BAV cases with/without AscAA (e.g. NOTCH1 , SMAD6 ) 5 – 8 , impeding mechanistic insight and development of therapeutic strategies. We report the identification of mutations in ROBO4 , encoding a factor known to contribute to endothelial performance, that segregate with disease in two families. Targeted sequencing of ROBO4 revealed enrichment for rare variants in BAV/AscAA probands compared to controls. Targeted silencing of ROBO4 or mutant ROBO4 expression in endothelial cell lines results in impaired barrier function and a synthetic repertoire suggestive of endothelial-to-mesenchymal transition (EnMT); concordant BAV/AscAA-associated findings are observed in patients and animal models deficient for ROBO4. These data identify a novel endothelial etiology for this common human disease phenotype.