P3-032: combining sex, apoe genotype, and mitochondrial genetic variance as predictive responder identifier to regenerative therapeutic allopregnanolone for alzheimer's disease

Late onset Alzheimer's disease (LOAD) is a systemic disease with multiple etiologies, and is associated with compromised brain metabolism and regenerative capacity. Allopregnanolone has been shown to promote brain mitochondrial function, neurogenesis, and memory in mouse models, and is currently being investigated as a regenerative therapeutic for AD (NCT02221622). While genetic markers such as APOE genotype may predict risk of AD, there is currently no genetic markers to predict therapeutic outcomes for AD. Because mitochondrial genetic variances and APOE genotype are known to be differentially associated with respiratory capacity and cell proliferation, in this study, we evaluate whether they can be used as potential genetic markers to predict responders for Alzheimer's disease therapeutics. Induced pluripotent stem cells were derived from clinical trial participants and then differentiated into NSCs. Mitochondrial respiration was determined by metabolic flux analysis on these cells. To determine mitochondrial haplogroups of the participants, DNA was extracted from whole blood of the participants, and Hypervariable region 1 and 2 of mitochondrial DNA were amplified, sequenced, and aligned to the Revised Cambridge Reference Sequence. Mitochondrial haplogroup was assigned using HaploGrep2 based on identified variants. RNA-Seq analysis was used to elucidate transcriptomic changes and underlying mechanism of action of allopregnanolone. Analysis revealed that allopregnanolone treatment preferentially increased maximum respiration in NSCs derived from females, APOE4 carriers, and participants of certain mitochondrial haplogroups (A, L, M, and N compared to those from haplogroups H, HV, and J). RNA-Seq analysis also supported differential effect of allopregnanolone on differentiation and proliferation on the transcriptome level. Sex, APOE genotype, and mitochondrial genetic variation in combination is a promising predictive genetic marker to identify potential allopregnanolone responders. Predictive biomarkers will significantly contribute to a precision medicine strategy to identify responders to therapeutic agents for Alzheimer's disease.