The identification of multiple genetic risk factors for Alzheimer Disease (AD) provides evidence to support that many pathways contribute to AD onset and progression. However, the metabolomic and lipidomic profiles in carriers of distinct genetic risk factors are not fully understood. The metabolome can provide a direct image of dysregulated pathways in the brain, including information on treatment targets. In this study, we interrogate the metabolomic and lipidomic signatures in the AD brain, including carriers of pathogenic variants in APP, PSEN1, and PSEN2 (autosomal dominant AD; ADAD), APOE ε4 and TREM2 risk variant carriers, and non-carrier sporadic AD (sAD). We generated metabolomic and lipidomic data from parietal cortical tissue from 366 participants with AD pathology and 26 cognitively unimpaired controls using the Metabolon global metabolomics platform. We identified 133 metabolites associated with disease status (FDR q-value<0.05). In sAD brains these include tryptophan betaine (b=-0.57) and N-acetylputrescine (b=-0.14). Metabolites associated with sAD and ADAD include ergothioneine (b=-0.21 and -0.26 respectively) and serotonin (b=-0.34 and -0.58, respectively). TREM2 and ADAD showed association with α-tocopherol (b=-0.12 and -0.12) and CDP-ethanolamine (b=-0.13 and -0.10). β-citrylglutamate levels are associated with sAD, ADAD, and TREM2 compared to controls (b=-0.15; -0.22; and -0.29, respectively). Additionally, we identified a signature of 16 metabolites that is significantly altered between genetic groups (sAD vs. control p = 1.05×10-7, ADAD vs. sAD p = 3.21×10-5) and is associated with Braak tau stage and disease duration. These data are available to the scientific community through a public web browser (http://ngi.pub/Metabolomics). Our findings were replicated in an independent cohort of 327 individuals.

Objective: To determine whether the genetic architecture of sporadic late--onset Alzheimer's Disease (sLOAD) has an effect on familial late--onset AD (fLOAD), sporadic early--onset (sEOAD) and autosomal dominant early--onset (eADAD).Methods: Polygenic risk scores (PRS) were constructed using previously identified 21 genome--wide significant loci for LOAD risk.Results: We found that there is an overlap in the genetic architecture among sEOAD, fLOAD, and sLOAD. sEOAD showed the highest odds for the PRS (OR=2.27; p=1.29×10 --7 ), followed by fLOAD (OR=1.75; p=1.12×10 --7 ) and sLOAD (OR=1.40; p=1.21×10 --3 ). PRS is associated with cerebrospinal fluid ptau 181 --Aβ 42 on eADAD.Conclusion: Our analysis confirms that the genetic factors identified for sLOAD also modulate risk in fLOAD and sEOAD cohorts. Furthermore, our results suggest that the burden of these risk variants is associated with familial clustering and earlier--onset of AD. Although these variants are not associated with risk in the eADAD, they may be modulating age at onset.peer-reviewed)

DPP6 encodes a transmembrane protein that expresses highly in the hippocampal regions of the brain and regulates dendritic excitability. Recently, rare and loss of function variants were reported in DPP6 and further demonstrated to be associated with early onset Alzheimer Disease (AD) and frontotemporal dementia. We performed single variant and gene-based analyses in three non- Hispanic white cohorts: a familial late onset AD (cases=1212, controls=341), an unrelated early onset AD (cases=1385, controls=3864) and in the unrelated Alzheimer disease sequencing project (ADSP, cases=5679, controls=4601). Neither single variant or gene-based analysis revealed any significant statistical association of DPP6 variants with the risk for AD in the cohorts examined.