Integrative metabolomics‐genomics approach reveals that pathways related to the metabolism of acylcarnitines and amines are new potential targets of Alzheimer’s disease - Horgusluoglu‐Moloch, Emrin; Wang, Minghui; Arnold, Matthias; Krumsiek, Jan; Galindo‐Prieto, Beatriz; Kastenmüller, Gabi; Han, Xianlin; Baillie, Rebecca; Nho, Kwangsik; Saykin, Andrew J.; Kaddurah‐Daouk, Rima F.; Zhang, Bin (Alzheimer's & dementia, 2020)
Background The metabolic basis of Alzheimer’s Disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD pathogenesis remain elusive. In this study, we systematically interrogated metabolomics, genetics, proteomics, and clinical data from the matched subjects in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to identify key drivers and metabolic pathways associated with changes in metabolites with disease severity. Method 140 Metabolites in fasting serum samples from the ADNI (362 controls, 94 significant memory concerns, 764 mild cognitive impairment, and 298 AD) were analyzed using the AbsoluteIDQ‐p180 kit. Values adjusted for age, gender, body mass index (BMI), education, cohort, and medication. A metabolite co‐expression network was constructed using Multiscale Embedded Gene co‐Expression Network Analysis (MEGENA). Co‐expressed metabolite modules were then prioritized for the strength of association with clinical/cognitive and pathology biomarker variables. Correlation analysis of the co‐metabolite modules and the matched gene/protein expression data was performed. The ROS/MAP cohort was used as a replication study of the co‐expression network. Six brain transcriptomic datasets from the Mount Sinai Brain Bank, ROS/MAP, and MAYO clinic cohorts were utilized to build up gene‐centered correlation networks to elucidate functions of upstream regulators of candidate metabolites. Result Modules comprised of short‐chain acylcarnitines/amino acids (M8, M3), and medium/long‐chain acylcarnitines (M6) were most associated with worse AD clinical outcomes, including episodic memory scores and disease severity (CDR‐SB) (Figure 1A‐C). CPT1A gene expression was highly correlated with an increased level of the medium/long‐chain acylcarnitines (corrected p‐value = 1.87 × 10‐6). Increased ABCA1 gene expression and adiponectin protein (a regulator of ABCA1) levels corresponded to decreased short‐chain acylcarnitines and amines in AD (corrected p‐value < 0.02) (Figure 2A‐C). In addition, CPT1A and ABCA1 were differently expressed in the brains of AD patients compared to controls (Table 1), and their subnetworks were enriched for AD, aging, and neuronal system‐related gene signatures/pathways (Figure 3A‐D). Eight out of eleven modules were highly preserved between the ADNI and ROS/MAP cohorts (Z summary preservation score > 5; corrected p‐value < 0.05). Conclusion Identification of acylcarnitines enriched modules and their potential upstream genetic and transcriptional regulators paves the way for developing novel biomarkers and targets for AD.