Integrative metabolomics-genomics approach reveals key metabolic pathways and regulators of Alzheimer's disease

Abstract

Metabolites, the biochemical products of the cellular process, can be used to measure alterations in biochemical pathways related to the pathogenesis of Alzheimer's disease (AD). However, the relationships between systemic abnormalities in metabolism and the pathogenesis of AD are poorly understood. In this study, we aim to identify AD-specific metabolomic changes and their potential upstream genetic and transcriptional regulators through an integrative systems biology framework for analyzing genetic, transcriptomic, metabolomic, and proteomic data in AD. Metabolite co-expression network analysis of the blood metabolomic data in the Alzheimer's Disease Neuroimaging Initiative (ADNI) shows short-chain acylcarnitines/amino acids and medium/long-chain acylcarnitines are most associated with AD clinical outcomes, including episodic memory scores and disease severity. Integration of the gene expression data in both the blood from the ADNI and the brain from the Accelerating Medicines Partnership Alzheimer's Disease (AMP-AD) program reveals ABCA1 and CPT1A are involved in the regulation of acylcarnitines and amino acids in AD. Gene co-expression network analysis of the AMP-AD brain RNA-seq data suggests the CPT1A- and ABCA1-centered subnetworks are associated with neuronal system and immune response, respectively. Increased ABCA1 gene expression and adiponectin protein, a regulator of ABCA1, correspond to decreased short-chain acylcarnitines and amines in AD in the ADNI. In summary, our integrated analysis of large-scale multiomics data in AD systematically identifies novel metabolites and their potential regulators in AD and the findings pave a way for not only developing sensitive and specific diagnostic biomarkers for AD but also identifying novel molecular mechanisms of AD pathogenesis.

Keywords: ABCA1; Alzheimer's disease; CPT1A; acylcarnitines; adiponectin; amino acids; genetic; metabolomics; multiscale metabolite co-expression network; risk factors.

FIGURE 1

Multiscale metabolite co‐expression network analysis of the blood metabolomic data in the Alzheimer's Disease Neuroimaging Initiative (ADNI). A, The global metabolite co‐expression network. Two parent modules M3 and M5 are not shown here. B, Rank‐ordered metabolite modules by the extent of association to the clinical outcomes. C, Heatmap of the correlations between clinical/cognitive Alzheimer's disease–pathology related traits and metabolite modules. Cognitive and pathological traits are shown on the right axis while the metabolite modules are shown at the bottom axis. The intensity of the color in each cell indicates the magnitude of the Spearman rank correlation coefficient between the corresponding row and column variables, for those correlations with adjusted P values < .05. Red and blue colors indicate positive and negative correlations, respectively

FIGURE 2

The expression level of the module M6 (i.e., module eigen‐metabolite represented by the first principal component of the module) significantly increases in the subjects with conversion from mild genitiveve impairment (MCI) to Alzheimer's disease (AD; termed MCI converters) compared to those MCI subjects without conversion (termed MCI stable group) in 2 years

FIGURE 3

CPT1A centered co‐expression networks. A, The genes positively correlated with CPT1A (false discovery rate [FDR] < 10‐6). B, MSigDB GO and canonical pathways enriched in the CPT1A centered subnetwork shown in (A). C, The genes negatively correlated with CPT1A (FDR < 10‐6). D, MSigDB GO and canonical pathways enriched in the CPT1A centered subnetwork shown in (C). The blue bars represent the –log10 values of the adjusted P‐values

FIGURE 4

ABCA1 centered co‐expression networks. A, The genes positively correlated with ABCA1 (false discovery rate [FDR] < 10‐6). B, MSigDB GO and canonical pathways enriched in the ABCA1 centered subnetwork shown in (A). C, The genes negatively correlated with ABCA1 (FDR < 10‐6). D, MSigDB GO and canonical pathways enriched in the ABCA1 centered subnetwork shown in (C). The blue bars represent the –log10 values of the adjusted P‐values

FIGURE 5

Integrative analysis of metabolites, genes, and proteins. A, The expression level of the module M8 (i.e., the eigen‐metabolite represented by the first principal component of the module), which contains short‐chain acylcarnitine and amino acid, varies significantly across five diagnosis groups (P‐value < .05). B, ABCA1 mRNA level in the blood is significantly different across four diagnosis groups. C, Adiponectin protein level in the blood is significantly different across Alzheimer's disease (AD), late mild cognitive impairment (LMCI), and control

FIGURE 6

Medium/long chain acylcarnitines are significantly associated with neutrophil gelatinase‐associated lipocalin (NGAL) protein level in Alzheimer's disease (AD). A, Medium/long‐chain acylcarnitines module (M6) expression level increases during the disease progression from control to late mild cognitive impairment (LMCI) and to AD. B, NGAL protein level in blood is significantly different across diagnosis groups (P‐value < .05)