A systems-level "misunderstanding": the plasma metabolome in Huntington's disease

Abstract

Objective: Huntington's disease (HD) is a rare neurodegenerative disease caused by the expansion of an N-terminal repeat in the huntingtin protein. The protein is expressed in all cells in the body; hence, peripheral tissues, such as blood, may recapitulate processes in the brain. The plasma metabolome may provide a window into active processes that influence brain health and a unique opportunity to noninvasively identify processes that may contribute to neurodegeneration. Alterations in metabolic pathways in brain have been shown to profoundly impact HD. Therefore, identification and quantification of critical metabolomic perturbations could provide novel biomarkers for disease onset and disease progression.

Methods: We analyzed the plasma metabolomic profiles from 52 premanifest (PHD), 102 early symptomatic HD, and 140 healthy controls (NC) using liquid chromatography coupled with a highly sensitive electrochemical detection platform.

Results: Alterations in tryptophan, tyrosine, purine, and antioxidant pathways were identified, including many related to energetic and oxidative stress and derived from the gut microbiome. Multivariate statistical modeling demonstrated mutually distinct metabolomic profiles, suggesting that the processes that determine onset were likely distinct from those that determine progression. Gut microbiome-derived metabolites particularly differentiated the PHD metabolome, while the symptomatic HD metabolome was increasingly influenced by metabolites that may reflect mutant huntingtin toxicity and neurodegeneration.

Interpretation: Understanding the complex changes in the delicate balance of the metabolome and the gut microbiome in HD, and how they relate to disease onset, progression, and phenotypic variability in HD are critical questions for future research.

Figures

Figure 1

Receiver operator curves. (A) NC versus PHD. (B) NC versus HD. (C) PHD versus HD. In each case, the AUC demonstrated excellent sensitivity and specificity, demonstrating clear separation between groups and suggesting specific effects on the HD plasma metabolome. AUC, area under the curve.

Figure 2

One out testing scores using PLSDA models for NC versus PHD, NC versus HD and PHD versus HD, using the 29 chosen compounds from the tyrosine, tryptophan, purine pathways and markers of oxidative progression (from Table1). The CCR are summarized in Table3. PLSDA, partial least squares discriminant analysis; HD, Huntington’s disease; CCR, correct classification rates.

Figure 3

Heat map demonstrating altered correlations in the cross-metabolite correlations. Red demonstrates a positive correlation, blue a negative correlation, between pairs of metabolites.

Figure 4

Network graph representing Pearson correlations between metabolites for NC, PHD, and HD groups (r = ±0.7 to ±0.2) for each pathway. Red lines represent negative correlations while blue lines represent positive correlations. These results demonstrate altered relationships amongst metabolites across disease groups, suggesting unique alterations in the feedback control of key enzymatic processes that change with HD progression.

Figure 5

Summation of one-out scoring. The graph is presented with 0.5 subtracted from all values to center around 0 and scaled by a factor of 100 for visualization. From the left, the first two columns score NC versus HD with NC as category A. The third and fourth columns score NC versus PHD with NC as category A. The fifth and sixth columns score HD versus PHD with HD as category A.

Figure 6

PLSDA modeling of effects of medications on metabolomics profiling. (A) There was no difference in the metabolomic profiles of PHD and HD individuals taking SSRI’s (Red) and those who were not on SSRI’s (Green). (B) There was no difference in the metabolomic profiles of PHD and HD individuals taking Neuroleptics (Green) and those not on neuroleptics (Red). This suggests that the HD metabotype is sufficiently robust to be insignificantly affected by these medications.