Whole-blood metabolomics of dementia patients reveal classes of disease-linked metabolites

Abstract

Dementia is caused by factors that damage neurons. We quantified small molecular markers in whole blood of dementia patients, using nontargeted liquid chromatography–mass spectroscopy (LC-MS). Thirty-three metabolites, classified into five groups (A to E), differed significantly in dementia patients, compared with healthy elderly subjects. Seven A metabolites present in plasma, including quinolinic acid, kynurenine, and indoxyl-sulfate, increased. Possibly they act as neurotoxins in the central nervous system (CNS). The remaining 26 compounds (B to E) decreased, possibly causing a loss of support or protection of the brain in dementia. Six B metabolites, normally enriched in red blood cells (RBCs), all contain trimethylated ammonium moieties. These metabolites include ergothioneine and structurally related compounds that have scarcely been investigated as dementia markers, validating the examination of RBC metabolites. Ergothioneine, a potent antioxidant, is significantly decreased in various cognition-related disorders, such as mild cognitive impairment and frailty. C compounds also include some oxidoreductants and are normally abundant in RBCs (NADP+, glutathione, adenosine triphosphate, pantothenate, S-adenosyl-methionine, and gluconate). Their decreased levels in dementia patients may also contribute to depressed brain function. Twelve D metabolites contains plasma compounds, such as amino acids, glycerophosphocholine, dodecanoyl-carnitine, and 2-hydroxybutyrate, which normally protect the brain, but their diminution in dementia may reduce that protection. Seven D compounds have been identified previously as dementia markers. B to E compounds may be critical to maintain the CNS by acting directly or indirectly. How RBC metabolites act in the CNS and why they diminish significantly in dementia remain to be determined.

Reply to Zheng et al.: Clinical metabolomics: Detailed analysis by nontargeted method is complementary to large-scale studies

“…First, they express concern about the sample size of our study ( n = 16) ( 2 ). However, our findings ( 3 ) do not conflict with other studies. Rather, they are well supported by other work.…”

“…Second, Zheng et al. ( 2 ) note the age difference between test subjects with dementia and those who served as controls in our study ( 3 ). It is possible that aging increases the risk of neurodegenerative diseases ( 6 ).…”

Precautions for study design and data interpretation of clinical metabolomics

“…Third, medications and diet have significant influences on the metabolome and thus the interpretation of clinical metabolomics results. As described by the authors ( 1 ), subjects in the dementia group were taking a variety of drugs, while the healthy groups did not. It is known that these drugs can alter the metabolomic profiles ( 5 ).…”

“…First, the sample size in this study ( 1 ) is relatively small, which might lead to a high chance of false discovery in clinical metabolomics. We roughly estimated the minimum sample size to obtain the true statistical differences of 33 discriminating features reported in the paper.…”

“…Second, age matters for clinical metabolomics. We noted that the age was not balanced between the dementia group and the healthy elderly (HE) group, and patients with dementia were significantly older than the HE group (84.6 ± 4.3 y for dementia vs. 74.8 ± 4.1 y for the HE group, P = 0.0014, Mann–Whitney U test) ( 1 ). A Cohen's d effect size of 2.3 for age indicated that age differences might have a very large contribution to the metabolomic differences between two groups, as many metabolites were reported to show continuous changes after the age of 50 y for both men and women ( 4 ).…”