Peripheral serum metabolomic profiles inform central cognitive impairment

Abstract

The incidence of Alzheimer's disease (AD) increases with age and is becoming a significant cause of worldwide morbidity and mortality. However, the metabolic perturbation behind the onset of AD remains unclear. In this study, we performed metabolite profiling in both brain (n = 109) and matching serum samples (n = 566) to identify differentially expressed metabolites and metabolic pathways associated with neuropathology and cognitive performance and to identify individuals at high risk of developing cognitive impairment. The abundances of 6 metabolites, glycolithocholate (GLCA), petroselinic acid, linoleic acid, myristic acid, palmitic acid, palmitoleic acid and the deoxycholate/cholate (DCA/CA) ratio, along with the dysregulation scores of 3 metabolic pathways, primary bile acid biosynthesis, fatty acid biosynthesis, and biosynthesis of unsaturated fatty acids showed significant differences across both brain and serum diagnostic groups ( P -value < 0.05). Significant associations were observed between the levels of differential metabolites/pathways and cognitive performance, neurofibrillary tangles, and neuritic plaque burden. Metabolites abundances and personalized metabolic pathways scores were used to derive machine learning models, respectively, that could be used to differentiate cognitively impaired persons from those without cognitive impairment (median area under the receiver operating characteristic curve (AUC) = 0.772 for the metabolite level model; median AUC = 0.731 for the pathway level model). Utilizing these two models on the entire baseline control group, we identified those who experienced cognitive decline in the later years (AUC = 0.804, sensitivity = 0.722, specificity = 0.749 for the metabolite level model; AUC = 0.778, sensitivity = 0.633, specificity = 0.825 for the pathway level model) and demonstrated their pre-AD onset prediction potentials. Our study provides a proof-of-concept that it is possible to discriminate antecedent cognitive impairment in older adults before the onset of overt clinical symptoms using metabolomics. Our findings, if validated in future studies, could enable the earlier detection and intervention of cognitive impairment that may halt its progression.

Pectin with various degrees of esterification differentially alters gut microbiota and metabolome of healthy adults

“…Monopalmitin was negatively correlated with impaired fasting blood glucose (Zeng et al, 2010), and sebacic acid was inversely associated with the risk of type 2 diabetes (Jiang et al, 2020). Moreover, petroselinic acid, as a biomarker of AD, was observed to be rich in pectin H121 supplementation as well (Wang et al, 2020a). On the other hand, oleic acid, which increased with pectin H121 supplementation, could exert beneficial effects on insulin sensitivity (Palomer et al, 2018).…”

Human Gray and White Matter Metabolomics to Differentiate APOE and Stage Dependent Changes in Alzheimer’s Disease

“…Previous studies investigating metabolomics changes in AD reported changes in phosphatidylcholine and acylcarnitine metabolism [ 34 ], taurine transport, bile acid synthesis, and cholesterol metabolism [ 10 , 11 , 35 ], lipids, sphingolipids (notably GM 3 gangliosides) and lipid classes previously associated with cardiometabolic disease (phosphatidylethanolamine and triglycerides) [ 36 , 37 ]. Results using Metabolon’s untargeted assay showed changes in not only phospholipid, phosphatidylcholine, and fatty acid metabolism, but also the TCA cycle, pyrimidine, and several amino acids including aspartate, lysine, glycine, glutamate, creatine, histidine.…”

“…To our knowledge, only three reports have been published describing a brain metabolomics signature of AD. These reports demonstrated that the principal metabolites that classify AD in brain tissue include glycerophospholipids, spermidine, sphingolipids, and changes in bile acids [9][10][11]. These reports analyzed between 15 and 111 samples per group to develop a brain metabolomics signature based on targeted lipids or bile acids assays.…”

Metabolic Network Analysis Reveals Altered Bile Acid Synthesis and Metabolism in Alzheimer’s Disease

“…Details of sample collection, preparation, and metabolite quantification are provided in previously published work. 59 Sample details and quantified bile acids are provided in Table S2 .…”