This study combined high resolution mass spectrometry (HRMS), advanced chemometrics and pathway enrichment analysis to analyse the blood metabolome of patients attending the memory clinic: cases of mild cognitive impairment (MCI; n = 16), cases of MCI who upon subsequent follow-up developed Alzheimer’s disease (MCI_AD; n = 19), and healthy age-matched controls (Ctrl; n = 37). Plasma was extracted in acetonitrile and applied to an Acquity UPLC HILIC (1.7μm x 2.1 x 100 mm) column coupled to a Xevo G2 QTof mass spectrometer using a previously optimised method. Data comprising 6751 spectral features were used to build an OPLS-DA statistical model capable of accurately distinguishing Ctrl, MCI and MCI_AD. The model accurately distinguished (R2 = 99.1%; Q2 = 97%) those MCI patients who later went on to develop AD. S-plots were used to shortlist ions of interest which were responsible for explaining the maximum amount of variation between patient groups. Metabolite database searching and pathway enrichment analysis indicated disturbances in 22 biochemical pathways, and excitingly it discovered two interlinked areas of metabolism (polyamine metabolism and L-Arginine metabolism) were differentially disrupted in this well-defined clinical cohort. The optimised untargeted HRMS methods described herein not only demonstrate that it is possible to distinguish these pathologies in human blood but also that MCI patients ‘at risk’ from AD could be predicted up to 2 years earlier than conventional clinical diagnosis. Blood-based metabolite profiling of plasma from memory clinic patients is a novel and feasible approach in improving MCI and AD diagnosis and, refining clinical trials through better patient stratification.

Certain endogenous bile acids have been proposed as potential therapies for ameliorating Alzheimer’s disease (AD) but their role, if any, in the pathophysiology of this disease is not currently known. Given recent evidence of bile acids having protective and anti-inflammatory effects on the brain, it is important to establish how AD affects levels of endogenous bile acids. Using LC-MS/MS, this study profiled 22 bile acids in brain extracts and blood plasma from AD patients (n = 10) and age-matched control subjects (n = 10). In addition, we also profiled brain/plasma samples from APP/PS1 and WT mice (aged 6 and 12 months). In human plasma, we detected significantly lower cholic acid (CA, p = 0.03) in AD patients than age-matched control subjects. In APP/PS1 mouse plasma we detected higher CA (p = 0.05, 6 months) and lower hyodeoxycholic acid (p = 0.04, 12 months) than WT. In human brain with AD pathology (Braak stages V-VI) taurocholic acid (TCA) were significantly lower (p = 0.01) than age-matched control subjects. In APP/PS1 mice we detected higher brain lithocholic acid (p = 0.05) and lower tauromuricholic acid (TMCA; p = 0.05, 6 months). TMCA was also decreased (p = 0.002) in 12-month-old APP/PS1 mice along with 5 other acids: CA (p = 0.02), β-muricholic acid (p = 0.02), Ω-muricholic acid (p = 0.05), TCA (p = 0.04), and tauroursodeoxycholic acid (p = 0.02). The levels of bile acids are clearly disturbed during the development of AD pathology and, since some bile acids are being proposed as potential AD therapeutics, we demonstrate a method that can be used to support work to advance bile acid therapeutics.

The gut microbiome can impact brain health and is altered in Parkinson’s disease (PD). The vermiform appendix is a lymphoid tissue in the cecum implicated in the storage and regulation of the gut microbiota. We sought to determine whether the appendix microbiome is altered in PD and to analyze the biological consequences of the microbial alterations. We investigated the changes in the functional microbiota in the appendix of PD patients relative to controls (n = 12 PD, 16 C) by metatranscriptomic analysis. We found microbial dysbiosis affecting lipid metabolism, including an upregulation of bacteria responsible for secondary bile acid synthesis. We then quantitatively measure changes in bile acid abundance in PD relative to the controls in the appendix (n = 15 PD, 12 C) and ileum (n = 20 PD, 20 C). Bile acid analysis in the PD appendix reveals an increase in hydrophobic and secondary bile acids, deoxycholic acid (DCA) and lithocholic acid (LCA). Further proteomic and transcriptomic analysis in the appendix and ileum corroborated these findings, highlighting changes in the PD gut that are consistent with a disruption in bile acid control, including alterations in mediators of cholesterol homeostasis and lipid metabolism. Microbially derived toxic bile acids are heightened in PD, which suggests biliary abnormalities may play a role in PD pathogenesis.

Alzheimer’s disease (AD) is reported to be closely linked with abnormal lipid metabolism. To gain a more comprehensive understanding of what causes AD and its subsequent development, we profiled the lipidome of postmortem (PM) human brains (neocortex) of people with a range of AD pathology (Braak 0–6). Using high-resolution mass spectrometry, we employed a semi-targeted, fully quantitative lipidomics profiling method (Lipidyzer) to compare the biochemical profiles of brain tissues from persons with mild AD (n = 15) and severe AD (AD; n = 16), and compared them with age-matched, cognitively normal controls (n = 16). Univariate analysis revealed that the concentrations of 420 lipid metabolites significantly (p < 0.05; q < 0.05) differed between AD and controls. A total of 49 lipid metabolites differed between mild AD and controls, and 439 differed between severe AD and mild AD. Interestingly, 13 different subclasses of lipids were significantly perturbed, including neutral lipids, glycerolipids, glycerophospholipids, and sphingolipids. Diacylglycerol (DAG) (14:0/14:0), triacylglycerol (TAG) (58:10/FA20:5), and TAG (48:4/FA18:3) were the most notably altered lipids when AD and control brains were compared (p < 0.05). When we compare mild AD and control brains, phosphatidylethanolamine (PE) (p-18:0/18:1), phosphatidylserine (PS) (18:1/18:2), and PS (14:0/22:6) differed the most (p < 0.05). PE (p-18:0/18:1), DAG (14:0/14:0), and PS (18:1/20:4) were identified as the most significantly perturbed lipids when AD and mild AD brains were compared (p < 0.05). Our analysis provides the most extensive lipid profiling yet undertaken in AD brain tissue and reveals the cumulative perturbation of several lipid pathways with progressive disease pathology. Lipidomics has considerable potential for studying AD etiology and identifying early diagnostic biomarkers.

Using ¹ H NMR metabolomics, we biochemically profiled saliva samples collected from healthy-controls ( n = 12), mild cognitive impairment (MCI) sufferers ( n = 8), and Alzheimer’s disease (AD) patients ( n = 9). We accurately identified significant concentration changes in 22 metabolites in the saliva of MCI and AD patients compared to controls. This pilot study demonstrates the potential for using metabolomics and saliva for the early diagnosis of AD. Given the ease and convenience of collecting saliva, the development of accurate and sensitive salivary biomarkers would be ideal for screening those at greatest risk of developing AD.

The pathogenesis of Alzheimer's disease (AD) is complex involving multiple contributing factors. The extent to which AD pathology affects the metabolome is still not understood nor is it known how disturbances change as the disease progresses. For the first time, we have profiled longitudinally (6, 8, 10, 12, and 18 months) both the brain and plasma metabolome of APPswe/PS1deltaE9 double transgenic and wild-type mice. A total of 187 metabolites were quantified using a targeted metabolomic methodology. Multivariate statistical analysis produced models that distinguished APPswe/PS1deltaE9 from wild-type mice at 8, 10, and 12 months. Metabolic pathway analysis found perturbed polyamine metabolism in both brain and blood plasma. There were other disturbances in essential amino acids, branched-chain amino acids, and also in the neurotransmitter serotonin. Pronounced imbalances in phospholipid and acylcarnitine homeostasis were evident in 2 age groups. AD-like pathology, therefore, affects greatly on both the brain and blood metabolomes, although there appears to be a clear temporal sequence whereby changes to brain metabolites precede those in blood.