Luke Whiley

Evidence of altered phosphatidylcholine metabolism in Alzheimer's disease

Abberant lipid metabolism is implicated in Alzheimers disease (AD) pathophysiology, but the connections between AD and lipid metabolic pathways are not fully understood. To investigate plasma lipids in AD, a multiplatform screen (n = 35 by liquid chromatography-mass spectrometry and n = 35 by nuclear magnetic resonance) was developed, which enabled the comprehensive analysis of plasma from 3 groups (individuals with AD, individuals with mild cognitive impairment (MCI), and age-matched controls). This screen identified 3 phosphatidylcholine (PC) molecules that were significantly diminished in AD cases. In a subsequent validation study (n = 141), PC variation in a bigger sample set was investigated, and the same 3 PCs were found to be significantly lower in AD patients: PC 16:0/20:5 (p < 0.001), 16:0/22:6 (p < 0.05), and 18:0/22:6 (p < 0.01). A receiver operating characteristic (ROC) analysis of the PCs, combined with apolipoprotein E (ApoE) data, produced an area under the curve predictive value of 0.828. Confirmatory investigations into the background biochemistry indiciated no significant change in plasma levels of 3 additional PCs of similar structure, total choline containing compounds or total plasma omega fatty acids, adding to the evidence that specific PCs play a role in AD pathology.

In-Vial Dual Extraction for Direct LC-MS Analysis of Plasma for Comprehensive and Highly Reproducible Metabolic Fingerprinting

Metabolic fingerprinting of biological tissues has become an important area of research, particularly in the biomarker discovery field. Methods have inherent analytical variation, and new approaches are necessary to ensure that the vast numbers of intact metabolites present in biofluids are detected. Here, we describe an in-vial dual extraction (IVDE) method and a direct injection method that shows the total number of features recovered to be over 4500 from a single 20 μL plasma aliquot. By applying a one-step extraction consisting of a lipophilic and hydrophilic layer within a single vial insert, we showed that analytical variation was decreased. This was achieved by reducing sample preparation stages including procedures of drying and transfers. The two phases in the vial, upper and lower, underwent HPLC-QTOF analysis on individually customized LC gradients in both positive and negative ionization modes. A 60 min lipid profiling HPLC-QTOF method for the lipophilic phase was specifically developed, enabling the separation and putative identification of fatty acids, glycerolipids, glycerophospholipids, sphingolipids, and sterols. The aqueous phase of the extract underwent direct injection onto a 45 min gradient, enabling the detection of both polarities. The IVDE method was compared to two traditional extraction methods. The first method was a two-step ether evaporation and IPA resuspension, and the second method was a methanol precipitation typically used in fingerprinting studies. The IVDE provided a 378% increase in reproducible features when compared to evaporation and a 269% increase when compared to the precipitate and inject method. As a proof of concept, the method was applied to an animal model of diabetes. A 2-fold increase in discriminant metabolites was found when comparing diabetic and control rats with IVDE. These discriminant metabolites accounted for around 600 entities, out of which 388 were identified in available databases.

Plasma lipidomics analysis finds long chain cholesteryl esters to be associated with Alzheimer's disease.

There is an urgent need for the identification of Alzheimer’s disease (AD) biomarkers. Studies have now suggested the promising use of associations with blood metabolites as functional intermediate phenotypes in biomedical and pharmaceutical research. The aim of this study was to use lipidomics to identify a battery of plasma metabolite molecules that could predict AD patients from controls. We performed a comprehensive untargeted lipidomic analysis, using ultra-performance liquid chromatography/mass spectrometry on plasma samples from 35 AD patients, 40 elderly controls and 48 individuals with mild cognitive impairment (MCI) and used multivariate analysis methods to identify metabolites associated with AD status. A combination of 10 metabolites could discriminate AD patients from controls with 79.2% accuracy (81.8% sensitivity, 76.9% specificity and an area under curve of 0.792) in a novel test set. Six of the metabolites were identified as long chain cholesteryl esters (ChEs) and were reduced in AD (ChE 32:0, odds ratio (OR)=0.237, 95% confidence interval (CI)=0.10–0.48, P=4.19E−04; ChE 34:0, OR=0.152, 95% CI=0.05–0.37, P=2.90E−04; ChE 34:6, OR=0.126, 95% CI=0.03–0.35, P=5.40E−04; ChE 32:4, OR=0.056, 95% CI=0.01–0.24, P=6.56E−04 and ChE 33:6, OR=0.205, 95% CI=0.06–0.50, P=2.21E−03, per (log2) metabolite unit). The levels of these metabolites followed the trend control>MCI>AD. We, additionally, found no association between cholesterol, the precursor of ChE and AD. This study identified new ChE molecules, involved in cholesterol metabolism, implicated in AD, which may help identify new therapeutic targets; although, these findings need to be replicated in larger well-phenotyped cohorts.

Association of blood lipids with Alzheimer's disease: A comprehensive lipidomics analysis

The aim of this study was to (1) replicate previous associations between six blood lipids and Alzheimers disease (AD) (Proitsi et al 2015) and (2) identify novel associations between lipids, clinical AD diagnosis, disease progression and brain atrophy (left/right hippocampus/entorhinal cortex).

In-vial dual extraction liquid chromatography coupled to mass spectrometry applied to streptozotocin-treated diabetic rats. Tips and pitfalls of the method.

The aim of metabolomics studies is the comprehensive and quantitative analysis of all metabolites in a cell, tissue or organism. This approach requires sample preparation methods to be fast, reproducible and able to extract a wide range of analytes with different polarities, as well as analytical platforms able to detect the extracted metabolites. Recently, we have developed a one-step extraction method consisting of a lipophilic and hydrophilic layer within a single vial insert, in-vial dual extraction (IVDE). In order to check possible application of this method to real biological case, analysis of plasma samples obtained from three streptozotocin-induced diabetic and three control rats was performed. Analytical validity of the method was proved by the calculation (in quality control samples) of relative standard deviation (RSD) for detected metabolites. The percentage of metabolites with RSD<30% was 93% for Fatty acyls, 80% for Glycerolipids, 93% for Glycerophospholipids, 68% for Sterol lipids, and 91% for Sphingolipids. IVDE allowed for selection of more than 600 different features discriminating two studied groups. For around 40% of these masses putative identification was possible. Adequate, with several considerations described within this paper, application of IVDE method enables wide metabolite coverage from a single 20μL plasma aliquot. Within the features putatively identified, glycerolipids and glycerophospholipids arose as the most important groups of compounds discriminating diabetic rats from controls. All discriminating metabolites give an idea of the large metabolic differences that can be present in non-controlled type 1 diabetes.

Metabolic Phenotype of the Healthy Rodent Model Using In-Vial Extraction of Dried Serum, Urine, and Cerebrospinal Fluid Spots

High-throughput multiplatform metabolomics experiments are becoming an integral part of clinical and systems biology research. Such methods call for the adoption of robust sample storage and transport formats for small volumes of biofluids. One such format is the dried biofluid spot, which combines small volume requirements with easy portability. Here, we describe ultra high-performance liquid chromatography-mass spectrometry (UHPLC-MS) metabolomics of dried rodent serum, urine, and cerebrospinal fluid spots. An in-vial extraction and UHPLC-MS analysis method was first developed and validated by fingerprinting two test fluids, rat serum and RPMI cell nutrient medium. Data for these extracts were compared in terms of (i) peak area measurements of selected features to assess reproducibility and (ii) total fingerprint variation after data pretreatment. Results showed that percentage peak area variation was found to range between 1.4 and 9.4% relative standard deviation (RSD) for a representative set of molecular features. Upon application of the method to spots bearing serum, urine or cerebrospinal fluid (CSF) from healthy rats and mice, a total of 1,182 and 2,309 reproducible molecular features were obtained in positive and negative ionization modes, respectively, of which 610 (positive) and 991 (negative) were found in both rats and mice. Feature matching was used to detect similarities and differences between biofluids, with the biggest overlap found between fingerprints obtained in urine and CSF. Our results thus demonstrate the potential of such direct fingerprinting of dried biofluid spots as a viable alternative to the use of small (10-15 μL) volumes of neat biofluids in animal studies.

Association between Plasma Ceramides and Phosphatidylcholines and Hippocampal Brain Volume in Late Onset Alzheimer's Disease

Lipids such as ceramides and phosphatidylcholines (PC) have been found altered in the plasma of Alzheimer’s disease (AD) patients in a number of discovery studies. For this reason, the levels of 6 ceramides and 3 PCs, with different fatty acid length and saturation levels, were measured in the plasma from 412 participants (AD n = 205, Control n = 207) using mass spectrometry coupled with ultra-performance liquid chromatography. After this, associations with AD status, brain atrophy, and age-related effects were studied. In the plasma of AD participants, cross-sectional analysis revealed elevated levels of three ceramides (Cer16:0 p < 0.01, Cer18:0 p < 0.01, Cer24:1 p < 0.05). In addition, two PCs in AD plasma (PC36:5 p < 0.05, PC38:6 p < 0.05) were found to be depleted compared to the control group, with PC36:5 also associating with hippocampal atrophy (p < 0.01). Age-specific analysis further revealed that levels of Cer16:0, Cer18:0, and Cer20:0 were associated with hippocampal atrophy only in younger participants (age < 75, p < 0.05), while all 3 PCs did so in the older participants (age > 75, p < 0.05). PC36:5 was associated with AD status in the younger group (p < 0.01), while PC38:6 and 40:6 did so in the older group (p < 0.05). In this study, elevated ceramides and depleted PCs were found in the plasma from 205 AD volunteers. Our findings also suggest that dysregulation in PC and ceramide metabolism could be occurring in different stages of AD progression.