Qatar Metabolomics Study on Diabetes

The Qatar Metabolomics Study on Diabetes (QMDiab) is a type 2 diabetes case-control, which was conducted in 2012 at the Dermatology Department of Hamad Medical Corporation and the Weill Cornell Medical College in Doha, Qatar. The study was approved by the Institutional Review Boards of HMC and WCM-Q under research protocol number 11131/11. All study participants provided written informed consent.<br><br>Untargeted metabolomics measurements (LC/MS+, LC/MS-, and GC/MS) from plasma, urine, and saliva samples of 374 participants, which are aged 17-81 years, were performed by Metabolon Inc.<br><br>The OrigScale dataset comprises median-scaled data for each body fluid. The Preprocessed dataset comprises missing values treated, normalized, transformed, and scaled data. In both datasets, rows correspond to participants (anonymized) and columns correspond to metabolites. <br><br>Phenotype information (type 2 diabetes status, age, gender, BMI, ethnicity) are available as the last six columns of each dataset.<br>Annotations and pathway assigments are also provided for each metabolite

Machine-learning methods to discriminate between AD and CN samples.

<p>Machine-learning methods to discriminate between AD and CN samples.</p

Metabolic pathways and signaling cascades involving glycerophospholipids and sphingolipids: relevance to AD pathogenesis.

<p>Schematic articulation of the core metabolic and signaling pathways in neurons, highlighting links between glycerophospholipid and sphingolipid classes of lipid species identified in the current study to be associated with the severity of AD pathology in the brain. Nutrient transporters (SLC5A7, SLC1A5, CD36, FATPs) present both at the BBB as well as the neuronal cell membrane mediate the uptake of amino acids, long chain fatty acids, and vitamin precursors into neurons necessary for the de novo synthesis of glycerophospholipid and SM lipid species [<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002482#pmed.1002482.ref035" target="_blank">35</a>,<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002482#pmed.1002482.ref036" target="_blank">36</a>]. The “metabolic pathway” section of the diagram represents the core metabolic pathways involved in the synthesis and recycling of glycerophospholipid and sphingolipid species. The “signaling pathway” section connects these lipid species to the core representative signaling cascades implicated in mediating multiple aspects of AD pathology in the brain, such as formation of neuritic plaques, neurofibrillary tangles, and AD-like brain atrophy. In a condition-dependent manner, incoming free fatty acids are incorporated into glycerolipids or ceramides in the endoplasmic reticulum. Similarly, LCFAs are processed in peroxisomal organelles to generate ether lipids. Coupling with the Kennedy pathway, glycerolipids and ether lipids are converted to either aa or ae PC species [<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002482#pmed.1002482.ref037" target="_blank">37</a>]. PCs are metabolized by the phospholipase or SML enzymes to recycle back phosphatidic acid or DAG or to generate SM, respectively. These lipid species are critical in the formation of lipid rafts, which represent essential structural and functional domains for maintaining neuronal function [<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002482#pmed.1002482.ref038" target="_blank">38</a>]. In AD, remodeling of lipid rafts, especially with enhanced activity of SMLs, results in an increased ceramide to SM ratio, which facilitates Aβ production by posttranslational stabilization of BACE1 enzyme. This leads to further generation of oligomeric Aβ due to a feed forward regulatory loop between Aβ and the SML enzymes [<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002482#pmed.1002482.ref039" target="_blank">39</a>]. Similarly, PC with saturated and unsaturated long-chain fatty acyl groups positively influence activity of the Ƴ-secretase enzyme by modulating cell membrane thickness and the lipid microenvironment of the enzyme [<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002482#pmed.1002482.ref040" target="_blank">40</a>]. Meanwhile, generation of lysophosphatidylcholine from membrane PC by both cytosolic PLA2G4A in Land’s cycle [<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002482#pmed.1002482.ref041" target="_blank">41</a>] as well as the secretory soluble PLA2G2A can lead to dysregulation of intracellular calcium signaling in a G-protein receptor (GPR132, G2A) coupled manner. Dysregulated Ca2+ signaling can result in enhanced activity of CAMKII, which, in coordination with the ceramide–PP2A–GSK3β pathway, results in tau hyperphosphorylation, leading to the generation of PHF and enhanced neurofibrillary tangle formation [<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002482#pmed.1002482.ref042" target="_blank">42</a>]. Furthermore, altered ceramide signaling by down-regulation of AKT kinase activity via PP2A can trigger neuronal apoptosis by augmenting activity of the pro-apoptotic proteins, BAD and BIM_EL. aa, diacyl; Aβ, amyloid-β; AD, Alzheimer disease; ae, acyl-alkyl; AKT, protein kinase B; BACE1, β-secretase; BAD, BCL2 associated agonist of cell death; BBB, blood-brain barrier; BIM_EL, BCL2 interacting mediator of cell death-extra long; CAMKII, calmodulin kinase; CD36, CD36 molecule; DAG, diacylglycerol; ECF, extracellular fluid; ER, endoplasmic reticulum FATP, fatty acid transport protein; LCFA, long-chain fatty acid; LysoPC, lysophosphatidylcholine; PC, phosphatidylcholine; PHF, paired helical filaments; PLA2G2A, phospholipase A2 group IIA; PLA2G4A, phospholipase A2 Group IVA; PP2A, protein phosphatase; SLC1A5, solute carrier family 1 member 5; SLC5A7, solute carrier family 5 member 7; SM, sphingomyelin; SML, sphingomyelinase.</p

Heat map summarizing associations between metabolites and AD endophenotypes.

<p>Meanings of column headings: AD-ASY-CN, association between brain tissue metabolite concentration and clinical diagnosis of AD; CERAD, association between brain tissue metabolite concentration and plaques measured by CERAD score; Braak, association between brain tissue metabolite concentration and neurofibrillary tangle burden measured by Braak score; SPARE-AD, association between blood tissue metabolite concentration in ADNI and SPARE-AD score; A Beta, association between blood tissue metabolite concentration in ADNI and CSF Aβ_1–42; t-tau, association between blood tissue metabolite concentration in ADNI and CSF (t-tau); p-tau, association between blood tissue metabolite concentration in ADNI and CSF (p-tau); Cog perfor, association between blood tissue metabolite concentration and cognitive performance prior to AD onset; EASE-AD, sum of significant associations across AD-related endophenotypes. ADNI Cox: association between blood tissue metabolite concentration and risk of incident AD in ADNI among MCI individuals. BLSA Cox: association between blood tissue metabolite concentration and risk of incident AD/MCI in BLSA among cognitively normal individuals. Aβ_1–42, amyloid beta 1–42; AD, Alzheimer disease; ADNI, Alzheimer’s Disease Neuroimaging Initiative; ASY, asymptomatic Alzheimer’s disease; BLSA, Baltimore Longitudinal Study of Aging; CERAD, Consortium to Establish a Registry for Alzheimer's Disease; CN, control; CSF, cerebrospinal fluid; EASE-AD, Endophenotype Association Score in Early Alzheimer’s disease; MCI, mild cognitive impairment; OH, hydroxyl; p-tau, phosphorylated tau; PC, phosphatidylcholine; SM, sphingomyelin; SPARE-AD, Spatial Pattern of Abnormality for Recognition of Early Alzheimer’s disease; t-tau, total tau.</p

Demographic characteristics of study samples.

<p>Demographic characteristics of study samples.</p

Associations between blood metabolite concentration and SPARE-AD index, CSF concentrations of Aβ_1–42, t-tau, and p-tau.

<p>Please note that vertical axes scales differ across graphs in panels A and B. (<b>A</b>) ρs and <i>p</i>-values showing associations between representative metabolites and AD-like patterns of brain atrophy on MRI scans (SPARE-AD index). (<b>B</b>) ρs and <i>p</i>-values showing associations between representative metabolites and CSF markers of AD: Aβ_1–42, t-tau, and p-tau. ρ, correlation coefficient; Aβ_1–42, amyloid beta 1–42; AD, Alzheimer disease; CSF, cerebrospinal fluid; MRI, magnetic resonance imaging; OH, hydroxyl; p-tau, phosphorylated tau; PC, phosphatidylcholine; SM, sphingomyelin; SPARE-AD, Spatial Patterns of Abnormality for Recognition of Early Alzheimer’s disease; t-tau, total tau.</p

Associations between brain tissue metabolite concentration and clinical groups, CERAD scores, and Braak scores.

<p>Please note that vertical axes scales differ across graphs in panels A and B. (<b>A</b>) Group differences and global <i>p</i>-values for significance across clinical groups for brain tissue concentration of three representative sphingolipids and three representative glycerophospholipids in the ITG. (<b>B</b>) ρs and <i>p</i>-values showing associations between three representative sphingolipids and three representative glycerophospholipids and severity of neuritic plaque burden (CERAD scores). (<b>C</b>) ρs and <i>p</i>-values showing associations between three representative sphingolipids and three representative glycerophospholipids and severity of neurofibrillary pathology (Braak scores). ρ, correlation coefficient; AD, Alzheimer disease; ASYMAD, asymptomatic Alzheimer’s disease; CERAD, Consortium to Establish a Registry for Alzheimer's Disease; CN, control; ITG, inferior temporal gyrus; OH, hydroxy; PC, phosphatidylcholine; SM, sphingomyelin.</p

Schematic representation of study design.

<p>In Step 1, we used a quantitative and targeted metabolomics approach followed by two machine-learning methods to identify a panel of metabolites—a “brain metabolite signature of AD”—that accurately differentiated brain tissue samples from neuropathologically confirmed AD and CN subjects. In Step 2, using that same metabolite panel, we explored whether blood concentrations of metabolites in two independent samples representing prodromal AD (ADNI) and preclinical AD (BLSA) were associated with distinct clinical, cognitive, neuroimaging, and CSF endophenotypes of AD. In Step 3, we summarized results by developing an integrated blood and brain endophenotype score capturing the relative importance of specific brain and blood metabolites to severity of AD pathology and disease progression. In Step 4, we mapped the main metabolite classes (emerging from Step 3) to key biological pathways implicated in AD pathogenesis. Aβ_1–42, amyloid beta 1–42; AD, Alzheimer disease; ADNI, Alzheimer’s Disease Neuroimaging Initiative; ASYMAD, asymptomatic Alzheimer’s disease; BLSA, Baltimore Longitudinal Study of Aging; CERAD, Consortium to Establish a Registry for Alzheimer's Disease; CN, control; CSF, cerebrospinal fluid; EASE-AD, Endophenotype Association Score in Early Alzheimer’s disease; IDQ, Identification and Quantification; MCI, mild cognitive impairment; MRI, magnetic resonance imaging; p-tau, phosphorylated tau; SPARE-AD, Spatial Patterns of Abnormality for Recognition of Early Alzheimer’s disease; t-tau, total tau.</p

Top metabolites based on SVM and RF algorithms in the ITG.

<p>Top metabolites based on SVM and RF algorithms in the ITG.</p