Zhang, Fan

AbstractIntroductionRepresentation of Mexican Americans in Alzheimer's disease (AD) clinical research has been extremely poor.MethodsData were examined from the ongoing community‐based, multi‐ethnic Health & Aging Brain among Latino Elders (HABLE) study. Participants underwent functional exams, clinical labs, neuropsychological testing, and 3T magnetic resonance imaging of the brain. Fasting proteomic markers were examined for predicting mild cognitive impairment (MCI) and AD using support vector machine models.ResultsData were examined from n = 1649 participants (Mexican American n = 866; non‐Hispanic White n = 783). Proteomic profiles were highly accurate in detecting MCI (area under the curve [AUC] = 0.91) and dementia (AUC = 0.95). The proteomic profiles varied significantly between ethnic groups and disease state. Negative predictive value was excellent for ruling out MCI and dementia across ethnic groups.DiscussionA blood‐based screening tool can serve as a method for increasing access to state‐of‐the‐art AD clinical research by bridging between community‐based and clinic‐based settings.

AbstractIntroductionWe sought to determine if a proteomic profile approach developed to detect Alzheimer's disease would distinguish patients with Lewy body disease from normal controls, and if it would distinguish dementia with Lewy bodies (DLB) from Parkinson's disease (PD).MethodsStored plasma samples were obtained from 145 patients (DLB n = 57, PD without dementia n = 32, normal controls n = 56) enrolled from patients seen in the Behavioral Neurology or Movement Disorders clinics at the Mayo Clinic, Florida. Proteomic assays were conducted and analyzed as per our previously published protocols.ResultsIn the first step, the proteomic profile distinguished the DLB‐PD group from controls with a diagnostic accuracy of 0.97, sensitivity of 0.91, and specificity of 0.86. In the second step, the proteomic profile distinguished the DLB from PD groups with a diagnostic accuracy of 0.92, sensitivity of 0.94, and specificity of 0.88.DiscussionThese data provide evidence of the potential utility of a multitiered blood‐based proteomic screening method for detecting DLB and distinguishing DLB from PD.

Background: There is a significant need for rapid and cost-effective biomarkers of Alzheimer’s disease (AD) for advancement of clinical practice and therapeutic trials. Objective: The aim of the current study was to cross-validate our previously published serum-based algorithm on an independent assay platform as well as validate across tissues and species. Preliminary analyses were conducted to examine the utility in distinguishing AD from non-AD neurological disease (Parkinson’s disease, PD). Methods: Serum proteins from our previously published algorithm were quantified from 150 AD cases and 150 controls on the Meso Scale Discovery (MSD) platform. Serum samples were analyzed from 49 PD cases and compared to a random sample of 51 AD cases and 62 controls. Support vector machines (SVM) were used to discriminate PD versus AD versus controls. Human and AD mouse model microvessel images were quantified with HAMAMATSU imaging software. Mouse serum biomarkers were assayed via MSD. Results: Analysis of 21 serum proteins from 150 AD cases and 150 controls yielded an algorithm with sensitivity and specificity of 0.90 for correctly classifying AD. This multi-marker approach was then validated across species and tissue. Assay of the top proteins in human and AD mouse model brain microvessels correctly classified 90–100% of the samples. SVM analyses were highly accurate at distinguishing PD versus AD versus controls. Conclusions: This serum-based biomarker panel should be tested in a community-based setting to determine its utility as a first-line screen for AD and non-AD neurological diseases for primary care providers.

AbstractIntroductionThis study investigated the comparability of potential Alzheimer's disease (AD) biomarkers across blood fractions and assay platforms.MethodsNonfasting serum and plasma samples from 300 participants (150 AD patients and 150 controls) were analyzed. Proteomic markers were obtained via electrochemiluminescence or Luminex technology. Comparisons were conducted via Pearson correlations. The relative importance of proteins within an AD diagnostic profile was examined using random forest importance plots.ResultsOn the Meso Scale Discovery multiplex platform, 10 of the 21 markers shared >50% of the variance across blood fractions (serum amyloid A R2 = 0.99, interleukin (IL)10 R2 = 0.95, fatty acid‐binding protein (FABP) R2 = 0.94, I309 R2 = 0.94, IL‐5 R2 = 0.94, IL‐6 R2 = 0.94, eotaxin3 R2 = 0.91, IL‐18 R2 = 0.87, soluble tumor necrosis factor receptor 1 R2 = 0.85, and pancreatic polypeptide R2 = 0.81). When examining protein concentrations across platforms, only five markers shared >50% of the variance (beta 2 microglobulin R2 = 0.92, IL‐18 R2 = 0.80, factor VII R2 = 0.78, CRP R2 = 0.74, and FABP R2 = 0.70).DiscussionThe current findings highlight the importance of considering blood fractions and assay platforms when searching for AD relevant biomarkers.