Discovery and Subsequent Confirmation of Novel Serum Biomarkers Diagnosing Alzheimer’s Disease

Gender differences contribute to variability of serum lipid biomarkers for Alzheimer's disease

Background: Alzheimer's disease (AD) cannot currently be diagnosed by a blood test. One reason may be gender differences. Another may be the statistical methods used. The authors evaluate these possibilities. Objective: The authors applied serum lipidomics to find AD biomarkers in men and women. They hypothesized that AD biomarkers would differ between genders and that machine-learning algorithms would improve diagnostic performance. Methods: Serum lipids were analyzed by mass spectrometry for a training set of AD cases and controls and in a blinded test set. Statistical analyses considered gender differences. Results: Lipids best classifying AD subjects differed significantly between men and women. Robust statistical algorithms did not improve diagnostic performance. Conclusion: Poor performance of AD biomarkers appears to be due primarily to inherent variability in AD patients.

Why Inclusion Matters for Alzheimer’s Disease Biomarker Discovery in Plasma

Background: African American/Black adults have a disproportionate incidence of Alzheimer’s disease (AD) and are underrepresented in biomarker discovery efforts. Objective: This study aimed to identify potential diagnostic biomarkers for AD using a combination of proteomics and machine learning approaches in a cohort that included African American/Black adults. Methods: We conducted a discovery-based plasma proteomics study on plasma samples (N = 113) obtained from clinically diagnosed AD and cognitively normal adults that were self-reported African American/Black or non-Hispanic White. Sets of differentially-expressed proteins were then classified using a support vector machine (SVM) to identify biomarker candidates. Results: In total, 740 proteins were identified of which, 25 differentially-expressed proteins in AD came from comparisons within a single racial and ethnic background group. Six proteins were differentially-expressed in AD regardless of racial and ethnic background. Supervised classification by SVM yielded an area under the curve (AUC) of 0.91 and accuracy of 86%for differentiating AD in samples from non-Hispanic White adults when trained with differentially-expressed proteins unique to that group. However, the same model yielded an AUC of 0.49 and accuracy of 47%for differentiating AD in samples from African American/Black adults. Other covariates such as age, APOE4 status, sex, and years of education were found to improve the model mostly in the samples from non-Hispanic White adults for classifying AD. Conclusion: These results demonstrate the importance of study designs in AD biomarker discovery, which must include diverse racial and ethnic groups such as African American/Black adults to develop effective biomarkers.

Nano-liquid chromatography-mass spectrometry and recent applications in omics investigations

Liquid chromatography coupled to mass spectrometry (LC-MS) is one of the most powerful tools in identifying and quantitating molecular species. Decreasing column diameter from the millimeter to micrometer scale is now a well-developed method which allows for sample limited analysis. Specific fabrication of capillary columns is required for proper implementation and optimization when working in the nanoflow regime. Coupling the capillary column to the mass spectrometer for electrospray ionization (ESI) requires reduction of the subsequent emitter tip. Reduction of column diameter to capillary scale can produce improved chromatographic efficiency and the reduction of emitter tip size increased sensitivity of the electrospray process. This improved sensitivity and ionization efficiency is valuable in analysis of precious biological samples where analytes vary in size, ion affinity, and concentration. In this review we will discuss common approaches and challenges in implementing nLC-MS methods and how the advantages can be leveraged to investigate a wide range of biomolecules.

IL-12p40 and sRAGE in serum correlate with chemically induced cleft palate in mice

Cleft palate (CP), a congenital defect in the oral and maxillofacial regions, is difficult to detect prenatally. This study investigated the correlation between differentially expressed proteins in serum and CP induced by all-trans retinoic acid (atRA) and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in mice. We studied 80 mice in the following groups: male mice (male; n = 6), nonpregnant female control mice (NP-CRL; n = 6), healthy pregnant controls (P-CRL; Con; n = 24), pregnant mice with CP induced by atRA (n = 24), or pregnant mice with CP induced by TCDD (TCDD; n = 20). Pregnant mice were given with atRA (100 mg/kg) or TCDD (40 μg/kg), or corn oil by oral gavage at E10.5. The serum samples were collected and eight proteins-including interleukin (IL)-12p40, IL-12p70, receptor for advanced glycation end products (RAGE), interferon (IFN)-γ, IFN-β, IL-10, leukemia inhibitory factor (LIF), and epiregulin-were detected by enzyme-linked immunosorbent assay. Placental tissues were immunostained for IL-12p40 and RAGE from stages E13.5 to E16.5. In P-CRL mice, serum IL-12p40 was significantly increased at E13.5 and declined over E14.5-E16.5. P-CRL had lower IFN-γ levels at E13.5 compared with NP-CRL. The CP groups showed lower concentrations of IL-12p40 at E13.5-E14.5 and clearly higher concentrations of soluble RAGE (sRAGE) at E13.5 when compared with P-CRL. IL-12p40 immunostaining clearly decreased in placental tissue sections obtained from E13.5 to E14.5 in both CP groups. These findings suggest that reduced levels of IL-12p40 and increased levels of sRAGE in serum may be correlated with chemically induced CP in mice, but further studies would be required to establish this.

Biomarkers in Alzheimer's, Frontotemporal, Lewy Body, and Vascular Dementias

This article reviews the current evidence base for biomarkers of the most common causes of dementia in later life: Alzheimer's disease (AD), frontotemporal lobar degenerations, Lewy body dementias, and vascular cognitive impairment and dementia. Biomarkers are objectively measurable indicators of normal physiology, pathological processes, or response to an intervention. Ideally, they are sensitive, specific, easy to obtain, and closely reflect the underlying biological processes of interest. While such markers are well established and in broad clinical use for common disorders in general medicine (e.g., thallium stress tests for coronary artery disease or serum blood urea nitrogen and creatinine for renal failure), analogous, validated markers for AD or other common dementias are limited, although biomarkers in research settings and specialty dementia clinics are progressing toward clinical use. By way of introducing current and future biomarkers for dementias of later life, this article will benefit the practicing clinician by increasing awareness of the availability and utility of current and emerging biomarkers in dementia diagnosis and prognosis and for monitoring new disease-modifying therapeutics that arrive in the clinic over the coming decade.

Extracellular matrix proteomics in schizophrenia and Alzheimer's disease

Brain extracellular matrix (ECM) is a highly organized system that consists of collagens, noncollagenous proteins, glycoproteins, hyaluronan, and proteoglycans. Recognized physiological roles of ECM include developmental regulation, tissue homeostasis, cell migration, cell proliferation, cell differentiation, neuronal plasticity, and neurite outgrowth. Aberrant ECM structure is associated with brain neurodegenerative conditions. This review focuses on two neurodegenerative conditions, schizophrenia and Alzheimer's disease, and summarizes recent findings of altered ECM components, including proteoglycans, glycosaminoglycans, proteins, and glycoproteins, and proteins and genes related to other brain components. The scope includes immunohistochemical, genomics, transcriptomics, proteomics, and glycomics studies, and a critical assessment of current state of proteomic studies for neurodegenerative disorders. The intent is to summarize the ECM molecular alterations associated with neurodegenerative pathophysiology. Graphical Abstract Brain extracellular matrix showing HSPGs, CSPGs, HA, collagens, and other glycoproteins.

The Role of Clinical Proteomics, Lipidomics, and Genomics in the Diagnosis of Alzheimer's Disease

The early diagnosis of Alzheimer’s disease (AD) has become important to the reversal and treatment of neurodegeneration, which may be relevant to premature brain aging that is associated with chronic disease progression. Clinical proteomics allows the detection of various proteins in fluids such as the urine, plasma, and cerebrospinal fluid for the diagnosis of AD. Interest in lipidomics has accelerated with plasma testing for various lipid biomarkers that may with clinical proteomics provide a more reproducible diagnosis for early brain aging that is connected to other chronic diseases. The combination of proteomics with lipidomics may decrease the biological variability between studies and provide reproducible results that detect a community’s susceptibility to AD. The diagnosis of chronic disease associated with AD that now involves genomics may provide increased sensitivity to avoid inadvertent errors related to plasma versus cerebrospinal fluid testing by proteomics and lipidomics that identify new disease biomarkers in body fluids, cells, and tissues. The diagnosis of AD by various plasma biomarkers with clinical proteomics may now require the involvement of lipidomics and genomics to provide interpretation of proteomic results from various laboratories around the world.