Plasma biomarkers for Alzheimer's disease: much needed but tough to find

A plasma protein signature associated with cognitive function in men without severe cognitive impairment

BACKGROUND

A minimally invasive blood-based assessment of cognitive function could be a promising screening strategy to identify high-risk groups for the incidence of Alzheimer's disease.

METHODS

The study included 448 cognitively unimpaired men (mean age 64.1 years) drawn from the Geelong Osteoporosis Study. A targeted mass spectrometry-based proteomic assay was performed to measure the abundance levels of 269 plasma proteins followed by linear regression analyses adjusted for age and APOE ε4 carrier status to identify the biomarkers related to overall cognitive function. Furthermore, two-way interactions were conducted to see whether Alzheimer's disease-linked genetic variants or health conditions modify the association between biomarkers and cognitive function.

RESULTS

Ten plasma proteins showed an association with overall cognitive function. This association was modified by allelic variants in genes ABCA7, CLU, BDNF and MS4A6A that have been previously linked to Alzheimer's disease. Modifiable health conditions such as mood disorders and poor bone health, which are postulated to be risk factors for Alzheimer's disease, also impacted the relationship observed between protein marker levels and cognition. In addition to the univariate analyses, an 11-feature multianalyte model was created using the least absolute shrinkage and selection operator regression that identified 10 protein features and age associated with cognitive function.

CONCLUSIONS

Overall, the present study revealed plasma protein candidates that may contribute to the development of a blood-based screening test for identifying early cognitive changes. This study also highlights the importance of considering other risk factors in elucidating the relationship between biomarkers and cognition, an area that remains largely unexplored.

Genetic models of cleavage-reduced and soluble TREM2 reveal distinct effects on myelination and microglia function in the cuprizone model

Triggering receptor expressed on myeloid cells 2 (TREM2) is a cell-surface immunoreceptor expressed on microglia, osteoclasts, dendritic cells and macrophages. Heterozygous loss-of-function mutations in TREM2, including mutations enhancing shedding form the cell surface, have been associated with myelin/neuronal loss and neuroinflammation in neurodegenerative diseases, such as Alzheimer`s disease and Frontotemporal Dementia. Using the cuprizone model, we investigated the involvement of soluble and cleavage-reduced TREM2 on central myelination processes in cleavage-reduced (TREM2-IPD), soluble-only (TREM2-sol), knockout (TREM2-KO) and wild-type (WT) mice. The TREM2-sol mouse is a new model with selective elimination of plasma membrane TREM2 and a reduced expression of soluble TREM2. In the acute cuprizone model demyelination and remyelination events were reflected by a T2-weighted signal intensity change in magnetic resonance imaging (MRI), most prominently in the external capsule (EC). In contrast to WT and TREM2-IPD, TREM2-sol and TREM2-KO showed an additional increase in MRI signal during the recovery phase. Histological analyses of TREM2-IPD animals revealed no recovery of neuroinflammation as well as of the lysosomal marker LAMP-1 and displayed enhanced cytokine/chemokine levels in the brain. TREM2-sol and, to a much lesser extent, TREM2-KO, however, despite presenting reduced levels of some cytokines/chemokines, showed persistent microgliosis and astrocytosis during recovery, with both homeostatic (TMEM119) as well as activated (LAMP-1) microglia markers increased. This was accompanied, specifically in the EC, by no myelin recovery, with appearance of myelin debris and axonal pathology, while oligodendrocytes recovered. In the chronic model consisting of 12-week cuprizone administration followed by 3-week recovery TREM2-IPD displayed sustained microgliosis and enhanced remyelination in the recovery phase. Taken together, our data suggest that sustained microglia activation led to increased remyelination, whereas microglia without plasma membrane TREM2 and only soluble TREM2 had reduced phagocytic activity despite efficient lysosomal function, as observed in bone marrow-derived macrophages, leading to a dysfunctional phenotype with improper myelin debris removal, lack of remyelination and axonal pathology following cuprizone intoxication.

Towards a WPA Position Document on the Human Rights of Older Adults with Mental Health Conditions: К документу с изложением позиции Всемирной психиатрической ассоциации по вопросу соблюдения прав пожилых людей с психическими расстройствами

The increasing number of older adults in countries across the world is a huge challenge to those that are in charge of promoting, protecting, and implementing their human rights. This task is particularly difficult in the absence of a strong international framework addressing the principles required to guide the actions to combat all human rights violations. The existence of such a specific framework for older adults with mental health conditions is justified in view of the particular vulnerability of this section of the population by virtue of societal ageism, stigmatization, exclusion, as well as the disability and dependency which mental health conditions in old age may confer. The present article is a development of a previous statement by the International Psychogeriatric Association and the World Psychiatric Association Section of Old Age Psychiatry. As there is a call to all organizations to support efforts to combat Human Rights violations among older adults, a text will be submitted to the Executive Committee of the World Psychiatric Association to approve an official position statement on Human Rights of Older Persons with Mental Health Conditions.

The Evolution of Diagnostic Boundaries of Alzheimer's Disease and Novel Therapeutic Options: Эволюция диагностических границ болезни Альцгеймера и новые терапевтические возможности

Over the past three decades, the definition and diagnostic boundaries of Alzheimer's disease (AD) have been repeatedly revised due to significant progress in understanding of the pathogenesis of neurodegeneration associated with Alzheimer's disease and in the development of high-tech diagnostic methods. The current approach to AD diagnostics relies on the detection of biomarkers that reflect two main neuropathological processes involved in the primary neurodegeneration that underlies AD: abnormal amyloidogenesis, and neuronal degeneration. The currently available diagnostic tools are limited to the detection of cerebrospinal biomarkers and/or assessment of the abnormal amyloid and tau protein burden in the brain via amyloid and tau positron emission tomography (PET) ligands. Practical implementation (mostly in the research field) of the biological model of AD diagnosis has led to a significant expansion of its diagnostic boundaries with the inclusion of predementia AD stages: asymptomatic and symptomatic, the latter is clinically corresponding to amnestic mild cognitive impairment (aMCI-amnestic mild cognitive impairment). On the one hand, this approach significantly expands the possibilities to study and use preventive technologies aiming to avert or delay the progression of predementia cognitive impairment to dementia but, on the other, it is associated with a number of negative implications from both the clinical and ethical points of view. A significant limitation of purely biological diagnosis of AD based on biomarker levels is due to the low prognostic value of biomarkers, which can cause diagnostic confusion in certain circumstances. Moreover, since the future evolution of the asymptomatic stage is not yet clear and there are still no reliable ways to prevent the cognitive and behavioral symptoms associated with AD, disclosure of stressful information about this "terrifying" diagnosis to patients can cause irreversible damage by triggering depressive disorder, which is a risk factor of AD itself. The current knowledge about AD prognosis in amyloid-positive cognitively unimpaired patients is insufficient.The most adequate approach to early AD diagnostics appears to be the clinical and biological model, as recommended by the International Working Group (IWG 2021), which requires a combination of the clinical AD phenotype and the detection of biomarkers specific to this disease. The article discusses the potential directions for the development of biological diagnostic methods, including those based on the so-called peripheral (serum) biomarker technologies and promising directions for the development of biological methods of secondary AD prevention.

Blood-based Biomarkers of Alzheimer's Disease: The Long and Winding Road

BACKGROUND

Blood-based biomarkers can be very useful in formulating new diagnostic and treatment proposals in the field of dementia, especially in Alzheimer's disease (AD). However, due to the influence of several factors on the reproducibility and reliability of these markers, their clinical use is still very uncertain. Thus, up-to-date knowledge about the main blood biomarkers that are currently being studied is extremely important in order to discover clinically useful and applicable tools, which could also be used as novel pharmacological strategies for the AD treatment.

METHODS

A narrative review was performed based on the current candidates of blood-based biomarkers for AD to show the main results from different studies, focusing on their clinical applicability and association with AD pathogenesis.

OBJECTIVE

The aim of this paper was to carry out a literature review on the major blood-based biomarkers for AD, connecting them with the pathophysiology of the disease.

RESULTS

Recent advances in the search of blood-based AD biomarkers were summarized in this review. The biomarkers were classified according to the topics related to the main hallmarks of the disease such as inflammation, amyloid, and tau deposition, synaptic degeneration and oxidative stress. Moreover, molecules involved in the regulation of proteins related to these hallmarks were described, such as non-coding RNAs, neurotrophins, growth factors and metabolites. Cells or cellular components with the potential to be considered as blood-based AD biomarkers were described in a separate topic.

CONCLUSION

A series of limitations undermine new discoveries on blood-based AD biomarkers. The lack of reproducibility of findings due to the small size and heterogeneity of the study population, different analytical methods and other assay conditions make longitudinal studies necessary in this field to validate these structures, especially when considering a clinical evaluation that includes a broad panel of these potential and promising blood-based biomarkers.

CCL23: A Chemokine Associated with Progression from Mild Cognitive Impairment to Alzheimer's Disease

CCL23 is a chemokine implicated in inflammation and host defense responses. It has been recently associated with acquired brain damage and stroke outcomes. In this study, we reported the role of CCL23 in Alzheimer's disease (AD). We evaluated the levels of CCL23 in 659 individuals: cognitively normal, mild cognitive impaired (MCI), and AD patients. Two cross-sectional (study 1, n = 53; study 2, n = 200) and two longitudinal (study 3, n = 74; study 4, n = 332) studies were analyzed separately. CCL23 levels in the blood and/or cerebrospinal fluid (CSF) of each study were measured by immunoassays. Globally, our results suggest a predictive role of CCL23 protein levels both in the plasma in study 3 (hazard ratio (HR) = 2.5 (confidence interval (CI) 95% : 1.2-5.3), p = 0.02) and in the CSF in study 4 (HR = 3.05 (CI 95% : 1.02-5), p = 0.04) in cases of MCI that progress to AD. Moreover, we observed that the APOEɛ4 allele was associated with higher levels of CCL23 in study 2 (470.33 pg/mL (interquartile range (IQR): 303.33-597.76) versus 377.94 pg/mL (IQR: 267.16-529.19), p = 0.01) (APOE genotypes were available in studies 2 and 4). Together, these findings support the role of CCL23 in neuroinflammation in the early stages of AD, suggesting that CCL23 might be a candidate blood biomarker for MCI to AD progression.

An Exploratory Analysis of Potential New Biomarkers of Cognitive Function

We examined the relationship between serially measured, novel serum biomarkers and a measure of cognitive functioning in older adults. We assayed stored serum samples from two Fels Longitudinal Study visits in N = 100 adult participants (visit 1 ages 59.3 ± 8.5 years; 53% female), and Montreal Cognitive Assessment (MoCA) scores also assessed at the second visit. Assays included acylcarnitines, amino acids, and 2-hydroxybutyric acid (b-HBA). Cross-sectional correlations between acylcarnitines and amino acids and MoCA were identified. Serial change in short-chain acylcarnitines and visit 2 MoCA were also correlated. Participants with MoCA scores <26 were more likely to have an increase in short-chain acylcarnitines between visits 1 and 2 [adjusted odds ratio (OR) = 5.24; 95% confidence interval (CI) 1.07-25.9]. b-HBA was also correlated with acylcarnitines. Several cross-sectional and serial associations between novel serum biomarkers and cognitive functioning were identified. b-HBA may also be a cost-effective marker of dysregulation associated with cognitive decline.

Plasma Biomarkers: Potent Screeners of Alzheimer's Disease

Alzheimer's disease (AD), a neurological disorder, is as a complex chronic disease of brain cell death that usher to cognitive decline and loss of memory. Its prevalence differs according to risk factors associated with it and necropsy performs vital role in its definite diagnosis. The stages of AD vary from preclinical to severe that proceeds to death of patient with no availability of treatment. Biomarker may be a biochemical change that can be recognized by different emerging technologies such as proteomics and metabolomics. Plasma biomarkers, 5-protein classifiers, are readily being used for the diagnosis of AD and can also predict its progression with a great accuracy, specificity, and sensitivity. In this review, upregulation or downregulation of few plasma proteins in patients with AD has also been discussed, when juxtaposed with control, and thus serves as potent biomarker in the diagnosis of AD.

Inflammatory biomarkers in Alzheimer's disease plasma

Introduction

Plasma biomarkers for Alzheimer's disease (AD) diagnosis/stratification are a “Holy Grail” of AD research and intensively sought; however, there are no well-established plasma markers.

Methods

A hypothesis-led plasma biomarker search was conducted in the context of international multicenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL; 259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed.

Results

Ten analytes showed significant intergroup differences. Logistic regression identified five (FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APOε4 adjusted, optimally differentiated AD and CTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI (AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Two analytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71).

Discussion

Plasma markers of inflammation and complement dysregulation support diagnosis and outcome prediction in AD and MCI. Further replication is needed before clinical translation.

A plasma protein classifier for predicting amyloid burden for preclinical Alzheimer's disease

A blood-based assessment of preclinical disease would have huge potential in the enrichment of participants for Alzheimer's disease (AD) therapeutic trials. In this study, cognitively unimpaired individuals from the AIBL and KARVIAH cohorts were defined as Aβ negative or Aβ positive by positron emission tomography. Nontargeted proteomic analysis that incorporated peptide fractionation and high-resolution mass spectrometry quantified relative protein abundances in plasma samples from all participants. A protein classifier model was trained to predict Aβ-positive participants using feature selection and machine learning in AIBL and independently assessed in KARVIAH. A 12-feature model for predicting Aβ-positive participants was established and demonstrated high accuracy (testing area under the receiver operator characteristic curve = 0.891, sensitivity = 0.78, and specificity = 0.77). This extensive plasma proteomic study has unbiasedly highlighted putative and novel candidates for AD pathology that should be further validated with automated methodologies.

Lipidomic Profiles in Diabetes and Dementia

Lipids are a diverse class of hydrophobic and amphiphilic molecules which make up the bulk of most biological systems and are essential for human life. The role of lipids in health and disease has been recognized for many decades, as evidenced by the early identification of cholesterol as an important risk factor of heart disease and the development and introduction of statins as a one of the most successful therapeutic interventions to date. While several studies have demonstrated an increased risk of dementia, including Alzheimer's disease (AD), in those with diabetes mellitus, the nature of this risk is not well understood. Recent developments in the field of lipidomics, driven primarily by technological advances in high pressure liquid chromatography and particularly mass spectrometry, have enabled the detailed characterization of the many hundreds of individual lipid species in mammalian systems and their association with disease states. Diabetes mellitus and AD have received particular attention due to their prominence in Western societies as a result of the ongoing obesity epidemic and the aging populations. In this review, we examine how these lipidomic studies are informing on the relationship between lipid metabolism with diabetes and AD and how this may inform on the common pathological pathways that link diabetes risk with dementia.

Predictors for drug effects with brain disease: Shed new light from EEG parameters to brain connectomics

Though researchers spent a lot of effort to develop treatments for neuropsychiatric disorders, the poor translation of drug efficacy data from animals to human hampered the success of these therapeutic approaches in human. Pharmaceutical industry is challenged by low clinical success rates for new drug registration. To maximize the success in drug development, biomarkers are required to act as surrogate end points and predictors of drug effects. The pathology of brain disease could be in part due to synaptic dysfunction. Electroencephalogram (EEG), generating from the result of the postsynaptic potential discharge between cells, could be a potential measure to bridge the gaps between animal and human data. Here we discuss recent progress on using relevant EEG characteristics and brain connectomics as biomarkers to monitor drug effects and measure cognitive changes on animal models and human in real-time. It is expected that the novel approach, i.e. EEG connectomics, will offer a deeper understanding on the drug efficacy at a microcirculatory level, which will be useful to support the development of new treatments for neuropsychiatric disorders.

FTIR and Raman Spectroscopy Applied to Dementia Diagnosis Through Analysis of Biological Fluids

To date, it is still difficult to perform an early and accurate diagnosis of dementia, therefore significant research has focused on finding new dementia biomarkers that can aid in this respect. There is an urgent need for non-invasive, rapid, and relatively inexpensive procedures for early diagnostics. Studies have demonstrated that of spectroscopic techniques, such as Fourier Transform Infrared Spectroscopy (FTIR) and Raman Spectroscopy could be a useful and accurate procedure to diagnose dementia. Given that several biochemical mechanisms related to neurodegeneration and dementia can lead to changes in plasma components and others peripheral body fluids; blood-based samples coupled to spectroscopic analyses can be used as a simple and less invasive approach.

Metabolomic-guided discovery of Alzheimer's disease biomarkers from body fluid

The rapid increase in the older population has made age-related diseases like Alzheimer's disease (AD) a global concern. Given that there is still no cure for this neurodegenerative disease, the drastic growth in the number of susceptible individuals represents a major emerging threat to public health. The poor understanding of the mechanisms underlying AD is deemed the greatest stumbling block against progress in definitive diagnosis and management of this disease. There is a dire need for biomarkers that can facilitate early diagnosis, classification, prognosis, and treatment response. Efforts have been directed toward discovery of reliable and distinctive AD biomarkers but with very little success. With the recent emergence of high-throughput technology that is able to collect and catalogue vast datasets of small metabolites, metabolomics offers hope for a better understanding of AD and subsequent identification of biomarkers. This review article highlights the potential of using multiple metabolomics platforms as useful means in uncovering AD biomarkers from body fluids. © 2017 Wiley Periodicals, Inc.

Genetic Risk as a Marker of Amyloid-β and Tau Burden in Cerebrospinal Fluid

BACKGROUND

The search for a biomarker of Alzheimer's disease (AD) pathology (amyloid-β (Aβ) and tau) is ongoing, with the best markers currently being measurements of Aβ and tau in cerebrospinal fluid (CSF) and via positron emission tomography (PET) scanning. These methods are relatively invasive, costly, and often have high screening failure rates. Consequently, research is aiming to elucidate blood biomarkers of Aβ and tau.

OBJECTIVE

This study aims to investigate a case/control polygenic risk score (PGRS) as a marker of tau and investigate blood markers of a combined Aβ and tau outcome for the first time. A sub-study also considers plasma tau as markers of Aβ and tau pathology in CSF.

METHODS

We used data from the EDAR*, DESCRIPA**, and Alzheimer's Disease Neuroimaging Initiative (ADNI) cohorts in a logistic regression analysis to investigate blood markers of Aβ and tau in CSF. In particular, we investigated the extent to which a case/control PGRS is predictive of CSF tau, CSF amyloid, and a combined amyloid and tau outcome. The predictive ability of models was compared to that of age, gender, and APOE genotype ('basic model').

RESULTS

In EDAR and DESCRIPA test data, inclusion of a case/control PGRS was no more predictive of Aβ, and a combined Aβ and tau endpoint than the basic models (accuracies of 66.0%, and 73.3% respectively). The tau model saw a small increase in accuracy compared to basic models (59.6%). ADNI 2 test data also showed a slight increase in accuracy for the Aβ model when compared to the basic models (61.4%).

CONCLUSION

We see some evidence that a case/control PGRS is marginally more predictive of Aβ and tau pathology than the basic models. The search for predictive factors of Aβ and tau pathologies, above and beyond demographic information, is still ongoing. Better understanding of AD risk alleles, development of more sensitive assays, and studies of larger sample size are three avenues that may provide such factors. However, the clinical utility of possible predictors of brain Aβ and tau pathologies must also be investigated.*'Beta amyloid oligomers in the early diagnosis of AD and as marker for treatment response'**'Development of screening guidelines and criteria for pre-dementia Alzheimer's disease'.

A Pathway Based Classification Method for Analyzing Gene Expression for Alzheimer's Disease Diagnosis

Background:

Recent studies indicate that gene expression levels in blood may be able to differentiate subjects with Alzheimer’s disease (AD) from normal elderly controls and mild cognitively impaired (MCI) subjects. However, there is limited replicability at the single marker level. A pathway-based interpretation of gene expression may prove more robust.

Objectives:

This study aimed to investigate whether a case/control classification model built on pathway level data was more robust than a gene level model and may consequently perform better in test data. The study used two batches of gene expression data from the AddNeuroMed (ANM) and Dementia Case Registry (DCR) cohorts.

Methods:

Our study used Illumina Human HT-12 Expression BeadChips to collect gene expression from blood samples. Random forest modeling with recursive feature elimination was used to predict case/control status. Age and APOE ɛ4 status were used as covariates for all analysis.

Results:

Gene and pathway level models performed similarly to each other and to a model based on demographic information only.

Conclusions:

Any potential increase in concordance from the novel pathway level approach used here has not lead to a greater predictive ability in these datasets. However, we have only tested one method for creating pathway level scores. Further, we have been able to benchmark pathways against genes in datasets that had been extensively harmonized. Further work should focus on the use of alternative methods for creating pathway level scores, in particular those that incorporate pathway topology, and the use of an endophenotype based approach.

Translation of Pre-Clinical Studies into Successful Clinical Trials for Alzheimer's Disease: What are the Roadblocks and How Can They Be Overcome?

Preclinical studies are essential for translation to disease treatments and effective use in clinical practice. An undue emphasis on single approaches to Alzheimer's disease (AD) appears to have retarded the pace of translation in the field, and there is much frustration in the public about the lack of an effective treatment. We critically reviewed past literature (1990-2014), analyzed numerous data, and discussed key issues at a consensus conference on Brain Ageing and Dementia to identify and overcome roadblocks in studies intended for translation. We highlight various factors that influence the translation of preclinical research and highlight specific preclinical strategies that have failed to demonstrate efficacy in clinical trials. The field has been hindered by the domination of the amyloid hypothesis in AD pathogenesis while the causative pathways in disease pathology are widely considered to be multifactorial. Understanding the causative events and mechanisms in the pathogenesis are equally important for translation. Greater efforts are necessary to fill in the gaps and overcome a variety of confounds in the generation, study design, testing, and evaluation of animal models and the application to future novel anti-dementia drug trials. A greater variety of potential disease mechanisms must be entertained to enhance progress.

Serum-based protein profiles of Alzheimer's disease and mild cognitive impairment in elderly Hispanics

AIM

To describe the biomarker profiles in elderly Panamanians diagnosed with Alzheimer's disease (AD), mild cognitive impairment (MCI) or no impairment using serum-based biomarkers.

METHODS

Twenty-four proteins were analyzed using an electrochemiluminescence-based multiplex biomarker assay platform. A biomarker profile was generated using random forest analyses.

RESULTS

Two proteins differed among groups: IL-18 and T-lymphocyte-secreted protein I-309. The AD profile was highly accurate and independent of age, gender, education and Apolipoprotein E ε4 status. AD and MCI profiles had substantial overlap among the top markers, suggesting common functions in AD and MCI but differences in their relative importance.

CONCLUSION

Our results underscore the potential influence of genetic and environmental differences within Hispanic populations on the proteomic profile of AD.

[Development of preclinical diagnosis and preventive treatment of neurodegenerative diseases]

Neurodegenerative diseases (NDD) are serious fatal neurological and mental diseases that resulted in disability and fethal outcome. Based on the advances of basic sciences over the last two decades, new knowledge on the risk factors for NDD and molecular mechanisms of the pathogenesis are obtained. It has been shown that the accelerated process of neuronal death which is the main cause of NDD development begins long before the appearance of clinical symptoms. The first symptoms appeared only after the death of most specific regulatory neurons and exhaustion of brain compensatory reserve. Only at that time, one can make the diagnosis and start traditional treatment of patients that accounts for the extremely low efficacy of the latter. Currently, complex preclinical diagnosis based on the identification of relatively specific clinical precursors and peripheral biomarkers has been developing. Development of preclinical diagnosis and preventive treatment is a strategic issue of modern neurology and psychiatry. The resolution of this issue allows to consider NDD as cured, but not fatal, diseases.

Detection of Alzheimer's disease at mild cognitive impairment and disease progression using autoantibodies as blood-based biomarkers

Introduction

There is an urgent need to identify biomarkers that can accurately detect and diagnose Alzheimer's disease (AD). Autoantibodies are abundant and ubiquitous in human sera and have been previously demonstrated as disease-specific biomarkers capable of accurately diagnosing mild-moderate stages of AD and Parkinson's disease.

Methods

Sera from 236 subjects, including 50 mild cognitive impairment (MCI) subjects with confirmed low CSF Aβ42 levels, were screened with human protein microarrays to identify potential biomarkers for MCI. Autoantibody biomarker performance was evaluated using Random Forest and Receiver Operating Characteristic curves.

Results

Autoantibody biomarkers can differentiate MCI patients from age-matched and gender-matched controls with an overall accuracy, sensitivity, and specificity of 100.0%. They were also capable of differentiating MCI patients from those with mild-moderate AD and other neurologic and non-neurologic controls with high accuracy.

Discussion

Autoantibodies can be used as noninvasive and effective blood-based biomarkers for early diagnosis and staging of AD.

Blood metabolite markers of neocortical amyloid-β burden: discovery and enrichment using candidate proteins

We believe this is the first study to investigate associations between blood metabolites and neocortical amyloid burden (NAB) in the search for a blood-based biomarker for Alzheimer's disease (AD). Further, we present the first multi-modal analysis of blood markers in this field. We used blood plasma samples from 91 subjects enrolled in the University of California, San Francisco Alzheimer's Disease Research Centre. Non-targeted metabolomic analysis was used to look for associations with NAB using both single and multiple metabolic feature models. Five metabolic features identified subjects with high NAB, with 72% accuracy. We were able to putatively identify four metabolites from this panel and improve the model further by adding fibrinogen gamma chain protein measures (accuracy=79%). One of the five metabolic features was studied in the Alzheimer's Disease Neuroimaging Initiative cohort, but results were inconclusive. If replicated in larger, independent studies, these metabolic features and proteins could form the basis of a blood test with potential for enrichment of amyloid pathology in anti-amyloid trials.

Longitudinal Protein Changes in Blood Plasma Associated with the Rate of Cognitive Decline in Alzheimer's Disease

Biomarkers of Alzheimer's disease (AD) progression are needed to support the development of urgently needed disease modifying drugs. We employed a SOMAscan assay for quantifying 1,001 proteins in blood samples from 90 AD subjects, 37 stable mild cognitive impaired (MCI) subjects, 39 MCI subjects converting to AD within a year and 69 controls at baseline and one year follow up. We used linear mixed effects models to identify proteins changing significantly over one year with the rate of cognitive decline, which was quantified as the reduction in Mini Mental State Examination (MMSE) scores. Additionally, we investigated proteins changing differently across disease groups and during the conversion from MCI to AD. We found that levels of proteins belonging to the complement cascade increase significantly in fast declining AD patients. Longitudinal changes in the complement cascade might be a surrogate biomarker for disease progression. We also found that members of the cytokine-cytokine receptor interaction pathway change during AD when compared to healthy aging subjects.

Blood Protein Markers of Neocortical Amyloid-β Burden: A Candidate Study Using SOMAscan Technology

BACKGROUND

Four previously reported studies have tested for association of blood proteins with neocortical amyloid-β burden (NAB). If shown to be robust, these proteins could have utility as a blood test for enrichment in clinical trials of Alzheimer's disease (AD) therapeutics.

OBJECTIVE

This study aimed to investigate whether previously identified blood proteins also show evidence for association with NAB in serum samples from the Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing (AIBL). The study considers candidate proteins seen in cohorts other than AIBL and candidates previously discovered in the AIBL cohort.

METHODS

Our study used the SOMAscan platform for protein quantification in blood serum. Linear and logistic regressions were used to model continuous NAB and dichotomized NAB respectively using single proteins as a predictor. Multiple protein models were built using stepwise regression techniques and support vectors machines. Age and APOEɛ4 carriage were used as covariates for all analysis.

RESULTS

Of the 41 proteins previously reported, 15 AIBL candidates and 20 non-AIBL candidates were available for testing. Of these candidates, pancreatic polypeptide (PPY) and IgM showed a significant association with NAB. Notably, IgM was found to associate with continuous NAB across cognitively normal control subjects.

CONCLUSIONS

We have further demonstrated the association of PPY and IgM with NAB, despite technical differences between studies. There are several reasons for a lack of significance for the other candidates including platform differences and the use of serum rather than plasma samples. To investigate the possibility of technical differences causing lack of replication, further studies are required.

CSF Biomarkers of Alzheimer’s Disease: Impact on Disease Concept, Diagnosis, and Clinical Trial Design

Data from clinicopathologic and biomarker studies have converged to support the view of Alzheimer’s disease (AD) as a continuum, with pathology developing decades prior to the onset of cognitive symptoms which culminate as dementia at the end stage of the disease. This concept is impacting disease nomenclature, diagnostic criteria, prognostic potential, and clinical trial design. Revisions to diagnostic criteria to incorporate biomarker results have recently been proposed in order to increase the confidence of AD as the underlying etiology of a clinical impairment and to permit a diagnosis of AD across the disease continuum, eventually perhaps in the asymptomatic period. Individuals in this preclinical stage are receiving intense focus as a targeted population for secondary prevention trials aimed at identifying disease-modifying therapies that have the best chance of preserving normal cognitive function. The goal is to bring validated biomarkers to clinical practice for the purpose of disease diagnosis, prognosis, and evaluation of therapeutic efficacy once disease-modifying treatments become available. Realization of this goal requires worldwide biomarker standardization efforts, consensus among researchers and clinicians regarding the clinical utility of assessing biomarkers in patient care settings, and eventually the endorsement and adoption of such procedures and practices into global health care systems.

Circulating biomarkers that predict incident dementia

Dementia is currently diagnosed based on clinical symptoms and signs, but significant brain damage has already occurred by the time a clinical diagnosis of dementia is made, and it is increasingly recognized that this may be too late for any effective intervention. It would therefore be of great public health and preventive value to define a variety of biomarkers that could permit early detection of persons at a higher risk for developing dementia, and specifically dementia due to Alzheimer's disease. Nevertheless, for the purpose of large-scale screening, circulating biomarkers are more appropriate because they are less invasive than lumbar puncture, less costly than brain amyloid imaging and can be easily assessed repeatedly in a primary care clinic setting. In this brief review we will review a number of candidate molecules implicated as possible predictors of dementia risk. These candidates include markers of vascular injury, metabolic and inflammatory states, amyloid and tau pathway markers, measures of neural degeneration and repair efforts, and other molecules that might contribute to anatomical and functional changes characteristic of dementia and Alzheimer's disease.

A curated review of recent literature of biomarkers used for assessing air pollution exposures and effects in humans

This is a cross-sectional review of biomarkers used in air pollution research from January 2009 through December 2012. After an initial keyword search in PubMed retrieving 426 articles, a comprehensive abstract review identified 54 articles of experimental design that used biomarkers of exposure or effect in human studies in the area of air pollution research during this specified time period. A thorough bibliographic search of the included articles retrieved an additional 65 articles meeting the inclusion criteria. This review presents these 119 studies and the 234 biomarkers employed in these air pollution research investigations. Data presented are 70 biomarkers of exposure with 54% relating to polycyclic aromatic hydrocarbons, 36% volatile organic carbons, and 10% classified as other. Of the 164 biomarkers of effect, 91 and 130 were used in investigating effects of short-term and chronic exposure, respectively. Results of biomarkers used in short-term exposure describe different lag times and pollutant components such as primary and secondary pollutants, and particle number associated with corresponding physiological mechanisms including airway inflammation, neuroinflammation, ocular, metabolic, early endothelial dysfunction, coagulation, atherosclerosis, autonomic nervous system, oxidative stress, and DNA damage. The review presents three different exposure scenarios of chronic, occupational, and extreme exposure scenarios (indoor cooking) with associated biomarker findings presented in three broad categories of (1) immune profile, (2) oxidative stress, and (3) DNA damage. This review offers a representation of the scope of data being explored by air pollution researchers through the use of biomarkers and has deliberately been restricted to this particular subject rather than an extensive or in-depth review. This article provides a contextualization of air pollution studies conducted with biomarkers in human subjects in given areas while also integrating this complex body of information to offer a useful review for investigators in this field of study.

Mass spectrometry strategies for clinical metabolomics and lipidomics in psychiatry, neurology, and neuro-oncology

Metabolomics research has the potential to provide biomarkers for the detection of disease, for subtyping complex disease populations, for monitoring disease progression and therapy, and for defining new molecular targets for therapeutic intervention. These potentials are far from being realized because of a number of technical, conceptual, financial, and bioinformatics issues. Mass spectrometry provides analytical platforms that address the technical barriers to success in metabolomics research; however, the limited commercial availability of analytical and stable isotope standards has created a bottleneck for the absolute quantitation of a number of metabolites. Conceptual and financial factors contribute to the generation of statistically under-powered clinical studies, whereas bioinformatics issues result in the publication of a large number of unidentified metabolites. The path forward in this field involves targeted metabolomics analyses of large control and patient populations to define both the normal range of a defined metabolite and the potential heterogeneity (eg, bimodal) in complex patient populations. This approach requires that metabolomics research groups, in addition to developing a number of analytical platforms, build sufficient chemistry resources to supply the analytical standards required for absolute metabolite quantitation. Examples of metabolomics evaluations of sulfur amino-acid metabolism in psychiatry, neurology, and neuro-oncology and of lipidomics in neurology will be reviewed.

Biomarkers in amyloid-β immunotherapy trials in Alzheimer's disease

Drug candidates directed against amyloid-β (Aβ) are mainstream in Alzheimer's disease (AD) drug development. Active and passive Aβ immunotherapy is the principle that has come furthest, both in number and in stage of clinical trials. However, an increasing number of reports on major difficulties in identifying any clinical benefit in phase II-III clinical trials on this type of anti-Aβ drug candidates have caused concern among researchers, pharmaceutical companies, and other stakeholders. This has provided critics of the amyloid cascade hypothesis with fire for their arguments that Aβ deposition may merely be a bystander, and not the cause, of the disease or that the amyloid hypothesis may only be valid for the familial form of AD. On the other hand, most researchers argue that it is the trial design that will need refinement to allow for identifying a positive clinical effect of anti-Aβ drugs. A consensus in the field is that future trials need to be performed in an earlier stage of the disease and that biomarkers are essential to guide and facilitate drug development. In this context, it is reassuring that, in contrast to most brain disorders, research advances in the AD field have led to both imaging (magnetic resonance imaging (MRI) and PET) and cerebrospinal fluid (CSF) biomarkers for the central pathogenic processes of the disease. AD biomarkers will have a central role in future clinical trials to enable early diagnosis, and Aβ biomarkers (CSF Aβ42 and amyloid PET) may be essential to allow for testing a drug on patients with evidence of brain Aβ pathology. Pharmacodynamic Aβ and amyloid precursor protein biomarkers will be of use to verify target engagement of a drug candidate in humans, thereby bridging the gap between mechanistic data from transgenic AD models (that may not be relevant to the neuropathology of human AD) and large and expensive phase III trials. Last, downstream biomarker evidence (CSF tau proteins and MRI volumetry) that the drug ameliorates neurodegeneration will, together with beneficial clinical effects on cognition and functioning, be essential for labeling an anti-Aβ drug as disease modifying.

Progress towards a consensus on biomarkers for Alzheimer’s disease: a review of peripheral analytes

Alzheimer’s disease (AD) is the most common cause of dementia in the elderly population and attempts to develop therapies have been unsuccessful because there is no means to target an effective therapeutic window. CNS biomarkers are insightful but impractical for high-throughput population-based screening. Therefore, a peripheral, blood-based biomarker for AD would significantly improve early diagnosis, potentially enable presymptomatic detection and facilitate effective targeting of disease-modifying treatments. The various constituents of blood, including plasma, platelets and cellular fractions, are now being systematically explored as a pool of putative peripheral biomarkers for AD. In this review we cover some less known peripheral biomarkers and highlight the latest developments for their clinical application.

Circulating miRNA biomarkers for Alzheimer's disease

A minimally invasive diagnostic assay for early detection of Alzheimer's disease (AD) is required to select optimal patient groups in clinical trials, monitor disease progression and response to treatment, and to better plan patient clinical care. Blood is an attractive source for biomarkers due to minimal discomfort to the patient, encouraging greater compliance in clinical trials and frequent testing. MiRNAs belong to the class of non-coding regulatory RNA molecules of ∼22 nt length and are now recognized to regulate ∼60% of all known genes through post-transcriptional gene silencing (RNAi). They have potential as useful biomarkers for clinical use because of their stability and ease of detection in many tissues, especially blood. Circulating profiles of miRNAs have been shown to discriminate different tumor types, indicate staging and progression of the disease and to be useful as prognostic markers. Recently their role in neurodegenerative diseases, both as diagnostic biomarkers as well as explaining basic disease etiology has come into focus. Here we report the discovery and validation of a unique circulating 7-miRNA signature (hsa-let-7d-5p, hsa-let-7g-5p, hsa-miR-15b-5p, hsa-miR-142-3p, hsa-miR-191-5p, hsa-miR-301a-3p and hsa-miR-545-3p) in plasma, which could distinguish AD patients from normal controls (NC) with >95% accuracy (AUC of 0.953). There was a >2 fold difference for all signature miRNAs between the AD and NC samples, with p-values<0.05. Pathway analysis, taking into account enriched target mRNAs for these signature miRNAs was also carried out, suggesting that the disturbance of multiple enzymatic pathways including lipid metabolism could play a role in AD etiology.

Personalized medicine in Alzheimer's disease and depression

Latest research in the mental health field brings new hope to patients and promises to revolutionize the field of psychiatry. Personalized pharmacogenetic tests that aid in diagnosis and treatment choice are now becoming available for clinical practice. Amyloid beta peptide biomarkers in the cerebrospinal fluid of patients with Alzheimer's disease are now available. For the first time, radiologists are able to visualize amyloid plaques specific to Alzheimer's disease in live patients using Positron Emission Tomography-based tests approved by the FDA. A novel blood-based assay has been developed to aid in the diagnosis of depression based on activation of the HPA axis, metabolic, inflammatory and neurochemical pathways. Serotonin reuptake inhibitors have shown increased remission rates in specific ethnic subgroups and Cytochrome P450 gene polymorphisms can predict antidepressant tolerability. The latest research will help to eradicate "trial and error" prescription, ushering in the most personalized medicine to date. Like all major medical breakthroughs, integration of new algorithms and technologies requires sound science and time. But for many mentally ill patients, diagnosis and effective therapy cannot happen fast enough. This review will describe the newest diagnostic tests, treatments and clinical studies for the diagnosis and treatment of Alzheimer's disease and unipolar, major depressive disorder.