Developing predictive CSF biomarkers-a challenge critical to success in Alzheimer's disease and neuropsychiatric translational medicine

Identification of key lipid metabolism-related genes in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) represents profound degenerative conditions of the brain that cause significant deterioration in memory and cognitive function. Despite extensive research on the significant contribution of lipid metabolism to AD progression, the precise mechanisms remain incompletely understood. Hence, this study aimed to identify key differentially expressed lipid metabolism-related genes (DELMRGs) in AD progression.

METHODS

Comprehensive analyses were performed to determine key DELMRGs in AD compared to controls in GSE122063 dataset from Gene Expression Omnibus. Additionally, the ssGSEA algorithm was utilized for estimating immune cell levels. Subsequently, correlations between key DELMRGs and each immune cell were calculated specifically in AD samples. The key DELMRGs expression levels were validated via two external datasets. Furthermore, gene set enrichment analysis (GSEA) was utilized for deriving associated pathways of key DELMRGs. Additionally, miRNA-TF regulatory networks of the key DELMRGs were constructed using the miRDB, NetworkAnalyst 3.0, and Cytoscape software. Finally, based on key DELMRGs, AD samples were further segmented into two subclusters via consensus clustering, and immune cell patterns and pathway differences between the two subclusters were examined.

RESULTS

Seventy up-regulated and 100 down-regulated DELMRGs were identified. Subsequently, three key DELMRGs (DLD, PLPP2, and PLAAT4) were determined utilizing three algorithms [(i) LASSO, (ii) SVM-RFE, and (iii) random forest]. Specifically, PLPP2 and PLAAT4 were up-regulated, while DLD exhibited downregulation in AD cerebral cortex tissue. This was validated in two separate external datasets (GSE132903 and GSE33000). The AD group exhibited significantly altered immune cell composition compared to controls. In addition, GSEA identified various pathways commonly associated with three key DELMRGs. Moreover, the regulatory network of miRNA-TF for key DELMRGs was established. Finally, significant differences in immune cell levels and several pathways were identified between the two subclusters.

CONCLUSION

This study identified DLD, PLPP2, and PLAAT4 as key DELMRGs in AD progression, providing novel insights for AD prevention/treatment.

Integrative metabolomics-genomics approach reveals key metabolic pathways and regulators of Alzheimer's disease

Metabolites, the biochemical products of the cellular process, can be used to measure alterations in biochemical pathways related to the pathogenesis of Alzheimer's disease (AD). However, the relationships between systemic abnormalities in metabolism and the pathogenesis of AD are poorly understood. In this study, we aim to identify AD-specific metabolomic changes and their potential upstream genetic and transcriptional regulators through an integrative systems biology framework for analyzing genetic, transcriptomic, metabolomic, and proteomic data in AD. Metabolite co-expression network analysis of the blood metabolomic data in the Alzheimer's Disease Neuroimaging Initiative (ADNI) shows short-chain acylcarnitines/amino acids and medium/long-chain acylcarnitines are most associated with AD clinical outcomes, including episodic memory scores and disease severity. Integration of the gene expression data in both the blood from the ADNI and the brain from the Accelerating Medicines Partnership Alzheimer's Disease (AMP-AD) program reveals ABCA1 and CPT1A are involved in the regulation of acylcarnitines and amino acids in AD. Gene co-expression network analysis of the AMP-AD brain RNA-seq data suggests the CPT1A- and ABCA1-centered subnetworks are associated with neuronal system and immune response, respectively. Increased ABCA1 gene expression and adiponectin protein, a regulator of ABCA1, correspond to decreased short-chain acylcarnitines and amines in AD in the ADNI. In summary, our integrated analysis of large-scale multiomics data in AD systematically identifies novel metabolites and their potential regulators in AD and the findings pave a way for not only developing sensitive and specific diagnostic biomarkers for AD but also identifying novel molecular mechanisms of AD pathogenesis.

Alpha7 nicotinic-N-methyl-D-aspartate hypothesis in the treatment of schizophrenia and beyond

Development of novel treatments for positive, cognitive, and negative symptoms continue to be a high-priority area of schizophrenia research and a major unmet clinical need. Given that all randomized controlled trials (RCTs) conducted to date failed with one add-on medication/mechanism of action, future RCTs with the same approach are not warranted. Even if the field develops a medication for cognition, others are still needed to treat negative and positive symptoms. Therefore, fixing one domain does not completely solve the problem. Also, targeting the cholinergic system, glutamatergic system, and cholinergic plus alpha7 nicotinic and N-methyl-D-aspartate (NMDA) receptors failed independently. Hence, targeting other less important pathophysiological mechanisms/targets is unlikely to be successful. Meta-analyses of RCTs targeting major pathophysiological mechanisms have found some efficacy signal in schizophrenia; thus, combination treatments with different mechanisms of action may enhance the efficacy signal. The objective of this article is to highlight the importance of conducting RCTs with novel combination treatments in schizophrenia to develop antischizophrenia treatments. Positive RCTs with novel combination treatments that target the alpha7 nicotinic and NMDA receptors simultaneously may lead to a disease-modifying therapeutic armamentarium in schizophrenia. Novel combination treatments that concurrently improve the three domains of psychopathology and several prognostic and theranostic biomarkers may facilitate therapeutic discovery in schizophrenia.

Galantamine-Memantine combination in the treatment of Alzheimer's disease and beyond

Alzheimer's disease (AD) is the most prevalent form of dementia in the elderly population worldwide. Despite the major unmet clinical need, no new medications for the treatment of AD have been approved since 2003. Galantamine is an acetylcholinesterase inhibitor that is also a positive allosteric modulator at the α4β2 and α7nACh receptors. Memantine is an N-methyl-d-aspartate receptor modulator/agonist. Both galantamine and memantine are FDA-approved medications for the treatment of AD. The objective of this review is to highlight the potential of the galantamine-memantine combination to conduct randomized controlled trials (RCTs) in AD. Several studies have shown the combination to be effective. Neurodegenerative diseases involve multiple pathologies; therefore, combination treatment appears to be a rational approach. Although underutilized, the galantamine-memantine combination is the standard of care in the treatment of AD. Positive RCTs with the combination with concurrent improvement in symptoms and biomarkers may lead to FDA approval, which may lead to greater utilization of this combination in clinical practice.

Dielectric Constant and Conductivity of Blood Plasma: Possible Novel Biomarkers for Alzheimer's Disease

Alzheimer's disease is a complex debilitating neurodegenerative disease for which there is no cure. The lack of reliable biomarkers for Alzheimer's disease has made the evaluation of the efficacy of new treatments difficult and reliant on only clinical symptoms. In an aged population where cognitive function may be deteriorating for other reasons, the dependence on clinical symptoms is also unreliable. However, it is well established that infusion of β-amyloid into the dorsal hippocampus of rats leads to cognitive impairment in a rat model of Alzheimer's disease. Moreover, the blood plasma of β-amyloid-lesioned rats exhibits a distinct variation of the dielectric constant and conductivity when compared to that of normal rats in a time-dependent manner. These two electric parameters of blood plasma may therefore act as potential biomarkers for dementia due to Alzheimer's disease. This review is aimed at highlighting evidences that support blood plasma electrical properties, e.g., dielectric constant and conductivity as possible novel biomarkers for the early development and progression of dementia due to Alzheimer's disease.

Metal based donepezil analogues designed to inhibit human acetylcholinesterase for Alzheimer's disease

Among neurodegenerative disorders, Alzheimer's disease (AD) is one of the most common disorders showing slow progressive cognitive decline. Targeting acetylcholinesterase (AChE) is one of the major strategies for AD therapeutics, as cholinergic pathways in the cerebral cortex and basal forebrain are compromised. Herein, we report the design of some copper and other metal based donepezil derivatives, employing density functional theory (DFT). All designed compounds are optimized at the B3LYP/SDD level of theory. Dipole moments, electronic energie, enthalpies, Gibbs free energies, and HOMO-LUMO gaps of these modified compounds are also investigated in the subsequent analysis. The molecules were then subjected to molecular docking analysis with AChE to study the molecular interactions broadly. Ensemble based docking and molecular dynamics (MD) simulations of the best candidates were also performed. Docking and MD simulation reveal that modified drugs are more potent than unmodified donepezil, where Trp86, Tyr337, Phe330 residues play some important roles in drug-receptor interactions. According to ensemble based docking, D9 shows greater binding affinity compared to the parent in most conformations obtained from protein data bank and MD simulation. In addition, it is observed that the π- π stacking with the residues of Trp86, Tyr337, Tyr341, Tyr124 and Trp286 may be required for strong ligand binding. Moreover, ADME/T analysis suggests that modified derivatives are less toxic and have improved pharmacokinetic properties than those of the parent drug. These results further confirm the ability of metal-directed drugs to bind simultaneously to the active sites of AChE and support them as potential candidates for the future treatment of Alzheimer's disease.

Alzheimer's disease (AD) therapeutics - 2: Beyond amyloid - Re-defining AD and its causality to discover effective therapeutics

Compounds targeted for the treatment of Alzheimer's Disease (AD) have consistently failed in clinical trials despite evidence for target engagement and pharmacodynamic activity. This questions the relevance of compounds acting at current AD drug targets - the majority of which reflect the seminal amyloid and, to a far lesser extent, tau hypotheses - and limitations in understanding AD causality as distinct from general dementia. The preeminence of amyloid and tau led to many alternative approaches to AD therapeutics being ignored or underfunded to the extent that their causal versus contributory role in AD remains unknown. These include: neuronal network dysfunction; cerebrovascular disease; chronic, local or systemic inflammation involving the innate immune system; infectious agents including herpes virus and prion proteins; neurotoxic protein accumulation associated with sleep deprivation, circadian rhythm and glymphatic/meningeal lymphatic system and blood-brain-barrier dysfunction; metabolic related diseases including diabetes, obesity hypertension and hypocholesterolemia; mitochondrial dysfunction and environmental factors. As AD has become increasingly recognized as a multifactorial syndrome, a single treatment paradigm is unlikely to work in all patients. However, the biomarkers required to diagnose patients and parse them into mechanism/disease-based sub-groups remain rudimentary and unvalidated as do non-amyloid, non-tau translational animal models. The social and economic impact of AD is also discussed in the context of new FDA regulatory draft guidance and a proposed biomarker-based Framework (re)-defining AD and its stages as part of the larger landscape of treating dementia via the 2013 G8 initiative to identify a disease-modifying therapy for dementia/AD by 2025.

Application of Multiplex Biomarker Approaches to Accelerate Drug Discovery and Development

Multiplex biomarker tests are becoming an essential part of the drug development process. This chapter explores the role of biomarker-based tests as effective tools in improving preclinical research and clinical development, and the challenges that this presents. The potential of incorporating biomarkers in the clinical pipeline to improve decision making, accelerate drug development, improve translation, and reduce development costs is discussed. This chapter also discusses the latest biomarker technologies in use to make this possible and details the next steps that must undertaken to keep driving this process forwards.

A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data

BACKGROUND

Stratification of patient subpopulations that respond favorably to treatment or experience and adverse reaction is an essential step toward development of new personalized therapies and diagnostics. It is currently feasible to generate omic-scale biological measurements for all patients in a study, providing an opportunity for machine learning models to identify molecular markers for disease diagnosis and progression. However, the high variability of genetic background in human populations hampers the reproducibility of omic-scale markers. In this paper, we develop a biological network-based regularized artificial neural network model for prediction of phenotype from transcriptomic measurements in clinical trials. To improve model sparsity and the overall reproducibility of the model, we incorporate regularization for simultaneous shrinkage of gene sets based on active upstream regulatory mechanisms into the model.

RESULTS

We benchmark our method against various regression, support vector machines and artificial neural network models and demonstrate the ability of our method in predicting the clinical outcomes using clinical trial data on acute rejection in kidney transplantation and response to Infliximab in ulcerative colitis. We show that integration of prior biological knowledge into the classification as developed in this paper, significantly improves the robustness and generalizability of predictions to independent datasets. We provide a Java code of our algorithm along with a parsed version of the STRING DB database.

CONCLUSION

In summary, we present a method for prediction of clinical phenotypes using baseline genome-wide expression data that makes use of prior biological knowledge on gene-regulatory interactions in order to increase robustness and reproducibility of omic-scale markers. The integrated group-wise regularization methods increases the interpretability of biological signatures and gives stable performance estimates across independent test sets.

Association of Amyloid Pathology With Myelin Alteration in Preclinical Alzheimer Disease

Importance

The accumulation of aggregated β-amyloid and tau proteins into plaques and tangles is a central feature of Alzheimer disease (AD). While plaque and tangle accumulation likely contributes to neuron and synapse loss, disease-related changes to oligodendrocytes and myelin are also suspected of playing a role in development of AD dementia. Still, to our knowledge, little is known about AD-related myelin changes, and even when present, they are often regarded as secondary to concomitant arteriosclerosis or related to aging.

Objective

To assess associations between hallmark AD pathology and novel quantitative neuroimaging markers while being sensitive to white matter myelin content.

Design, Setting, and Participants

Magnetic resonance imaging was performed at an academic research neuroimaging center on a cohort of 71 cognitively asymptomatic adults enriched for AD risk. Lumbar punctures were performed and assayed for cerebrospinal fluid (CSF) biomarkers of AD pathology, including β-amyloid 42, total tau protein, phosphorylated tau 181, and soluble amyloid precursor protein. We measured whole-brain longitudinal and transverse relaxation rates as well as the myelin water fraction from each of these individuals.

Main Outcomes and Measures

Automated brain mapping algorithms and statistical models were used to evaluate the relationships between age, CSF biomarkers of AD pathology, and quantitative magnetic resonance imaging relaxometry measures, including the longitudinal and transverse relaxation rates and the myelin water fraction.

Results

The mean (SD) age for the 19 male participants and 52 female participants in the study was 61.6 (6.4) years. Widespread age-related changes to myelin were observed across the brain, particularly in late myelinating brain regions such as frontal white matter and the genu of the corpus callosum. Quantitative relaxometry measures were negatively associated with levels of CSF biomarkers across brain white matter and in areas preferentially affected in AD. Furthermore, significant age-by-biomarker interactions were observed between myelin water fraction and phosphorylated tau 181/β-amyloid 42, suggesting that phosphorylated tau 181/β-amyloid 42 levels modulate age-related changes in myelin water fraction.

Conclusions and Relevance

These findings suggest amyloid pathologies significantly influence white matter and that these abnormalities may signify an early feature of the disease process. We expect that clarifying the nature of myelin damage in preclinical AD may be informative on the disease's course and lead to new markers of efficacy for prevention and treatment trials.

Attitudes to Alzheimer's disease testing of Australian general practice patients: a cross-sectional questionnaire-based study

OBJECTIVE

In view of proposed screening for presymptomatic Alzheimer's disease (AD) with advanced imaging, and blood and cerebral spinal fluid analysis, we aimed to establish levels, and associations, of acceptance of AD testing modalities by general practice patients.

METHODS

A cross-sectional questionnaire-based study of consecutive patients (aged 50 years and over) of general practices of an Australian practice-based research network was used. The questionnaire elicited demographic data and attitudes to screening for other diseases and included the screening acceptance domain of the Perceptions Regarding Investigational Screening for Memory in Primary Care (PRISM-PC) instrument. This assesses receptivity to modalities of testing for AD: short questionnaire, blood test, cerebral imaging, and annual physician examination. Reflecting speculation of possible future AD diagnostic methods, an item regarding testing cerebral spinal fluid was also included. Associations of PRISM-PC scores were analyzed with multiple linear regression.

RESULTS

Of 489 participants (response rate 87%), 66.2% would like to know if they had AD. Participants were more accepting of testing modalities that were noninvasive or familiar (questionnaire, physician's examination, and blood test) as opposed to cerebral imaging or lumbar puncture. Attitudes to AD testing are influenced by a positive attitude to disease screening in general. Patients with a self-perceived higher risk of AD were less accepting of testing, as were participants with an educational level of junior high school (10 school years) or less.

CONCLUSIONS

This study demonstrates that a majority of patients would like to know if they have AD. Acceptability of testing modalities, however, varies. Noninvasive, familiar methods are more acceptable.

Update on the core and developing cerebrospinal fluid biomarkers for Alzheimer disease

Alzheimer disease (AD) is a complex neurodegenerative disorder, whose prevalence will dramatically rise by 2050. Despite numerous clinical trials investigating this disease, there is still no effective treatment. Many trials showed negative or inconclusive results, possibly because they recruited only patients with severe disease, who had not undergone disease-modifying therapies in preclinical stages of AD before severe degeneration occurred. Detection of AD in asymptomatic at risk individuals (and a few presymptomatic individuals who carry an autosomal dominant monogenic AD mutation) remains impractical in many of clinical situations and is possible only with reliable biomarkers. In addition to early diagnosis of AD, biomarkers should serve for monitoring disease progression and response to therapy. To date, the most promising biomarkers are cerebrospinal fluid (CSF) and neuroimaging biomarkers. Core CSF biomarkers (amyloid β_1-42, total tau, and phosphorylated tau) showed a high diagnostic accuracy but were still unreliable for preclinical detection of AD. Hence, there is an urgent need for detection and validation of novel CSF biomarkers that would enable early diagnosis of AD in asymptomatic individuals. This article reviews recent research advances on biomarkers for AD, focusing mainly on the CSF biomarkers. In addition to core CSF biomarkers, the potential usefulness of novel CSF biomarkers is discussed.

The end of Alzheimer's disease--from biochemical pharmacology to ecopsychosociology: a personal perspective

The future of the Alzheimer's disease (AD) field involves a more complete understanding not only the state of current scientific approaches, but also the linguistic and cultural context of preclinical and clinical research and policy activities. The challenges surrounding dementia are large and growing but are only part of broader social and health concerns. In this latter context, the current state of research in the AD area is reviewed together with necessary priorities in moving forward. Creating a more optimistic future will depend less on genetic and reductionist approaches and more on environmental and intergenerative approaches that will aid in recalibrating the study of AD from an almost exclusive focus on biochemical, molecular and genetic aspects to better encompass "real world" ecological and psychosocial models of health.

Replicated, replicable and relevant-target engagement and pharmacological experimentation in the 21st century

A pharmacological experiment is typically conducted to: i) test or expand a hypothesis regarding the potential role of a target in the mechanism(s) underlying a disease state using an existing drug or tool compound in normal and/or diseased tissue or animals; or ii) characterize and optimize a new chemical entity (NCE) targeted to modulate a specific disease-associated target to restore homeostasis as a potential drug candidate. Hypothesis testing necessitates an intellectually rigorous, null hypothesis approach that is distinct from a high throughput fishing expedition in search of a hypothesis. In conducting an experiment, the protocol should be transparently defined along with its powering, design, appropriate statistical analysis and consideration of the anticipated outcome (s) before it is initiated. Compound-target interactions often involve the direct study of phenotype(s) unique to the target at the cell, tissue or animal/human level. However, in vivo studies are often compromised by a lack of sufficient information on the compound pharmacokinetics necessary to ensure target engagement and also by the context-free analysis of ubiquitous cellular signaling pathways downstream from the target. The use of single tool compounds/drugs at one concentration in engineered cell lines frequently results in reductionistic data that have no physiologically relevance. This overview, focused on trends in the peer-reviewed literature, discusses the execution and reporting of experiments and the criteria recommended for the physiologically-relevant assessment of target engagement to identify viable new drug targets and facilitate the advancement of translational studies.

Translational paradigms in pharmacology and drug discovery

The translational sciences represent the core element in enabling and utilizing the output from the biomedical sciences and to improving drug discovery metrics by reducing the attrition rate as compounds move from preclinical research to clinical proof of concept. Key to understanding the basis of disease causality and to developing therapeutics is an ability to accurately diagnose the disease and to identify and develop safe and effective therapeutics for its treatment. The former requires validated biomarkers and the latter, qualified targets. Progress has been hampered by semantic issues, specifically those that define the end product, and by scientific issues that include data reliability, an overt reductionistic cultural focus and a lack of hierarchically integrated data gathering and systematic analysis. A necessary framework for these activities is represented by the discipline of pharmacology, efforts and training in which require recognition and revitalization.

Animal models of human disease: challenges in enabling translation

Animal models have historically played a critical role in the exploration and characterization of disease pathophysiology, target identification, and in the in vivo evaluation of novel therapeutic agents and treatments. In the wake of numerous clinical trial failures of new chemical entities (NCEs) with promising preclinical profiles, animal models in all therapeutic areas have been increasingly criticized for their limited ability to predict NCE efficacy, safety and toxicity in humans. The present review discusses some of the challenges associated with the evaluation and predictive validation of animal models, as well as methodological flaws in both preclinical and clinical study designs that may contribute to the current translational failure rate. The testing of disease hypotheses and NCEs in multiple disease models necessitates evaluation of pharmacokinetic/pharmacodynamic (PK/PD) relationships and the earlier development of validated disease-associated biomarkers to assess target engagement and NCE efficacy. Additionally, the transparent integration of efficacy and safety data derived from animal models into the hierarchical data sets generated preclinically is essential in order to derive a level of predictive utility consistent with the degree of validation and inherent limitations of current animal models. The predictive value of an animal model is thus only as useful as the context in which it is interpreted. Finally, rather than dismissing animal models as not very useful in the drug discovery process, additional resources, like those successfully used in the preclinical PK assessment used for the selection of lead NCEs, must be focused on improving existing and developing new animal models.

Biomarkers in Parkinson's disease (recent update)

Parkinson's disease (PD) is the second most common neurodegenerative disorder mostly affecting the aging population over sixty. Cardinal symptoms including, tremors, muscle rigidity, drooping posture, drooling, walking difficulty, and autonomic symptoms appear when a significant number of nigrostriatal dopaminergic neurons are already destroyed. Hence we need early, sensitive, specific, and economical peripheral and/or central biomarker(s) for the differential diagnosis, prognosis, and treatment of PD. These can be classified as clinical, biochemical, genetic, proteomic, and neuroimaging biomarkers. Novel discoveries of genetic as well as nongenetic biomarkers may be utilized for the personalized treatment of PD during preclinical (premotor) and clinical (motor) stages. Premotor biomarkers including hyper-echogenicity of substantia nigra, olfactory and autonomic dysfunction, depression, hyposmia, deafness, REM sleep disorder, and impulsive behavior may be noticed during preclinical stage. Neuroimaging biomarkers (PET, SPECT, MRI), and neuropsychological deficits can facilitate differential diagnosis. Single-cell profiling of dopaminergic neurons has identified pyridoxal kinase and lysosomal ATPase as biomarker genes for PD prognosis. Promising biomarkers include: fluid biomarkers, neuromelanin antibodies, pathological forms of α-Syn, DJ-1, amyloid β and tau in the CSF, patterns of gene expression, metabolomics, urate, as well as protein profiling in the blood and CSF samples. Reduced brain regional N-acetyl-aspartate is a biomarker for the in vivo assessment of neuronal loss using magnetic resonance spectroscopy and T2 relaxation time with MRI. To confirm PD diagnosis, the PET biomarkers include [(18)F]-DOPA for estimating dopaminergic neurotransmission, [(18)F]dG for mitochondrial bioenergetics, [(18)F]BMS for mitochondrial complex-1, [(11)C](R)-PK11195 for microglial activation, SPECT imaging with (123)Iflupane and βCIT for dopamine transporter, and urinary salsolinol and 8-hydroxy, 2-deoxyguanosine for neuronal loss. This brief review describes the merits and limitations of recently discovered biomarkers and proposes coenzyme Q10, mitochondrial ubiquinone-NADH oxidoreductase, melatonin, α-synculein index, Charnoly body, and metallothioneins as novel biomarkers to confirm PD diagnosis for early and effective treatment of PD.

Recent advances in quantitative neuroproteomics

The field of proteomics is undergoing rapid development in a number of different areas including improvements in mass spectrometric platforms, peptide identification algorithms and bioinformatics. In particular, new and/or improved approaches have established robust methods that not only allow for in-depth and accurate peptide and protein identification and modification, but also allow for sensitive measurement of relative or absolute quantitation. These methods are beginning to be applied to the area of neuroproteomics, but the central nervous system poses many specific challenges in terms of quantitative proteomics, given the large number of different neuronal cell types that are intermixed and that exhibit distinct patterns of gene and protein expression. This review highlights the recent advances that have been made in quantitative neuroproteomics, with a focus on work published over the last five years that applies emerging methods to normal brain function as well as to various neuropsychiatric disorders including schizophrenia and drug addiction as well as of neurodegenerative diseases including Parkinson's disease and Alzheimer's disease. While older methods such as two-dimensional polyacrylamide electrophoresis continued to be used, a variety of more in-depth MS-based approaches including both label (ICAT, iTRAQ, TMT, SILAC, SILAM), label-free (label-free, MRM, SWATH) and absolute quantification methods, are rapidly being applied to neurobiological investigations of normal and diseased brain tissue as well as of cerebrospinal fluid (CSF). While the biological implications of many of these studies remain to be clearly established, that there is a clear need for standardization of experimental design and data analysis, and that the analysis of protein changes in specific neuronal cell types in the central nervous system remains a serious challenge, it appears that the quality and depth of the more recent quantitative proteomics studies is beginning to shed light on a number of aspects of neuroscience that relates to normal brain function as well as of the changes in protein expression and regulation that occurs in neuropsychiatric and neurodegenerative disorders.

Testes sanguíneos de biomarcadores para diagnóstico e tratamento de desordens mentais: foco em esquizofrenia

A descoberta e a aplicação clínica de biomarcadores para desordens mentais são confrontadas com muitos desafios. Em geral, os atuais métodos de descoberta e validação de biomarcadores não produziram os resultados que foram inicialmente aguardados depois da finalização do Projeto Genoma Humano. Isso se deve principalmente à falta de processos padronizados conectando a descoberta de marcadores com tecnologias para a validação e a tradução para uma plataforma que ofereça precisão e fácil uso em clínica. Como consequência, a maior parte dos psiquiatras e praticantes em geral são relutantes em aceitar que testes de biomarcadores pode suplementar ou substituir os métodos de diagnóstico utilizados baseados em entrevista. Apesar disso, agências regulatórias concordam agora que melhoras nos correntes métodos são essenciais. Além disso, essas agências estipularam que biomarcadores são importantes para o desenvolvimento de futuras drogas e iniciaram esforços no sentido de modernizar métodos e técnicas para suportar esses esforços. Aqui revisamos os desafios encontrados por essa tentativa do ponto de vista de psiquiatras, praticantes em geral, agências reguladoras e cientistas de biomarcadores. Também descrevemos o desenvolvimento de um novo teste sanguíneo molecular para esquizofrenia como um primeiro passo a esse objetivo.

Association of the interleukin 1 beta gene and brain spontaneous activity in amnestic mild cognitive impairment

Purpose

The inflammatory response has been associated with the pathogenesis of Alzheimer’s disease (AD). The purpose of this study is to determine whether the rs1143627 polymorphism of the interleukin-1 beta (IL-1β) gene moderates functional magnetic resonance imaging (fMRI)-measured brain regional activity in amnestic mild cognitive impairment (aMCI).

Methods

Eighty older participants (47 with aMCI and 33 healthy controls) were recruited for this study. All of the participants were genotyped for variant rs1143627 in the IL1B gene and were scanned using resting-state fMRI. Brain activity was assessed by amplitude of low-frequency fluctuation (ALFF).

Results

aMCI patients had abnormal ALFF in many brain regions, including decreases in the inferior frontal gyrus, the superior temporal lobe and the middle temporal lobe, and increases in the occipital cortex (calcarine), parietal cortex (Pcu) and cerebellar cortex. The regions associated with an interaction of group X genotypes of rs1143627 C/T were the parietal cortex (left Pcu), frontal cortex (left superior, middle, and medial gyrus, right anterior cingulum), occipital cortex (left middle lobe, left cuneus) and the bilateral posterior lobes of the cerebellum. Regarding the behavioral significance, there were significant correlations between ALFF in different regions of the brain and with the cognitive scores of each genotype group.

Conclusions

The present study provided evidence that aMCI patients had abnormal ALFF in many brain regions. Specifically, the rs1143627 C/T polymorphism of the IL1B gene may modulate regional spontaneous brain activity in aMCI patients.

Alzheimer's therapeutics: continued clinical failures question the validity of the amyloid hypothesis-but what lies beyond?

The worldwide incidence of Alzheimer's disease (AD) is increasing with estimates that 115 million individuals will have AD by 2050, creating an unsustainable healthcare challenge due to a lack of effective treatment options highlighted by multiple clinical failures of agents designed to reduce the brain amyloid burden considered synonymous with the disease. The amyloid hypothesis that has been the overarching focus of AD research efforts for more than two decades has been questioned in terms of its causality but has not been unequivocally disproven despite multiple clinical failures, This is due to issues related to the quality of compounds advanced to late stage clinical trials and the lack of validated biomarkers that allow the recruitment of AD patients into trials before they are at a sufficiently advanced stage in the disease where therapeutic intervention is deemed futile. Pursuit of a linear, reductionistic amyloidocentric approach to AD research, which some have compared to a religious faith, has resulted in other, equally plausible but as yet unvalidated AD hypotheses being underfunded leading to a disastrous roadblock in the search for urgently needed AD therapeutics. Genetic evidence supporting amyloid causality in AD is reviewed in the context of the clinical failures, and progress in tau-based and alternative approaches to AD, where an evolving modus operandi in biomedical research fosters excessive optimism and a preoccupation with unproven, and often ephemeral, biomarker/genome-based approaches that override transparency, objectivity and data-driven decision making, resulting in low probability environments where data are subordinate to self propagating hypotheses.

Muscle-directed anti-Aβ single-chain antibody delivery via AAV1 reduces cerebral Aβ load in an Alzheimer's disease mouse model

We previously reported that anti-amyloid-beta (Aβ) single-chain antibody (scFv59) brain delivery via recombinant adeno-associated virus (rAAV) was effective in reducing cerebral Aβ load in an Alzheimer's disease (AD) mouse model without inducing inflammation. Here, we investigated the prophylactic effects and mechanism of a muscle-directed gene therapy modality in an AD mouse model. We injected rAAV serotype 1 encoding scFv59 into the right thigh muscles of 3-month-old mice. Nine months later, high levels of scFv59 expression were confirmed in the thigh muscles by both immunoblotting and immunohistochemistry. As controls, model mice were similarly injected with rAAV1 encoding antihuman immunodeficiency virus Gag antibody (scFvGag). AAV1-mediated scFv59 gene delivery was effective in decreasing Aβ deposits in the brain. Compared with the scFvGag group, levels of Aβ in cerebrospinal fluid (CSF) decreased significantly while Aβ in serum tended to increase in the scFv59 group. AAV1-mediated scFv59 gene delivery may alter the equilibrium of Aβ between the blood and brain, resulting in an increased efflux of Aβ from the brain owing to antibody-mediated sequestration/clearance of peripheral Aβ. Our results suggest that muscle-directed scFv59 delivery via rAAV1 may be a prophylactic option for AD and that levels of CSF Aβ may be used to evaluate the efficacy of anti-Aβ immunotherapy.

The future: biomarkers, biosensors, neuroinformatics, and e-neuropsychiatry

The emergence of molecular biomarkers for psychological, psychiatric, and neurodegenerative disorders is beginning to change current diagnostic paradigms for this debilitating family of mental illnesses. The development of new genomic, proteomic, and metabolomic tools has created the prospect of sensitive and specific biochemical tests to replace traditional pen-and-paper questionnaires. In the future, the realization of biosensor technologies, point-of-care testing, and the fusion of clinical biomarker data, electroencephalogram, and MRI data with the patient's past medical history, biopatterns, and prognosis may create personalized bioprofiles or fingerprints for brain disorders. Further, the application of mobile communications technology and grid computing to support data-, computation- and knowledge-based tasks will assist disease prediction, diagnosis, prognosis, and compliance monitoring. It is anticipated that, ultimately, mobile devices could become the next generation of personalized pharmacies.

Use of cerebrospinal fluid biomarkers in clinical trials for schizophrenia and depression

The pharmaceutical industry is increasingly using biomarkers in clinical trials in order to determine if new drug candidates are displaying the expected pharmacological properties and to give early indications if they are showing efficacy or unexpected toxicity. This is especially true for the development of new drug candidates for psychiatric disorders such as schizophrenia and depression, where it is imperative to understand whether the drug is reaching the brain and acting on the target. A particular challenge for biochemical biomarkers used to determine centrally mediated activity is the relative inaccessibility of the brain to direct sampling of cells or tissues. As a result, the use of biomarkers located in the cerebrospinal fluid and in close contact with the interstitial fluid of the brain has risen in prominence. Cerebrospinal fluid biomarkers allow for the analysis of biochemical changes that reflect pharmacological activity or that may be related to the disease. In the area of psychiatric disorders, many studies have utilized biochemical biomarkers in the cerebrospinal fluid for gaining pharmacodynamic or disease modification information. This review summarizes many of these efforts, and identifies challenges and opportunities for utilizing biomarkers for new drug candidates targeting psychiatric disorders.

Translational researches require effective protocols for knowledge and technology transfer and integration

Integration of several disciplines (nonclinical, preclinical and clinical researches) during drug discovery and development through learning and confirmation process needs a dynamic process; "translational medicine" (TM) to give a holistic understanding of the entire process. To achieve the highest impacts, however, effective standard protocols need to be performed.

Qualitative pharmacology in a quantitative world: diminishing value in the drug discovery process

Preclinical characterization of new chemical entities (NCEs) in terms of efficacy, safety and their pharmacokinetic (PK), pharmacodynamic and pharmaceutical properties, is key to advancing appropriate compounds to clinical trials. The use of high throughput synthetic and screening methodologies has frequently led to NCE characterization becoming highly reductionistic, to the extent that compounds are often selected without adequate characterization. Classical, null hypothesis-based approaches involving the use of concentration/dose response curves and antagonists have been replaced by more qualitative approaches that limit NCE characterization. The return to a more integrated, hierarchical and pharmacologically driven approach will aid in ensuring that the NCEs advanced to clinical status are better understood, strengthening the process and predictivity of the translational approach in drug discovery.

Challenges of introducing new biomarker products for neuropsychiatric disorders into the market

There are many challenges associated with the discovery and development of serum-based biomarkers for psychiatric disorders such as schizophrenia. Here, we review these challenges from the point of view of psychiatrists, general practitioners, the regulatory agencies, and biomarker scientists. There is a general opinion in psychiatric medicine that improvements over the current subjective tests are essential. Despite this, there is a reluctance to accept that peripheral molecules can do the job any better. In addition, psychiatrists find it difficult to accept that peripheral molecules, such as those found in blood, can reflect what is happening in the brain. However, the regulatory health authorities now consider biomarkers as important for the future of drug development and have called for efforts to modernize methods, tools, and techniques for the purpose of developing more efficient and safer drugs. We also describe here the development of the first ever molecular blood test for schizophrenia, and its reception in the market place, as a case in point.