Serum epidermal growth factor predicts cognitive functions in early, drug-naive Parkinson's disease patients

Association of postoperative delirium with serum and cerebrospinal fluid proteomic profiles: a prospective cohort study in older hip fracture patients

Postoperative delirium (POD) is a common neuropsychiatric complication in geriatric inpatients after hip fracture surgery and its occurrence is associated with poor outcomes. The purpose of this study was to investigate the relationship between preoperative biomarkers in serum and cerebrospinal fluid (CSF) and the development of POD in older hip fracture patients, exploring the possibility of integrating objective methods into future predictive models of delirium. Sixty hip fracture patients were recruited. Blood and CSF samples were collected at the time of spinal anesthesia when none of the subjects had delirium. Patients were assessed daily using the 4AT scale, and based on these results, they were divided into POD and non-POD groups. The Olink® platform was used to analyze 45 cytokines. Twenty-one patients (35%) developed POD. In the subsample of 30 patients on whom proteomic analyses were performed, a proteomic profile was associated with the incidence of POD. Chemokine (C-X-C motif) ligand 9 (CXCL9) had the strongest correlation between serum and CSF samples in patients with POD (rho = 0.663; p < 0.05). Although several cytokines in serum and CSF were associated with POD after hip fracture surgery in older adults, there was a significant association with lower preoperative levels of CXCL9 in CSF and serum. Despite the small sample size, this study provides preliminary evidence of the potential role of molecular biomarkers in POD, which may provide a basis for the development of new delirium predictive models.

Clinical biomarkers for Lewy body diseases

Synucleinopathies are a group of neurodegenerative disorders characterized by pathologic aggregates of neural and glial α-synuclein (α-syn) in the form of Lewy bodies (LBs), Lewy neurites, and cytoplasmic inclusions in both neurons and glia. Two major classes of synucleinopathies are LB disease and multiple system atrophy. LB diseases include Parkinson's disease (PD), PD with dementia, and dementia with LBs. All are increasing in prevalence. Effective diagnostics, disease-modifying therapies, and therapeutic monitoring are urgently needed. Diagnostics capable of differentiating LB diseases are based on signs and symptoms which might overlap. To date, no specific diagnostic test exists despite disease-specific pathologies. Diagnostics are aided by brain imaging and cerebrospinal fluid evaluations, but more accessible biomarkers remain in need. Mechanisms of α-syn evolution to pathologic oligomers and insoluble fibrils can provide one of a spectrum of biomarkers to link complex neural pathways to effective therapies. With these in mind, we review promising biomarkers linked to effective disease-modifying interventions.

Promising biomarkers and therapeutic targets for the management of Parkinson's disease: recent advancements and contemporary research

Parkinson's disease (PD) is one of the progressive neurological diseases which affect around 10 million population worldwide. The clinical manifestation of motor symptoms in PD patients appears later when most dopaminergic neurons have degenerated. Thus, for better management of PD, the development of accurate biomarkers for the early prognosis of PD is imperative. The present work will discuss the potential biomarkers from various attributes covering biochemical, microRNA, and neuroimaging aspects (α-synuclein, DJ-1, UCH-L1, β-glucocerebrosidase, BDNF, etc.) for diagnosis, recent development in PD management, and major limitations with current and conventional anti-Parkinson therapy. This manuscript summarizes potential biomarkers and therapeutic targets, based on available preclinical and clinical evidence, for better management of PD.

Investigation of Paraoxonase-1 Genotype and Enzyme-Kinetic Parameters in the Context of Cognitive Impairment in Parkinson's Disease

Cognitive impairment is a common non-motor symptom of Parkinson's disease (PD), which often progresses to PD dementia. PD patients with and without dementia may differ in certain biochemical parameters, which could thus be used as biomarkers for PD dementia. The enzyme paraoxonase 1 (PON1) has previously been investigated as a potential biomarker in the context of other types of dementia. In a cohort of PD patients, we compared a group of 89 patients with cognitive impairment with a group of 118 patients with normal cognition. We determined the kinetic parameters K_m and V_max for PON1 for the reaction with dihydrocoumarin and the genotype of four single nucleotide polymorphisms in PON1. We found that no genotype or kinetic parameter correlated significantly with cognitive impairment in PD patients. However, we observed associations between PON1 rs662 and PON1 K_m (p < 10^-10), between PON1 rs662 and PON1 V_max (p = 9.33 × 10^-7), and between PON1 rs705379 and PON1 V_max (p = 2.21 × 10^-10). The present study is novel in three main aspects. (1) It is the first study to investigate associations between the PON1 genotype and enzyme kinetics in a large number of subjects. (2) It is the first study to report kinetic parameters of PON1 in a large number of subjects and to use time-concentration progress curves instead of initial velocities to determine K_m and V_max in a clinical context. (3) It is also the first study to calculate enzyme-kinetic parameters in a clinical context with a new algorithm for data point removal from progress curves, dubbed iFIT. Although our results suggest that in the context of PD, there is no clinically useful correlation between cognitive status on the one hand and PON1 genetic and enzyme-kinetic parameters on the other hand, this should not discourage future investigation into PON1's potential associations with other types of dementia.

Non-Motor Symptoms of Parkinson's Disease: The Neurobiology of Early Psychiatric and Cognitive Dysfunction

Parkinson's disease (PD) is a progressive neurodegenerative disorder that has been recognized for over 200 years by its clinically dominant motor system impairment. There are prominent non-motor symptoms as well, and among these, psychiatric symptoms of depression and anxiety and cognitive impairment are common and can appear earlier than motor symptoms. Although the neurobiology underlying these particular PD-associated non-motor symptoms is not completely understood, the identification of PARK genes that contribute to hereditary and sporadic PD has enabled genetic models in animals that, in turn, have fostered ever deepening analyses of cells, synapses, circuits, and behaviors relevant to non-motor psychiatric and cognitive symptoms of human PD. Moreover, while it has long been recognized that inflammation is a prominent component of PD, recent studies demonstrate that brain-immune signaling crosstalk has significant modulatory effects on brain cell and synaptic function in the context of psychiatric symptoms. This review provides a focused update on such progress in understanding the neurobiology of PD-related non-motor psychiatric and cognitive symptoms.

Plasma MIA, CRP, and Albumin Predict Cognitive Decline in Parkinson's Disease

OBJECTIVE

Using a multi-cohort, discovery-replication-validation design, we sought new plasma biomarkers that predict which individuals with Parkinson's disease (PD) will experience cognitive decline.

METHODS

In 108 discovery cohort PD individuals and 83 replication cohort PD individuals, we measured 940 plasma proteins on an aptamer-based platform. Using proteins associated with subsequent cognitive decline in both cohorts, we trained a logistic regression model to predict which patients with PD showed fast (> = 1 point drop/year on Montreal Cognitive Assessment [MoCA]) versus slow (< 1 point drop/year on MoCA) cognitive decline in the discovery cohort, testing it in the replication cohort. We developed alternate assays for the top 3 proteins and confirmed their ability to predict cognitive decline - defined by change in MoCA or development of incident mild cognitive impairment (MCI) or dementia - in a validation cohort of 118 individuals with PD. We investigated the top plasma biomarker for causal influence by Mendelian randomization (MR).

RESULTS

A model with only 3 proteins (melanoma inhibitory activity protein [MIA], C-reactive protein [CRP], and albumin) separated fast versus slow cognitive decline subgroups with an area under the curve (AUC) of 0.80 in the validation cohort. The individuals with PD in the validation cohort in the top quartile of risk for cognitive decline based on this model were 4.4 times more likely to develop incident MCI or dementia than those in the lowest quartile. Genotypes at MIA single nucleotide polymorphism (SNP) rs2233154 associated with MIA levels and cognitive decline, providing evidence for MIA's causal influence.

CONCLUSIONS

An easily obtained plasma-based predictor identifies individuals with PD at risk for cognitive decline. MIA may participate causally in development of cognitive decline. ANN NEUROL 2022.

Path analysis of biomarkers for cognitive decline in early Parkinson’s disease

Clinical and biochemical diversity of Parkinson’s disease (PD) and numerous demographic, clinical, and pathological measures influencing cognitive function and its decline in PD create problems with the determination of effects of individual measures on cognition in PD. This is particularly the case where these measures significantly interrelate with each other producing intricate networks of direct and indirect effects on cognition. Here, we use generalized structural equation modelling (GSEM) to identify and characterize significant paths for direct and indirect effects of 14 baseline measures on global cognition in PD at baseline and at 4 years later. We consider 269 drug-naïve participants from the Parkinson’s Progression Marker Initiative database, diagnosed with idiopathic PD and observed for at least 4 years after baseline. Two GSEM networks are derived, highlighting the possibility of at least two different molecular pathways or two different PD sub-types, with either CSF p-tau181 or amyloid beta (1–42) being the primary protein variables potentially driving progression of cognitive decline. The models provide insights into the interrelations between the 14 baseline variables, and determined their total effects on cognition in early PD. High CSF amyloid concentrations (> 500 pg/ml) are associated with nearly full protection against cognitive decline in early PD in the whole range of baseline age between 40 and 80 years, and irrespectively of whether p-tau181 or amyloid beta (1–42) are considered as the primary protein variables. The total effect of depression on cognition is shown to be strongly amplified by PD, but not at the time of diagnosis or at prodromal stages. CSF p-tau181 protein could not be a reliable indicator of cognitive decline because of its significantly heterogeneous effects on cognition. The outcomes will enable better understanding of the roles of the clinical and pathological measures and their mutual effects on cognition in early PD.

Proteins in the pathway from high red blood cell width distribution to all-cause mortality

Background

The pathophysiological mechanisms underlying the association between red blood cell distribution width (RDW) and all-cause mortality are unknown. We conducted a data-driven discovery investigation to identify plasma proteins that mediate the association between RDW and time to death in community-dwelling adults.

Methods

At baseline, 962 adults (women, 54·4%; age range, 21–98 years) participated in the InCHIANTI, “Aging in the Chianti Area” study, and proteomics data were generated from their plasma specimens. Of these, 623 participants had proteomics data available at the 9-year follow-up. For each visit, a total of 1301 plasma proteins were measured using SOMAscan technology. Complete data on vital status were available up to the 15-year follow-up period. Protein-specific exponential distribution accelerated failure time, and linear regression analyses adjusted for possible covariates were used for mortality and mediation analyses, respectively (survival data analysis).

Findings

Baseline values of EGFR, GHR, NTRK3, SOD2, KLRF1, THBS2, TIMP1, IGFBP2, C9, APOB, and LRP1B mediated the association between baseline RDW and all-cause mortality. Changes in IGFBP2 and C7 over 9 years mediated the association between changes in RDW and 6-year all-cause mortality.

Interpretation

Cellular senescence may contribute to the association between RDW and mortality.

Funding

This study was funded by grants from the National Institutes of Health (NIH) and the National Institute on Aging (NIA) contract and was supported by the Intramural Research Program of the NIA, NIH. The InCHIANTI study was supported as a ‘targeted project’ by the Italian Ministry of Health and in part by the U.S. NIA.

Experimental Models of Cognitive Impairment for Use in Parkinson's Disease Research: The Distance Between Reality and Ideal

Parkinson’s disease (PD) is the second most common neurodegenerative disease. Cognitive impairment is one of the key non-motor symptoms of PD, affecting both mortality and quality of life. However, there are few experimental studies on the pathology and treatments of PD with mild cognitive impairment (PD-MCI) and PD dementia (PDD) due to the lack of representative models. To identify new strategies for developing representative models, we systematically summarized previous studies on PD-MCI and PDD and compared differences between existing models and diseases. Our initial search identified 5432 articles, of which 738 were duplicates. A total of 227 articles met our inclusion criteria and were included in the analysis. Models fell into three categories based on model design: neurotoxin-induced, transgenic, and combined. Although the neurotoxin-induced experimental model was the most common type that was used during every time period, transgenic and combined experimental models have gained significant recent attention. Unfortunately, there remains a big gap between ideal and actual experimental models. While each model has its own disadvantages, there have been tremendous advances in the development of PD models of cognitive impairment, and almost every model can verify a hypothesis about PD-MCI or PDD. Finally, our proposed strategies for developing novel models are as follows: a set of plans that integrate symptoms, biochemistry, neuroimaging, and other objective indicators to judge and identify that the novel model plays a key role in new strategies for developing representative models; novel models should simulate different clinical features of PD-MCI or PDD; inducible α-Syn overexpression and SH-SY5Y-A53T cellular models are good candidate models of PD-MCI or PDD.

Serum epidermal growth factor, clinical illness course, and limbic brain volumes in early-stage bipolar disorder

BACKGROUND

Epidermal growth factor (EGF) belongs to a family of growth factors implicated in the etiology of psychiatric illnesses. We conducted this cross-sectional case-control study to determine whether (1) serum EGF levels differ between bipolar disorder (BD) patients and non-BD comparison subjects, (2) EGF levels in patients are influenced by mood illness related factors (number of past mood episodes, medication treatment) and non-mood illness related factors (body mass index), and (3) lower EGF levels predict lower limbic brain volumes in BD.

METHODS

We measured serum EGF in 51 early-stage BD patients and 22 healthy comparison subjects (HS). A subset of 25 patients underwent cerebral magnetic resonance imaging (MRI). Participants were assessed at the University of British Columbia Mood Disorders Centre between June 2004 and June 2012.

RESULTS

A general linear model with diagnosis and BMI category (overweight/obese vs normal weight) as factors showed that patients had lower mean log(e)-transformed EGF (LnEGF) than HS (4.99 vs 5.47, p = .011). There was no effect of BMI and no diagnosis x BMI interaction. Multiple linear regression models showed that in patients, more past mood episodes predicted lower LnEGF (β = -0.358, t = -2.585, p = .013) and lower LnEGF predicted lower bilateral temporal lobe volumes (left: β = 0.560, p = .011; right: β = 0.543, p = .009).

LIMITATIONS

Our cross-sectional study design limits our ability to make inferences about the causal directions of the relationships between EGF, diagnosis, mood episodes, and brain volumes.

CONCLUSIONS

These findings provide preliminary evidence that EGF is a novel biomarker that may play a role in the pathophysiology of BD.

Decreased Serum EGF in First-episode and Chronic Schizophrenia Patients: Negative Correlation with Psychopathology

Previous studies have demonstrated that neurotrophic factors may play a critical role in the severity of clinical symptoms in schizophrenia. However, it remains unknown whether serum levels of epidermal growth factor (EGF) in schizophrenia are similar to those observed in the case of other neurotrophic factors. Therefore, we compared serum EGF concentrations in first-episode drug-naive (FEP) patients and medicated chronic schizophrenic patients with healthy controls in order to explore whether EGF levels are related to psychopathological symptoms. We measured the serum levels of EGF in 78 first-episode medication-naive schizophrenia patients, 76 medicated chronic schizophrenic patients, and 75 healthy controls using the sandwich ELISA method. Disease severity were measured using the positive and negative syndrome scale (PANSS). Serum EGF levels showed a significant decrease in schizophrenia patients in comparison to healthy subjects. Serum EGF levels in FEP patients are indistinguishable from chronic cases. EGF levels were related to PANSS general symptom subscales in both FEP never-medicated and medicated patients. It is interesting that serum EGF levels were negatively correlated with the PANSS cognitive subscales, with the exception of the patients with chronic schizophrenia. Our preliminary results indicated that EGF may play a role in this illness and that it could be used as a potential biomarker of disease severity. Moreover, EGF may be associated with cognitive subscales of PANSS in FEP patients. Future studies should investigate the relationship between EGF and cognitive function as measured using standardized neuropsychological assessments to identify potential biomarkers related with cognition.

Serum Epidermal Growth Factor is Low in Schizophrenia and Not Affected by Antipsychotics Alone or Combined With Electroconvulsive Therapy

BACKGROUND

Epidermal growth factor (EGF) is implicated in the pathogenesis of schizophrenia, suggesting possible value as a biomarker for disease severity or treatment response. However, basal EGF levels and changes during treatment are inconsistent across studies. The goal of this study is to compare serum EGF in schizophrenia patients before and after treatment with antipsychotics alone or combined with electroconvulsive therapy (ECT).

METHOD

Patients meeting DSM-IV diagnostic criteria for schizophrenia were recruited from June 2013 to December 2015 (n = 186) and followed up after 8 weeks of treatment with antipsychotics alone (n = 119, drug group) or combined with ECT (n = 67, ECT group). Serum EGF levels were measured by ELISA and compared among patients and 74 healthy control subjects. Psychopathology and clinical effects were assessed using the Positive and Negative Syndrome Scale (PANSS).

RESULTS

Basal serum EGF was significantly lower in the entire patient cohort compared to healthy controls (P < 0.05). Repeated-measures ANOVA showed no main effect of time (F = 1.273; P = 0.261), time × group interaction (F = 1.228; P = 0.270), main effect of clinical response (F = 0.191; P = 0.663), or group × clinical interaction (F = 1.765; P = 0.186) on serum EGF. Serum EGF levels did not change significantly following antipsychotic drug or combined therapy (P > 0.05). Additionally, neither basal EGF nor EGF change was associated with the clinical response to drug or combined treatment (P > 0.05). However, baseline serum EGF was weakly associated with PANSS positive score (pretreatment: r = 0.206, posttreatment: r = 0.201) and general symptom score (pretreatment: r = -0.244). Serum EGF was also associated with duration of illness (pretreatment: r = 0.285, posttreatment: r = -0.231).

CONCLUSIONS

Serum EGF concentration is low in schizophrenia but is unchanged following treatment with antipsychotics alone or combined with ECT, regardless of clinical response. Thus, serum EGF is not a surrogate biomarker for treatment response and is unlikely to be involved in the therapeutic mechanisms of antipsychotics or ECT.

Biomarkers for Dementia, Fatigue, and Depression in Parkinson's Disease

Parkinson's disease is a common multisystem neurodegenerative disorder characterized by typical motor and non-motor symptoms. There is an urgent need for biomarkers for assessment of disease severity, complications and prognosis. In addition, biomarkers reporting the underlying pathophysiology assist in understanding the disease and developing neuroprotective therapies. Ultimately, biomarkers could be used to develop a more efficient personalized approach for clinical trials and treatment strategies. With the goal to improve quality of life in Parkinson's disease it is essential to understand and objectively monitor non-motor symptoms. This narrative review provides an overview of recent developments of biomarkers (biofluid samples and imaging) for three common neuropsychological syndromes in Parkinson's disease: dementia, fatigue, and depression.

Peripheral Biomarkers for Early Detection of Alzheimer's and Parkinson's Diseases

Neurological disorders are found to be influencing the peripheral tissues outside CNS. Recent developments in biomarkers for CNS have emerged with various diagnostic and therapeutic shortcomings. The role of central biomarkers including CSF-based and molecular imaging-based probes are still unclear for early diagnosis of major neurological diseases. Current trends show that early detection of neurodegenerative diseases with non-invasive methods is a major focus of researchers, and the development of biomarkers aiming peripheral tissues is in demand. Alzheimer's and Parkinson's diseases are known for the progressive loss in neural structures or functions, including the neural death. Various dysfunctions of metabolic and biochemical pathways are associated with early occurrence of neuro-disorders in peripheral tissues including skin, blood cells, and eyes. This article reviews the peripheral biomarkers explored for early detection of Alzheimer's and Parkinson's diseases including blood cells, skin fibroblast, proteomics, saliva, olfactory, stomach and colon, heart and peripheral nervous system, and others. Graphical Abstract.

Multifactorial Analysis of a Biomarker Pool for Alzheimer Disease Risk in a North Indian Population

BACKGROUND

Alzheimer disease (AD) is a progressive neurodegenerative disease with a complex multifactorial etiology. Here, we aim to identify a biomarker pool comprised of genetic variants and blood biomarkers as predictor of AD risk.

METHODS

We performed a case-control study involving 108 cases and 159 non-demented healthy controls to examine the association of multiple biomarkers with AD risk.

RESULTS

The APOE genotyping revealed that ε4 allele frequency was significantly high (p value = 0.0001, OR = 2.66, 95% CI 1.58-4.46) in AD as compared to controls, whereas ε2 (p = 0.0430, OR = 0.29, CI 0.07-1.10) was overrepresented in controls. In biochemical assays, significant differences in levels of total copper, free copper, zinc, copper/zinc ratio, iron, epidermal growth factor receptor (EGFR), leptin, and albumin were also observed. The AD risk score (ADRS) as a linear combination of 6 candidate markers involving age, education status, APOE ε4 allele, levels of iron, Cu/Zn ratio, and EGFR was created using stepwise linear discriminant analysis. The area under the ROC curve of the ADRS panel for predicting AD risk was significantly high (AUC = 0.84, p < 0.0001, 95% CI 0.78-0.89, sensitivity = 70.0%, specificity = 83.8%) compared to individual parameters.

CONCLUSION

These findings support the multifactorial etiology of AD and demonstrate the ability of a panel involving 6 biomarkers to discriminate AD cases from non-demented healthy controls.

Parkinson's Disease Biomarkers: Where Are We and Where Do We Go Next?

Background

Objective measures of Parkinson's disease (PD) are needed for purposes of diagnosis and prognostication, as well as identification of those at risk of PD. In this qualitative review, we provide an overview of the current state of the field of PD biomarker development, delineate challenges, and discuss how the field is evolving.

Methods

A search of PubMed was conducted for articles pertaining to objective biomarkers for PD. Articles were selected based on relevance and methodology; where available, meta-analyses, systematic reviews, and comprehensive qualitative review articles were preferentially referenced.

Results

There are several potential sources of objective PD biomarkers including biofluids, peripheral tissue, imaging, genetics, and technology based objective motor testing. Approaches to biomarker identification include the candidate biomarker approach and unbiased discovery methods, each of which has advantages and disadvantages. Several emerging techniques hold promise in each of these areas. Advances in technology and bioinformatics, and the increasing availability of biobanks, are expected to facilitate future PD biomarker development.

Conclusions

The field of objective biomarkers for PD has made great progress but much remains to be done in translating putative biomarkers into tools useful in the clinic and for research. Multimodal biomarker platforms have the potential to capitalize on the utility and strengths of individual biomarkers. Rigorous methodology and standards for replication of findings will be key to meaningful progress in the field.

Biomarkers of Parkinson's Disease: An Introduction

The development of biomarkers is of great importance in Parkinson's disease (PD) as it may contribute to confirmation and support of the diagnosis, tracking of progression, and prediction of the natural history of PD. Biomarkers also help in the identification of targets for treatment and measuring the efficacy of interventions. Biomarkers are, therefore, crucial to understanding the pathophysiology of PD, the second commonest neurodegenerative disorder in the world. Modern understanding of PD suggests that it is a multipeptide, multiorgan disorder presenting with a heterogeneous clinical condition, both motor and nonmotor. Biomarkers need to reflect this neuropathological and clinical heterogeneity of PD. In this review, we outline some key advances in the field of clinical, genetic, neuroimaging, and tissue-based biomarkers proposed or used for PD. The individual sections will be covered in relevant chapters and our review is largely a primer aimed to alert readers to the current state of the various biomarkers proposed for PD. In doing so, we have also underlined the important role multimodal rather than single biomarkers could play in our future understanding of PD.

Parkinson's disease biomarkers: perspective from the NINDS Parkinson's Disease Biomarkers Program

Biomarkers for Parkinson's disease (PD) diagnosis, prognostication and clinical trial cohort selection are an urgent need. While many promising markers have been discovered through the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) and other mechanisms, no single PD marker or set of markers are ready for clinical use. Here we discuss the current state of biomarker discovery for platforms relevant to PDBP. We discuss the role of the PDBP in PD biomarker identification and present guidelines to facilitate their development. These guidelines include: harmonizing procedures for biofluid acquisition and clinical assessments, replication of the most promising biomarkers, support and encouragement of publications that report negative findings, longitudinal follow-up of current cohorts including the PDBP, testing of wearable technologies to capture readouts between study visits and development of recently diagnosed (de novo) cohorts to foster identification of the earliest markers of disease onset.

Integrative transcriptomic meta-analysis of Parkinson's disease and depression identifies NAMPT as a potential blood biomarker for de novo Parkinson's disease

Emerging research indicates that depression could be one of the earliest prodromal symptoms or risk factors associated with the pathogenesis of Parkinson’s disease (PD), the second most common neurodegenerative disorder worldwide, but the mechanisms underlying the association between both diseases remains unknown. Understanding the molecular networks linking these diseases could facilitate the discovery of novel diagnostic and therapeutics. Transcriptomic meta-analysis and network analysis of blood microarrays from untreated patients with PD and depression identified genes enriched in pathways related to the immune system, metabolism of lipids, glucose, fatty acids, nicotinamide, lysosome, insulin signaling and type 1 diabetes. Nicotinamide phosphoribosyltransferase (NAMPT), an adipokine that plays a role in lipid and glucose metabolism, was identified as the most significant dysregulated gene. Relative abundance of NAMPT was upregulated in blood of 99 early stage and drug-naïve PD patients compared to 101 healthy controls (HC) nested in the cross-sectional Parkinson’s Progression Markers Initiative (PPMI). Thus, here we demonstrate that shared molecular networks between PD and depression provide an additional source of biologically relevant biomarkers. Evaluation of NAMPT in a larger prospective longitudinal study including samples from other neurodegenerative diseases, and patients at risk of PD is warranted.

Biomarkers for dementia and mild cognitive impairment in Parkinson's disease

Cognitive decline is one of the most frequent and disabling nonmotor features of Parkinson's disease. Around 30% of patients with Parkinson's disease experience mild cognitive impairment, a well-established risk factor for the development of dementia. However, mild cognitive impairment in patients with Parkinson's disease is a heterogeneous entity that involves different types and extents of cognitive deficits. Because it is not currently known which type of mild cognitive impairment confers a higher risk of progression to dementia, it would be useful to define biomarkers that could identify these patients to better study disease progression and possible interventions. In this sense, the identification among patients with Parkinson's disease and mild cognitive impairment of biomarkers associated with dementia would allow the early detection of this process. This review summarizes studies from the past 25 years that have assessed the potential biomarkers of dementia and mild cognitive impairment in Parkinson's disease patients. Despite the potential importance, no biomarker has as yet been validated. However, features such as low levels of epidermal and insulin-like growth factors or uric acid in plasma/serum and of Aß in CSF, reduction of cerebral cholinergic innervation and metabolism measured by PET mainly in posterior areas, and hippocampal atrophy in MRI might be indicative of distinct deficits with a distinct risk of dementia in subgroups of patients. Longitudinal studies combining the existing techniques and new approaches are needed to identify patients at higher risk of dementia. © 2016 International Parkinson and Movement Disorder Society.

Plasma EGF and cognitive decline in Parkinson's disease and Alzheimer's disease

Objective

Cognitive decline occurs in multiple neurodegenerative diseases, including Alzheimer's disease (AD) and Parkinson's disease (PD). Shared underlying mechanisms may exist and manifest as shared biomarker signatures. Previously, we nominated plasma epidermal growth factor (EGF) as a biomarker predicting cognitive decline in patients with established PD. Here, we investigate EGF as a predictive biomarker in prodromal PD, as well as AD.

Methods

A cohort of PD patients (n = 236) was recruited to replicate our finding that low baseline EGF levels predict future cognitive decline. Additionally, plasma EGF and cognitive outcome measures were obtained from individuals with normal cognition (NC, n = 58), amnestic mild cognitive impairment (AD‐MCI, n = 396), and Alzheimer's disease (AD, n = 112) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort to investigate whether low EGF levels correlate with cognitive status and outcome in AD‐MCI and AD. Third, plasma EGF and cognitive measures were evaluated in the high‐risk asymptomatic Parkinson's Associated Risk Study (PARS) cohort (n = 165) to investigate the association of EGF and cognitive performance in a PD prodromal context.

Results

In both PD and AD‐MCI, low baseline plasma EGF predicted poorer long‐term cognitive outcomes. In asymptomatic individuals at highest risk for developing PD from the PARS cohort, low baseline plasma EGF associated with poorer performance in the visuospatial domain but not in other cognitive domains.

Interpretation

Low plasma EGF at baseline predicts cognitive decline in both AD and PD. Evidence for this signal may exist in prodromal stages of both diseases.

Converging mediators from immune and trophic pathways to identify Parkinson disease dementia

Objective:

To identify a panel of peripheral inflammatory/immune mediators that could discriminate Parkinson disease with dementia (PDD) from Parkinson disease (PD) without dementia.

Methods:

Plasma samples from 52 patients with PD and 22 patients with PDD were prepared from freshly collected blood following an institutional review board–approved protocol. A total of 160 proteins were measured using a multiplex antibody array. Plasma α-synuclein levels were analyzed by an electrochemiluminescence immunoassay. The main objective of the statistical analyses was to identify PDD discriminants using the plasma protein profile alone or in combination with age.

Results:

The PD and PDD groups differed significantly in cognitive measurements (Mini-Mental State Examination, Auditory Verbal Learning Test-A7, and Clinical Dementia Rating) and age. The age-adjusted levels of thymus and activation-regulated chemokine (TARC) and platelet-derived growth factor (PDGF)-AA were significantly different between disease groups. The levels of plasma α-synuclein significantly correlated with 26 proteins; among them, PDGF-BB, TARC, PDGF-AA, and epidermal growth factor were the highest. Linear discriminant analysis with leave-one-out cross-validation identified a 14-protein panel with age as discriminants of PDD (96% sensitivity, 89% specificity, area under the curve = 0.9615).

Conclusions:

We showed that multiple proteins that are mediators of growth/trophic and immune response-related pathways had discriminatory power for identifying PDD in patients with PD. Validation of this discovery-based study in longitudinal population-based studies is warranted.

Classification of evidence:

This study provides Class III evidence that a 14-protein panel plasma assay combined with age has a sensitivity of 96% and a specificity of 89% for PDD.

An Alzheimer's Disease-Derived Biomarker Signature Identifies Parkinson's Disease Patients with Dementia

Biomarkers from multiple modalities have been shown to correlate with cognition in Parkinson's disease (PD) and in Alzheimer's disease (AD). However, the relationships of these markers with each other, and the use of multiple markers in concert to predict an outcome of interest, are areas that are much less explored. Our objectives in this study were (1) to evaluate relationships among 17 biomarkers previously reported to associate with cognition in PD or AD and (2) to test performance of a five-biomarker classifier trained to recognize AD in identifying PD with dementia (PDD). To do this, we evaluated a cross-sectional cohort of PD patients (n = 75) across a spectrum of cognitive abilities. All PD participants had 17 baseline biomarkers from clinical, genetic, biochemical, and imaging modalities measured, and correlations among biomarkers were assessed by Spearman's rho and by hierarchical clustering. We found that internal correlation among all 17 candidate biomarkers was modest, showing a maximum pairwise correlation coefficient of 0.51. However, a five-marker subset panel derived from AD (CSF total tau, CSF phosphorylated tau, CSF amyloid beta 42, APOE genotype, and SPARE-AD imaging score) discriminated cognitively normal PD patients vs. PDD patients with 80% accuracy, when employed in a classifier originally trained to recognize AD. Thus, an AD-derived biomarker signature may identify PDD patients with moderately high accuracy, suggesting mechanisms shared with AD in some PDD patients. Based on five measures readily obtained during life, this AD-derived signature may prove useful in identifying PDD patients most likely to respond to AD-based crossover therapies.

Blood Biomarkers Associated with Cognitive Decline in Early Stage and Drug-Naive Parkinson's Disease Patients

Early diagnosis of Parkinson's disease (PD) continues to be a major challenge in the field. The lack of a robust biomarker to detect early stage PD patients has considerably slowed the progress toward the development of potential therapeutic agents. We have previously evaluated several RNA biomarkers in whole blood from participants enrolled in two independent clinical studies. In these studies, PD patients were medicated, thus, expression of these biomarkers in de novo patients remains unknown. To this end, we tested ten RNA biomarkers in blood samples from 99 untreated PD patients and 101 HC nested in the cross-sectional Parkinson's Progression Markers Initiative by quantitative real-time PCR. One biomarker out of ten, COPZ1 trended toward significance (nominal p = 0.009) when adjusting for age, sex, and educational level. Further, COPZ1, EFTUD2 and PTBP1 mRNAs correlated with clinical features in PD patients including the Hoehn and Yahr scale, Movement Disorder Society revision of Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and Montreal Cognitive Assessment (MoCA) score. Levels of EFTUD2 and PTBP1 were significantly higher in cognitively normal PD patients (PD-CN) compared to cognitively impaired PD patients (PD-MCI). Interestingly, blood glucose levels were significantly higher in PD and PD-MCI patients (≥ 100 mg/dL, pre-diabetes) compared to HC. Collectively, we report the association of three RNA biomarkers, COPZ1, EFTUD2 and PTBP1 with clinical features including cognitive decline in early drug-naïve PD patients. Further, our results show that drug-naïve PD and PD-MCI patients have glucose levels characteristic of pre-diabetes patients, suggesting that impaired glucose metabolism is an early event in PD. Evaluation of these potential biomarkers in a larger longitudinal study is warranted.

Plasma epidermal growth factor decreased in the early stage of Parkinson's disease

Epidermal growth factor (EGF) is a neurotrophic factor that plays an important role in Parkinson's disease (PD). We measured plasma EGF level in PD, essential tremor (ET) and normal controls to investigate whether it changes in PD and whether it is associated with motor and non-motor symptoms of PD. 100 patients with PD, 40 patients with ET as disease control and 76 healthy persons were enrolled in the present study. Motor and non-motor symptoms were assessed by different scales. Plasma EGF levels of three groups were measured by enzyme-linked immunosorbent assay kit. Spearman test and linear logistics regression model were used to test the correlation of EGF with motor and non-motor symptoms of PD. Plasma EGF level was significantly decreased in early PD patients compared with normal control, but not in advanced PD patients. Interestingly, plasma EGF level was significantly increased in advanced PD and total PD patients compared with ET patients, but not in early PD patients. In addition, plasma EGF level was correlated with UPDRS-III scores in PD. Also plasma EGF level was correlated with UPDRS-III scores and NMS scores in early PD. Our results suggested that plasma EGF decreased in the early stage of PD and increased later on in the PD disease course. Also, plasma EGF level was increased significantly in PD compared with ET patients and correlated with motor and non-motor symptoms in early PD.

Cognitive impairment in Parkinson's disease

Cognitive impairment is a significant non-motor symptom of Parkinson's disease (PD). Longitudinal cohort studies have demonstrated that approximately 50% of those with PD develop dementia after 10 years, increasing to over 80% after 20 years. Deficits in cognition can be identified at the time of PD diagnosis in some patients and this mild cognitive impairment (PD-MCI) has been studied extensively over the last decade. Although PD-MCI is a risk factor for developing Parkinson's disease dementia there is evidence to suggest that PD-MCI might consist of distinct subtypes with different pathophysiologies and prognoses. The major pathological correlate of Parkinson's disease dementia is Lewy body deposition in the limbic system and neocortex although Alzheimer's related pathology is also an important contributor. Pathological damage causes alteration to neurotransmitter systems within the brain, producing behavioural change. Management of cognitive impairment in PD requires a multidisciplinary approach and accurate communication with patients and relatives is essential.

Prevalent polymorphism in thyroid hormone-activating enzyme leaves a genetic fingerprint that underlies associated clinical syndromes

CONTEXT

A common polymorphism in the gene encoding the activating deiodinase (Thr92Ala-D2) is known to be associated with quality of life in millions of patients with hypothyroidism and with several organ-specific conditions. This polymorphism results in a single amino acid change within the D2 molecule where its susceptibility to ubiquitination and proteasomal degradation is regulated.

OBJECTIVE

To define the molecular mechanisms underlying associated conditions in carriers of the Thr92Ala-D2 polymorphism.

DESIGN, SETTING, PATIENTS

Microarray analyses of 19 postmortem human cerebral cortex samples were performed to establish a foundation for molecular studies via a cell model of HEK-293 cells stably expressing Thr92 or Ala92 D2.

RESULTS

The cerebral cortex of Thr92Ala-D2 carriers exhibits a transcriptional fingerprint that includes sets of genes involved in CNS diseases, ubiquitin, mitochondrial dysfunction (chromosomal genes encoding mitochondrial proteins), inflammation, apoptosis, DNA repair, and growth factor signaling. Similar findings were made in Ala92-D2-expressing HEK-293 cells and in both cases there was no evidence that thyroid hormone signaling was affected ie, the expression level of T3-responsive genes was unchanged, but that several other genes were differentially regulated. The combined microarray analyses (brain/cells) led to the development of an 81-gene classifier that correctly predicts the genotype of homozygous brain samples. In contrast to Thr92-D2, Ala92-D2 exhibits longer half-life and was consistently found in the Golgi. A number of Golgi-related genes were down-regulated in Ala92-D2-expressing cells, but were normalized after 24-h-treatment with the antioxidant N-acetylecysteine.

CONCLUSIONS

Ala92-D2 accumulates in the Golgi, where its presence and/or ensuing oxidative stress disrupts basic cellular functions and increases pre-apoptosis. These findings are reminiscent to disease mechanisms observed in other neurodegenerative disorders such as Huntington's disease, and could contribute to the unresolved neurocognitive symptoms of affected carriers.

What can biomarkers tell us about cognition in Parkinson's disease?

Cognitive decline is common in Parkinson's disease (PD), even in the early motor stage, and this non-motor feature impacts quality of life and prognosis tremendously. In this article, we discuss marker candidates for cognitive decline in PD from different angles, including functional and structural imaging techniques, biological fluid markers in cerebrospinal fluid, and blood genetic predictors, as well as gait as a surrogate marker of cognitive decline. Specifically, imaging-based markers of cognitive impairment in PD include cortical atrophy, reduced cortical metabolism, loss of cortical cholinergic and frontal dopaminergic function, as well as an increased cortical amyloid load. Reduced β-amyloid(1-42) in cerebrospinal fluid and lower plasma levels of epidermal growth factor are predictors for cognitive decline in PD. In addition, genetic variation in the apolipoprotein E (APOE), catechol-O-methyltransferase (COMT), microtubule-associated protein tau (MAPT), and glucocerebrosidase (GBA) genes may confer risk for cognitive impairment in PD; and gait disturbance may also indicate an increased risk for dementia. Other marker candidates have been proposed and are discussed. All of the current studies are hampered by gaps in our knowledge about the molecular causes of cognitive decline, which will have to be considered in future biomarker studies.

Unbiased approaches to biomarker discovery in neurodegenerative diseases

Neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and frontotemporal dementia have several important features in common. They are progressive, they affect a relatively inaccessible organ, and we have no disease-modifying therapies for them. For these brain-based diseases, current diagnosis and evaluation of disease severity rely almost entirely on clinical examination, which may be only a rough approximation of disease state. Thus, the development of biomarkers-objective, relatively easily measured, and precise indicators of pathogenic processes-could improve patient care and accelerate therapeutic discovery. Yet existing, rigorously tested neurodegenerative disease biomarkers are few, and even fewer biomarkers have translated into clinical use. To find new biomarkers for these diseases, an unbiased, high-throughput screening approach may be needed. In this review, I will describe the potential utility of such an approach to biomarker discovery, using Parkinson's disease as a case example.

Blood-based biomarkers for Parkinson's disease

There is a pressing need for biomarkers to diagnose Parkinson's disease (PD), assess disease severity, and prognosticate course. Various types of biologic specimens are potential candidates for identifying biomarkers--defined here as surrogate indicators of physiological or pathophysiological states--but blood has the advantage of being minimally invasive to obtain. There are, however, several challenges to identifying biomarkers in blood. Several candidate biomarkers identified in other diseases or in other types of biological fluids are being pursued as blood-based biomarkers in PD. In addition, unbiased discovery is underway using techniques including metabolomics, proteomics, and gene expression profiling. In this review, we summarize these techniques and discuss the challenges and successes of blood-based biomarker discovery in PD. Blood-based biomarkers that are discussed include α-synuclein, DJ-1, uric acid, epidermal growth factor, apolipoprotein-A1, and peripheral inflammatory markers.

Targeted discovery and validation of plasma biomarkers of Parkinson's disease

Despite extensive research, an unmet need remains for protein biomarkers of Parkinson's disease (PD) in peripheral body fluids, especially blood, which is easily accessible clinically. The discovery of such biomarkers is challenging, however, due to the enormous complexity and huge dynamic range of human blood proteins, which are derived from nearly all organ systems, with those originating specifically from the central nervous system (CNS) being exceptionally low in abundance. In this investigation of a relatively large cohort (∼300 subjects), selected reaction monitoring (SRM) assays (a targeted approach) were used to probe plasma peptides derived from glycoproteins previously found to be altered in the CNS based on PD diagnosis or severity. Next, the detected peptides were interrogated for their diagnostic sensitivity and specificity as well as the correlation with PD severity, as determined by the Unified Parkinson's Disease Rating Scale (UPDRS). The results revealed that 12 of the 50 candidate glycopeptides were reliably and consistently identified in plasma samples, with three of them displaying significant differences among diagnostic groups. A combination of four peptides (derived from PRNP, HSPG2, MEGF8, and NCAM1) provided an overall area under curve (AUC) of 0.753 (sensitivity: 90.4%; specificity: 50.0%). Additionally, combining two peptides (derived from MEGF8 and ICAM1) yielded significant correlation with PD severity, that is, UPDRS (r = 0.293, p = 0.004). The significance of these results is at least two-fold: (1) it is possible to use a targeted approach to identify otherwise very difficult to detect CNS related biomarkers in peripheral blood and (2) the novel biomarkers, if validated in independent cohorts, can be employed to assist with clinical diagnosis of PD as well as monitoring disease progression.

Effects of the adenosine A2A receptor antagonist on cognitive dysfunction in Parkinson's disease

Parkinson's disease (PD) is primarily characterized by motor abnormalities, but cognitive changes also occur in the early and late stages of the disease process. In PD patients, cognitive dysfunction is associated with reduced quality of life, as well as increased morbidity and mortality, resulting in increases in caregiver burden, and health-related costs. Therefore, safe and effective approaches are needed to treat cognitive dysfunction in PD patients. The underlying pathophysiology of cognitive dysfunction is complex and not fully understood, however. α-Synuclein, amyloid-related proteins, and cholinergic deficits have been reported to partially contribute to cognitive dysfunction. Changes in cortical dopamine (DA) content may also be responsible for early cognitive changes in patients with PD. Certainly, dopaminergic afferents to the frontal cortex degenerate in PD, and there is a reduction of DA content in the prefrontal cortex (PFC). It has also been reported that PFC dopaminergic input plays an important role in working memory performance. Moreover, PFC DA levels and working memory performance are significantly reduced by a 6-hydroxydopamine lesion in the PFC of a rat. Recent findings in the areas of pharmacological manipulation and genetic ablation suggest that the adenosine A2A receptor is also related to cognitive functions, especially working memory. In addition, the blockade of adenosine A2A receptors reverses cognitive dysfunction in PFC-lesioned rats, and this blocking effect may be due to an increase in PFC DA content. Therefore, adenosine A2A receptor antagonists not only improve motor performance, but they may also lead to improved cognitive function in those with PD.

Clinical correlates of serum insulin-like growth factor-1 in patients with Parkinson's disease, multiple system atrophy and progressive supranuclear palsy

BACKGROUND

Recently, increased serum insulin-like growth factor-1 (IGF-1) levels have been reported in patients with Parkinson's disease (PD) and multiple system atrophy (MSA).

OBJECTIVE

To assess a correlation between the serum IGF-1 levels and clinical background factors in patients with PD and related disorders such as MSA and progressive supranuclear palsy (PSP).

METHODS

A total of 79 PD patients, 25 MSA patients, 16 PSP patients and 52 healthy controls were included in this study. The serum IGF-1 and growth hormone (GH) levels were measured in a fasting state. Unified PD Rating Scale (UPDRS) part III was used to evaluate motor function. Unified MSA Rating Scale (UMSARS) part II was also employed for the MSA patients.

RESULTS

The serum IGF-1 levels were significantly increased in the MSA patients compared with the PD patients and controls. No significant differences were observed in the serum GH levels among the patients and controls. The serum IGF-1 levels of PD patients with Hoehn and Yahr stage 2 were significantly higher than those of patients with Hoehn and Yahr stages 3-5. In patients with PD and PSP, the serum IGF-1 levels were negatively correlated with UPDRS part III. In contrast, patients with MSA showed a positive correlation of the serum IGF-1 levels with disease duration, UPDRS part III and UMSARS part II.

CONCLUSION

The difference in the serum IGF-1 level and its correlation with clinical variables among these disorders may reflect different ongoing disease processes in each disorder.

Parkinson's disease dementia: convergence of α-synuclein, tau and amyloid-β pathologies

Dementia is increasingly being recognized in cases of Parkinson's disease (PD); such cases are termed PD dementia (PDD). The spread of fibrillar α-synuclein (α-syn) pathology from the brainstem to limbic and neocortical structures seems to be the strongest neuropathological correlate of emerging dementia in PD. In addition, up to 50% of patients with PDD also develop sufficient numbers of amyloid-β plaques and tau-containing neurofibrillary tangles for a secondary diagnosis of Alzheimer's disease, and these pathologies may act synergistically with α-syn pathology to confer a worse prognosis. An understanding of the relationships between these three distinct pathologies and their resultant clinical phenotypes is crucial for the development of effective disease-modifying treatments for PD and PDD.