Accuracy of Parkinson disease diagnosis unchanged in 2 decades

Plasma Metabolic Analysis Reveals the Dysregulation of Short-Chain Fatty Acid Metabolism in Parkinson's Disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder, characterized by high morbidity, high disability rate, and slow course of disease. The clinical diagnostic method of PD is complex and time-consuming, and there is no clear biomarker for clinical use. We aimed to investigate the plasma metabolites in PD and find out potential biomarkers with diagnostic ability. In the analysis of more than 40 metabolites including short-chain fatty acids, long-chain fatty acids, amino acids, and carbohydrates, the difference of short-chain fatty acids was observed. Acetic acid concentration was higher in PD than in healthy controls, and propanoic acid and 2,3,4-trihydroxybutyric acid were lower in PD. Compared with the early stage of PD, acetic acid increased significantly in the advanced stage of PD. Propanoic acid increased significantly in medicated PD compared with drug naïve PD. ROC analysis revealed acetic acid discriminated PD from healthy controls with 100% sensitivity, 88.9% specificity, and an area under the curve (AUC) of 0.981, and propanoic acid discriminated PD from healthy controls with an AUC of 0.981, 100% sensitivity, and 94.4% specificity. Acetic acid and propanoic acid may be a potential biomarker for differentiating PD from health, and the propanoic acid was evaluated as the most potential diagnostic marker because of its extremely high sensitivity and specificity.

The challenging quest of neuroimaging: From clinical to molecular-based subtyping of Parkinson disease and atypical parkinsonisms

The current framework of Parkinson disease (PD) focuses on phenotypic classification despite its considerable heterogeneity. We argue that this method of classification has restricted therapeutic advances and therefore limited our ability to develop disease-modifying interventions in PD. Advances in neuroimaging have identified several molecular mechanisms relevant to PD, variation within and between clinical phenotypes, and potential compensatory mechanisms with disease progression. Magnetic resonance imaging (MRI) techniques can detect microstructural changes, disruptions in neural pathways, and metabolic and blood flow alterations. Positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging have informed the neurotransmitter, metabolic, and inflammatory dysfunctions that could potentially distinguish disease phenotypes and predict response to therapy and clinical outcomes. However, rapid advancements in imaging techniques make it challenging to assess the significance of newer studies in the context of new theoretical frameworks. As such, there needs to not only be a standardization of practice criteria in molecular imaging but also a rethinking of target approaches. In order to harness precision medicine, a coordinated shift is needed toward divergent rather than convergent diagnostic approaches that account for interindividual differences rather than similarities within an affected population, and focus on predictive patterns rather than already lost neural activity.

Detecting Parkinson's Disease through Gait Measures Using Machine Learning

Parkinson’s disease (PD) is one of the most common long-term degenerative movement disorders that affects the motor system. This progressive nervous system disorder affects nearly one million Americans, and more than 20,000 new cases are diagnosed each year. PD is a chronic and progressive painful neurological disorder and usually people with PD live 10 to 20 years after being diagnosed. PD is diagnosed based on the identification of motor signs of bradykinesia, rigidity, tremor, and postural instability. Though several attempts have been made to develop explicit diagnostic criteria, this is still largely unrevealed. In this manuscript, we aim to build a classifier with gait data from Parkinson patients and healthy controls using machine learning methods. The classifier could help facilitate a more accurate and cost-effective diagnostic method. The input to our algorithm is the Gait in Parkinson’s Disease dataset published on PhysioNet containing force sensor data as the measurement of gait from 92 healthy subjects and 214 patients with idiopathic Parkinson’s Disease. Different machine learning methods, including logistic regression, SVM, decision tree, KNN were tested to output a predicted classification of Parkinson patients and healthy controls. Baseline models including frequency domain method can reach similar performance and may be another good approach for the PD diagnostics.

Sensitivity of Sniffer Dogs for a Diagnosis of Parkinson's Disease: A Diagnostic Accuracy Study

BACKGROUND

The diagnostic criteria for Parkinson's disease (PD) remain complex, which is especially problematic for nonmovement disorder experts. A test is required to establish a diagnosis of PD with improved accuracy and reproducibility.

OBJECTIVE

The study aimed to investigate the sensitivity and specificity of tests using sniffer dogs to diagnose PD.

METHODS

A prospective, diagnostic case-control study was conducted in four tertiary medical centers in China to evaluate the accuracy of sniffer dogs to distinguish between 109 clinically established medicated patients with PD, 654 subjects without PD, 37 drug-naïve patients with PD, and 185 non-PD controls. The primary outcomes were sensitivity and specificity of sniffer dog's identification.

RESULTS

In the study with patients who were medicated, when two or all three sniffer dogs yielded positive detection results in a sample tested, the index test sensitivity, specificity, and positive and negative likelihood ratios were 91% (95% CI: 84%-96%), 95% (95% CI: 93%-97%), and 19.16 (95% CI: 13.52-27.16) and 0.10 (95% CI: 0.05-0.17), respectively. The corresponding sensitivity, specificity, and positive and negative likelihood ratios in patients who were drug-naïve were 89% (95% CI: 75%-96%), 86% (95% CI: 81%-91%), and 6.6 (95% CI: 4.51-9.66) and 0.13 (95% CI: 0.05-0.32), respectively.

CONCLUSIONS

Tests using sniffer dogs may be a useful, noninvasive, fast, and cost-effective method to identify patients with PD in community screening and health prevention checkups as well as in neurological practice. © 2022 International Parkinson and Movement Disorder Society.

Synuclein-One study: skin biopsy detection of phosphorylated α-synuclein for diagnosis of synucleinopathies

Finding an easily accessible and reliable tool to diagnose the diseases collectively defined as 'synucleinopathies' is an urgent, unmet priority. The synucleinopathies include Parkinson's disease, multiple system atrophy, pure autonomic failure and dementia with Lewy bodies. There are millions of people who have a diagnosis of a synucleinopathy, with more diagnosed every year. With accessibility, ease of implementation, consistently high sensitivity (>80%) and specificity approaching 100%, skin biopsy has great potential as the clinical test of choice for the diagnosis of synucleinopathies. The large, multi-center Synuclein-One study will determine the sensitivity, specificity, accuracy and precision of α-synuclein detection within punch skin biopsies in patients with clinically established synucleinopathies using standardized, robust methods suitable for large-scale analysis. Clinical Trial Registration: NCT04700722 (ClinicalTrials.gov).

Imaging the Substantia Nigra in Parkinson Disease and Other Parkinsonian Syndromes

Parkinson disease is characterized by dopaminergic cell loss in the substantia nigra of the midbrain. There are various imaging markers for Parkinson disease. Recent advances in MRI have enabled elucidation of the underlying pathophysiologic changes in the nigral structure. This has contributed to accurate and early diagnosis and has improved disease progression monitoring. This article aims to review recent developments in nigral imaging for Parkinson disease and other parkinsonian syndromes, including nigrosome imaging, neuromelanin imaging, quantitative iron mapping, and diffusion-tensor imaging. In particular, this article examines nigrosome imaging using 7-T MRI and 3-T susceptibility-weighted imaging. Finally, this article discusses volumetry and its clinical importance related to symptom manifestation. This review will improve understanding of recent advancements in nigral imaging of Parkinson disease. Published under a CC BY 4.0 license.

Challenges in the diagnosis of Parkinson's disease

Parkinson's disease is the second most common neurodegenerative disease and its prevalence has been projected to double over the next 30 years. An accurate diagnosis of Parkinson's disease remains challenging and the characterisation of the earliest stages of the disease is ongoing. Recent developments over the past 5 years include the validation of clinical diagnostic criteria, the introduction and testing of research criteria for prodromal Parkinson's disease, and the identification of genetic subtypes and a growing number of genetic variants associated with risk of Parkinson's disease. Substantial progress has been made in the development of diagnostic biomarkers, and genetic and imaging tests are already part of routine protocols in clinical practice, while novel tissue and fluid markers are under investigation. Parkinson's disease is evolving from a clinical to a biomarker-supported diagnostic entity, for which earlier identification is possible, different subtypes with diverse prognosis are recognised, and novel disease-modifying treatments are in development.

PTPRC Expression in Blood is Downregulated in Parkinson's and Progressive Supranuclear Palsy Disorders

BACKGROUND

Parkinson's disease (PD) shares pathological and clinical features with progressive supranuclear palsy (PSP) patients making the diagnosis challenging. Distinguishing PD from PSP is crucial given differences in disease course, treatment and clinical management.

OBJECTIVE

Although some progress has been made in the discovery of biomarkers for PD and PSP, there is an urgent need to identify additional biomarkers capable of distinguishing between these diseases.

METHODS

In this study, we tested the phosphatases DUSP8 and PTPRC for their diagnostic potential using quantitative PCR assays, in blood of 138 samples from participants nested in the Parkinson's Disease Biomarkers Program.

RESULTS

Relative abundance of PTPRC mRNA was downregulated in PSP patients compared to PD and healthy controls, whereas there was no significant difference in the expression of DUSP8. Interestingly, PTPRC mRNA correlated with the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) total score and MDS-UPDRS- part III, thus indicating it might be useful as part of a biosignature to stratify patients according to disease severity and progression.

CONCLUSIONS

Collectively, these results suggest that PTPRC expression may be useful for distinguishing PD from PSP patients as part of a biosignature. Evaluation of PTPRC along with additional biomarkers in a larger and well-characterized longitudinal study is warranted.

GRP78 Level Is Altered in the Brain, but Not in Plasma or Cerebrospinal Fluid in Parkinson's Disease Patients

Accumulation of misfolded proteins results in cellular stress, and is detected by specific sensors in the endoplasmic reticulum, collectively known as the unfolded protein response (UPR). It has been prominently proposed that the UPR is involved in the pathophysiology of Parkinson's disease (PD). In the present study, the levels of the UPR proteins and mRNA transcripts were quantified in post mortem brain tissue from PD patients and matched controls. The level of a key mediator of the UPR pathway, glucose-regulated protein 78 (GRP78), was significantly decreased in temporal cortex and cingulate gyrus, whereas there were no significant changes in the caudate nucleus, prefrontal, or parietal cortex regions. On the other hand, GRP78 mRNA level was significantly increased in caudate nucleus, cingulate gyrus, prefrontal, and parietal cortex regions. GRP78 protein level was also measured in plasma and cerebrospinal fluid, but there were no differences in these levels between PD patients and control subjects. Furthermore, immunofluorescence labeling of the CD4⁺ T cells from PD patients showed that GRP78 protein is found in the cytoplasm. However, GRP78 level in PD patients was not significantly different from control subjects. Unlike the previous Lewy body dementia study, the present investigation reports reduced cortical protein, but increased transcript levels of GPR78 in PD. In summary, these data provide further evidence that GRP78 regulation is dysfunctional in the brains of PD patients.

Evaluation of RNA Blood Biomarkers in the Parkinson's Disease Biomarkers Program

There is a high misdiagnosis rate between Parkinson’s disease (PD) and atypical parkinsonian disorders (APD), such as progressive supranuclear palsy (PSP), the second most common parkinsonian syndrome. In our earlier studies, we identified and replicated RNA blood biomarkers in several independent cohorts, however, replication in a cohort that includes PSP patients has not yet been performed. To this end, we evaluated the diagnostic potential of nine previously identified RNA biomarkers using quantitative PCR assays in 138 blood samples at baseline from PD, PSP and healthy controls (HCs) nested in the PD Biomarkers Program. Linear discriminant analysis showed that COPZ1 and PTPN1 distinguished PD from PSP patients with 62.5% accuracy. Five biomarkers, PTPN1, COPZ1, FAXDC2, SLC14A1s and NAMPT were useful for distinguishing PSP from controls with 69% accuracy. Several biomarkers correlated with clinical features in PD patients. SLC14A1-s correlated with Unified Parkinson’s Disease Rating Scale total and part III scores. In addition, COPZ1, PTPN1 and MLST8, correlated with Montreal Cognitive Assessment (MoCA). Interestingly, COPZ1, EFTUD2 and PTPN1 were downregulated in cognitively impaired (CI) compared to normal subjects. Linear discriminant analysis showed that age, PTPN1, COPZ1, FAXDC2, EFTUD2 and MLST8 distinguished CI from normal subjects with 65.9% accuracy. These results suggest that COPZ1 and PTPN1 are useful for distinguishing PD from PSP patients. In addition, the combination of PTPN1, COPZ1, FAXDC2, EFTUD2 and MLST8 is a useful signature for cognitive impairment. Evaluation of these biomarkers in a larger study will be a key to advancing these biomarkers into the clinic.

α-Synuclein Heterocomplexes with β-Amyloid Are Increased in Red Blood Cells of Parkinson's Disease Patients and Correlate with Disease Severity

Neurodegenerative disorders (NDs) are characterized by abnormal accumulation/misfolding of specific proteins, primarily α-synuclein (α-syn), β-amyloid1-42 (Aβ1-42) and tau, in both brain and peripheral tissues. In addition to oligomers, the role of the interactions of α-syn with Aβ or tau has gradually emerged. Nevertheless, despite intensive research, NDs have no accepted peripheral markers for biochemical diagnosis. In this respect, Red Blood Cells (RBCs) are emerging as a valid peripheral model for the study of aging-related pathologies. Herein, a small cohort (N = 28) of patients affected by Parkinson's disease (PD) and age-matched controls were enrolled to detect the content of α-syn (total and oligomeric), Aβ1-42 and tau (total and phosphorylated) in RBCs. Moreover, the presence of α-syn association with tau and Aβ1-42 was explored by co-immunoprecipitation/western blotting in the same cells, and quantitatively confirmed by immunoenzymatic assays. For the first time, PD patients were demonstrated to exhibit α-syn heterocomplexes with Aβ1-42 and tau in peripheral tissues; interestingly, α-syn-Aβ1-42 concentrations were increased in PD subjects with respect to healthy controls (HC), and directly correlated with disease severity and motor deficits. Moreover, total-α-syn levels were decreased in PD subjects and inversely related to their motor deficits. Finally, an increase of oligomeric-α-syn and phosphorylated-tau was observed in RBCs of the enrolled patients. The combination of three parameters (total-α-syn, phosphorylated-tau and α-syn-Aβ1-42 concentrations) provided the best fitting predictive index for discriminating PD patients from controls. Nevertheless further investigations should be required, overall, these data suggest α-syn hetero-aggregates in RBCs as a putative tool for the diagnosis of PD.

The role of gene variants in the pathogenesis of neurodegenerative disorders as revealed by next generation sequencing studies: a review

The clinical diagnosis of neurodegenerative disorders based on phenotype is difficult in heterogeneous conditions with overlapping symptoms. It does not take into account the disease etiology or the highly variable clinical course even amongst patients diagnosed with the same disorder. The advent of next generation sequencing (NGS) has allowed for a system-wide, unbiased approach to identify all gene variants in the genome simultaneously. With the plethora of new genes being identified, genetic rather than phenotype-based classification of Mendelian diseases such as spinocerebellar ataxia (SCA), hereditary spastic paraplegia (HSP) and Charcot-Marie-Tooth disease (CMT) has become widely accepted. It has also become clear that gene variants play a role in common and predominantly sporadic neurodegenerative diseases such as Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS). The observation of pleiotropy has emerged, with mutations in the same gene giving rise to diverse phenotypes, which further increases the complexity of phenotype-genotype correlation. Possible mechanisms of pleiotropy include different downstream effects of different mutations in the same gene, presence of modifier genes, and oligogenic inheritance. Future directions include development of bioinformatics tools and establishment of more extensive public genotype/phenotype databases to better distinguish deleterious gene variants from benign polymorphisms, translation of genetic findings into pathogenic mechanisms through in-vitro and in-vivo studies, and ultimately finding disease-modifying therapies for neurodegenerative disorders.

Past, present, and future of Parkinson's disease: A special essay on the 200th Anniversary of the Shaking Palsy

This article reviews and summarizes 200 years of Parkinson's disease. It comprises a relevant history of Dr. James Parkinson's himself and what he described accurately and what he missed from today's perspective. Parkinson's disease today is understood as a multietiological condition with uncertain etiopathogenesis. Many advances have occurred regarding pathophysiology and symptomatic treatments, but critically important issues are still pending resolution. Among the latter, the need to modify disease progression is undoubtedly a priority. In sum, this multiple-author article, prepared to commemorate the bicentenary of the shaking palsy, provides a historical state-of-the-art account of what has been achieved, the current situation, and how to progress toward resolving Parkinson's disease. © 2017 International Parkinson and Movement Disorder Society.

Magnetic resonance imaging for the diagnosis of Parkinson's disease

The differential diagnosis of parkinsonian syndromes is considered one of the most challenging in neurology and error rates in the clinical diagnosis can be high even at specialized centres. Despite several limitations, magnetic resonance imaging (MRI) has undoubtedly enhanced the diagnostic accuracy in the differential diagnosis of neurodegenerative parkinsonism over the last three decades. This review aims to summarize research findings regarding the value of the different MRI techniques, including advanced sequences at high- and ultra-high-field MRI and modern image analysis algorithms, in the diagnostic work-up of Parkinson's disease. This includes not only the exclusion of alternative diagnoses for Parkinson's disease such as symptomatic parkinsonism and atypical parkinsonism, but also the diagnosis of early, new onset, and even prodromal Parkinson's disease.

Is survival improved by the use of NIV and PEG in amyotrophic lateral sclerosis (ALS)? A post-mortem study of 80 ALS patients

Background

Non-invasive ventilation (NIV) and percutaneous gastrostomy (PEG) are guideline-recommended interventions for symptom management in amyotrophic lateral sclerosis (ALS). Their effect on survival is controversial and the impact on causes of death is unknown.

Objective

To investigate the effect of NIV and PEG on survival and causes of death in ALS patients.

Methods

Eighty deceased ALS patients underwent a complete post mortem analysis for causes of death between 2003 and 2015. Forty-two of these patients consented for genetic testing. Effects of NIV and PEG on survival and causes of death were analyzed in a multivariable Cox proportional hazard regression.

Results

Six patients, who requested assisted suicide causing drug-induced hypoxia, were excluded from final analysis. Respiratory failure was the main cause of death in 72 out of 74 patients. Fifteen out of 74 died of aspiration pneumonia 23/74 of bronchopneumonia and 8/74 of a combination of aspiration pneumonia and bronchopneumonia. Twenty died of hypoxia without concomitant infection, and six patients had pulmonary embolism alone or in combination with pneumonia. NIV (p = 0.01) and PEG (p<0.01) had a significant impact on survival. In patients using NIV bronchopneumonia was significantly more frequent (p <0.04) compared to non-NIV patients. This effect was even more pronounced in limb onset patients (p<0.002). Patients with C9orf72 hexanucleotide repeat expansions showed faster disease progression and shorter survival (p = 0.01).

Conclusion

The use of NIV and PEG prolongs survival in ALS. This study supports current AAN and EFNS guidelines which recommend NIV and PEG as a treatment option in ALS. The risk of bronchopneumonia as cause of death may be increased by NIV.

Femur Fractures in Parkinsonism: Analysis of a National Sample Cohort in South Korea

Background and Purpose

Falling with a femur fracture is a serious event that negatively affects the quality of life of elderly individuals as well as patients with parkinsonism. This study investigated the association between parkinsonism and femur fracture and compared the risk of femur fracture between subjects with and without parkinsonism.

Methods

This study examined a population-based matched cohort constructed using the National Sample Cohort data set, which comprises approximately one million subscribers to medical insurance and aid in South Korea. Subjects with parkinsonism during 2003–2013 were identified as the exposed group, and up to five individuals matched for age, sex, and index years were identified as the controls for each parkinsonism subject. The risk of femur fracture for parkinsonism was evaluated using Cox regression.

Results

The incidence of femur fracture according to age, sex, and body mass index varied significantly between subjects with parkinsonism and controls (p<0.001). The presence of parkinsonism was associated with a higher risk of femur fractures for males [hazard ratio (HR)=2.85, 95% confidence interval [CI]=1.87–4.34], subjects younger than 65 years (HR=2.89, 95% CI=1.64–5.11), and underweight subjects (HR=3.90, 95% CI=1.82–8.35). The adjusted HR for femur fracture with parkinsonism was highest within 2 years of the disease diagnosis (HR=3.10, 95% CI=2.12–4.53).

Conclusions

Our study found that the presence of parkinsonism is more strongly related to femur fracture in males, and increases the influence of traditional risk factors on femur fracture. It is necessary to consider how factors associated with the amount of ambulatory activity–even in an early diagnosed state–can play an important role in femur fracture in subjects with parkinsonism.

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.

CSF Nrf2 and HSPA8 in Parkinson's disease patients with and without LRRK2 gene mutations

Leucine-rich repeat kinase 2 (LRRK2) gene mutations are the most common genetic cause of Parkinson's disease (PD). CSF specimens from LRRK2 + PD patients and healthy LRRK2 mutation carriers are, therefore, useful for biomarker studies. This study examined the hypothesis that differences are present between subjects with sporadic PD (sPD), PD carriers of LRRK2 mutations (LRRK2 + PD), healthy control subjects lacking LRRK2 mutations (CTL), and LRRK2 mutation-carrying healthy controls (LRRK2 + CTL) for CSF concentrations of six potential PD biomarkers. Two of these proteins, nuclear factor (erythroid-derived 2)-like 2 ("Nrf2") and heat shock 70 kDa protein 8 ("HSPA8"), were detected in preliminary ELISAs, then measured in a larger cohort (60 sPD, 10 LRRK2 + PD, 23 CTL, 31 LRRK2 + CTL). No statistically significant differences were found between the groups (Nrf2 p = 0.13, HSPA8 p = 0.21). Nrf2 concentrations in LRRK2 + PD subjects were strongly positively associated with Unified Parkinson's Disease Rating Scale (UPDRS) total and motor scores [Spearman rho = 0.77 (p = 0.012) and 0.83 (p = 0.005)] and negatively associated with Montreal Cognitive Assessment (MoCA) scores (rho = -0.57; p = 0.11). Partial correlation coefficient calculations indicated that disease duration contributed to the associations of Nrf2 levels with UPDRS scores and with MoCA scores in this group. While CSF Nrf2 and HSPA8 do not appear to offer diagnostic biomarkers for PD, the associations between Nrf2 levels and UPDRS scores in LRRK2 + PD patients merit further investigation.

Biomarkers in Parkinson's disease: Advances and strategies

Parkinson's disease (PD) is a neurodegenerative disorder characterized by progressive motor disturbances and affects more than 1% of the worldwide population. Despite considerable progress in understanding PD pathophysiology, including genetic and biochemical causes, diagnostic approaches lack accuracy and interventions are restricted to symptomatic treatments. PD is a complex syndrome with different clinical subtypes and a wide variability in disorder course. In order to deliver better clinical management of PD patients and discovery of novel therapies, there is an urgent need to find sensitive, specific, and reliable biomarkers. The development of biomarkers will not only help the scientific community to identify populations at risk, but also facilitate clinical diagnosis. Furthermore, these tools could monitor progression, which could ultimately deliver personalized therapeutic strategies. The field of biomarker discovery in PD has attracted significant attention and there have been numerous contributions in recent years. Although none of the parameters have been validated for clinical practice, some candidates hold promise. This review summarizes recent advances in the development of PD biomarkers and discusses new strategies for their utilization.

Saskatchewan movement disorders program

We review the Saskatchewan Movement Disorders Program, which started in 1968 and has had the dual goals of patient care and research. The clinics are structured to collect research-worthy data including videos, longitudinal follow-up, and autopsy studies of patients seen in the clinics. At every clinic visit, the patient is evaluated by one or both authors. A total of 25% to 30% of the deceased come to autopsy. Frozen half-brain and formalin-fixed remnants from autopsy are preserved in our laboratories. Patients not seen in our clinic are not included in research, which makes it different from brain banks. So far, 515 cases have come to autopsy. So far, there have been 17 collaborating scientific teams from Canada, the United States, Europe, and Japan. The collaborators are not charged for access to our resources. This program offers a unique opportunity to study multiple aspects of movement disorder patients seen in clinical practice.

Network analysis identifies SOD2 mRNA as a potential biomarker for Parkinson's disease

Increasing evidence indicates that Parkinson's disease (PD) and type 2 diabetes (T2DM) share dysregulated molecular networks. We identified 84 genes shared between PD and T2DM from curated disease-gene databases. Nitric oxide biosynthesis, lipid and carbohydrate metabolism, insulin secretion and inflammation were identified as common dysregulated pathways. A network prioritization approach was implemented to rank genes according to their distance to seed genes and their involvement in common biological pathways. Quantitative polymerase chain reaction assays revealed that a highly ranked gene, superoxide dismutase 2 (SOD2), is upregulated in PD patients compared to healthy controls in 192 whole blood samples from two independent clinical trials, the Harvard Biomarker Study (HBS) and the Diagnostic and Prognostic Biomarkers in Parkinson's disease (PROBE). The results from this study reinforce the idea that shared molecular networks between PD and T2DM provides an additional source of biologically meaningful biomarkers. Evaluation of this biomarker in de novo PD patients and in a larger prospective longitudinal study is warranted.