Biomarker research in Parkinson’s disease: objective measures needed for patient stratification in future cause-directed trials

Integrating Big Data, Artificial Intelligence, and motion analysis for emerging precision medicine applications in Parkinson's Disease

One of the key challenges in Big Data for clinical research and healthcare is how to integrate new sources of data, whose relation to disease processes are often not well understood, with multiple classical clinical measurements that have been used by clinicians for years to describe disease processes and interpret therapeutic outcomes. Without such integration, even the most promising data from emerging technologies may have limited, if any, clinical utility. This paper presents an approach to address this challenge, illustrated through an example in Parkinson's Disease (PD) management. We show how data from various sensing sources can be integrated with traditional clinical measurements used in PD; furthermore, we show how leveraging Big Data frameworks, augmented by Artificial Intelligence (AI) algorithms, can distinctively enrich the data resources available to clinicians. We showcase the potential of this approach in a cohort of 50 PD patients who underwent both evaluations with an Integrated Motion Analysis Suite (IMAS) composed of a battery of multimodal, portable, and wearable sensors and traditional Unified Parkinson's Disease Rating Scale (UPDRS)-III evaluations. Through techniques including Principal Component Analysis (PCA), elastic net regression, and clustering analysis we demonstrate how this combined approach can be used to improve clinical motor assessments and to develop personalized treatments. The scalability of our approach enables systematic data generation and analysis on increasingly larger datasets, confirming the integration potential of IMAS, whose use in PD assessments is validated herein, within Big Data paradigms. Compared to existing approaches, our solution offers a more comprehensive, multi-dimensional view of patient data, enabling deeper clinical insights and greater potential for personalized treatment strategies. Additionally, we show how IMAS can be integrated into established clinical practices, facilitating its adoption in routine care and complementing emerging methods, for instance, non-invasive brain stimulation. Future work will aim to augment our data repositories with additional clinical data, such as imaging and biospecimen data, to further broaden and enhance these foundational methodologies, leveraging the full potential of Big Data and AI.

Cerebrospinal Fluid Total, Phosphorylated and Oligomeric A-Synuclein in Parkinson's Disease: A Systematic Review, Meta-Analysis and Meta-Regression Study

Background: The diagnostic accuracy for Parkinson's disease (PD), a synucleinopathy, based on diagnostic criteria is suboptimal. A biomarker for synucleinopathies is pivotal both from a clinical and from a research point of view. CSF a-synuclein has been extensively studied over the past two decades as a candidate biomarker of synucleinopathies. Herein, we present data on studies focusing on total, phosphorylated and oligomeric CSF a-synuclein in PD. Methods: Pubmed, Scopus and Web of Science were searched for studies with >10 PD patients and control subjects, with data (mean, SD) on total, phosphorylated or oligomeric a-synuclein. Cohen's d, as a measure of effect size, was calculated for all a-synuclein forms. Subgroup analysis and meta-regression were performed in an effort to explain between-study heterogeneity. Results: Thirty studies on total, six studies on oligomeric and one study on phosphorylated a-synuclein were included. Total a-synuclein was decreased and oligomeric a-synuclein increased in PD patients vs. controls. The effect size was medium for total and high for oligomeric a-synuclein. A-syn forms provided suboptimal combined sensitivity/specificity for the differentiation of PD from controls. There was significant between-study heterogeneity. The PD cohort characteristics (sex, age, disease duration, UPDRS, H & Y) and study characteristics (study design, healthy vs. neurological controls, control for CSF blood contamination, method of a-syn measurement) could not account for between-study heterogeneity. Publication bias was limited. Conclusions: CSF a-synuclein levels lack sufficient accuracy to be used as biomarkers for PD. The standardization of (pre)analytical variables may improve the discriminatory power of a-synuclein forms in the future.

Modelling idiopathic Parkinson disease as a complex illness can inform incidence rate in healthy adults: the PR EDIGT score

Fifty-five years after the concept of dopamine replacement therapy was introduced, Parkinson disease (PD) remains an incurable neurological disorder. To date, no disease-modifying therapeutic has been approved. The inability to predict PD incidence risk in healthy adults is seen as a limitation in drug development, because by the time of clinical diagnosis ≥ 60% of dopamine neurons have been lost. We have designed an incidence prediction model founded on the concept that the pathogenesis of PD is similar to that of many disorders observed in ageing humans, i.e. a complex, multifactorial disease. Our model considers five factors to determine cumulative incidence rates for PD in healthy adults: (i) DNA variants that alter susceptibility (D), e.g. carrying a LRRK2 or GBA risk allele; (ii) Exposure history to select environmental factors including xenobiotics (E); (iii) Gene-environment interactions that initiate pathological tissue responses (I), e.g. a rise in ROS levels, misprocessing of amyloidogenic proteins (foremost, α-synuclein) and dysregulated inflammation; (iv) sex (or gender; G); and importantly, (v) time (T) encompassing ageing-related changes, latency of illness and propagation of disease. We propose that cumulative incidence rates for PD (PR ) can be calculated in healthy adults, using the formula: PR (%) = (E + D + I) × G × T. Here, we demonstrate six case scenarios leading to young-onset parkinsonism (n = 3) and late-onset PD (n = 3). Further development and validation of this prediction model and its scoring system promise to improve subject recruitment in future intervention trials. Such efforts will be aimed at disease prevention through targeted selection of healthy individuals with a higher prediction score for developing PD in the future and at disease modification in subjects that already manifest prodromal signs.

Biomarkers of Parkinson's disease: present and future

Sporadic or idiopathic Parkinson's disease (PD) is an age-related neurodegenerative disorder of unknown origin that ranks only second behind Alzheimer's disease (AD) in prevalence and its consequent social and economic burden. PD neuropathology is characterized by a selective loss of dopaminergic neurons in the substantia nigra pars compacta; however, more widespread involvement of other CNS structures and peripheral tissues now is widely documented. The onset of molecular and cellular neuropathology of PD likely occurs decades before the onset of the motor symptoms characteristic of PD. The hallmark symptoms of PD, resting tremors, rigidity and postural disabilities, are related to dopamine (DA) deficiency. Current therapies treat these symptoms by replacing or boosting existing DA. All current interventions have limited therapeutic benefit for disease progression because damage likely has progressed over an estimated period of ~5 to 15years to a loss of 60%-80% of the nigral DA neurons, before symptoms emerge. There is no accepted definitive biomarker of PD. An urgent need exists to develop early diagnostic biomarkers for two reasons: (1) to intervene at the onset of disease and (2) to monitor the progress of therapeutic interventions that may slow or stop the course of the disease. In the context of disease development, one of the promises of personalized medicine is the ability to predict, on an individual basis, factors contributing to the susceptibility for the development of a given disease. Recent advances in our understanding of genetic factors underlying or contributing to PD offer the potential for monitoring susceptibility biomarkers that can be used to identify at-risk individuals and possibly prevent the onset of disease through treatment. Finally, the exposome concept is new in the biomarker discovery arena and it is suggested as a way to move forward in identifying biomarkers of neurological diseases. It is a two-stage scheme involving a first stage of exposome-wide association studies (EWAS) to profile omic features in serum to discover molecular biomarkers. The second stage involves application of this knowledge base in follow-up studies. This strategy is unique in that it promotes the use of data-driven (omic) strategies in interrogating diseased and healthy populations and encourages a movement away from using only reductionist strategies to discover biomarkers of exposure and disease. In this short review we will examine 1) advances in our understanding of the molecular mechanisms underlying PD that have led to candidate biomarkers for diagnosis and treatment efficacy and 2) new technologies on the horizon that will lead to novel approaches in biomarker development.

Parkinson’s Disease: Symptoms, Unmet Needs and New Therapeutic Targets

Parkinson’s disease is classically defined by the presence of two or more of the following cardinal motor symptoms: bradykinesia, rigidity, tremor at rest, and gait disturbances. In the past two decades, the non‐motor symptom complex of the disease has gained increasing attention, warranted by the impact it has on patient quality of life. In this introductory chapter, the clinical characterization of the motor and non‐motor symptoms is extensively described and the possible pathophysiological mechanisms underlying each symptom are delineated. Furthermore, the subtypes of Parkinson’s disease, based on empirical and data‐driven systems, are discussed. An updated summary of the current state‐of‐the‐art in diagnosis and treatment is briefly covered. Finally, the currently unmet needs and direction of investigative efforts are analyzed, focusing on the non‐dopamine responsive symptoms and the search for biomarkers, cause‐directed effective treatments and neuroprotective therapies.

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.

Αlpha-synuclein levels in blood plasma from LRRK2 mutation carriers

The diagnosis of Parkinson's disease (PD) remains primarily a clinical issue, based mainly on phenotypic patterns. The identification of biomarkers capable of permitting the preclinical detection of PD is critically needed. α-Synuclein is a key protein in PD, with missense and multiplication mutations in the gene encoding α-synuclein (SNCA) having been reported in familial cases of PD, and accumulation of the protein identified in Lewy bodies (LBs) and Lewy neurites (LNs) in affected brain regions. With the objective of validating the use of α-synuclein as a clinical or progressive biomarker in an accessible tissue, we used an enzyme-linked immunosorbent assay (ELISA) to measure α-synuclein levels in the peripheral blood plasma of idiopathic PD and LRRK2 mutation carrier patients and compared our findings with healthy control subjects. Compared to healthy controls, we found a significant decrease in plasma total α-synuclein levels in idiopathic PD (iPD) patients (n = 134, p = 0.010). However, the reduction was less significant in patients who were LRRK2 mutation carriers (n = 32, p = 0.133). This lack of significance could be due to the small number of individuals employed in this group. No predictive value of total α-synuclein in the diagnosis of PD was found in a receiver operating characteristic (ROC) curve analysis. Although this is a pilot study requiring corroboration on a larger cohort of patients, our results highlight the possible use of plasma α-synuclein as a biomarker for PD.

Urate in Parkinson's disease: more than a biomarker?

Parkinson's disease (PD) is a progressive neurodegenerative disease with characteristic motor manifestations. Although appreciation of PD as a multisystem disorder has grown, loss of dopaminergic neurons in the substantia nigra remains a pathological and neurochemical hallmark, accounting for the substantial symptomatic benefits of dopamine replacement therapies. However, currently no treatment has been shown to prevent or forestall the progression of the disease in spite of tremendous efforts. Among multiple environmental and genetic factors that have been implicated in the pathogenesis of PD, oxidative stress is proposed to play a critical role. A recent confluence of clinical, epidemiological, and laboratory evidence identified urate, an antioxidant and end product of purine metabolism, as not only a molecular predictor for both reduced risk and favorable progression of PD but also a potential neuroprotectant for the treatment of PD. This review summarizes recent findings on urate in PD and their clinical implications.

Considerations regarding the etiology and future treatment of autosomal recessive versus idiopathic Parkinson disease

OPINION STATEMENT

We postulate that the frequently encountered grouping of different Parkinson disease (PD) variants into a single pathogenetic concept-rather than differentiation into its molecular subtypes-has hindered progress toward curative interventions. Parkinsonism is a clinical syndrome that in rare cases can be explained by a single genetic event or by a single environmental cause, thereby leading to monogenic PD and secondary parkinsonism, respectively. Under the former category, mutations in both alleles of the Parkin-encoding PARK2 gene leads to young-onset, autosomal recessive PD, in which neurodegeneration is restricted to dopamine-producing cells of the brainstem. Under the latter category, exposure to one of several environmental factors with neuroanatomic selectivity can cause rapid-onset, secondary parkinsonism most likely irrespective of the patient's age and genetic makeup. Sandwiched between these two extreme and rare types, the most common variant is referred to as late-onset, idiopathic PD. In extension of a disease model first proposed by Braak et al., we consider idiopathic PD the result of an encounter between one or several environmental triggers and one or more susceptibility alleles. Importantly, this interaction produces a pre-motor syndrome followed by the typical PD phenotype over a period of decades. In our opinion, this pathophysiological process should thus be viewed as a "complex disease." As is true for many complex human disorders, successful intervention for the common PD variant will likely occur when genetic leads as well as environmental contributors are targeted in parallel. However, successful proof-of-concept studies could arrive sooner, namely for select PD variants that can be attributed to a single genetic event and that are neuropathologically restricted. Therefore, the authors decided to focus the second portion of their review on treatment considerations regarding autosomal recessive PD cases that are caused by Parkin deficiency. We briefly draw attention to aspects of existing pharmacological and surgical therapies as they relate to the PARK2-linked variant; thereafter, we comment on new research avenues that are aimed at future therapeutic interventions to eventually slow or arrest the progression of a first variant of PD.

Post mortem cerebrospinal fluid α-synuclein levels are raised in multiple system atrophy and distinguish this from the other α-synucleinopathies, Parkinson's disease and Dementia with Lewy bodies

Differentiating clinically between Parkinson's disease (PD) and the atypical parkinsonian syndromes of Progressive supranuclear palsy (PSP), corticobasal syndrome (CBS) and multiple system atrophy (MSA) is challenging but crucial for patient management and recruitment into clinical trials. Because PD (and the related disorder Dementia with Lewy bodies (DLB)) and MSA are characterised by the deposition of aggregated forms of α-synuclein protein (α-syn) in the brain, whereas CBS and PSP are tauopathies, we have developed immunoassays to detect levels of total and oligomeric forms of α-syn, and phosphorylated and phosphorylated oligomeric forms of α-syn, within body fluids, in an attempt to find a biomarker that will differentiate between these disorders. Levels of these 4 different forms of α-syn were measured in post mortem samples of ventricular cerebrospinal fluid (CSF) obtained from 76 patients with PD, DLB, PSP or MSA, and in 20 healthy controls. Mean CSF levels of total and oligomeric α-syn, and phosphorylated α-syn, did not vary significantly between the diagnostic groups, whereas mean CSF levels of phosphorylated oligomeric α-syn did differ significantly (p<0.001) amongst the different diagnostic groups. Although all 4 measures of α-syn were higher in patients with MSA compared to all other diagnostic groups, these were only significantly raised (p<0.001) in MSA compared to all other diagnostic groups, for phosphorylated oligomeric forms of α-syn. This suggests that this particular assay may have utility in differentiating MSA from control subject and patients with other α-synucleinopathies. However, it does not appear to be of help in distinguishing patients with PD and DLB from those with PSP or from control subjects. Western blots show that the principal form of α-syn within CSF is phosphorylated, and the finding that the phosphorylated oligomeric α-syn immunoassay appears to be the most informative of the 4 assays would be consistent with this observation.

Cytokines as potential biomarkers for Parkinson's disease: a multiplex approach

Cytokines, which are immunological messengers facilitating both intra- and inter-system communication, are considered central players in the neuroinflammatory cascades associated with the neurodegenerative process in Parkinson's disease (PD) and other neurological disorders. They have also been implicated in depression and other cognitive (e.g., memory impairment, dementia) and affective disturbances (e.g., anxiety) that show high co-morbidity with neurodegenerative diseases. As such, cytokines may hold great promise as serological biomarkers in PD, with potential applications ranging from early diagnosis and disease staging, to prognosis, drug discovery, and tracking the response to treatment. Subclassification or risk stratification in PD could be based (among other things) on reliably determined cytokine panel profiles or "signatures" of particular co-morbid disease states or at-risk groups (e.g., PD alone, PD with depression and/or dementia). Researchers and clinicians seeking to describe cytokine variations in health vs. disease will benefit greatly from technologies that allow a high degree of multiplexing and thus permit the simultaneous determination of a large roster of cytokines in single small-volume samples. The need for such highly paralleled assays is underscored by the fact that cytokines do not act in isolation but rather against a backdrop of complementary and antagonistic cytokine effects; ascribing valence to the actions of any one cytokine thus requires specific knowledge about the larger cytokine milieu. This chapter provides a technological overview of the major cytokine multiplex assay platforms before discussing the implications of such tools for biomarker discovery and related applications in PD and its depressive and cognitive co-morbidities.

α-Synuclein and tau concentrations in cerebrospinal fluid of patients presenting with parkinsonism: a cohort study

BACKGROUND

Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy are brain disorders characterised by intracellular α-synuclein deposits. We aimed to assess whether reduction of α-synuclein concentrations in CSF was a marker for α-synuclein deposition in the brain, and therefore diagnostic of synucleinopathies.

METHODS

We assessed potential extracellular-fluid markers of α-synuclein deposition in the brain (total α-synuclein and total tau in CSF, and total α-synuclein in serum) in three cohorts: a cross-sectional training cohort of people with Parkinson's disease, multiple system atrophy, dementia with Lewy bodies, Alzheimer's disease, or other neurological disorders; a group of patients with autopsy-confirmed dementia with Lewy bodies, Alzheimer's disease, or other neurological disorders (CSF specimens were drawn ante mortem during clinical investigations); and a validation cohort of patients who between January, 2003, and December, 2006, were referred to a specialised movement disorder hospital for routine inpatient admission under the working diagnosis of parkinsonism. CSF and serum samples were assessed by ELISA, and clinical diagnoses were made according to internationally established criteria. Mean differences in biomarkers between diagnostic groups were assessed with conventional parametric and non-parametric statistics.

FINDINGS

In our training set, people with Parkinson's disease, multiple system atrophy, and dementia with Lewy bodies had lower CSF α-synuclein concentrations than patients with Alzheimer's disease and other neurological disorders. CSF α-synuclein and tau values separated participants with synucleinopathies well from those with other disorders (p<0·0001; area under the receiver operating characteristic curve [AUC]=0·908). In the autopsy-confirmed cases, CSF α-synuclein discriminated between dementia with Lewy bodies and Alzheimer's disease (p=0·0190; AUC=0·687); in the validation cohort, CSF α-synuclein discriminated Parkinson's disease and dementia with Lewy bodies versus progressive supranuclear palsy, normal-pressure hydrocephalus, and other neurological disorders (p<0·0001; AUC=0·711). Other predictor variables tested in this cohort included CSF tau (p=0·0798), serum α-synuclein (p=0·0502), and age (p=0·0335). CSF α-synuclein concentrations of 1·6 pg/μL or lower showed 70·72% sensitivity (95% CI 65·3-76·1%) and 52·83% specificity (39·4-66·3%) for the diagnosis of Parkinson's disease. At this cutoff, the positive predictive value for any synucleinopathy was 90·7% (95% CI 87·3-94·2%) and the negative predictive value was 20·4% (13·7-27·2%).

INTERPRETATION

Mean CSF α-synuclein concentrations as measured by ELISA are significantly lower in Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy than in other neurological diseases. Although specificity was low, the high positive predictive value of CSF α-synuclein concentrations in patients presenting with synucleinopathy-type parkinsonism might be useful in stratification of patients in future clinical trials.

FUNDING

American Parkinson Disease Association, Stifterverband für die Deutsche Wissenschaft, Michael J Fox Foundation for Parkinson's Research, National Institutes of Health, Parkinson Research Consortium Ottawa, and the Government of Canada.

Quantification of α-synuclein in cerebrospinal fluid as a biomarker candidate: review of the literature and considerations for future studies

The pursuit of laboratory tests that allow for the reliable and inexpensive identification of subjects with parkinsonism represents a hot topic in translational neuroscience. This unmet need affects the counseling of presymptomatic, at-risk subjects and delays the accurate diagnosis of already symptomatic individuals. The absence of validated markers that are closely linked to the pathological disease process also compromises the objective monitoring of therapeutic interventions in clinical trials. Typical Parkinson’s disease represents a heterogenous syndrome (but the majority of patients suffer from neurodegeneration) that is linked to the misprocessing of α-synuclein (α-Syn). The identification of α-Syn as a bona fide constituent of human cerebrospinal fluid and its quantification in early cross-sectional studies represent the beginning of a new chapter in Parkinson’s disease research. It will determine what role, if any, cerebrospinal fluid α-Syn plays as a biomarker candidate in Lewy inclusion-positive forms of parkinsonism. This article focuses on the progress that has been made in seven recently published papers and highlights the challenges that lie ahead. We also provide specific information regarding standardized operating procedures for cerebrospinal fluid collection in PD biomarker research efforts.