Plasma proteomics identify biomarkers predicting Parkinson’s disease up to 7 years before symptom onset

Your doctor should be using this test on you because of your risk of Parkinsons post stroke.

Parkinson’s Disease May Have Link to Stroke March 2017

Your doctor is then required to have EXACT PROTOCOLS that prevent Parkinsons.  Your doctor has no excuses for not having EXACT PARKINSONS PREVENTION PROTOCOLS! 7 years is plenty of time for competent doctors to come up with those protocols, especially since thousands of doctors need those protocols! But since there is NO leadership in stroke, NOTHING ever gets done!

Plasma proteomics identify biomarkers predicting Parkinson’s disease up to 7 years before symptom onset

• Jenny Hällqvist,
• Michael Bartl,
• Mohammed Dakna,
• Sebastian Schade,
• Paolo Garagnani,
• Maria-Giulia Bacalini,
• Chiara Pirazzini,
• Kailash Bhatia,
• Sebastian Schreglmann,
• Mary Xylaki,
• Sandrina Weber,
• Marielle Ernst,
• Maria-Lucia Muntean,
• Friederike Sixel-Döring,
• Claudio Franceschi,
• Ivan Doykov,
• Justyna Śpiewak,
• Héloїse Vinette,
• Claudia Trenkwalder,
• Wendy E. Heywood,
• Kevin Mills &
• Brit Mollenhauer 

Nature Communications volume 15, Article number: 4759 (2024) Cite this article

Abstract

Parkinson’s disease is increasingly prevalent. It progresses from the pre-motor stage (characterised by non-motor symptoms like REM sleep behaviour disorder), to the disabling motor stage. We need objective biomarkers for early/pre-motor disease stages to be able to intervene and slow the underlying neurodegenerative process. Here, we validate a targeted multiplexed mass spectrometry assay for blood samples from recently diagnosed motor Parkinson’s patients (n = 99), pre-motor individuals with isolated REM sleep behaviour disorder (two cohorts: n = 18 and n = 54 longitudinally), and healthy controls (n = 36). Our machine-learning model accurately identifies all Parkinson patients and classifies 79% of the pre-motor individuals up to 7 years before motor onset by analysing the expression of eight proteins—Granulin precursor, Mannan-binding-lectin-serine-peptidase-2, Endoplasmatic-reticulum-chaperone-BiP, Prostaglaindin-H2-D-isomaerase, Interceullular-adhesion-molecule-1, Complement C3, Dickkopf-WNT-signalling pathway-inhibitor-3, and Plasma-protease-C1-inhibitor. Many of these biomarkers correlate with symptom severity. This specific blood panel indicates molecular events in early stages and could help identify at-risk participants for clinical trials aimed at slowing/preventing motor Parkinson’s disease.

Introduction

Parkinson’s disease (PD) is a complex and increasingly prevalent neurodegenerative disease of the central nervous system (CNS). It is clinically characterised by progressive motor and non-motor symptoms that are caused by α-synuclein aggregation predominantly in dopaminergic cells, which leads to Lewy body (LB) formation¹. The failure of neuroprotective strategies in preventing disease progression is due, in part, to the clinical heterogeneity of the disease—it has several phenotypes—and to the lack of objective biomarker readouts². To facilitate the approval of neuroprotective strategies, governing agencies and pharmaceutical companies need regulatory pathways that use objectively measurable markers—potential therapeutical targets as well as state and rate biomarkers—directly associated with PD pathophysiology and clinical phenotypes³.

The recently emerged α-synuclein seed amplification assays (SAA) can identify α-synuclein pathology in vivo and support stratification purposes but still rely on cerebrospinal fluid (CSF) obtained through relatively invasive lumbar punctures⁴. Therefore, this test remains specialised and not readily suitable for large-scale clinical use. As peripheral fluid biomarkers are less invasive and easier to obtain, they could be used in repeated and long-term monitoring, which is necessary for population-based screenings for upcoming neuroprotective trials. While the only emerged serum biomarker in the last years, axonal marker neurofilament light chain (NfL), increases longitudinally and correlates with motor and cognitive PD progression⁵, it is non-specific to the disease process.

Growing data support evidence of PD pathology in the peripheral system, which increases the likelihood of finding a source of matrices for less invasive biomarkers. We know α-synuclein aggregation induces neurodegeneration, which is propagated throughout the CNS. Evidence indicates that additional inflammatory events are an early and potentially initial step in a pathophysiological cascade leading to downstream α-synuclein aggregation that activates the immune system⁶. Inflammatory risk factors in circulating blood (i.e. C-reactive-protein and Interleukin-6 and α-synuclein-specific T-cells) are associated with motor deterioration and cognitive decline in PD^7,8. These inflammatory blood markers can even be identified in plasma/serum samples of individuals with isolated REM sleep behaviour disorder (iRBD), the early stage of a neuronal synuclein disease (NSD), and the most specific predictor for PD and dementia with Lewy bodies (DLB)⁶. NSD was recently proposed as a biologically defined term, for a spectrum of clinical syndromes, including iRBD, PD and DLB, that follow an integrated clinical staging system of progressing neuronal α-synuclein pathology (NSD-ISS)⁹.

In this study, we used mass spectrometry-based proteomic phenotyping to identify a panel of blood biomarkers in early PD. In the initial discovery stage, we analysed samples from a well-characterised cohort of de novo PD patients and healthy controls (HC) who had been subjected to rigorous collection protocols¹⁰. Using unbiased state-of-the-art mass spectrometry, we identified putatively involved proteins, suggesting an early inflammatory profile in plasma. We thereafter moved on to the validation phase by creating a high-throughput and targeted proteomic assay that was applied to samples from an independent replication cohort, consisting of de novo PD, HC and iRBD patients. Finally, after refining the targeted proteomic panel to include a multiplex of only the biomarkers which were reliably measured, an independent analysis was performed on a larger and independent cohort of longitudinal, high-risk subjects who had been confirmed as iRBD by state-of-the-art video-recorded polysomnography (vPSG), including follow-up sampling of up to 7 years.

In summary, using a panel of eight blood biomarkers identified in a machine-learning approach, we were able to differentiate between PD and HC with a specificity of 100%, and to identify 79% of the iRBD subjects, up to 7 years before the development of either DLB or motor PD (NSD stage 3). Our identified panel of biomarkers significantly advances NSD research by providing potential screening and detection markers for use in the earliest stages of NSD for subject identification/stratification for the upcoming prevention trials.

Results

Proteomic discovery phase 0

We performed a bottom-up proteomics analysis of plasma, which had been depleted of the major blood proteins, using two-dimensional in-line liquid chromatography fractionation into ten fractions and label-free mass spectrometric analysis by QTOF MS^E. The discovery cohort consisted of ten randomly selected drug-naïve patients with PD and ten matched HC from the de novo Parkinson’s disease (DeNoPa¹⁰) cohort (details can be found in Supplementary Table 1). This analysis identified 1238 proteins when restricting identification to originate from at least one peptide per protein and at least two fragments per peptide. After excluding proteins with less than two unique peptides or with an identification score below a set threshold (see method section below), 895 distinct proteins remained. Of these proteins, 47 were differentially expressed between the de novo PD and control groups on a nominal significance level of 95%. Pathway analysis suggested enrichment in several inflammatory pathways. Workflow and Results are shown in Fig. 1, and 2 Supplementary Figs. 1, 2.

Fig. 1: All-over workflow of the study.

The study included three phases. Phase 0 consisted of discovery proteomics by untargeted mass spectrometry to identify putative biomarkers, followed by phase I in which targets from the discovery phase were transferred to a targeted, mass spectrometric MRM method and applied to a new and larger cohort of samples, and finally phase II in which the targeted MRM method was refined and a larger number of samples were analysed to evaluate the clinical feasibility of the targeted protein panel.

Full size image

Fig. 2: Discovery phase in plasma samples of de novo PD (n = 10) and healthy controls (n = 10) represented by a Volcano plot showing the protein expression differences between PD and controls (phase 0).

The circle radii in the Volcano plot represent the identification certainty, where large radii represent proteins identified by at least two unique peptides and an identification score >15, smaller radii are given for proteins identified by two or more unique peptides or a confidence score >15. The horizontal axis shows log₂ of the average fold-change and the vertical axis shows −log₁₀ of the p values. The significantly different proteins are annotated by gene name and coloured in pink, while the non-significant proteins are coloured in grey. GO annotations for the significant proteins are shown, the dashed line represents p = 0.05. Disease and function annotations from IPA are shown, divided into annotations with a positive or negative activation score. Source data are provided as a Source Data file.

 

 More at link.

Biomarkers Predict Parkinson’s Disease 7 Years Before Symptom Onset

 Your doctor should be using this test on you because of your risk of Parkinsons post stroke.

Parkinson’s Disease May Have Link to Stroke March 2017

Your doctor is then required to have EXACT PROTOCOLS that prevent Parkinsons.  Your doctor has no excuses for not having EXACT PARKINSONS PREVENTION PROTOCOLS! 7 years is plenty of time for competent doctors to come up with those protocols, especially since thousands of doctors need those protocols! But since there is NO leadership in stroke, NOTHING ever gets done!

Biomarkers Predict Parkinson’s Disease 7 Years Before Symptom Onset

A simple blood test that uses artificial intelligence (AI) can predict Parkinson’s disease up to 7 years before the onset of symptoms, according to a study published in Nature Communications.

Currently, people with Parkinson’s disease are treated with dopamine replacement therapy after they have already developed symptoms.

“As new therapies become available to treat Parkinson’s, we need to diagnose patients before they have developed the symptoms,” said Kevin Mills, PhD, University College London, London, United Kingdom. “We cannot regrow our brain cells and therefore we need to protect those that we have.”

For the study, Jenny Hällqvist, PhD, University College London, and colleagues developed a panel of 8 blood-based biomarkers that are typically altered in patients with Parkinson’s disease. They then looked at whether machine learning could use the biomarkers to predict the likelihood that a person would go on to develop Parkinson’s disease. To validate the biomarkers, the researchers used blood samples from patients with recently diagnosed motor Parkinson’s disease (n = 99), pre-motor individuals with isolated rapid eye movement sleep behaviour disorder (2 cohorts: n = 18 and n = 54 longitudinally), and healthy controls (n = 36).

When the machine learning tool analysed the blood of pre-motor individuals, it identified that 79% had the same profile as patients with Parkinson’s disease.

Over 10 years, the AI predictions matched the clinical conversion rate, correctly predicting 16 patients who went on to develop Parkinson’s disease. The biomarkers were able to make this determination up to 7 years before the onset of any symptoms.

“By determining 8 proteins in the blood, we can identify potential patients [with Parkinson’s disease] several years in advance,” said Michael Bartl, PhD, University Medical Center Goettingen, Goettingen, Germany. “This means that drug therapies could potentially be given at an earlier stage, which could possibly slow down disease progression or even prevent it from occurring.”

“We have not only developed a test, but can diagnose the disease based on markers that are directly linked to processes such as inflammation and degradation of non-functional proteins,” he concluded. “These markers represent possible targets for new drug treatments.”

Reference: https://www.nature.com/articles/s41467-024-48961-3

SOURCE: University College London

PET Scans May Predict Parkinson’s Disease, Lewy Body Dementia in At-Risk Individuals

 

With your risk of Parkinsons post stroke, your competent doctor should be ready to apply this on you. Or don't you have a competent doctor?

Parkinson’s Disease May Have Link to Stroke March 2017

The latest here:

PET Scans May Predict Parkinson’s Disease, Lewy Body Dementia in At-Risk Individuals

Positron emission tomography (PET) scans of the heart may identify people who will go on to develop Parkinson’s disease or Lewy body dementia among those at-risk for these diseases, according to a study published in the Journal of Clinical Investigation.

For the study, David S. Goldstein, MD, National Institute

click or scroll down to continue reading the article

article continues here

of Neurological Disorders and Stroke, part of the National Institutes of Health, Bethesda, Maryland, and colleagues conducted 18F-dopamine PET scans of the heart in 34 people with Parkinson’s disease risk factors to gain insight into levels of the neurotransmitter norepinephrine. 

Norepinephrine is derived from dopamine, which is deficient in the brains of people with Parkinson’s disease. Earlier work from Dr. Goldstein demonstrated that people with Lewy body diseases had severe depletion of cardiac norepinephrine, which is normally released by the nerves that supply the heart.

In the current study, at-risk individuals with low 18F-dopamine-derived radioactivity in the heart were highly likely to develop Parkinson’s or Lewy body dementia during long-term follow-up, compared with individuals with the same risk factors but with normal radioactivity. 

The patients in the study had cardiac 18F-dopamine PET scans every 18 months for up to about 7.5 years or until they were diagnosed with the disease. Participants had ≥3 Parkinson’s risk factors, which included a family history of the disease, loss of sense of smell, dream enactment behaviour, and symptoms of orthostatic intolerance.

Of the 9 individuals with low cardiac 18F-dopamine-derived radioactivity at their first scan, 8 were diagnosed later with Parkinson’s or Lewy body dementia. Only 1 of 11 participants with normal initial radioactivity developed a central Lewy body disease. All 9 participants who developed a Lewy body disease had low radioactivity before or at the time of diagnosis.  

The study supports the view that synuclein disorders such as Parkinson’s disease and Lewy body dementia affect the nerves of the autonomic nervous system.

“We think that in many cases of Parkinson’s and dementia with Lewy bodies the disease processes don’t actually begin in the brain,” said Dr. Goldstein. “Through autonomic abnormalities the processes eventually make their way to the brain. The loss of norepinephrine in the heart predicts and precedes the loss of dopamine in the brain in Lewy body diseases.”  

Finding biomarkers that could help detect diseases before symptoms begin is critical for testing early interventions. The visible motor symptoms of Parkinson’s occur only after substantial damage or loss of dopamine-producing neurons in regions of the brain that control movement.

“Once symptoms begin, most of the damage has already been done,” said Dr. Goldstein. “You want to be able to detect the disease early on. If you could salvage the dopamine terminals that are sick but not yet dead, then you might be able to prolong the time before the person shows symptoms.”  

Using the PET scans to identify people with preclinical Lewy body diseases could enable testing of preventative approaches such as lifestyle modifications, dietary supplements, or medications.

Reference: https://www.jci.org/articles/view/172460

SOURCE: National Institutes of Health