Crying out for a new biomarker

The hunt for a biomarker for Parkinson's has led researchers to investigate a lot of different bodily fluids and techniques! A biomarker is a test that can diagnose Parkinson's, at the moment the only way to diagnose Parkinson's is by using your eyes and your ears. Previously people have tested blood, CSF (the fluid around your brain), skin, saliva, MRI scans, skin samples and even samples of colon. But this pilot study is about a potential location for a biomarker that I had not yet heard of: Tears.

Its well known already that people with Parkinson's have reduced amounts of tears and a lower blink rate. And the researchers point out the the nerves that control the tear gland (lacrimal gland) connect to the brainstem. The brainstem is where a lot of the changes in early Parkinson's take place.

In this study they took 36 people with Parkinson's and 18 healthy people without Parkinson's and collected their tears by using some filter paper to absorb them. They then extracted the proteins from the collected tears.

They found that the Parkinson's participants had a smaller volume of tears but the protein concentration in the tears was about the same as healthy controls. They also identified 21 proteins that people with Parkinson's had significantly higher amounts of and 19 that were significantly reduced in Parkinson's too.

This is only a very small pilot study so we need some further studies in larger groups of patients before we draw any conclusions. But tears are a very attractive biomarker simply because they are so accessible. So this is definitely one to keep in mind and watch out for any further studies about.

Parkinsonism Relat Disord. 2019 Mar 6. pii: S1353-8020(19)30094-X. doi:

Proteomic analysis of tear fluid reveals disease-specific patterns in patients with Parkinson's disease - A pilot study.

Boerger M¹, Funke S², Leha A³, Roser AE⁴, Wuestemann AK⁵, Maass F⁶, Bähr M⁷, Grus F⁸, Lingor P⁹.

Abstract

BACKGROUND:

The diagnosis of Parkinson's disease (PD) is still challenging and biomarkers could contribute to an improved diagnostic accuracy. Tear fluid (TF) is an easily accessible body fluid reflecting pathophysiological changes in systemic and ocular diseases and is already used as a biomarker source for several ophthalmological disorders. Here, we analyzed the TF of patients with PD and controls (CTR) to describe disease-related changes in TF and identify putative biomarkers for the diagnosis of PD.

METHODS:

Unstimulated TF samples of a pilot cohort with 36 PD patients and 18 CTR were collected via Schirmer tear test strips and then analyzed via a Bottom-up liquid chromatography electrospray ionization tandem mass spectrometry (BULCMS) workflow, followed by functional analysis encompassing protein-protein interaction as well as cellular component and pathway analysis.

RESULTS:

BULCMS analysis lead to the identification of 571 tear proteins (false discovery rate, FDR < 1%), whereby 31 proteins were exclusively detected in the PD group and 7 only in the CTR group. Whereas 21 proteins were significantly increased in the PD versus CTR groups, 19 proteins were significantly decreased. Core networks of proteins involved in immune response, lipid metabolism and oxidative stress were distinctly altered in PD patients.

CONCLUSIONS:

To our best knowledge, this is the first description of TF proteome in PD patients. Tear protein level alterations suggest the contribution of different disease-related mechanisms in ocular pathology in PD and propose candidate proteins to be validated as potential biomarkers in larger cohorts.

Why aren't you developing a treatment for Parkinson's Disease???

I gave a presentation to my neurology department on PREDICT-PD this week and, in preparation, my unsuspecting partner was put to use as a test audience. His first comment was - "You keep talking about identifying people for future Parkinson's Disease treatments, why aren't you developing a treatment???"

It's a good question, and this recent article, published in Drug Discovery Today, illuminates the issues around drug-development well. It calls for adopting a more human approach to developing treatments, focussing on human cells, tissues and subjects. Levodopa therapy for Parkinson's, which treats the symptoms but not the process that leads to cell damage, was introduced around 50 years ago. It was the result of investigations into the human brain and observations on the side effects of anti-dopaminergic substances. Since then, there has been very little progress in developing treatments which actually prevent the death of brain cells.

This article suggests that a focus on imperfect animal models has delayed progress - for example animal models often don't show the same side effects that humans do. No animal model has exactly the combination of brain damage and progressive symptoms we see with Parkinson's in humans and so promising results in animals have often not translated into humans. They discuss different therapeutic approaches - for example surgical approaches to repairing cells or DNA including stem cell treatments, gene therapy and peptide therapy, suggesting the need to observe results in human cells and tissues. They go on to discuss the use of computer-based techniques to model the potential interactions between new molecules and human systems as well as the detrimental effects of toxic molecules. Finally, they mention the importance of imaging techniques to monitor disease progression before symptoms develop.

The key to the success of all of these techniques is defining the right group of people to give treatments to, before they develop disease. Whilst the PREDICT-PD study may offer new insights into risk factors that could potentially suggest new therapies, it's main role will be in the selection of this group, in whom the benefits of treatment outweigh the risks. So, in a sense we are developing treatments, by playing a role in the bigger picture.

-Anna

https://www.sciencedirect.com/science/article/pii/S1359644618301442#bib1115

Drug Discov Today. 2018 Sep 18. pii: S1359-6446(18)30144-2. doi: 10.1016/j.drudis.2018.09.010. [Epub ahead of print]

Parkinson's disease research: adopting a more human perspective to accelerate advances.
Marshall LJ, Willett C

Parkinson's disease (PD) affects 1% of the population over 60 years old and, with global increases in the aging population, presents huge economic and societal burdens. The etiology of PD remains unknown; most cases are idiopathic, presumed to result from genetic and environmental risk factors. Despite 200 years since the first description of PD, the mechanisms behind initiation and progression of the characteristic neurodegenerative processes are not known. Here, we review progress and limitations of the multiple PD animal models available and identify advances that could be implemented to better understand pathological processes, improve disease outcome, and reduce dependence on animal models. Lessons learned from reducing animal use in PD research could serve as guideposts for wider biomedical research.

Cerebrospinal fluid NFL in the differential diagnosis of parkinsonian disorders: A meta-analysis.

It is no secret that one of the major unmet needs for Parkinson's research is the development of biomarkers that allow us to measure change in the underlying disease process. As clinicians, we are frequently confronted with a patient that has some features of Parkinson's, but the diagnosis cannot be made definitively and they may in fact have a Parkinson's mimic. Neurofilament light chain (NFL) in spinal fluid has been studied in a variety of neurological diseases and when raised is a marker of nerve cell damage... in this meta-analysis NFL is shown to differentiate between Parkinson's and more aggressive Parkinson's mimics. It may aid accurate diagnosis of Parkinson's in the clinical setting. 

Of course we are interested in identifying who might be at risk of Parkinson's and predicting who might go on to get a diagnosis in years to come. NFL could yet be an important marker of nerve cell damage in such people and build confidence in the prediction process... 

Neurosci Lett. 2018 Jul 20;685:35-41. doi: 10.1016/j.neulet.2018.07.030. [Epub ahead of print]
Ge F, Ding J, Liu Y, Lin H, Chang T.

https://www.sciencedirect.com/science/article/abs/pii/S0304394018305032

Abstract

Neurofilament light chain (NFL) in cerebrospinal fluid (CSF) is a promising biomarker candidate which may discriminate atypical parkinsonian disorders (APD), mainly including multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBD), from Parkinson's disease (PD). We aim to evaluate the diagnostic accuracy of CSF NFL level as a differentiating biomarker between APD and PD. Databases of PubMed, OVID and Web of Science were searched for studies (published until May 31, 2017) that reported on CSF NFL as a diagnostic biomarker between APD and PD. Eight studies were pooled in this meta-analysis, including 341 PD and 396 APD patients and 388 healthy controls. The pooled sensitivity was 82% (95% CI, 68%-91%) and specificity was 85% (95% CI, 79%-89%) in differentiating APD from PD. The pooled positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratio (DOR) were 5.4 (95% CI, 3.6%-8.1%), 0.21 (95% CI, 0.11%-0.40%), and 25 (95% CI, 9%-69%) respectively; and the area under the curve (AUC) was 0.89 (95% CI, 0.86%-0.91%). Subgroup analysis revealed sensitivity and specificity were significantly influenced by study design. The APD subtypes, disease duration and severity were the main heterogeneity sources in specificity. The results of Deeks' test revealed a low risk of publication bias. The CSF NFL level may be used as a biomarker in discriminating APD from PD with high diagnostic accuracy at an early stage of disease. Large and longitudinal studies are still needed on individuals who are suspected to have APD.