Keep it simple..

Predictive medicine is becoming increasingly complex, with predictive models which incorporate both clinical information and a huge range of biomarkers. Biomarkers commonly used in neurodegenerative disease include molecules in bodily fluids such as saliva, blood and spinal fluid and genetic data from these sources, scans for both structural aspects of the brain and molecular studies which can quantify the amount of protein build up in the brain. These biomarkers vary in how invasive and risky they are to collect and while they may help us understand the disease process, many people are uncomfortable with going through an invasive procedure such as lumbar puncture. 

The basis of the current PREDICT-PD model is to use participant survey to collect clinical information to predict risk. The study below, from a team in Quebec, also uses a clinical approach. They looked at a group of people with Parkinsons' disease and used an 8 item scoring scale including age, evidence of cognitive impairment at baseline, motor features such as freezing or falls, drop in blood pressure on standing and features of rapid eye movement sleep behaviour disorder. 

Interestingly, the predictive value of this model seems to be as good as studies which include biomarker values such as amyloid protein levels in the spinal fluid. Biomarker studies in this area will continue to be important, especially as they hold the hope of elucidating the molecular processes which can be interrupted to disrupt the progression of disease. But this is a good reminder of the power that can be harnessed from information which is available simply by asking questions of and examining our patients. 

-Anna

https://www.ncbi.nlm.nih.gov/pubmed/29582054

Office-Based Screening for Dementia in Parkinson Disease: The Montreal Parkinson Risk of Dementia Scale in 4 Longitudinal Cohorts.

IMPORTANCE:
Parkinson disease dementia dramatically increases mortality rates, patient expenditures, hospitalization risk, and caregiver burden. Currently, predicting Parkinson disease dementia risk is difficult, particularly in an office-based setting, without extensive biomarker testing.

OBJECTIVE:
To appraise the predictive validity of the Montreal Parkinson Risk of Dementia Scale, an office-based screening tool consisting of 8 items that are simply assessed.

DESIGN, SETTING, AND PARTICIPANTS:
This multicenter study (Montreal, Canada; Tottori, Japan; and Parkinson Progression Markers Initiative sites) used 4 diverse Parkinson disease cohorts with a prospective 4.4-year follow-up. A total of 717 patients with Parkinson disease were recruited between May 2005 and June 2016. Of these, 607 were dementia-free at baseline and followed-up for 1 year or more and so were included. The association of individual baseline scale variables with eventual dementia risk was calculated. Participants were then randomly split into cohorts to investigate weighting and determine the scale's optimal cutoff point. Receiver operating characteristic curves were calculated and correlations with selected biomarkers were investigated.

MAIN OUTCOMES AND MEASURES:
Dementia, as defined by Movement Disorder Society level I criteria.

RESULTS:
Of the 607 patients (mean [SD] age, 63.4 [10.1]; 376 men [62%]), 70 (11.5%) converted to dementia. All 8 items of the Montreal Parkinson Risk of Dementia Scale independently predicted dementia development at the 5% significance level. The annual conversion rate to dementia in the high-risk group (score, >5) was 14.9% compared with 5.8% in the intermediate group (score, 4-5) and 0.6% in the low-risk group (score, 0-3). The weighting procedure conferred no significant advantage. Overall predictive validity by the area under the receiver operating characteristic curve was 0.877 (95% CI, 0.829-0.924) across all cohorts. A cutoff of 4 or greater yielded a sensitivity of 77.1% (95% CI, 65.6-86.3) and a specificity of 87.2% (95% CI, 84.1-89.9), with a positive predictive value (as of 4.4 years) of 43.90% (95% CI, 37.76-50.24) and a negative predictive value of 96.70% (95% CI, 95.01-97.85). Positive and negative likelihood ratios were 5.94 (95% CI, 4.08-8.65) and 0.26 (95% CI, 0.17-0.40), respectively. Scale results correlated with markers of Alzheimer pathology and neuropsychological test results.

CONCLUSIONS AND RELEVANCE:
Despite its simplicity, the Montreal Parkinson Risk of Dementia Scale demonstrated predictive validity equal or greater to previously described algorithms using biomarker assessments. Future studies using head-to-head comparisons or refinement of weighting would be of interest.

The Parkinson's Phenome: Traits Associated with Parkinson's Disease in a Large and Deeply Phenotyped Cohort

This is one of the first collaborative endeavours between Karl Heilbron (23andMe) and I... and I hope one of many. I have to say Karl did the bulk of the leg work and I was grateful for the opportunity to help pull it all together...

These data from 23andMe offer unparalleled opportunity to explore reported associations with Parkinson's. Using a rigorous pipeline for selecting phenotypic traits (self reported health conditions, dietary preferences, non-motor symptoms etc) we were able to produce an incredibly detailed exploration of the Parkinson's phenome (the sum total of Parkinson's associated traits). One of the fascinating things about the results is that many of the traits are instantly recognisable to those of us that see patients with Parkinson's regularly... this in turn increases our confidence about the novel associations that we observed and which offer further avenue for further research.

Additionally, where possible each trait was tested to if it was associated with disease duration, thereby suggesting that it might be a manifestation of disease rather than a risk factor or prodromal feature. Of course cross-sectional data has limitations when it comes to understanding cause and effect, but for the clinical neurologist seeing patients with PD this report of co-existing symptoms, behaviours and related health conditions could have huge practical use. The plan is to make all analyses available in order to stimulate further research in this area...

- Alastair Noyce

Karl Heilbron, Alastair Noyce, Pierre Fontanillas, Babak Alipanahi, The 23andMe Research Team, Mike Nalls, Paul Cannon

doi: https://doi.org/10.1101/270934

https://www.biorxiv.org/content/early/2018/02/28/270934

Background
Observational studies have begun to characterize the wide spectrum of phenotypes associated with Parkinson's disease (PD), but recruiting large numbers of PD cases and assaying a diversity of phenotypes has often been difficult. Here, we set out to systematically describe the PD phenome using a cross-sectional case-control design in a large database.

Methods
We analyzed the association between PD and 840 phenotypes derived from online surveys. For each phenotype, we ran a logistic regression using an average of 5,141 PD cases and 65,459 age- and sex-matched controls. We selected uncorrelated phenotypes, determined statistical significance after correcting for multiple testing, and systematically assessed the novelty of each significant association. We tested whether significant phenotypes were also associated with disease duration in PD cases.

Findings
PD diagnosis was associated with 149 independent phenotypes. We replicated 32 known associations and discovered 49 associations that have not previously been reported. We found that migraine, obsessive-compulsive disorder, seasonal allergies, and anemia were associated with PD, but were not significantly associated with PD duration, and tend to occur decades before the average age of diagnosis for PD. Further work is needed to determine whether these phenotypes are PD risk factors or whether they share common disease mechanisms.

Interpretation
We used a systematic approach in a single large dataset to assess the spectrum of traits that were associated with PD. Some of these traits may be risk factors for PD, features of the pre-diagnostic phase of disease, or manifestations of PD pathology. The model outputs from all 840 logistic regressions are available to the research community and may be used to generate hypotheses regarding PD etiology.

Funding
The Michael J. Fox Foundation, Parkinson's UK, Barts Charity, National Institute on Aging, and 23andMe, Inc.

Treat the person not the scan

When learning clinical medicine, (junior) doctors can often show an over-reliance on blood tests and scans, rather than focussing on the patient and their holistic care. This can lead in turn to more intensive investigation, which is both costly and incurs extra risk, as well as in turn creating more ‘abnormal results’.

An important report has been published in pre-symptomatic Alzheimer’s this week, in the journal Lancet Neurology. The research team at the Salpêtrière Hospital in Paris studied over 300 older adults with subjective, but no objective, memory complaints. The participants completed detailed neuropsychological and cognitive assessment, structural and functional brain scans (MRI and PET), brain-wave tests (EEG), genetic testing and lumbar punctures. These tests were repeated every 6-12 months for over 2 years. They set out to see if they could identify particular markers that would identify who would develop prodromal Alzheimer’s. They separated their cohort into two groups: one with normal amyloid scans and one with evidence of amyloid build up in the brain. (Amyloid is one of two major abnormal proteins that are thought to cause this form of dementia)

With two years of follow up, only four individuals converted to prodromal Alzheimer’s. All four had some evidence of amyloid build up at the beginning of the study, although with such small numbers it is difficult to say this wasn’t due to chance. All four were also older than most (average age 80.2 years compared to 76.8 years), and ¾ had the genetic variant that confers the highest risk of Alzheimers, APOE-ε4, compared to 33/83 who were tested and didn’t progress. Importantly, evidence of amyloid in the brain did not seem to be a good discriminator for likelihood of progression from ‘the worried well’ to prodromal Alzheimers. In fact, the strongest findings from this study were that CSF and imaging markers of increased amyloid were associated with each other!

What does this mean for Parkinson’s? Firstly, we don’t have an equivalent brain scan, i.e. one that shows build up of α-synuclein with which to predict risk. Secondly, with these complex conditions one marker that doesn’t test the function of the individual will be hard pressed to be hugely predictive. Thirdly, one of the biggest limitations of this study is that the follow up was only 2 years. Given all these individuals had normal memory at the beginning, and most were highly educated, it is perhaps not suprising that so few converted to the prodromal stage.

This figure is worth considering as an alternative model of thinking about the earliest stages of Alzheimer’s and perhaps Parkinson’s

Two hypothetical models of the natural history of Alzheimer's disease

(A) Model 1 illustrates the dominant view of progressive deterioration: in Alzheimer's disease, cognition is progressively impaired from the preclinical phase (characterised by amyloid β deposition followed by tau pathology), to the prodromal clinical stage (with subtle cognitive changes), then the clinical stages of MCI and dementia. (B) Model 2 represents an alternative view of preclinical compensation that we have based on our data for brain β-amyloidosis. Cognition remains stable in the preclinical phase of the disease despite underlying brain lesions, until brain compensatory mechanisms are overwhelmed, leading to clinical disease. MCI=mild cognitive impairment. AD=Alzheimer's disease.

RNR

Cognitive and neuroimaging features and brain β-amyloidosis in individuals at risk of Alzheimer's disease (INSIGHT-preAD): a longitudinal observational study.

Bruno Dubois et al

Lancet Neurology 2018, 17 (4), 335-346

http://www.thelancet.com/journals/laneur/article/PIIS1474-4422(18)30029-2/fulltext?%7B$trackingTag%7D

BACKGROUND:Improved understanding is needed of risk factors and markers of disease progression in preclinical Alzheimer's disease. We assessed associations between brain β-amyloidosis and various cognitive and neuroimaging parameters with progression of cognitive decline in individuals with preclinical Alzheimer's disease.

METHODS:The INSIGHT-preAD is an ongoing single-centre observational study at the Salpêtrière Hospital, Paris, France. Eligible participants were age 70-85 years with subjective memory complaints but unimpaired cognition and memory (Mini-Mental State Examination [MMSE] score ≥27, Clinical Dementia Rating score 0, and Free and Cued Selective Reminding Test [FCSRT] total recall score ≥41). We stratified participants by brain amyloid β deposition on18F-florbetapir PET (positive or negative) at baseline. All patients underwent baseline assessments of demographic, cognitive, and psychobehavioural, characteristics, APOE ε4 allele carrier status, brain structure and function on MRI, brain glucose-metabolism on18F-fluorodeoxyglucose (18F-FDG) PET, and event-related potentials on electroencephalograms (EEGs). Actigraphy and CSF investigations were optional. Participants were followed up with clinical, cognitive, and psychobehavioural assessments every 6 months, neuropsychological assessments, EEG, and actigraphy every 12 months, and MRI, and18F-FDG and18F-florbetapir PET every 24 months. We assessed associations of amyloid β deposition status with test outcomes at baseline and 24 months, and with clinical status at 30 months. Progression to prodromal Alzheimer's disease was defined as an amnestic syndrome of the hippocampal type.

FINDINGS:From May 25, 2013, to Jan 20, 2015, we enrolled 318 participants with a mean age of 76·0 years (SD 3·5). The mean baseline MMSE score was 28·67 (SD 0·96), and the mean level of education was high (score >6 [SD 2] on a scale of 1-8, where 1=infant school and 8=higher education). 88 (28%) of 318 participants showed amyloid β deposition and the remainder did not. The amyloid β subgroups did not differ for any psychobehavioural, cognitive, actigraphy, and structural and functional neuroimaging results after adjustment for age, sex, and level of education More participants positive for amyloid β deposition had the APOE ε4 allele (33 [38%] vs 29 [13%], p<0·0001). Amyloid β1-42concentration in CSF significantly correlated with mean18F-florbetapir uptake at baseline (r=-0·62, p<0·0001) and the ratio of amyloid β1-42to amyloid β1-40(r=-0·61, p<0·0001), and identified amyloid β deposition status with high accuracy (mean area under the curve values 0·89, 95% CI 0·80-0·98 and 0·84, 0·72-0·96, respectively). No difference was seen in MMSE (28·3 [SD 2·0] vs 28·9 [1·2], p=0·16) and Clinical Dementia Rating scores (0·06 [0·2] vs 0·05 [0·3]; p=0·79) at 30 months (n=274) between participants positive or negative for amyloid β. Four participants (all positive for amyloid β deposition at baseline) progressed to prodromal Alzheimer's disease. They were older than other participants positive for amyloid β deposition at baseline (mean 80·2 years [SD 4·1] vs 76·8 years [SD 3·4]) and had greater18F-florbetapir uptake at baseline (mean standard uptake value ratio 1·46 [SD 0·16] vs 1·02 [SD 0·20]), and more were carriers of the APOE ε4 allele (three [75%] of four vs 33 [39%] of 83). They also had mild executive dysfunction at baseline (mean FCSRT free recall score 21·25 [SD 2·75] vs 29·08 [5·44] and Frontal Assessment Battery total score 13·25 [1·50] vs 16·05 [1·68]).

INTERPRETATION:Brain β-amyloidosis alone did not predict progression to prodromal Alzheimer's disease within 30 months. Longer follow-up is needed to establish whether this finding remains consistent.

FUNDING:Institut Hospitalo-Universitaire and Institut du Cerveau et de la Moelle Epinière (IHU-A-ICM), Ministry of Research, Fondation Plan Alzheimer, Pfizer, and Avid.

An overview of sleep and circadian dysfunction in Parkinson's disease

A relationship between Parkinson's disease and sleep has been recognised for many years. Patients with PD suffer from REM sleep behaviour disorder, excessive daytime somnolence, insomnia, reversal of sleep-wake cycle, and some if not all of these can predate the diagnosis of PD.

There is a fascinating literature emerging on the role the circadian rhythm plays in Parkinson's disease. Circadian rhythm not only regulates our body clock but also has a major bearing on our mood, appetite, bowel habit etc. I started thinking a few years ago about whether abnormalities in circadian rhythm could explain much about the pre-diagnostic phase of PD. I wondered whether the structures in the brain that control circadian rhythm were affected early in PD... I later learned from colleagues that they were not. Now I am starting to wonder whether abnormalities in circadian rhythm are not simply an early manifestation of Parkinson's, but instead an actual risk factor for Parkinson's...

Research shows that normal circadian function is important for maintaining normal processes that go on with cells... it is plausible that when circadian rhythm goes awry brain cells stop clearing proteins so effectively and these then start to accumulate... or that mitcohondria in brain cells don't work so effectively when there is disordered circadian rhythm. Some of my recent research looks directly at the nature of the relationship between circadian rhythm and Parkinson's [watch this space!] but for now I agree with the authors of this review... normalising circadian rhythm may be an important therapeutic target for Parkinson's disease...

- Alastair Noyce

J Sleep Res. 2018 Mar 1. doi: 10.1111/jsr.12673. [Epub ahead of print]
Mantovani S, Smith SS, Gordon R, O'Sullivan JD

http://onlinelibrary.wiley.com/doi/10.1111/jsr.12673/abstract;jsessionid=D053C900C0F2B819BB00734F213B98FB.f02t02

Sleep and circadian alterations are amongst the very first symptoms experienced in Parkinson's disease, and sleep alterations are present in the majority of patients with overt clinical manifestation of Parkinson's disease. However, the magnitude of sleep and circadian dysfunction in Parkinson's disease, and its influence on the pathophysiology of Parkinson's disease remains often unclear and a matter of debate. In particular, the confounding influences of dopaminergic therapy on sleep and circadian dysfunction are a major challenge, and need to be more carefully addressed in clinical studies. The scope of this narrative review is to summarise the current knowledge around both sleep and circadian alterations in Parkinson's disease. We provide an overview on the frequency of excessive daytime sleepiness, insomnia, restless legs, obstructive apnea and nocturia in Parkinson's disease, as well as addressing sleep structure, rapid eye movement sleep behaviour disorder and circadian features in Parkinson's disease. Sleep and circadian disorders have been linked to pathological conditions that are often co-morbid in Parkinson's disease, including cognitive decline, memory impairment and neurodegeneration. Therefore, targeting sleep and circadian alterations could be one of the earliest and most promising opportunities to slow disease progression. We hope that this review will contribute to advance the discussion and inform new research efforts to progress our knowledge in this field.

Seeing is believing

People with Parkinson's often have subtle cognitive changes and a particular area of difficulty is in visuo-perceptual problems. Patients commonly report visual hallucinations - from very subtle "passage hallucinations" - the sense that there is some movement in the periphery of vision to more complex "formed" hallucinations of animals and people. It is now clear that the visual problems affect all aspects of the visual pathway, from the retina to higher processing areas in the brain. 

This understanding underpins the work presented here by one of our collaborators, Dr Rimona Weil. She has developed online visual tasks which are sensitive to some of these issues. Her 6 tests covered different aspects of visual processing; the test for object invariance, the ability to detect an image despite distortion is shown in the image below. Also tested were peripheral vision, the ability to detect hidden images, to detect biological motion, relative sizes of shapes and mental rotation. 

Image from the Cats-and-Dogs Test, which assesses object invariance. From https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5765443/

Interestingly, not all the tests differentiated Parkinson's patients from healthy participants. The distorted image was particularly sensitive to detect differences between groups but the results from mental rotation and subjective size perception were similar. 

The importance of these findings - that a short online test performed remotely can detect differences between Parkinson's patients and healthy older people - opens up many possibilities. These kinds of tools are likely to find a role in remote monitoring of patients, especially those who find it difficult to attend clinic. Here at PREDICT-PD we are interested in using these tests for screening and will be working with Dr Weil to find out whether any of the changes in visual processing are present before diagnosis of Parkinson's. 

-Anna


https://www.ncbi.nlm.nih.gov/pubmed/29473691

Assessing cognitive dysfunction in Parkinson's disease: An online tool to detect visuo-perceptual deficits.

Weil RS, Schwarzkopf DS, Bahrami B, Fleming SM, Jackson BM, Goch TJC, Saygin AP, Miller LE, Pappa K, Pavisic I, Schade RN, Noyce AJ, Crutch SJ, O'Keeffe AG, Schrag AE, Morris HR

BACKGROUND:
People with Parkinson's disease (PD) who develop visuo-perceptual deficits are at higher risk of dementia, but we lack tests that detect subtle visuo-perceptual deficits and can be performed by untrained personnel. Hallucinations are associated with cognitive impairment and typically involve perception of complex objects. Changes in object perception may therefore be a sensitive marker of visuo-perceptual deficits in PD.

OBJECTIVE:
We developed an online platform to test visuo-perceptual function. We hypothesised that (1) visuo-perceptual deficits in PD could be detected using online tests, (2) object perception would be preferentially affected, and (3) these deficits would be caused by changes in perception rather than response bias.

METHODS:
We assessed 91 people with PD and 275 controls. Performance was compared using classical frequentist statistics. We then fitted a hierarchical Bayesian signal detection theory model to a subset of tasks.

RESULTS:
People with PD were worse than controls at object recognition, showing no deficits in other visuo-perceptual tests. Specifically, they were worse at identifying skewed images (P < .0001); at detecting hidden objects (P = .0039); at identifying objects in peripheral vision (P < .0001); and at detecting biological motion (P = .0065). In contrast, people with PD were not worse at mental rotation or subjective size perception. Using signal detection modelling, we found this effect was driven by change in perceptual sensitivity rather than response bias.

CONCLUSIONS:
Online tests can detect visuo-perceptual deficits in people with PD, with object recognition particularly affected. Ultimately, visuo-perceptual tests may be developed to identify at-risk patients for clinical trials to slow PD dementia. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.