Precision Medicine in Parkinson's Disease - Exploring Patient-Initiated Self-Tracking

Balancing feeling 'prepared' without feeling 'devoured': A qualitative study of self-care from the perspective of self-empowered persons living with Parkinson's disease in Sweden

INTRODUCTION

Parkinson's Disease (PD) is a complex neurodegenerative disease resulting in a wide range of motor and nonmotor symptoms for which the treatment regimen is often complex. People with Parkinson's (PwP) spend time daily on self-care practices including self-tracking signs and symptoms or seeking disease-specific knowledge. Research suggests self-care interventions yield promising care and health outputs for PwP, yet most research focuses on the provider perspective rather than that of those conducting the self-care. This study explores the meaning of self-care, disease-specific knowledge, and self-tracking from the perspective of PwP in Sweden.

METHODS

Qualitative data from three data sets were analyzed and compared using qualitative content analysis: one focus group on self-care (n = 14), one free-text survey on disease-specific knowledge (n = 197) and one free-text survey on self-tracking (n = 33).

FINDINGS

The analysis resulted in three categories: illness-related tasks, internal resources and external resources. Illness-related tasks describe various tasks PwP carry out in self-care, including lifestyle choices, treatments, and self-tracking. Internal resources include personal knowledge/skills as well as mindsets which could facilitate or challenge completing these tasks. Finally, external resources include other PwP, literature, clinicians and other sources of disease-specific knowledge. Self-care was found to fluctuate between beneficial and burdensome depending on such resources.

CONCLUSIONS

In conclusion, self-care needs to be acknowledged and discussed more often in PD and other complex conditions. Future self-care interventions should consider self-tracking and disease-specific knowledge as well as internal and external resources in their design and implementation.

PATIENT OR PUBLIC CONTRIBUTION

A researcher with PD was actively involved in all phases of the research: study design, data collection and analysis, and preparing the manuscript.

A meta-analysis identifies factors predicting the future development of freezing of gait in Parkinson's disease

Freezing of gait (FOG) is a debilitating problem that is common among many, but not all, people with Parkinson's disease (PD). Numerous attempts have been made at treating FOG to reduce its negative impact on fall risk, functional independence, and health-related quality of life. However, optimal treatment remains elusive. Observational studies have recently investigated factors that differ among patients with PD who later develop FOG, compared to those who do not. With prediction and prevention in mind, we conducted a systematic review and meta-analysis of publications through 31.12.2022 to identify risk factors. Studies were included if they used a cohort design, included patients with PD without FOG at baseline, data on possible FOG predictors were measured at baseline, and incident FOG was assessed at follow-up. 1068 original papers were identified, 38 met a-priori criteria, and 35 studies were included in the meta-analysis (n = 8973; mean follow-up: 4.1 ± 2.7 years). Factors significantly associated with a risk of incident FOG included: higher age at onset of PD, greater severity of motor symptoms, depression, anxiety, poorer cognitive status, and use of levodopa and COMT inhibitors. Most results were robust in four subgroup analyses. These findings indicate that changes associated with FOG incidence can be detected in a subset of patients with PD, sometimes as long as 12 years before FOG manifests, supporting the possibility of predicting FOG incidence. Intriguingly, some of these factors may be modifiable, suggesting that steps can be taken to lower the risk and possibly even prevent the future development of FOG.

Targeting immunoproteasome in neurodegeneration: A glance to the future

The immunoproteasome is a specialized form of proteasome equipped with modified catalytic subunits that was initially discovered to play a pivotal role in MHC class I antigen processing and immune system modulation. However, over the last years, this proteolytic complex has been uncovered to serve additional functions unrelated to antigen presentation. Accordingly, it has been proposed that immunoproteasome synergizes with canonical proteasome in different cell types of the nervous system, regulating neurotransmission, metabolic pathways and adaptation of the cells to redox or inflammatory insults. Hence, studying the alterations of immunoproteasome expression and activity is gaining research interest to define the dynamics of neuroinflammation as well as the early and late molecular events that are likely involved in the pathogenesis of a variety of neurological disorders. Furthermore, these novel functions foster the perspective of immunoproteasome as a potential therapeutic target for neurodegeneration. In this review, we provide a brain and retina-wide overview, trying to correlate present knowledge on structure-function relationships of immunoproteasome with the variety of observed neuro-modulatory functions.

Community Exercise: A New Tool for Personalized Parkinson’s Care or Just an Addition to Formal Care?

Physiotherapy and exercise are associated with motor and non-motor benefits in Parkinson’s disease (PD). Community exercise programs may increase ongoing exercise participation and help people with Parkinson’s disease actively participate in their health management. But there is still limited knowledge about these programs regarding their benefits, safety, implications over the long-term, and effective implementation. These questions could hold relevant clinical implications. In this perspective article, we identify the current challenges and reflect upon potential solutions to help community exercise to be implemented as an additional anchor to personalize management models for Parkinson’s disease.

Redefining the hypotheses driving Parkinson's diseases research

Parkinson’s disease (PD) research has largely focused on the disease as a single entity centred on the development of neuronal pathology within the central nervous system. However, there is growing recognition that PD is not a single entity but instead reflects multiple diseases, in which different combinations of environmental, genetic and potential comorbid factors interact to direct individual disease trajectories. Moreover, an increasing body of recent research implicates peripheral tissues and non-neuronal cell types in the development of PD. These observations are consistent with the hypothesis that the initial causative changes for PD development need not occur in the central nervous system. Here, we discuss how the use of neuronal pathology as a shared, qualitative phenotype minimises insights into the possibility of multiple origins and aetiologies of PD. Furthermore, we discuss how considering PD as a single entity potentially impairs our understanding of the causative molecular mechanisms, approaches for patient stratification, identification of biomarkers, and the development of therapeutic approaches to PD. The clear consequence of there being distinct diseases that collectively form PD, is that there is no single biomarker or treatment for PD development or progression. We propose that diagnosis should shift away from the clinical definitions, towards biologically defined diseases that collectively form PD, to enable informative patient stratification. N-of-one type, clinical designs offer an unbiased, and agnostic approach to re-defining PD in terms of a group of many individual diseases.

A Hybrid Machine Learning and Network Analysis Approach Reveals Two Parkinson's Disease Subtypes from 115 RNA-Seq Post-Mortem Brain Samples

Precision medicine emphasizes fine-grained diagnostics, taking individual variability into account to enhance treatment effectiveness. Parkinson’s disease (PD) heterogeneity among individuals proves the existence of disease subtypes, so subgrouping patients is vital for better understanding disease mechanisms and designing precise treatment. The purpose of this study was to identify PD subtypes using RNA-Seq data in a combined pipeline including unsupervised machine learning, bioinformatics, and network analysis. Two hundred and ten post mortem brain RNA-Seq samples from PD (n = 115) and normal controls (NCs, n = 95) were obtained with systematic data retrieval following PRISMA statements and a fully data-driven clustering pipeline was performed to identify PD subtypes. Bioinformatics and network analyses were performed to characterize the disease mechanisms of the identified PD subtypes and to identify target genes for drug repurposing. Two PD clusters were identified and 42 DEGs were found (p adjusted ≤ 0.01). PD clusters had significantly different gene network structures (p < 0.0001) and phenotype-specific disease mechanisms, highlighting the differential involvement of the Wnt/β-catenin pathway regulating adult neurogenesis. NEUROD1 was identified as a key regulator of gene networks and ISX9 and PD98059 were identified as NEUROD1-interacting compounds with disease-modifying potential, reducing the effects of dopaminergic neurodegeneration. This hybrid data analysis approach could enable precision medicine applications by providing insights for the identification and characterization of pathological subtypes. This workflow has proven useful on PD brain RNA-Seq, but its application to other neurodegenerative diseases is encouraged.

Ethical Aspects of Personal Science for Persons with Parkinson's Disease: What Happens When Self-Tracking Goes from Selfcare to Publication?

Using Parkinson's disease as an exemplary chronic condition, this Commentary discusses ethical aspects of using self-tracking for personal science, as compared to using self-tracking in the context of conducting clinical research on groups of study participants. Conventional group-based clinical research aims to find generalisable answers to clinical or public health questions. The aim of personal science is different: to find meaningful answers that matter first and foremost to an individual with a particular health challenge. In the case of personal science, the researcher and the participant are one and the same, which means that specific ethical issues may arise, such as the need to protect the participant against self-harm. To allow patient-led research in the form of personal science in the Parkinson field to evolve further, the development of a specific ethical framework for self-tracking for personal science is needed.

A Long Way to Go: Patient Perspectives on Digital Health for Parkinson's Disease

Digital health promises to improve healthcare, health, and wellness through the use of digital technologies. The purpose of this commentary is to review and discuss the field of digital health for Parkinson’s disease (PD) focusing on the needs, expectations, and wishes of people with PD (PwP). Our analysis shows that PwP want to use digital technologies to actively manage the full complexity of living with PD on an individual level, including the unpredictability and variability of the condition. Current digital health projects focusing on PD, however, does not live up to the expectations of PwP. We conclude that for digital health to reach its full potential, the right of PwP to access their own data needs to be recognised, PwP should routinely receive personalised feedback based on their data, and active involvement of PwP as an equal partner in digital health development needs to be the norm.

A qualitative exploration of the healthcare challenges and pharmaceutical care needs of people with Parkinson's and their caregivers

Background People with Parkinson’s are at higher risk of healthcare and pharmaceutical care issues. Objective To determine the healthcare challenges, pharmaceutical care needs, and perceived need of a pharmacist-run clinic by people with Parkinson’s and their caregivers. Setting Malaysian Parkinson’s Disease Association. Method A focus group discussion adopting a descriptive qualitative approach was conducted involving people with Parkinson’s and their caregivers. A semi-structured interview guide was used to determine the challenges they faced with their medications and healthcare system, their pharmaceutical care needs, and their views on a pharmacist-run clinic. Data was thematically analysed. Main outcome measure: Healthcare challenges faced by people with Parkinson’s and caregivers along with their pharmaceutical care needs and perceived need of a pharmacist-run clinic. Results Nine people with Parkinson’s and four caregivers participated. Six themes were developed: (1) “It’s very personalised”: the need for self-experimentation, (2) “Managing it is quite difficult”: challenges with medication, (3) “The doctor has no time for you”: challenges with healthcare providers, (4) “Nobody can do it except me”: challenges faced by caregivers, (5) “It becomes a burden”: impact on quality of life, and (6) “Lack of consistency could be counterproductive”: views on pharmacist-run clinic. Conclusion The provision of pharmaceutical care services by pharmacists could help overcome issues people with Parkinson’s face, however there is a need for them to first see pharmacists in their expanded roles and change their limited perception of pharmacists. This can be achieved through integration of pharmacists within multidisciplinary teams in specialist clinics which they frequent.

Parkinson's disease

Parkinson's disease is a recognisable clinical syndrome with a range of causes and clinical presentations. Parkinson's disease represents a fast-growing neurodegenerative condition; the rising prevalence worldwide resembles the many characteristics typically observed during a pandemic, except for an infectious cause. In most populations, 3-5% of Parkinson's disease is explained by genetic causes linked to known Parkinson's disease genes, thus representing monogenic Parkinson's disease, whereas 90 genetic risk variants collectively explain 16-36% of the heritable risk of non-monogenic Parkinson's disease. Additional causal associations include having a relative with Parkinson's disease or tremor, constipation, and being a non-smoker, each at least doubling the risk of Parkinson's disease. The diagnosis is clinically based; ancillary testing is reserved for people with an atypical presentation. Current criteria define Parkinson's disease as the presence of bradykinesia combined with either rest tremor, rigidity, or both. However, the clinical presentation is multifaceted and includes many non-motor symptoms. Prognostic counselling is guided by awareness of disease subtypes. Clinically manifest Parkinson's disease is preceded by a potentially long prodromal period. Presently, establishment of prodromal symptoms has no clinical implications other than symptom suppression, although recognition of prodromal parkinsonism will probably have consequences when disease-modifying treatments become available. Treatment goals vary from person to person, emphasising the need for personalised management. There is no reason to postpone symptomatic treatment in people developing disability due to Parkinson's disease. Levodopa is the most common medication used as first-line therapy. Optimal management should start at diagnosis and requires a multidisciplinary team approach, including a growing repertoire of non-pharmacological interventions. At present, no therapy can slow down or arrest the progression of Parkinson's disease, but informed by new insights in genetic causes and mechanisms of neuronal death, several promising strategies are being tested for disease-modifying potential. With the perspective of people with Parkinson's disease as a so-called red thread throughout this Seminar, we will show how personalised management of Parkinson's disease can be optimised.

Digital Technology in Movement Disorders: Updates, Applications, and Challenges

Purpose of Review

Digital technology affords the opportunity to provide objective, frequent, and sensitive assessment of disease outside of the clinic environment. This article reviews recent literature on the application of digital technology in movement disorders, with a focus on Parkinson’s disease (PD) and Huntington’s disease.

Recent Findings

Recent research has demonstrated the ability for digital technology to discriminate between individuals with and without PD, identify those at high risk for PD, quantify specific motor features, predict clinical events in PD, inform clinical management, and generate novel insights.

Summary

Digital technology has enormous potential to transform clinical research and care in movement disorders. However, more work is needed to better validate existing digital measures, including in new populations, and to develop new more holistic digital measures that move beyond motor features.

Precision medicine in the care of rheumatoid arthritis: Focus on prediction and prevention of future clinically-apparent disease

There is an emerging understanding that an individual's risk for future rheumatoid arthritis (RA) can be determined using a combination of factors while they are still in a state where clinically-apparent inflammatory arthritis (IA) is not yet present. Indeed, this concept has underpinned several completed and ongoing prevention trials in RA. Importantly, risk factors can be divided into modifiable (e.g. smoking, exercise, dental care and diet) and non-modifiable factors (e.g. genetics, sex, age). In addition, there are now several biomarkers including autoantibodies, inflammatory markers and imaging techniques that are highly predictive of future clinically-apparent IA/RA. Although none of the prevention studies have yet provided major breakthroughs, several of them have provided valuable insights that can help to improve the design of future clinical trials and enable RA prevention. In aggregate, these findings suggest that the most accurate disease prediction models will require the combination of demographic and clinical information, biomarkers and potentially medical imaging data to identify individuals for intervention. This review summarizes some of the key aspects around precision medicine in RA with special focus on disease prediction and prevention.

Deep Phenotyping of Parkinson's Disease

Phenotype is the set of observable traits of an organism or condition. While advances in genetics, imaging, and molecular biology have improved our understanding of the underlying biology of Parkinson's disease (PD), clinical phenotyping of PD still relies primarily on history and physical examination. These subjective, episodic, categorical assessments are valuable for diagnosis and care but have left gaps in our understanding of the PD phenotype. Sensors can provide objective, continuous, real-world data about the PD clinical phenotype, increase our knowledge of its pathology, enhance evaluation of therapies, and ultimately, improve patient care. In this paper, we explore the concept of deep phenotyping-the comprehensive assessment of a condition using multiple clinical, biological, genetic, imaging, and sensor-based tools-for PD. We discuss the rationale for, outline current approaches to, identify benefits and limitations of, and consider future directions for deep clinical phenotyping.

"You have to know why you're doing this": a mixed methods study of the benefits and burdens of self-tracking in Parkinson's disease

Background

This study explores opinions and experiences of people with Parkinson’s disease (PwP) in Sweden of using self-tracking. Parkinson’s disease (PD) is a neurodegenerative condition entailing varied and changing symptoms and side effects that can be a challenge to manage optimally. Patients’ self-tracking has demonstrated potential in other diseases, but we know little about PD self-tracking. The aim of this study was therefore to explore the opinions and experiences of PwP in Sweden of using self-tracking for PD.

Method

A mixed methods approach was used, combining qualitative data from seven interviews with quantitative data from a survey to formulate a model for self-tracking in PD. In total 280 PwP responded to the survey, 64% (n = 180) of which had experience from self-tracking.

Result

We propose a model for self-tracking in PD which share distinctive characteristics with the Plan-Do-Study-Act (PDSA) cycle for healthcare improvement. PwP think that tracking takes a lot of work and the right individual balance between burdens and benefits needs to be found. Some strategies have here been identified; to focus on positive aspects rather than negative, to find better solutions for their selfcare, and to increase the benefits through improved tools and increased use of self-tracking results in the dialogue with healthcare.

Conclusion

The main identified benefits are that self-tracking gives PwP a deeper understanding of their own specific manifestations of PD and contributes to a more effective decision making regarding their own selfcare. The process of self-tracking also enables PwP to be more active in communicating with healthcare. Tracking takes a lot of work and there is a need to find the right balance between burdens and benefits.

Electronic supplementary material

The online version of this article (10.1186/s12911-019-0896-7) contains supplementary material, which is available to authorized users.

Patient, study thyself

The past 15 years have seen the emergence of a new paradigm in medical research, namely of people living with medical conditions (whether patients, parents, or caregivers) using digital tools to conduct N-of-1 trials and scientifically grounded research on themselves, whilst using the Internet to form communities of like-minded individuals willing to self-experiment. Prominent examples can be found in amyotrophic lateral sclerosis/motor neurone disease (the 'lithium study' on PatientsLikeMe), Parkinson's disease ('digital patient' Sara Riggare), and diabetes (the 'open artificial pancreas' of the #WeAreNotWaiting movement). Through transparency, data sharing, open source code, and publication in the peer-reviewed scientific literature, such activities conform to expected scientific conventions. However, other conventions, such as ethical oversight, regulation, professionalization, and the ability to translate this new form of relatively biased data into generalizable decisions, remain challenged. While critics worry such participant-led research merely muddies the waters of high-quality medical research and exposes patients to new harms, the potential is there to enroll millions of active minds in unravelling the wicked problems of complex medical disorders that degrade the human health span.