Parkinson's Disease Subtyping Using Clinical Features and Biomarkers: Literature Review and Preliminary Study of Subtype Clustering

Automated annotation of disease subtypes

BACKGROUND

Distinguishing diseases into distinct subtypes is crucial for study and effective treatment strategies. The Open Targets Platform (OT) integrates biomedical, genetic, and biochemical datasets to empower disease ontologies, classifications, and potential gene targets. Nevertheless, many disease annotations are incomplete, requiring laborious expert medical input. This challenge is especially pronounced for rare and orphan diseases, where resources are scarce.

METHODS

We present a machine learning approach to identifying diseases with potential subtypes, using the approximately 23,000 diseases documented in OT. We derive novel features for predicting diseases with subtypes using direct evidence. Machine learning models were applied to analyze feature importance and evaluate predictive performance for discovering both known and novel disease subtypes.

RESULTS

Our model achieves a high (89.4%) ROC AUC (Area Under the Receiver Operating Characteristic Curve) in identifying known disease subtypes. We integrated pre-trained deep-learning language models and showed their benefits. Moreover, we identify 515 disease candidates predicted to possess previously unannotated subtypes.

CONCLUSIONS

Our models can partition diseases into distinct subtypes. This methodology enables a robust, scalable approach for improving knowledge-based annotations and a comprehensive assessment of disease ontology tiers. Our candidates are attractive targets for further study and personalized medicine, potentially aiding in the unveiling of new therapeutic indications for sought-after targets.

Correlation between the MNCD classification-based staging of Parkinson's disease and quality of life: a cross-sectional study

Parkinson's disease (PD) is a highly heterogeneous neurodegenerative disorder with varying clinical subtypes. Recently, a novel classification called MNCD (Motor/Non-motor/Cognition/Dependency) has been proposed, which can also include staging based on disease severity. We aim to investigate which staging, the MNCD classification and staging or Hoehn and Yahr (H&Y) staging, exhibits a stronger correlation with the 39-item Parkinson's Disease Questionnaire (PDQ-39). In a cross-sectional study conducted at our single center, 357 PD patients were recruited. Data encompassed scores from various assessments such as the Movement Disorder Society of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Parts I, II, III and IV, Montreal Cognitive Assessment (MoCA), PDQ-39, and the H&Y scale. The mean age of these patients was 66.4 ± 9.1 years old, and the majority (54.6%) were male. MNCD stages: stage 1 (N = 3, 0.8%), stage 2 (N = 62, 17.4%), stage 3 (N = 187, 52.4%), stage 4 (N = 86, 24.1%), and stage 5 (N = 19, 5.3%). The top 5 most frequent PD-related clinical symptoms were sleep disturbances (89.6%), fatigue (69.7%), mild cognitive impairment (68.9%), constipation (65.8%), and postural instability (65.5%). The PDQ-39 demonstrated a positive correlation with both MNCD staging and H&Y staging. Moreover, the MNCD staging exhibited a stronger correlation with PDQ-39 compared to H&Y staging. The correlation between the MNCD classification and staging with the quality of life in PD patients is more statistically significant compared to the H&Y staging.

Exploring Traditional Medicine Diagnostic Classification for Parkinson's Disease Using Hierarchical Clustering

INTRODUCTION

Personalized diagnosis and therapy for Parkinson's disease (PD) are needed due to the clinical heterogeneity of PD. Syndrome differentiation (SD) in traditional medicine (TM) is a diagnostic method for customized therapy that comprehensively analyzes various symptoms and systemic syndromes. However, research identifying PD classification based on SD is limited.

METHODS

Ten electronic databases were systematically searched from inception to August 10, 2021. Clinical indicators, including 380 symptoms, 98 TM signs, and herbal medicine for PD diagnosed with SD, were extracted from 197 articles; frequency statistics on clinical indicators were conducted to classify several subtypes using hierarchical clustering.

RESULTS

Four distinct cluster groups were identified, each characterized by significant cluster-specific clinical indicators with 95% confidence intervals of distribution. Subtype 2 had the most severe progression, longest progressive duration, and highest association with greater late-stage PD-associated motor symptoms, including postural instability and gait disturbance. The action properties of the herbal formula and original SD presented in the data sources for subtype 2 were associated with Yin deficiency syndrome.

DISCUSSION/CONCLUSION

Hierarchical clustering analysis distinguished various symptoms and TM signs among patients with PD. These newly identified PD subtypes may optimize the diagnosis and treatment with TM and facilitate prognosis prediction. Our findings serve as a cornerstone for evidence-based guidelines for TM diagnosis and treatment.

Einleitung

Eine personalisierte Diagnose und Therapie des Morbus Parkinson (MP) ist angesichts der ausgeprägten klinischen Heterogenität des MP unerlässlich. Die Syndromdifferenzierung (SD) ist in der traditionellen Medizin (TM) eine diagnostische Methode für eine maßgeschneiderte Therapie, bei der verschiedene Symptome und systemische Syndrome umfassend analysiert werden. Es liegen jedoch nur begrenzt Forschungsergebnisse in Bezug auf eine SD-basierte Klassifikation des MP vor.

Methoden

Zehn elektronische Datenbanken wurden systematisch durchsucht, von der Einrichtung bis zum 10. August 2021. Klinische Indikatoren einschließlich von 380 Symptomen, 98 TM-Zeichen sowie pflanzlichen Heilmitteln für mittels SD diagnostiziertem MP wurden aus 197 Artikeln extrahiert, und Häufigkeitsstatistiken der klinischen Indikatoren wurden erstellt, um mittels hierarchischem Clustering eine Reihe von Subtypen zu klassifizieren.

Ergebnisse

Vier verschiedene Cluster-Gruppen wurden identifiziert, die jeweils durch signifikante, Cluster-spezifische klinische Indikatoren mit 95% Konfidenzintervall der Verteilung gekennzeichnet waren. Subtyp 2 hatte den schwersten Verlauf, die längste Progressionsdauer und die stärkste Assoziation mit einem höheren Ausmaß von motorischen Symptomen des MP im Spätstadium, darunter Haltungsinstabilität und Gangstörungen. Die Wirkungseigenschaften der pflanzlichen Formulierung sowie die ursprüngliche SD, die in den Datenquellen für Subtyp 2 genannt wurden, waren mit Yin-Mangel-Syndrom assoziiert.

Diskussion/Schlussfolgerung

Die hierarchische Clustering-Analyse hob verschiedene Symptome und TM-Zeichen bei Patienten mit MP hervor. Die neu identifizierten MP-Subtypen könnten die Diagnose und Behandlung mittels TM optimieren und zur Prognoseerstellung beitragen. Unsere Ergebnisse sind ein Fundament für eine evidenzbasierte Leitlinie für die TM-Diagnostik und -Therapie.

Functional neural networks stratify Parkinson's disease patients across the spectrum of cognitive impairment

INTRODUCTION

Cognitive impairment (CI) is a significant non-motor symptoms in Parkinson's disease (PD) that often precedes the emergence of motor symptoms by several years. Patients with PD hypothetically progress from stages without CI (PD-normal cognition [NC]) to stages with Mild CI (PD-MCI) and PD dementia (PDD). CI symptoms in PD are linked to different brain regions and neural pathways, in addition to being the result of dysfunctional subcortical regions. However, it is still unknown how functional dysregulation correlates to progression during the CI. Neuroimaging techniques hold promise in discriminating CI stages of PD and further contribute to the biomarker formation of CI in PD. In this study, we explore disparities in the clinical assessments and resting-state functional connectivity (FC) among three CI stages of PD.

METHODS

We enrolled 88 patients with PD and 26 healthy controls (HC) for a cross sectional clinical study and performed intra- and inter-network FC analysis in conjunction with comprehensive clinical cognitive assessment.

RESULTS

Our findings underscore the significance of several neural networks, namely, the default mode network (DMN), frontoparietal network (FPN), dorsal attention network, and visual network (VN) and their inter-intra-network FC in differentiating between PD-MCI and PDD. Additionally, our results showed the importance of sensory motor network, VN, DMN, and salience network (SN) in the discriminating PD-NC from PDD. Finally, in comparison to HC, we found DMN, FPN, VN, and SN as pivotal networks for further differential diagnosis of CI stages of PD.

CONCLUSION

We propose that resting-state networks (RSN) can be a discriminating factor in distinguishing the CI stages of PD and progressing from PD-NC to MCI or PDD. The integration of clinical and neuroimaging data may enhance the early detection of PD in clinical settings and potentially prevent the disease from advancing to more severe stages.

Study of the gut microbiome in Egyptian patients with Parkinson's Disease

BACKGROUND

Recently, an important relationship between Parkinson's disease and the gut microbiota, through the brain-gut axis interactions, has been established. Previous studies have declared that alterations in the gut microbiota have a great impact on the pathogenesis and clinical picture of Parkinson's disease (PD). The present study aimed to identify the gut microbiome that is likely related to Parkinson's disease as well as their possible relation to clinical phenotypes.

METHODS

Thirty patients with Parkinson's disease, who presented to the Parkinson's disease Neurology Clinic of Alexandria University Hospital were enrolled in our study. A cross-matching control group of 35 healthy subjects of similar age and sex were included. Stool specimens were taken from each. Quantitative SYBR Green Real-Time PCR was done for the identification and quantitation of selected bacterial phyla, genera and/or species.

RESULTS

There was a significant increase in Bacteroides and a significant decrease of Firmicutes and Firmicutes / Bacteroidetes ratio and Bifidobacteria in PD patients. Although Prevotella was decreased among PD patients relative to the healthy control, the difference was not statistically significant. Comparing the PD clinical phenotypes with the control group, the Mixed phenotype had significantly higher Bacteroides, Tremors predominant had lower Firmicutes and Firmicutes / Bacteroidetes ratio, and both tremors and postural instability and gait disability (PIGD) phenotypes had lower Bifidobacteria. However, there was no statistically significant difference between these phenotypes. Furthermore, when comparing tremors and non-tremors predominant phenotypes; Lactobacilli showed a significant decrease in non-tremors predominant phenotypes.

CONCLUSIONS

The current study showed evidence of changes in the gut microbiome of Parkinson's disease patients compared to the healthy controls. These observations may highlight the importance of the identification of microbiome and specific bacterial changes that can be targeted for the treatment of Parkinson's disease.

Two distinct trajectories of clinical and neurodegeneration events in Parkinson's disease

Increasing evidence suggests that Parkinson's disease (PD) exhibits disparate spatial and temporal patterns of progression. Here we used a machine-learning technique-Subtype and Stage Inference (SuStaIn) - to uncover PD subtypes with distinct trajectories of clinical and neurodegeneration events. We enrolled 228 PD patients and 119 healthy controls with comprehensive assessments of olfactory, autonomic, cognitive, sleep, and emotional function. The integrity of substantia nigra (SN), locus coeruleus (LC), amygdala, hippocampus, entorhinal cortex, and basal forebrain were assessed using diffusion and neuromelanin-sensitive MRI. SuStaIn model with above clinical and neuroimaging variables as input was conducted to identify PD subtypes. An independent dataset consisting of 153 PD patients and 67 healthy controls was utilized to validate our findings. We identified two distinct PD subtypes: subtype 1 with rapid eye movement sleep behavior disorder (RBD), autonomic dysfunction, and degeneration of the SN and LC as early manifestations, and cognitive impairment and limbic degeneration as advanced manifestations, while subtype 2 with hyposmia, cognitive impairment, and limbic degeneration as early manifestations, followed later by RBD and degeneration of the LC in advanced disease. Similar subtypes were shown in the validation dataset. Moreover, we found that subtype 1 had weaker levodopa response, more GBA mutations, and poorer prognosis than subtype 2. These findings provide new insights into the underlying disease biology and might be useful for personalized treatment for patients based on their subtype.

Structural and functional differences of the thalamus between drug-naïve Parkinson's disease motor subtypes

Objective

The thalamus is an integrative hub of motor circuits in Parkinson's disease (PD). This study aimed to investigate the alterations of structure and functional connectivity (FC) of the thalamic subregions in the tremor-dominant (TD) subtype and the postural instability and gait difficulty (PIGD) subtype in PD.

Methods

A total of 59 drug-naïve patients (24 TD and 35 PIGD) and 37 healthy controls were recruited. The volumes of the thalamus and the thalamic subregions were calculated using FreeSurfer. Functional connectivity (FC) analysis of the resting-state functional MRI (rsfMRI) was conducted on the thalamic subregions. Finally, the altered structure and FC were used for correlation analysis with clinical motor scores and for further motor subtypes differentiation.

Results

The volumes of the left posterior parietal thalamus (PPtha) in TD patients were significantly lower than those of PIGD patients. Compared with PIGD patients, TD patients exhibited higher FC between the thalamic subregions, the left middle temporal gyrus (MTG), the right dorsolateral superior frontal gyrus (SFGdl), the left middle occipital gyrus (MOG), and the right superior temporal gyrus (STG). Compared with HCs, TD patients showed higher FC between the thalamic subregions and the right SFGdl, as well as the left MOG. Compared with HCs, PIGD patients showed lower FC between the thalamic subregions and the left MTG. In addition, the altered FC was closely related to clinical symptoms and performed high-discriminative power in differentiating the motor subtypes.

Conclusion

Increased FC between the thalamic subregions and the sensory cortices in TD patients may indicate a better compensatory capacity for impairment of sensory information integration than that in PIGD patients. The altered FC between the thalamus and the MTG was a potential biomarker for the distinction of the PD motor subtypes.

Precision medicine for Parkinson's disease: The subtyping challenge

Despite many pharmacological and surgical treatments addressing the symptoms of Parkinson's disease, there are no approved treatments that slow disease progression. Genetic discoveries in the last 20 years have increased our understanding of the molecular contributors to Parkinson's pathophysiology, uncovered many druggable targets and pathways, and increased investment in treatments that might slow or stop the disease process. Longitudinal, observational studies are dissecting Parkinson's disease heterogeneity and illuminating the importance of molecularly defined subtypes more likely to respond to targeted interventions. Indeed, clinical and pathological differences seen within and across carriers of PD-associated gene mutations suggest the existence of greater biological complexity than previously appreciated and increase the likelihood that targeted interventions based on molecular characteristics will be beneficial. This article offers our current perspective on the promise and current challenges in subtype identification and precision medicine approaches in Parkinson's disease.

Association of Total Bilirubin with Motor Signs in Early Parkinson's Disease in LRRK2 Variant Carriers

Oxidative stress is considered a possible mechanism in Parkinson's disease (PD) progression. Bilirubin has been recognized as a powerful antioxidant that increases due to heme-oxygenase activity. We aimed to investigate the association of total bilirubin (TB) with motor signs and asymmetry in different stages of early PD. A case-control study was performed to investigate the differences in TB levels in PD patients and healthy controls (HC) both carrying LRRK2 variants. We compared TB levels in HC and Hoehn and Yahr (HY) I and II cohorts separately, followed by multiple linear regression analysis to evaluate the association between TB and motor dysfunction in each stage. We used Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (UPDRS) part III scores and asymmetry scores to address motor disability. Asymmetry scores were calculated from the corresponding UPDRS III tasks. TB was significantly increased in HY II compared to HC (P < 0.001). Positive correlations with TB were found for UPDRS III total score (ρ = 0.303, P = 0.034) and asymmetry score (ρ = 0.418, P = 0.003) in HY I. Multiple linear regression found a significant relationship between TB and asymmetry scores in HY I (R² = 0.261, P = 0.037), but no relationship was achieved with UPDRS III total scores. Increased TB serves as an important diagnostic marker in earlier stages of PD. A significant relationship was found between TB and motor asymmetry in HY I patients. According to our findings, bilirubin mainly exhibits its protective effects in HY I population.

Genetic architecture of Parkinson’s disease subtypes – Review of the literature

The heterogeneity of Parkinson’s disease (PD) has been recognized since its description by James Parkinson over 200 years ago. The complexity of motor and non-motor PD manifestations has led to many attempts of PD subtyping with different prognostic outcomes; however, the pathophysiological foundations of PD heterogeneity remain elusive. Genetic contributions to PD may be informative in understanding the underpinnings of PD subtypes. As such, recognizing genotype-phenotype associations may be crucial for successful gene therapy. We review the state of knowledge on the genetic architecture underlying PD subtypes, discussing the monogenic forms, as well as oligo- and polygenic risk factors associated with various PD subtypes. Based on our review, we argue for the unification of PD subtyping classifications, the dichotomy of studies on genetic factors and genetic modifiers of PD, and replication of results from previous studies.

Insights into Human-Induced Pluripotent Stem Cell-Derived Astrocytes in Neurodegenerative Disorders

Most neurodegenerative disorders have complex and still unresolved pathology characterized by progressive neuronal damage and death. Astrocytes, the most-abundant non-neuronal cell population in the central nervous system, play a vital role in these processes. They are involved in various functions in the brain, such as the regulation of synapse formation, neuroinflammation, and lactate and glutamate levels. The development of human-induced pluripotent stem cells (iPSCs) reformed the research in neurodegenerative disorders allowing for the generation of disease-relevant neuronal and non-neuronal cell types that can help in disease modeling, drug screening, and, possibly, cell transplantation strategies. In the last 14 years, the differentiation of human iPSCs into astrocytes allowed for the opportunity to explore the contribution of astrocytes to neurodegenerative diseases. This review discusses the development protocols and applications of human iPSC-derived astrocytes in the most common neurodegenerative conditions.