Srividhya Sainath

Molecular stratification of Parkinson’s Disease

Master student Srividhya Sainath analyzes genetic profiles of Parkinson's Disease patients to explore subtypes.

The Need for Parkinson’s Disease Subtyping

Parkinson's Disease (PD) is a complex neurodegenerative condition characterized by various symptoms, co-morbidities, and disease progression patterns. The presence of diverse manifestations across PD patients suggests the existence of distinct subtypes. Exploring and understanding these subtypes can provide valuable insights into the underlying biology of PD, enabling the development of personalized approaches for diagnosis, treatment, and subtype-focused clinical trials (Figure 1).

Figure 1: Subtyping PD patients into homogeneous groups for better disease management strategies

In our study, we performed data-driven molecular subtyping of our PD cohort using samples from the UK Biobank dataset. By analyzing the diverse genetic profiles of PD patients, we identified patterns and grouped them into more homogeneous clusters. To accomplish this, we utilized two methods: the Polygenic Risk Score (PRS) approach and the Genetic Burden Score (GBS) approach.

Polygenic Risk Score (PRS) Approach

PD is often associated with co-morbid conditions such as Type-II Diabetes Mellitus, Hypertension, Dementia, Cerebrovascular disorder, and Chronic obstructive pulmonary disorder (COPD) [2,3,4,5]. These co-morbidities share partial genetic liability with PD, potentially segregating PD patients into different subtypes. We used Polygenic Risk Scores (PRS) to capture this shared genetic liability. Through sparse non-negative matrix factorization, an unsupervised bi-clustering approach, we identified two distinct subtypes within our PD cohort (Figure 2). PD patients of one subtype showed a significantly higher prevalence of Diabetes, Ischemic stroke, COPD, and speech disturbances.

Figure 2: Polygenic Risk Score Approach of molecular subtyping

Genetic Burden Score (GBS) Approach

The Genetic Burden Score (GBS) approach is based on the clustering pipeline developed by Emon et al. [1], which aimed to identify subtypes in both Alzheimer's Disease (AD) and PD patients. Here, they identified shared molecular mechanisms between AD and PD and mapped it to single nucleotide polymorphisms (SNPs), thereby providing a genetic foundation for the analysis.

In our work, we again applied sparse non-negative matrix factorization to the final GBS matrix, identifying four distinct clusters. Notably, our findings were consistent with the original study conducted by Emon et al. [1]. Further statistical analysis revealed significant differences in the prevalence of acute Myocardial infarction and sleep disorders among the four subtypes. Moreover, our analysis showed that patients of a certain subtype were prescribed fewer diuretics before their PD diagnosis compared to those in other subtypes.

Figure 3: Genetic Burden Score Approach of molecular subtyping


Identifying these distinct subtypes and the differences in associated conditions offer valuable insights for tailored treatment approaches and potential risk factor considerations for PD patients. Our discoveries indicate significant differences between PD subtype membership and specific clinical symptoms and co-morbidities. To ensure reproducibility, we are validating our results on other PD cohorts. Additionally, we are investigating the relationships between subtypes and utilizing established biomarkers for adequate characterization. Understanding these distinctions can pave the way for personalized care and targeted interventions, ultimately improving the management and quality of life for individuals with PD.


  1. Emon, M.A., Heinson, A., Wu, P. et al. Clustering of Alzheimer’s and Parkinson’s disease based on genetic burden of shared molecular mechanisms. Sci Rep 10, 19097 (2020).
  2. Gang Hu, Pekka Jousilahti, Siamak Bidel, Riitta Antikainen, Jaakko Tuomilehto; Type 2 Diabetes and the Risk of Parkinson's Disease. Diabetes Care 1 April 2007; 30 (4): 842–847.
  3. Santos-García, Diego & Castro, E. & Expósito, I. & Deus, T. & Tuñas, C. & Aneiros, A. & Fernández, M. & Arias, D. & Torres, M.. (2016). Comorbid conditions associated with Parkinson's disease: A longitudinal and comparative study with Alzheimer's disease and control subjects. Journal of the Neurological Sciences. 373.
  4. C-H. Li and others, The association between chronic obstructive pulmonary disease and Parkinson’s disease: a nationwide population-based retrospective cohort study, QJM: An International Journal of Medicine, Volume 108, Issue 1, January 2015, Pages 39–45.
  5. Nanhoe-Mahabier, W., de Laat, K., Visser, J. et al. Parkinson's disease and comorbid cerebrovascular disease. Nat Rev Neurol 5, 533–541 (2009).