Advancing Personalized Medicine in Common Forms of Parkinson's Disease through Genetics: Current Therapeutics and the Future of Individualized Management

Polygenic Resilience Modulates the Penetrance of Parkinson Disease Genetic Risk Factors

OBJECTIVE

The aim of the current study is to understand why some individuals avoid developing Parkinson disease (PD) despite being at relatively high genetic risk, using the largest datasets of individual-level genetic data available.

METHODS

We calculated polygenic risk score to identify controls and matched PD cases with the highest burden of genetic risk for PD in the discovery cohort (International Parkinson's Disease Genomics Consortium, 7,204 PD cases and 9,412 controls) and validation cohorts (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease, 8,968 cases and 7,598 controls; UK Biobank, 2,639 PD cases and 14,301 controls; Accelerating Medicines Partnership-Parkinson's Disease Initiative, 2,248 cases and 2,817 controls). A genome-wide association study meta-analysis was performed on these individuals to understand genetic variation associated with resistance to disease. We further constructed a polygenic resilience score, and performed multimarker analysis of genomic annotation (MAGMA) gene-based analyses and functional enrichment analyses.

RESULTS

A higher polygenic resilience score was associated with a lower risk for PD (β = -0.054, standard error [SE] = 0.022, p = 0.013). Although no single locus reached genome-wide significance, MAGMA gene-based analyses nominated TBCA as a putative gene. Furthermore, we estimated the narrow-sense heritability associated with resilience to PD (h2  = 0.081, SE = 0.035, p = 0.0003). Subsequent functional enrichment analysis highlighted histone methylation as a potential pathway harboring resilience alleles that could mitigate the effects of PD risk loci.

INTERPRETATION

The present study represents a novel and comprehensive assessment of heritable genetic variation contributing to PD resistance. We show that a genetic resilience score can modify the penetrance of PD genetic risk factors and therefore protect individuals carrying a high-risk genetic burden from developing PD. ANN NEUROL 2022;92:270-278.

Integrating Multimorbidity into a Whole-Body Understanding of Disease Using Spatial Genomics

Multimorbidity is characterized by multidimensional complexity emerging from interactions between multiple diseases across levels of biological (including genetic) and environmental determinants and the complex array of interactions between and within cells, tissues and organ systems. Advances in spatial genomic research have led to an unprecedented expansion in our ability to link alterations in genome folding with changes that are associated with human disease. Studying disease-associated genetic variants in the context of the spatial genome has enabled the discovery of transcriptional regulatory programmes that potentially link dysregulated genes to disease development. However, the approaches that have been used have typically been applied to uncover pathological molecular mechanisms occurring in a specific disease-relevant tissue. These forms of reductionist, targeted investigations are not appropriate for the molecular dissection of multimorbidity that typically involves contributions from multiple tissues. In this perspective, we emphasize the importance of a whole-body understanding of multimorbidity and discuss how spatial genomics, when integrated with additional omic datasets, could provide novel insights into the molecular underpinnings of multimorbidity.

Polygenic Risk Scores Contribute to Personalized Medicine of Parkinson's Disease

Parkinson’s disease (PD) is the second most common neurodegenerative disorder characterized by the loss of dopaminergic neurons. The vast majority of PD patients develop the disease sporadically and it is assumed that the cause lies in polygenic and environmental components. The overall polygenic risk is the result of a large number of common low-risk variants discovered by large genome-wide association studies (GWAS). Polygenic risk scores (PRS), generated by compiling genome-wide significant variants, are a useful prognostic tool that quantifies the cumulative effect of genetic risk in a patient and in this way helps to identify high-risk patients. Although there are limitations to the construction and application of PRS, such as considerations of limited genetic underpinning of diseases explained by SNPs and generalizability of PRS to other populations, this personalized risk prediction could make a promising contribution to stratified medicine and tailored therapeutic interventions in the future.

Personalized Medicine Approach in Treating Parkinson's Disease, Using Oral Administration of Levodopa/Carbidopa Microtablets in Clinical Practice

Background: The most effective symptomatic treatment in Parkinson’s disease (PD) is levodopa in standard doses. However, as the disease progresses, there may be a need for a more personalized approach and fine tuning, in accordance with the patients’ needs. This study aims to evaluate the individual experience of levodopa/carbidopa 5/1.25 mg microtablets (LC-5) in clinical practice with respect to efficacy, tolerability, and usability. The method used was as follows: patients answered a questionnaire concerning the effect and usability of LC-5, and their medical records were reviewed. Regarding results, thirty-five survey responses were obtained, and 29 patients’ medical records were reviewed. The LC-5 dose dispenser usability was generally rated positively and facilitated medication adherence. The majority (85%) of patients reported symptom improvement while using LC-5, compared with previous standard treatments. These results suggest that LC-5 therapy is generally well-tolerated, with favorable patient-reported efficacy and user friendliness, as well as the possibility for an individualized, fine-tuned PD treatment. Further studies with a prospective design and larger study population are needed to confirm the results.