Mitochondrial and autophagy-lysosomal pathway polygenic risk scores predict Parkinson's disease

The effect of polygenic risk score on PD risk and phenotype in LRRK2 G2019S and GBA1 carriers

BackgroundWhile LRRK2 and GBA1 variants are associated with Parkinson's disease (PD), most carriers will not develop the disease.ObjectiveTo test if polygenic risk score (PRS) modifies disease risk and phenotypes in LRRK2 G2019S carriers, GBA1 carriers, and non-carriers (NC).MethodsWe genotyped 786 participants using Illumina's NeuroBooster-array (NBA) and sequenced the genome of 244, all of Ashkenazi ancestry (AJ), and calculated PRS to test its effects on clinically- and biologically-defined disease risk and phenotypes (n = 715). Among LRRK2 G2019S PD, we tested PRS association with α-synuclein seed-amplification-assay (n = 11). We used the PPMI and AMP-PD databases as validation cohorts.ResultsIn clinically-defined PD, PRS significantly modified disease risk in GBA1 carriers and in NC (p = 0.033 and p < 0.0001, respectively), and demonstrated a trend in LRRK2 G2019S carriers (p = 0.054), with similar effect sizes (OR = 1.55, 1.62, and 1.49, respectively). PRS association with PD risk in LRRK2 was primarily driven by the rs7938782-A risk allele, replicated in AMP-PD (268 AJs LRRK2 G2019S carriers). PRS and age-at-onset were negatively correlated in NC (p < 0.0001). NBA GBA1 genotype calls failed at GBA1 L483P and c.115 + 1G > A mutations. False negative call rate of 10.2% was observed for the imputed GBA1 N409S carriers.ConclusionsPRS contributes to PD risk across different genotypes. The genetic and epigenetic role of rs7938782 in LRRK2 PD risk should be further explored. Future PRS models should be tailored to specific genotypes to better understand penetrance and phenotypes. Furthermore, models predicting PD defined biologically rather than clinically may further identify genetic risk factors for synucleinopathies.

Polygenic scores for disease risk are not associated with clinical outcomes in Parkinson's disease

Polygenic risk scores (PRS) in Parkinson's disease (PD) are associated with disease risk. Recently, pathway-specific PRS have been created to take advantage of annotations inking variants to biological pathways or cell types. Here, we investigated 8 biological pathways or regions of open chromatin using pathway-specific PRS: alpha-synuclein pathway, adaptive immunity, innate immunity, lysosomal pathway1, endocytic membrane-trafficking pathway, mitochondrial pathway, microglial open chromatin single nucleotide polymorphisms (SNPs), and monocyte open chromatin SNPs. We analysed 7,402 PD patients across 18 'in-person' PD cohorts, and 6,717 patients from the online Fox Insight study. We did not find any significant associations between the 8 pathway-specific PRSs and 8 clinical outcomes in PD. Though this may be due to a lack of statistical power and limited sample size, it may also suggest that the genetic architecture of sporadic PD risk is different from the genetics of PD progression and clinical outcomes.

Recursive seed amplification detects distinct α-synuclein strains in cerebrospinal fluid of patients with Parkinson's disease

Parkinson's disease (PD) is a heterogeneous neurodegenerative disorder with a wide range of clinical phenotypes. Pathologically, it is characterized by neuronal inclusions containing misfolded, fibrillar alpha-synuclein (aSyn). Prion-like properties of aSyn contribute to the spread of aSyn pathology throughout the nervous system as the disease progresses. Utilizing these properties, seed amplification assays (SAA) enable the detection of aSyn pathology in living patients. We hypothesized that structurally distinct aSyn aggregates, or strains, may underlie the clinical heterogeneity of PD. To test this hypothesis, we recursively amplified aSyn fibrils from the cerebrospinal fluid (CSF) of 54 patients (34 people with PD and 20 controls). These fibrils were then characterized regarding SAA kinetic properties and detergent resistance. In addition, cultured cells were transfected with SAA products, and the extent of seeded aSyn pathology was quantified by staining for phosphorylated aSyn followed by automated high-throughput microscopy and image analysis. We found that fibrils, amplified from CSF by recursive SAA, exhibit two types of distinct biophysical properties and have different seeding capacities in cells. These properties are associated with clinical parameters and may therefore help explain the clinical heterogeneity in PD. Measuring aSyn strains may be relevant for prognosis and for therapies targeting aSyn pathology.

PADG-Pred: Exploring Ensemble Approaches for Identifying Parkinson's Disease Associated Biomarkers Using Genomic Sequences Analysis

Parkinson's disease (PD), a degenerative disorder affecting the nervous system, manifests as unbalanced movements, stiffness, tremors, and coordination difficulties. Its cause, believed to involve genetic and environmental factors, underscores the critical need for prompt diagnosis and intervention to enhance treatment effectiveness. Despite the array of available diagnostics, their reliability remains a challenge. In this study, an innovative predictor PADG-Pred is proposed for the identification of Parkinson's associated biomarkers, utilising a genomic profile. In this study, a novel predictor, PADG-Pred, which not only identifies Parkinson's associated biomarkers through genomic profiling but also uniquely integrates multiple statistical feature extraction techniques with ensemble-based classification frameworks, thereby providing a more robust and interpretable decision-making process than existing tools. The processed dataset was utilised for feature extraction through multiple statistical moments and it is further involved in extensive training of the model using diverse classification techniques, encompassing Ensemble methods; XGBoost, Random Forest, Light Gradient Boosting Machine, Bagging, ExtraTrees, and Stacking. State-of-the-art validation procedures are applied, assessing key metrics such as specificity, accuracy, sensitivity/recall, and Mathew's correlation coefficient. The outcomes demonstrate the outstanding performance of PADG-RF, showcasing accuracy metrics consistently achieving ∼91% for the independent set, ∼94% for 5-fold, and ∼96% for 10-fold in cross-validation.

In situ stoichiometry amounts of p62 and poly-ubiquitin exceed the increase of alpha-synuclein during degeneration of catecholamine cells induced by autophagy inhibition in vitro

Neurodegenerative disorders are typically featured by the occurrence of neuronal inclusions. In the case of Parkinson's disease (PD) these correspond to Lewy bodies (LBs), which are routinely defined as proteinaceous inclusions composed of alpha-synuclein (alpha-syn). In turn, alpha-syn is considered to be the key protein in producing PD and fostering its progression. Recent studies challenged such a concept and emphasized the occurrence of other proteins such as p62 and poly-ubiquitin (Poly-ub) in the composition of LBs, which are also composed of large amounts of tubulo-vesicular structures. All these components, which accumulate within the cytosol of affected neurons in PD, may be the consequence of a dysfunction of major clearing pathways. In fact, autophagy-related systems are constantly impaired in inherited PD and genetic models of PD. The present study was designed to validate whether a pharmacological inhibition of autophagy within catecholamine cells produces cell damage and accumulation of specific proteins and tubulo-vesicular structures. The stoichiometry counts of single proteins, which accumulate within catecholamine neurons was carried out along with the area of tubulo-vesicular structures. In these experimental conditions p62 and Poly-ub accumulation exceeded at large the amounts of alpha-syn. In those areas where Poly-ub and p62 were highly expressed, tubulo-vesicular structures were highly represented compared with surrounding cytosol. The present study confirms new vistas about LBs composition and lends substance to the scenario that autophagy inhibition rather than a single protein dysfunction as key determinant of PD.

Advantages and Challenges of Platform Trials for Disease Modifying Therapies in Parkinson's Disease

Traditional drug development in Parkinson's disease (PD) faces significant challenges because of its protracted timeline and high costs. In response, innovative master protocols are emerging and designed to address multiple research questions within a single overarching protocol. These trials may offer advantages such as increased efficiency, agility in adding new treatment arms, and potential cost savings. However, they also present organizational, methodological, funding, regulatory, and sponsorship challenges. We review the potential of master protocols, focusing on platform trials, for disease modifying therapies in PD. These trials share a common control group and allow for the termination or addition of treatment arms during a trial with non-predetermined end. Specific issues exist for a platform trial in the PD field considering the heterogeneity of patients in terms of phenotype, genotype and staging, the confounding effects of symptomatic treatments, and the choice of outcome measures with no consensus on a non-clinical biomarker to serve as a surrogate and the slowness of PD progression. We illustrate these aspects using the examples of the main PD platform trials currently in development with each one targeting distinct goals, populations, and outcomes. Overall, platform trials hold promise in expediting the evaluation of potential therapies for PD. However, it remains to be proven whether these theoretical benefits will translate into increased production of high-quality trial data. Success also depends on the willingness of pharmaceutical companies to engage in such trials and whether this approach will ultimately hasten the identification and licensing of effective disease-modifying drugs. © 2024 International Parkinson and Movement Disorder Society.

Transcriptomic changes in oligodendrocytes and precursor cells associate with clinical outcomes of Parkinson's disease

Several prior studies have proposed the involvement of various brain regions and cell types in Parkinson's disease (PD) pathology. Here, we performed snRNA-seq on the prefrontal cortex and anterior cingulate regions from a small cohort of post-mortem control and PD brain tissue. We found a significant association of oligodendrocytes (ODCs) and oligodendrocyte precursor cells (OPCs) with PD-linked risk loci and report several dysregulated genes and pathways, including regulation of tau-protein kinase activity, regulation of inclusion body assembly and protein processing involved in protein targeting to mitochondria. In an independent PD cohort with clinical measures (681 cases and 549 controls), polygenic risk scores derived from the dysregulated genes significantly predicted Montreal Cognitive Assessment (MoCA)-, and Beck Depression Inventory-II (BDI-II)-scores but not motor impairment (UPDRS-III). We extended our analysis of clinical outcome prediction by incorporating differentially expressed genes from three separate datasets that were previously published by different laboratories. In the first dataset from the anterior cingulate cortex, we identified an association between ODCs and BDI-II. In the second dataset obtained from the substantia nigra (SN), OPCs displayed an association with UPDRS-III. In the third dataset from the SN region, a distinct subtype of OPCs, labeled OPC_ADM, exhibited an association with UPDRS-III. Intriguingly, the OPC_ADM cluster also demonstrated a significant increase in PD samples. These results suggest that by expanding our focus to glial cells, we can uncover region-specific molecular pathways associated with PD symptoms.

Polygenic Risk Scores Validated in Patient-Derived Cells Stratify for Mitochondrial Subtypes of Parkinson's Disease

OBJECTIVE

The aim of our study is to better understand the genetic architecture and pathological mechanisms underlying neurodegeneration in idiopathic Parkinson's disease (iPD). We hypothesized that a fraction of iPD patients may harbor a combination of common variants in nuclear-encoded mitochondrial genes ultimately resulting in neurodegeneration.

METHODS

We used mitochondria-specific polygenic risk scores (mitoPRSs) and created pathway-specific mitoPRSs using genotype data from different iPD case-control datasets worldwide, including the Luxembourg Parkinson's Study (412 iPD patients and 576 healthy controls) and COURAGE-PD cohorts (7,270 iPD cases and 6,819 healthy controls). Cellular models from individuals stratified according to the most significant mitoPRS were subsequently used to characterize different aspects of mitochondrial function.

RESULTS

Common variants in genes regulating Oxidative Phosphorylation (OXPHOS-PRS) were significantly associated with a higher PD risk in independent cohorts (Luxembourg Parkinson's Study odds ratio, OR = 1.31[1.14-1.50], p-value = 5.4e-04; COURAGE-PD OR = 1.23[1.18-1.27], p-value = 1.5e-29). Functional analyses in fibroblasts and induced pluripotent stem cells-derived neuronal progenitors revealed significant differences in mitochondrial respiration between iPD patients with high or low OXPHOS-PRS (p-values < 0.05). Clinically, iPD patients with high OXPHOS-PRS have a significantly earlier age at disease onset compared to low-risk patients (false discovery rate [FDR]-adj p-value = 0.015), similar to prototypic monogenic forms of PD. Finally, iPD patients with high OXPHOS-PRS responded more effectively to treatment with mitochondrially active ursodeoxycholic acid.

INTERPRETATION

OXPHOS-PRS may provide a precision medicine tool to stratify iPD patients into a pathogenic subgroup genetically defined by specific mitochondrial impairment, making these individuals eligible for future intelligent clinical trial designs. ANN NEUROL 2024;96:133-149.

Common genetic risk for Parkinson's disease and dysfunction of the endo-lysosomal system

Parkinson's disease is a progressive neurological disorder, characterized by prominent movement dysfunction. The past two decades have seen a rapid expansion of our understanding of the genetic basis of Parkinson's, initially through the identification of monogenic forms and, more recently, through genome-wide association studies identifying common risk variants. Intriguingly, a number of cellular pathways have emerged from these analysis as playing central roles in the aetiopathogenesis of Parkinson's. In this review, the impact of data deriving from genome-wide analyses for Parkinson's upon our functional understanding of the disease will be examined, with a particular focus on examples of endo-lysosomal and mitochondrial dysfunction. The challenges of moving from a genetic to a functional understanding of common risk variants for Parkinson's will be discussed, with a final consideration of the current state of the genetic architecture of the disorder. This article is part of a discussion meeting issue 'Understanding the endo-lysosomal network in neurodegeneration'.

Transcriptomic changes in oligodendrocytes and precursor cells predicts clinical outcomes of Parkinson's disease

Several prior studies have proposed the involvement of various brain regions and cell types in Parkinson's disease (PD) pathology. Here, we performed snRNA-seq on the prefrontal cortex and anterior cingulate regions from post-mortem control and PD brain tissue. We found a significant association of oligodendrocytes (ODCs) and oligodendrocyte precursor cells (OPCs) with PD-linked risk loci and report several dysregulated genes and pathways, including regulation of tau-protein kinase activity, regulation of inclusion body assembly and protein processing involved in protein targeting to mitochondria. In an independent PD cohort with clinical measures (681 cases and 549 controls), polygenic risk scores derived from the dysregulated genes significantly predicted Montreal Cognitive Assessment (MoCA)-, and Beck Depression Inventory-II (BDI-II)-scores but not motor impairment (UPDRS-III). We extended our analysis of clinical outcome prediction by incorporating three separate datasets that were previously published by different laboratories. In the first dataset from the anterior cingulate cortex, we identified a correlation between ODCs and BDI-II. In the second dataset obtained from the substantia nigra (SN), OPCs displayed notable predictive ability for UPDRS-III. In the third dataset from the SN region, a distinct subtype of OPCs, labeled OPC_ADM, exhibited predictive ability for UPDRS-III. Intriguingly, the OPC_ADM cluster also demonstrated a significant increase in PD samples. These results suggest that by expanding our focus to glial cells, we can uncover region-specific molecular pathways associated with PD symptoms.

Interaction of Mitochondrial Polygenic Score and Lifestyle Factors in LRRK2 p.Gly2019Ser Parkinsonism

BACKGROUND

A mitochondrial polygenic score (MGS) is composed of genes related to mitochondrial function and found to be associated with Parkinson's disease (PD) risk.

OBJECTIVE

To investigate the impact of the MGS and lifestyle/environment on age at onset (AAO) in LRRK2 p.Gly2019Ser parkinsonism (LRRK2-PD) and idiopathic PD (iPD).

METHODS

We included N = 486 patients with LRRK2-PD and N = 9259 with iPD from the Accelerating Medicines Partnership® Parkinson's Disease Knowledge Platform (AMP-PD), Fox Insight, and a Tunisian Arab-Berber founder population. Genotyping data were used to perform the MGS analysis. Additionally, lifestyle/environmental data were obtained from the PD Risk Factor Questionnaire (PD-RFQ). Linear regression models were used to assess the relationship between MGS, lifestyle/environment, and AAO.

RESULTS

Our derived MGS was significantly higher in PD cases compared with controls (P = 1.1 × 10-8 ). We observed that higher MGS was significantly associated with earlier AAO in LRRK2-PD (P = 0.047, β = -1.40) and there was the same trend with a smaller effect size in iPD (P = 0.231, β = 0.22). There was a correlation between MGS and AAO in LRRK2-PD patients of European descent (P = 0.049, r = -0.12) that was visibly less pronounced in Tunisians (P = 0.449, r = -0.05). We found that the MGS interacted with caffeinated soda consumption (P = 0.003, β = -5.65) in LRRK2-PD and with tobacco use (P = 0.010, β = 1.32) in iPD. Thus, patients with a high MGS had an earlier AAO only if they consumed caffeinated soda or were non-smokers.

CONCLUSIONS

The MGS was more strongly associated with earlier AAO in LRRK2-PD compared with iPD. Caffeinated soda consumption or tobacco use interacted with MGS to predict AAO. Our study suggests gene-environment interactions as modifiers of AAO in LRRK2-PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

A genome-wide association study coupled with machine learning approaches to identify influential demographic and genomic factors underlying Parkinson's disease

Background: Despite the recent success of genome-wide association studies (GWAS) in identifying 90 independent risk loci for Parkinson's disease (PD), the genomic underpinning of PD is still largely unknown. At the same time, accurate and reliable predictive models utilizing genomic or demographic features are desired in the clinic for predicting the risk of Parkinson's disease. Methods: To identify influential demographic and genomic factors associated with PD and to further develop predictive models, we utilized demographic data, incorporating 200 variables across 33,473 participants, along with genomic data involving 447,089 SNPs across 8,840 samples, both derived from the Fox Insight online study. We first applied correlation and GWAS analyses to find the top demographic and genomic factors associated with PD, respectively. We further developed and compared a variety of machine learning (ML) models for predicting PD. From the developed ML models, we performed feature importance analysis to reveal the predictability of each demographic or the genomic input feature for PD. Finally, we performed gene set enrichment analysis on our GWAS results to identify PD-associated pathways. Results: In our study, we identified both novel and well-known demographic and genetic factors (along with the enriched pathways) related to PD. In addition, we developed predictive models that performed robustly, with AUC = 0.89 for demographic data and AUC = 0.74 for genomic data. Our GWAS analysis identified several novel and significant variants and gene loci, including three intron variants in LMNA (p-values smaller than 4.0e-21) and one missense variant in SEMA4A (p-value = 1.11e-26). Our feature importance analysis from the PD-predictive ML models highlighted some significant and novel variants from our GWAS analysis (e.g., the intron variant rs1749409 in the RIT1 gene) and helped identify potentially causative variants that were missed by GWAS, such as rs11264300, a missense variant in the gene DCST1, and rs11584630, an intron variant in the gene KCNN3. Conclusion: In summary, by combining a GWAS with advanced machine learning models, we identified both known and novel demographic and genomic factors as well as built well-performing ML models for predicting Parkinson's disease.

Parkinson's disease therapy: what lies ahead?

The worldwide prevalence of Parkinson's disease (PD) has been constantly increasing in the last decades. With rising life expectancy, a longer disease duration in PD patients is observed, further increasing the need and socioeconomic importance of adequate PD treatment. Today, PD is exclusively treated symptomatically, mainly by dopaminergic stimulation, while efforts to modify disease progression could not yet be translated to the clinics. New formulations of approved drugs and treatment options of motor fluctuations in advanced stages accompanied by telehealth monitoring have improved PD patients care. In addition, continuous improvement in the understanding of PD disease mechanisms resulted in the identification of new pharmacological targets. Applying novel trial designs, targeting of pre-symptomatic disease stages, and the acknowledgment of PD heterogeneity raise hopes to overcome past failures in the development of drugs for disease modification. In this review, we address these recent developments and venture a glimpse into the future of PD therapy in the years to come.

Current State and Future Directions in the Diagnosis of Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by loss of upper and lower motor neurons, resulting in progressive weakness of all voluntary muscles and eventual respiratory failure. Non-motor symptoms, such as cognitive and behavioral changes, frequently occur over the course of the disease. Considering its poor prognosis with a median survival time of 2 to 4 years and limited causal treatment options, an early diagnosis of ALS plays an essential role. In the past, diagnosis has primarily been determined by clinical findings supported by electrophysiological and laboratory measurements. To increase diagnostic accuracy, reduce diagnostic delay, optimize stratification in clinical trials and provide quantitative monitoring of disease progression and treatment responsivity, research on disease-specific and feasible fluid biomarkers, such as neurofilaments, has been intensely pursued. Advances in imaging techniques have additionally yielded diagnostic benefits. Growing perception and greater availability of genetic testing facilitate early identification of pathogenic ALS-related gene mutations, predictive testing and access to novel therapeutic agents in clinical trials addressing disease-modified therapies before the advent of the first clinical symptoms. Lately, personalized survival prediction models have been proposed to offer a more detailed disclosure of the prognosis for the patient. In this review, the established procedures and future directions in the diagnostics of ALS are summarized to serve as a practical guideline and to improve the diagnostic pathway of this burdensome disease.

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.