Multi-ancestry genome-wide association meta-analysis of Parkinson's disease

The Black and African American Connections to Parkinson's Disease (BLAAC PD) study protocol

Determining the genetic contributions to Parkinson's disease (PD) across diverse ancestries is a high priority as this work can guide therapeutic development in a global setting. The genetics of PD spans the etiological risk spectrum, from rare, highly deleterious variants linked to monogenic forms with Mendelian patterns of inheritance, to common variation involved in sporadic disease. A major limitation in PD genomics research is lack of racial and ethnic diversity. Enrollment disparities have detrimental consequences on the generalizability of results and exacerbate existing inequities in care. The Black and African American Connections to Parkinson's Disease (BLAAC PD) study is part of the Global Parkinson's Genetics Program, supported by the Aligning Science Across Parkinson's initiative. The goal of the study is to investigate the genetic architecture underlying PD risk and progression in the Black and/or African American populations. This cross-sectional multicenter study in the United States has a recruitment target of up to 2,000 individuals with PD and up to 2,000 controls, all of Black and/or African American ancestry. The study design incorporates several strategies to reduce barriers to research participation. The multifaceted recruitment strategy aims to involve individuals with and without PD in various settings, emphasizing community outreach and engagement. The BLAAC PD study is an important first step toward informing understanding of the genetics of PD in a more diverse population.

Plasma acellular transcriptome contains Parkinson's disease signatures that can inform clinical diagnosis

We aimed to identify plasma cell-free transcripts (cfRNA) associated with Parkinson's disease (PD) that also have a high predictive value to differentiate PD from healthy controls. Leveraging two independent populations from two different movement disorder centers we identified 2,188 differentially expressed cfRNAs after meta-analysis. The identified transcripts were enriched in PD relevant pathways, such as PD (p=9.26×10-4), ubiquitin-mediated proteolysis (p=7.41×10-5) and endocytosis (p=4.21×10-6). Utilizing in-house and publicly available brain, whole blood, and acellular plasma transcriptomic and proteomic PD datasets, we found significant overlap across dysregulated biological species in the different tissues and the different biological layers. We developed three predictive models containing increasing number of transcripts that can distinguish PD from healthy control with an area under the ROC Curve (AUC) ≥0.85. Finally, we showed that several of the predictive transcripts significantly correlate with symptom severity measured by UPDRS-III. Overall, we have demonstrated that cfRNA contains pathological signatures and has the potential to be utilized as biomarker to aid in PD diagnostics and monitoring.

A network-based systems genetics framework identifies pathobiology and drug repurposing in Parkinson's disease

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder. However, current treatments are directed at symptoms and lack ability to slow or prevent disease progression. Large-scale genome-wide association studies (GWAS) have identified numerous genomic loci associated with PD, which may guide the development of disease-modifying treatments. We presented a systems genetics approach to identify potential risk genes and repurposable drugs for PD. First, we leveraged non-coding GWAS loci effects on multiple human brain-specific quantitative trait loci (xQTLs) under the protein-protein interactome (PPI) network. We then prioritized a set of PD likely risk genes (pdRGs) by integrating five types of molecular xQTLs: expression (eQTLs), protein (pQTLs), splicing (sQTLs), methylation (meQTLs), and histone acetylation (haQTLs). We also integrated network proximity-based drug repurposing and patient electronic health record (EHR) data observations to propose potential drug candidates for PD treatments. We identified 175 pdRGs from QTL-regulated GWAS findings, such as SNCA, CTSB, LRRK2, DGKQ, CD38 and CD44. Multi-omics data validation revealed that the identified pdRGs are likely to be druggable targets, differentially expressed in multiple cell types and impact both the parkin ubiquitin-proteasome and alpha-synuclein (a-syn) pathways. Based on the network proximity-based drug repurposing followed by EHR data validation, we identified usage of simvastatin as being significantly associated with reduced incidence of PD (fall outcome: hazard ratio (HR) = 0.91, 95% confidence interval (CI): 0.87-0.94; for dementia outcome: HR = 0.88, 95% CI: 0.86-0.89), after adjusting for 267 covariates. Our network-based systems genetics framework identifies potential risk genes and repurposable drugs for PD and other neurodegenerative diseases if broadly applied.

Unveiling differential gene co-expression networks and its effects on levodopa-induced dyskinesia

Levodopa-induced dyskinesia (LID) refers to involuntary motor movements of chronic use of levodopa in Parkinson's disease (PD) that negatively impact the overall well-being of people with this disease. The molecular mechanisms involved in LID were investigated through whole-blood transcriptomic analysis for differential gene expression and identification of new co-expression and differential co-expression networks. We found six differentially expressed genes in patients with LID, and 13 in patients without LID. We also identified 12 co-expressed genes exclusive to LID, and six exclusive hub genes involved in 23 gene-gene interactions in patients with LID. Convergently, we identified novel genes associated with PD and LID that play roles in mitochondrial dysfunction, dysregulation of lipid metabolism, and neuroinflammation. We observed significant changes in disease progression, consistent with previous findings of maladaptive plastic changes in the basal ganglia leading to the development of LID, including a chronic pro-inflammatory state in the brain.

Clinical, mechanistic, biomarker, and therapeutic advances in GBA1-associated Parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disease. The development of PD is closely linked to genetic and environmental factors, with GBA1 variants being the most common genetic risk. Mutations in the GBA1 gene lead to reduced activity of the coded enzyme, glucocerebrosidase, which mediates the development of PD by affecting lipid metabolism (especially sphingolipids), lysosomal autophagy, endoplasmic reticulum, as well as mitochondrial and other cellular functions. Clinically, PD with GBA1 mutations (GBA1-PD) is characterized by particular features regarding the progression of symptom severity. On the therapeutic side, the discovery of the relationship between GBA1 variants and PD offers an opportunity for targeted therapeutic interventions. In this review, we explore the genotypic and phenotypic correlations, etiologic mechanisms, biomarkers, and therapeutic approaches of GBA1-PD and summarize the current state of research and its challenges.

Single-nucleus multiome analysis of human cerebellum in Alzheimer's disease-related dementia

Although human cerebellum is known to be neuropathologically impaired in Alzheimer's disease (AD) and AD-related dementias (ADRD), the cell type-specific transcriptional and epigenomic changes that contribute to this pathology are not well understood. Here, we report single-nucleus multiome (snRNA-seq and snATAC-seq) analysis of 103,861 nuclei isolated from cerebellum from 9 human cases of AD/ADRD and 8 controls, and with frontal cortex of 6 AD donors for additional comparison. Using peak-to-gene linkage analysis, we identified 431,834 significant linkages between gene expression and cell subtype-specific chromatin accessibility regions enriched for candidate cis-regulatory elements (cCREs). These cCREs were associated with AD/ADRD-specific transcriptomic changes and disease-related gene regulatory networks, especially for RAR Related Orphan Receptor A (RORA) and E74 Like ETS Transcription Factor 1 (ELF1) in cerebellar Purkinje cells and granule cells, respectively. Trajectory analysis of granule cell populations further identified disease-relevant transcription factors, such as RORA, and their regulatory targets. Finally, we prioritized two likely causal genes, including Seizure Related 6 Homolog Like 2 (SEZ6L2) in Purkinje cells and KAT8 Regulatory NSL Complex Subunit 1 (KANSL1) in granule cells, through integrative analysis of cCREs derived from snATAC-seq, genome-wide AD/ADRD loci, and Hi-C looping data. This first cell subtype-specific regulatory landscape in the human cerebellum identified here offer novel genomic and epigenomic insights into the neuropathology and pathobiology of AD/ADRD and other neurological disorders if broadly applied.

Daytime napping and the incidence of Parkinson's disease: a prospective cohort study with Mendelian randomization

BACKGROUND

The causal relationship between daytime napping and the risk of Parkinson's disease (PD) remains unclear, with prospective studies providing limited evidence. This study investigated the association between daytime napping frequency and duration and PD incidence and explored the causality relationship between this association by conducting Mendelian randomization (MR) analysis.

METHODS

This prospective cohort study included 393,302 participants, and accelerometer-measured daytime napping data were available only for 78,141 individuals. Cox proportional hazards regression was used to estimate the association between the daytime napping frequency and duration and the PD risk. The role of the systemic immune-inflammation index (SII) in the association between daytime napping frequency and PD risk was assessed through mediation analyses. Moreover, the causal association between the daytime napping frequency and the PD risk was preliminarily explored by conducting two-sample MR analyses.

RESULTS

The median follow-up duration was 12.18 years. The participants who reported napping sometimes or usually exhibited a significantly higher PD risk than those who never/rarely napped during the day [sometimes: hazard ratio (HR), 1.13; 95% confidence interval (CI), 1.03-1.23; usually: HR, 1.33; 95% CI, 1.14-1.55], and SII played a mediating role in this association. However, the MR analyses did not indicate that the daytime napping frequency and PD risk were significantly associated. The participants napping for over 1 h exhibited a significantly elevated PD risk (HR, 1.54; 95% CI, 1.11-2.16). Moreover, no significant interaction was identified between napping frequency or duration and genetic susceptibility to PD (P for interaction > 0.05).

CONCLUSIONS

In this study, increased daytime napping frequency and duration were associated with an increased PD risk, but no causal relationship was observed between napping frequency and PD risk in the MR analysis. Larger GWAS-based cohort studies and MR studies are warranted to explore potential causal relationships.

The Genetic Architecture of the Human Corpus Callosum and its Subregions

The corpus callosum (CC) is the largest set of white matter fibers connecting the two hemispheres of the brain. In humans, it is essential for coordinating sensorimotor responses, performing associative/executive functions, and representing information in multiple dimensions. Understanding which genetic variants underpin corpus callosum morphometry, and their shared influence on cortical structure and susceptibility to neuropsychiatric disorders, can provide molecular insights into the CC's role in mediating cortical development and its contribution to neuropsychiatric disease. To characterize the morphometry of the midsagittal corpus callosum, we developed a publicly available artificial intelligence based tool to extract, parcellate, and calculate its total and regional area and thickness. Using the UK Biobank (UKB) and the Adolescent Brain Cognitive Development study (ABCD), we extracted measures of midsagittal corpus callosum morphometry and performed a genome-wide association study (GWAS) meta-analysis of European participants (combined N = 46,685). We then examined evidence for generalization to the non-European participants of the UKB and ABCD cohorts (combined N = 7,040). Post-GWAS analyses implicate prenatal intracellular organization and cell growth patterns, and high heritability in regions of open chromatin, suggesting transcriptional activity regulation in early development. Results suggest programmed cell death mediated by the immune system drives the thinning of the posterior body and isthmus. Global and local genetic overlap, along with causal genetic liability, between the corpus callosum, cerebral cortex, and neuropsychiatric disorders such as attention-deficit/hyperactivity and bipolar disorders were identified. These results provide insight into variability of corpus callosum development, its genetic influence on the cerebral cortex, and biological mechanisms related to neuropsychiatric dysfunction.

Single-nucleus multi-omics of Parkinson's disease reveals a glutamatergic neuronal subtype susceptible to gene dysregulation via alteration of transcriptional networks

The genetic architecture of Parkinson's disease (PD) is complex and multiple brain cell subtypes are involved in the neuropathological progression of the disease. Here we aimed to advance our understanding of PD genetic complexity at a cell subtype precision level. Using parallel single-nucleus (sn)RNA-seq and snATAC-seq analyses we simultaneously profiled the transcriptomic and chromatin accessibility landscapes in temporal cortex tissues from 12 PD compared to 12 control subjects at a granular single cell resolution. An integrative bioinformatic pipeline was developed and applied for the analyses of these snMulti-omics datasets. The results identified a subpopulation of cortical glutamatergic excitatory neurons with remarkably altered gene expression in PD, including differentially-expressed genes within PD risk loci identified in genome-wide association studies (GWAS). This was the only neuronal subtype showing significant and robust overexpression of SNCA. Further characterization of this neuronal-subpopulation showed upregulation of specific pathways related to axon guidance, neurite outgrowth and post-synaptic structure, and downregulated pathways involved in presynaptic organization and calcium response. Additionally, we characterized the roles of three molecular mechanisms in governing PD-associated cell subtype-specific dysregulation of gene expression: (1) changes in cis-regulatory element accessibility to transcriptional machinery; (2) changes in the abundance of master transcriptional regulators, including YY1, SP3, and KLF16; (3) candidate regulatory variants in high linkage disequilibrium with PD-GWAS genomic variants impacting transcription factor binding affinities. To our knowledge, this study is the first and the most comprehensive interrogation of the multi-omics landscape of PD at a cell-subtype resolution. Our findings provide new insights into a precise glutamatergic neuronal cell subtype, causal genes, and non-coding regulatory variants underlying the neuropathological progression of PD, paving the way for the development of cell- and gene-targeted therapeutics to halt disease progression as well as genetic biomarkers for early preclinical diagnosis.

An Overview of Epigenetic Changes in the Parkinson's Disease Brain

Parkinson's disease is a progressive neurodegenerative disorder, predominantly of the motor system. Although some genetic components and cellular mechanisms of Parkinson's have been identified, much is still unknown. In recent years, emerging evidence has indicated that non-DNA-sequence variation (in particular epigenetic mechanisms) is likely to play a crucial role in the development and progression of the disease. Here, we present an up-to-date overview of epigenetic processes including DNA methylation, DNA hydroxymethylation, histone modifications and non-coding RNAs implicated in the brain of those with Parkinson's disease. We will also discuss the limitations of current epigenetic research in Parkinson's disease, the advantages of simultaneously studying genetics and epigenetics, and putative novel epigenetic therapies.

Key genes and convergent pathogenic mechanisms in Parkinson disease

Parkinson disease (PD) is a neurodegenerative disorder marked by the preferential dysfunction and death of dopaminergic neurons in the substantia nigra. The onset and progression of PD is influenced by a diversity of genetic variants, many of which lack functional characterization. To identify the most high-yield targets for therapeutic intervention, it is important to consider the core cellular compartments and functional pathways upon which the varied forms of pathogenic dysfunction may converge. Here, we review several key PD-linked proteins and pathways, focusing on the mechanisms of their potential convergence in disease pathogenesis. These dysfunctions primarily localize to a subset of subcellular compartments, including mitochondria, lysosomes and synapses. We discuss how these pathogenic mechanisms that originate in different cellular compartments may coordinately lead to cellular dysfunction and neurodegeneration in PD.

Towards a Global View of Parkinson's Disease Genetics

Parkinson's disease (PD) is a global health challenge, yet historically studies of PD have taken place predominantly in European populations. Recent genetics research conducted in non-European populations has revealed novel population-specific genetic loci linked to PD risk, highlighting the importance of studying PD globally. These insights have broadened our understanding of PD etiology, which is crucial for developing disease-modifying interventions. This review comprehensively explores the global genetic landscape of PD, emphasizing the scientific rationale for studying underrepresented populations. It underscores challenges, such as genotype-phenotype heterogeneity and inclusion difficulties for non-European participants, emphasizing the ongoing need for diverse and inclusive research in PD. ANN NEUROL 2024;95:831-842.

Molecular and cellular mechanisms of selective vulnerability in neurodegenerative diseases

The selective vulnerability of specific neuronal subtypes is a hallmark of neurodegenerative diseases. In this Review, I summarize our current understanding of the brain regions and cell types that are selectively vulnerable in different neurodegenerative diseases and describe the proposed underlying cell-autonomous and non-cell-autonomous mechanisms. I highlight how recent methodological innovations - including single-cell transcriptomics, CRISPR-based screens and human cell-based models of disease - are enabling new breakthroughs in our understanding of selective vulnerability. An understanding of the molecular mechanisms that determine selective vulnerability and resilience would shed light on the key processes that drive neurodegeneration and point to potential therapeutic strategies to protect vulnerable cell populations.

Novel Variants Linked to the Prodromal Stage of Parkinson's Disease (PD) Patients

BACKGROUND AND OBJECTIVE

The symptoms of most neurodegenerative diseases, including Parkinson's disease (PD), usually do not occur until substantial neuronal loss occurs. This makes the process of early diagnosis very challenging. Hence, this research used variant call format (VCF) analysis to detect variants and novel genes that could be used as prognostic indicators in the early diagnosis of prodromal PD.

MATERIALS AND METHODS

Data were obtained from the Parkinson's Progression Markers Initiative (PPMI), and we analyzed prodromal patients with gVCF data collected in the 2021 cohort. A total of 304 participants were included, including 100 healthy controls, 146 prodromal genetic individuals, 21 prodromal hyposmia individuals, and 37 prodromal individuals with RBD. A pipeline was developed to process the samples from gVCF to reach variant annotation and pathway and disease association analysis.

RESULTS

Novel variant percentages were detected in the analyzed prodromal subgroups. The prodromal subgroup analysis revealed novel variations of 1.0%, 1.2%, 0.6%, 0.3%, 0.5%, and 0.4% for the genetic male, genetic female, hyposmia male, hyposmia female, RBD male, and RBD female groups, respectively. Interestingly, 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300, and PPP6R2) that were recently detected in PD patients were detected in the prodromal stage of PD.

CONCLUSIONS

Genetic biomarkers are crucial for the early detection of Parkinson's disease and its prodromal stage. The novel PD genes detected in prodromal patients could aid in the use of gene biomarkers for early diagnosis of the prodromal stage without relying only on phenotypic traits.

The Role of Structural Variants in the Genetic Architecture of Parkinson's Disease

Parkinson's disease (PD) significantly impacts millions of individuals worldwide. Although our understanding of the genetic foundations of PD has advanced, a substantial portion of the genetic variation contributing to disease risk remains unknown. Current PD genetic studies have primarily focused on one form of genetic variation, single nucleotide variants (SNVs), while other important forms of genetic variation, such as structural variants (SVs), are mostly ignored due to the complexity of detecting these variants with traditional sequencing methods. Yet, these forms of genetic variation play crucial roles in gene expression and regulation in the human brain and are causative of numerous neurological disorders, including forms of PD. This review aims to provide a comprehensive overview of our current understanding of the involvement of coding and noncoding SVs in the genetic architecture of PD.

Federated learning for multi-omics: A performance evaluation in Parkinson's disease

While machine learning (ML) research has recently grown more in popularity, its application in the omics domain is constrained by access to sufficiently large, high-quality datasets needed to train ML models. Federated learning (FL) represents an opportunity to enable collaborative curation of such datasets among participating institutions. We compare the simulated performance of several models trained using FL against classically trained ML models on the task of multi-omics Parkinson's disease prediction. We find that FL model performance tracks centrally trained ML models, where the most performant FL model achieves an AUC-PR of 0.876 ± 0.009, 0.014 ± 0.003 less than its centrally trained variation. We also determine that the dispersion of samples within a federation plays a meaningful role in model performance. Our study implements several open-source FL frameworks and aims to highlight some of the challenges and opportunities when applying these collaborative methods in multi-omics studies.

Interpretation of Neurodegenerative GWAS Risk Alleles in Microglia and their Interplay with Other Cell Types

Microglia have been implicated in numerous neurodegenerative and neuroinflammatory disorders; however, the causal contribution of this immune cell type is frequently debated. Genetic studies offer a unique vantage point in that they infer causality over a secondary consequence. Genome-wide association studies (GWASs) have identified hundreds of loci in the genome that are associated with susceptibility to neurodegenerative disorders. GWAS studies implicate microglia in the pathogenesis of Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), and to a lesser degree suggest a role for microglia in vascular dementia (VaD), frontotemporal dementia (FTD), and amyotrophic lateral sclerosis (ALS), and other neurodegenerative and neuropsychiatric disorders. The contribution and function of GWAS risk loci on disease progression is an ongoing field of study, in which large genomic datasets, and an extensive framework of computational tools, have proven to be crucial. Several GWAS risk loci are shared between disorders, pointing towards common pleiotropic mechanisms. In this chapter, we introduce key concepts in GWAS and post-GWAS interpretation of neurodegenerative disorders, with a focus on GWAS risk genes implicated in microglia, their interplay with other cell types and shared convergence of GWAS risk loci on microglia.

Combining Biomarkers with Genetics In Prodromal/Earliest Phase Parkinson's Disease

 Family studies have linked several rare genetic variants to hereditary forms of Parkinson's disease (PD). In addition to these monogenic forms, many PD cases are associated with genetic risk factors. Asymptomatic individuals carrying pathogenic variants linked to PD are at risk of developing the disease later in life, thereby providing a unique opportunity for the detection of the earliest pathophysiological and later clinical changes and, importantly, also of protective and compensatory features and mechanisms. However, the rarity of monogenic PD-causing variants is a major challenge of this approach. In this review, we discuss recent advances in the search for biomarkers in the prodromal/earliest phase of genetically linked PD.

Parkinson's Disease Drug Therapies in the Clinical Trial Pipeline: 2024 Update

Background

For the past five years, our annual reports have been tracking the clinical development of new drug-based therapies for the neurodegenerative condition of Parkinson's disease (PD). These reviews have followed the progress both of "symptomatic treatments" (ST - improves/reduces symptoms of the condition) and "disease-modifying treatments" (DMT - attempts to delay/slow progression by addressing the underlying biology of PD). Efforts have also been made to further categorize these experimental treatments based on their mechanisms of action and class of drug.

Methods

A dataset of clinical trials for drug therapies in PD using trial data downloaded from the ClinicalTrials.gov online registry was generated. A breakdown analysis of all the studies that were active as of January 31st, 2024, was conducted. This analysis involved categorizing the trials based on both the mechanism of action (MOA) and the drug target.

Results

There were 136 active Phase 1-3 trials evaluating drug therapies for PD registered on ClinicalTrials.gov, as of January 31, 2024. Of these trials, 76 (56%) were classified as ST trials and 60 (44%) were designated DMT. More than half (58%) of the trials were in Phase 2 testing stage, followed by Phase 1 (30%) and Phase 3 (12%). 35 of the trials were registered since our last report, with the remaining 101 trials appearing in at least one earlier report.

Conclusions

The drug development pipeline for PD remains in a robust state with a wide variety of approaches being developed and evaluated in Phase 1 and 2. Yet again, however, only a limited number of DMTs are transitioning to Phase 3.

Parkinson's Disease is Predominantly a Genetic Disease

The discovery of a pathogenic variant in the alpha-synuclein (SNCA) gene in the Contursi kindred in 1997 indisputably confirmed a genetic cause in a subset of Parkinson's disease (PD) patients. Currently, pathogenic variants in one of the seven established PD genes or the strongest known risk factor gene, GBA1, are identified in ∼15% of PD patients unselected for age at onset and family history. In this Debate article, we highlight multiple avenues of research that suggest an important - and in some cases even predominant - role for genetics in PD aetiology, including familial clustering, high rates of monogenic PD in selected populations, and complete penetrance with certain forms. At first sight, the steep increase in PD prevalence exceeding that of other neurodegenerative diseases may argue against a predominant genetic etiology. Notably, the principal genetic contribution in PD is conferred by pathogenic variants in LRRK2 and GBA1 and, in both cases, characterized by an overall late age of onset and age-related penetrance. In addition, polygenic risk plays a considerable role in PD. However, it is likely that, in the majority of PD patients, a complex interplay of aging, genetic, environmental, and epigenetic factors leads to disease development.

Louis EK, Noyce AJ. Ethical Considerations for Identifying Individuals in the Prodromal/Early Phase of Parkinson's Disease: A Narrative Review

The ability to identify individuals in the prodromal phase of Parkinson's disease has improved in recent years, raising the question of whether and how those affected should be informed about the risk of future disease. Several studies investigated prognostic counselling for individuals with isolated REM sleep behavior disorder and have shown that most patients want to receive information about prognosis, but autonomy and individual preferences must be respected. However, there are still many unanswered questions about risk disclosure or early diagnosis of PD, including the impact on personal circumstances, cultural preferences and specific challenges associated with different profiles of prodromal symptoms, genetic testing or biomarker assessments. This narrative review aims to summarize the current literature on prognostic counselling and risk disclosure in PD, as well as highlight future perspectives that may emerge with the development of new biomarkers and their anticipated impact on the definition of PD.