Understanding monogenic Parkinson's disease at a global scale.

Until recently, about three-quarters of all monogenic Parkinson's disease (PD) studies were performed in European/White ancestry, thereby severely limiting our insights into genotype-phenotype relationships at global scale. The first systematic approach to embrace monogenic PD worldwide, The Michael J. Fox Foundation Global Monogenic PD (MJFF GMPD) Project, contacted authors of publications reporting individuals carrying pathogenic variants in known PD-causing genes. In contrast, the Global Parkinson's Genetics Program's (GP2) Monogenic Network took a different approach by targeting PD centers not yet represented in the medical literature. Here, we describe combining both efforts in a "merger project" resulting in a global monogenic PD cohort with build-up of a sustainable infrastructure to identify the multi-ancestry spectrum of monogenic PD and enable studies of factors modifying penetrance and expression of monogenic PD. This effort demonstrates the value of future research based on team science approaches to generate comprehensive and globally relevant results.

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.

Harnessing diversity to study Alzheimer's disease: A new iPSC resource from the NIH CARD and ADNI.

The iDA Project (iPSCs to Study Diversity in Alzheimer's and Alzheimer's Disease-related Dementias) is generating 200 induced pluripotent stem cell lines from Alzheimer's Disease Neuroimaging Initiative participants. These lines are sex balanced, include common APOE genotypes, span disease stages, and are ancestrally diverse. Cell lines and characterization data will be shared openly.

GBA1 rs3115534 Is Associated with REM Sleep Behavior Disorder in Parkinson's Disease in Nigerians.

BACKGROUND: Rapid eye movement (REM) sleep behavior disorder (RBD) is an early feature of Parkinson's disease (PD) and dementia with Lewy bodies (DLB). Damaging coding variants in Glucocerebrosidase (GBA1) are a genetic risk factor for RBD. Recently, a population-specific non-coding risk variant (rs3115534) was found to be associated with PD risk and earlier onset in individuals of African ancestry. OBJECTIVES: We aimed to investigate whether the GBA1 rs3115534 PD risk variant is associated with RBD in persons with PD. METHODS: We studied 709 persons with PD and 776 neurologically healthy controls from Nigeria. All DNA samples were genotyped and imputed, and the GBA1 rs3115534 risk variant was extracted. The RBD screening questionnaire (RBDSQ) was used to assess symptoms of possible RBD. RESULTS: RBD was present in 200 PD (28.2%) and 51 (6.6%) controls. We identified that the non-coding GBA1 rs3115534 risk variant is associated with possible RBD in individuals of Nigerian origin (ß, 0.3640; standard error [SE], 0.103, P = 4.093e-04), as well as in all samples after adjusting for PD status (ß, 0.2542; SE, 0.108; P = 0.019) suggesting that although non-coding, this variant may have the same downstream consequences as GBA1 coding variants. CONCLUSIONS: Our results indicate that the non-coding GBA1 rs3115534 risk variant is associated with an increasing number of RBD symptoms in persons with PD of Nigerian origin. Further research is needed to assess if this variant is also associated with polysomnography-defined RBD and with RBD symptoms in DLB. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Assessing the lack of diversity in genetics research across neurodegenerative diseases: a systematic review of the GWAS Catalog and literature.

Importance: The under-representation of participants with non-European ancestry in genome-wide association studies (GWAS) is a critical issue that has significant implications, including hindering the progress of precision medicine initiatives. This issue is particularly significant in the context of neurodegenerative diseases (NDDs), where current therapeutic approaches have shown limited success. Addressing this under-representation is crucial to harnessing the full potential of genomic medicine in underserved communities and improving outcomes for NDD patients. Objective: Our primary objective was to assess the representation of non-European ancestry participants in genetic discovery efforts related to NDDs. We aimed to quantify the extent of inclusion of diverse ancestry groups in NDD studies and determine the number of associated loci identified in more inclusive studies. Specifically, we sought to highlight the disparities in research efforts and outcomes between studies predominantly involving European ancestry participants and those deliberately targeting non-European or multi-ancestry populations across NDDs. Evidence Review: We conducted a systematic review utilizing existing GWAS results and publications to assess the inclusion of diverse ancestry groups in neurodegeneration and neurogenetics studies. Our search encompassed studies published up to the end of 2022, with a focus on identifying research that deliberately included non-European or multi-ancestry cohorts. We employed rigorous methods for the inclusion of identified articles and quality assessment. Findings: Our review identified a total of 123 NDD GWAS. Strikingly, 82% of these studies predominantly featured participants of European ancestry. Endeavors specifically targeting non-European or multi-ancestry populations across NDDs identified only 52 risk loci. This contrasts with predominantly European studies, which reported over 90 risk loci for a single disease. Encouragingly, over 65% of these discoveries occurred in 2020 or later, indicating a recent increase in studies deliberately including non-European cohorts. Conclusions and relevance: Our findings underscore the pressing need for increased diversity in neurodegenerative research. The significant under-representation of non-European ancestry participants in NDD GWAS limits our understanding of the genetic underpinnings of these diseases. To advance the field of neurodegenerative research and develop more effective therapies, it is imperative that future investigations prioritize and harness the genomic diversity present within and across global populations.

omicSynth: An open multi-omic community resource for identifying druggable targets across neurodegenerative diseases.

Treatments for neurodegenerative disorders remain rare, but recent FDA approvals, such as lecanemab and aducanumab for Alzheimer disease (MIM: 607822), highlight the importance of the underlying biological mechanisms in driving discovery and creating disease modifying therapies. The global population is aging, driving an urgent need for therapeutics that stop disease progression and eliminate symptoms. In this study, we create an open framework and resource for evidence-based identification of therapeutic targets for neurodegenerative disease. We use summary-data-based Mendelian randomization to identify genetic targets for drug discovery and repurposing. In parallel, we provide mechanistic insights into disease processes and potential network-level consequences of gene-based therapeutics. We identify 116 Alzheimer disease, 3 amyotrophic lateral sclerosis (MIM: 105400), 5 Lewy body dementia (MIM: 127750), 46 Parkinson disease (MIM: 605909), and 9 progressive supranuclear palsy (MIM: 601104) target genes passing multiple test corrections (pSMR_multi < 2.95 × 10-6 and pHEIDI > 0.01). We created a therapeutic scheme to classify our identified target genes into strata based on druggability and approved therapeutics, classifying 41 novel targets, 3 known targets, and 115 difficult targets (of these, 69.8% are expressed in the disease-relevant cell type from single-nucleus experiments). Our novel class of genes provides a springboard for new opportunities in drug discovery, development, and repurposing in the pre-competitive space. In addition, looking at drug-gene interaction networks, we identify previous trials that may require further follow-up such as riluzole in Alzheimer disease. We also provide a user-friendly web platform to help users explore potential therapeutic targets for neurodegenerative diseases, decreasing activation energy for the community.

Mis-spliced transcripts generate de novo proteins in TDP-43-related ALS/FTD.

Functional loss of TDP-43, an RNA binding protein genetically and pathologically linked to amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), leads to the inclusion of cryptic exons in hundreds of transcripts during disease. Cryptic exons can promote the degradation of affected transcripts, deleteriously altering cellular function through loss-of-function mechanisms. Here, we show that mRNA transcripts harboring cryptic exons generated de novo proteins in TDP-43-depleted human iPSC-derived neurons in vitro, and de novo peptides were found in cerebrospinal fluid (CSF) samples from patients with ALS or FTD. Using coordinated transcriptomic and proteomic studies of TDP-43-depleted human iPSC-derived neurons, we identified 65 peptides that mapped to 12 cryptic exons. Cryptic exons identified in TDP-43-depleted human iPSC-derived neurons were predictive of cryptic exons expressed in postmortem brain tissue from patients with TDP-43 proteinopathy. These cryptic exons produced transcript variants that generated de novo proteins. We found that the inclusion of cryptic peptide sequences in proteins altered their interactions with other proteins, thereby likely altering their function. Last, we showed that 18 de novo peptides across 13 genes were present in CSF samples from patients with ALS/FTD spectrum disorders. The demonstration of cryptic exon translation suggests new mechanisms for ALS/FTD pathophysiology downstream of TDP-43 dysfunction and may provide a potential strategy to assay TDP-43 function in patient CSF.

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.

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

Although over 90 independent risk variants have been identified for Parkinson's disease using genome-wide association studies, most studies have been performed in just one population at a time. Here we performed a large-scale multi-ancestry meta-analysis of Parkinson's disease with 49,049 cases, 18,785 proxy cases and 2,458,063 controls including individuals of European, East Asian, Latin American and African ancestry. In a meta-analysis, we identified 78 independent genome-wide significant loci, including 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300 and PPP6R2) and fine-mapped 6 putative causal variants at 6 known PD loci. By combining our results with publicly available eQTL data, we identified 25 putative risk genes in these novel loci whose expression is associated with PD risk. This work lays the groundwork for future efforts aimed at identifying PD loci in non-European populations.

The non-coding GBA1 rs3115534 variant is associated with REM sleep behavior disorder in Nigerians.

Background: Damaging coding variants in GBA1 are a genetic risk factor for rapid eye movement sleep behavior disorder (RBD), which is a known early feature of synucleinopathies. Recently, a population-specific non-coding variant (rs3115534) was found to be associated with PD risk and earlier disease onset in individuals of African ancestry. Objectives: To investigate whether the GBA1 rs3115534 PD risk variant is associated with RBD. Methods: We studied 709 persons with PD and 776 neurologically healthy controls from Nigeria. The GBA1 rs3115534 risk variant status was imputed from previous genotyping for all. Symptoms of RBD were assessed with the RBD screening questionnaire (RBDSQ). Results: The non-coding GBA1 rs3115534 risk variant is associated with possible RBD in individuals of Nigerian origin (Beta = 0.3640, SE = 0.103, P =4.093e-04), as well as after adjusting for PD status (Beta = 0.2542, SE = 0.108, P = 0.019) suggesting that this variant may have the same downstream consequences as GBA1 coding variants. Conclusions: We show that the non-coding GBA1 rs3115534 risk variant is associated with increased RBD symptomatology in Nigerians with PD. Further research is required to assess association with polysomnography-defined RBD.

Human brain single nucleus cell type enrichments in neurodegenerative diseases.

Background: Single-cell RNA sequencing has opened a window into clarifying the complex underpinnings of disease, particularly in quantifying the relevance of tissue- and cell-type-specific gene expression. Methods: To identify the cell types and genes important to therapeutic target development across the neurodegenerative disease spectrum, we leveraged genome-wide association studies, recent single-cell sequencing data, and bulk expression studies in a diverse series of brain region tissues. Results: We were able to identify significant immune-related cell types in the brain across three major neurodegenerative diseases: Alzheimer's disease, amyotrophic lateral sclerosis, and Parkinson's disease. Subsequently, putative roles of 30 fine-mapped loci implicating seven genes in multiple neurodegenerative diseases and their pathogenesis were identified. Conclusions: We have helped refine the genetic regions and cell types effected across multiple neurodegenerative diseases, helping focus future translational research efforts.

Sleep disturbances as risk factors for neurodegeneration later in life.

The relationship between sleep disorders and neurodegeneration is complex and multi-faceted. Using over one million electronic health records (EHRs) from Wales, UK, and Finland, we mined biobank data to identify the relationships between sleep disorders and the subsequent manifestation of neurodegenerative diseases (NDDs) later in life. We then examined how these sleep disorders' severity impacts neurodegeneration risk. Additionally, we investigated how sleep attributed risk may compensate for the lack of genetic risk factors (i.e. a lower polygenic risk score) in NDD manifestation. We found that sleep disorders such as sleep apnea were associated with the risk of Alzheimer's disease (AD), amyotrophic lateral sclerosis, dementia, Parkinson's disease (PD), and vascular dementia in three national scale biobanks, with hazard ratios (HRs) ranging from 1.31 for PD to 5.11 for dementia. These sleep disorders imparted significant risk up to 15 years before the onset of an NDD. Cumulative number of sleep disorders in the EHRs were associated with a higher risk of neurodegeneration for dementia and vascular dementia. Sleep related risk factors were independent of genetic risk for Alzheimer's and Parkinson's, potentially compensating for low genetic risk in overall disease etiology. There is a significant multiplicative interaction regarding the combined risk of sleep disorders and Parkinson's disease. Poor sleep hygiene and sleep apnea are relatively modifiable risk factors with several treatment options, including CPAP and surgery, that could potentially reduce the risk of neurodegeneration. This is particularly interesting in how sleep related risk factors are significantly and independently enriched in manifesting NDD patients with low levels of genetic risk factors for these diseases.

Genetics of NLRP3 suggests lack of involvement and inefficient druggability in Parkinson's disease.

Activation of the NLRP3-inflammasome has been proposed to play a role in Parkinson's disease pathogenesis based on in vitro and in vivo studies. Currently, clinical trials targeting the NLRP3 pathway in Parkinson's disease are at early stages. However, the evidence supporting NLRP3's involvement in Parkinson's disease from human genetics data remains limited. In this study, we conducted comprehensive analyses of common and rare variants in genes related to the NLRP3-inflammasome in large Parkinson's disease cohorts. Furthermore, we performed pathway-specific analyses using polygenic risk scores and studied potential causal associations using Mendelian randomization with the NLRP3 components and the cytokines released by its activation, IL-1ß and IL-18. Our findings showed no associations of common or rare variants, nor of the pathway polygenic risk score for the NLRP3 inflammasome, with risk of Parkinson's disease. Mendelian randomization analyses suggest that altering the expression of the NLRP3 inflammasome, IL-1ß or IL-18, is not likely to affect Parkinson's disease risk, age-at-onset, or progression. Therefore, our results do not support an important role for the NLRP3 inflammasome in Parkinson's disease pathogenesis or as a strong target for drug development.

Defining the causes of sporadic Parkinson's disease in the global Parkinson's genetics program (GP2).

The Global Parkinson's Genetics Program (GP2) will genotype over 150,000 participants from around the world, and integrate genetic and clinical data for use in large-scale analyses to dramatically expand our understanding of the genetic architecture of PD. This report details the workflow for cohort integration into the complex arm of GP2, and together with our outline of the monogenic hub in a companion paper, provides a generalizable blueprint for establishing large scale collaborative research consortia.

A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline.

Here, we present a standardized, "off-the-shelf" proteomics pipeline working in a single 96-well plate to achieve deep coverage of cellular proteomes with high throughput and scalability. This integrated pipeline streamlines a fully automated sample preparation platform, a data-independent acquisition (DIA) coupled with high-field asymmetric waveform ion mobility spectrometer (FAIMS) interface, and an optimized library-free DIA database search strategy. Our systematic evaluation of FAIMS-DIA showing single compensation voltage (CV) at -35 V not only yields the deepest proteome coverage but also best correlates with DIA without FAIMS. Our in-depth comparison of direct-DIA database search engines shows that Spectronaut outperforms others, providing the highest quantifiable proteins. Next, we apply three common DIA strategies in characterizing human induced pluripotent stem cell (iPSC)-derived neurons and show single-shot mass spectrometry (MS) using single-CV (-35 V)-FAIMS-DIA results in >9,000 quantifiable proteins with <10% missing values, as well as superior reproducibility and accuracy compared with other existing DIA methods.

Divergent patterns of healthy aging across human brain regions at single-cell resolution reveal links to neurodegenerative disease.

Age is a major common risk factor underlying neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. Previous studies reported that chronological age correlates with differential gene expression across different brain regions. However, prior datasets have not disambiguated whether expression associations with age are due to changes in cell numbers and/or gene expression per cell. In this study, we leveraged single nucleus RNA-sequencing (snRNAseq) to examine changes in cell proportions and transcriptomes in four different brain regions, each from 12 donors aged 20-30 years (young) or 60-85 years (old). We sampled 155,192 nuclei from two cortical regions (entorhinal cortex and middle temporal gyrus) and two subcortical regions (putamen and subventricular zone) relevant to neurodegenerative diseases or the proliferative niche. We found no changes in cellular composition of different brain regions with healthy aging. Surprisingly, we did find that each brain region has a distinct aging signature, with only minor overlap in differentially associated genes across regions. Moreover, each cell type shows distinct age-associated expression changes, including loss of protein synthesis genes in cortical inhibitory neurons, axonogenesis genes in excitatory neurons and oligodendrocyte precursor cells, enhanced gliosis markers in astrocytes and disease-associated markers in microglia, and genes critical for neuron-glia communication. Importantly, we find cell type-specific enrichments of age associations with genes nominated by Alzheimer's disease and Parkinson's disease genome-wide association studies (GWAS), such as apolipoprotein E (APOE), and leucine-rich repeat kinase 2 (LRRK2) in microglia that are independent of overall expression levels across cell types. We present this data as a new resource which highlights, first, region- and cell type-specific transcriptomic changes in healthy aging that may contribute to selective vulnerability and, second, provide context for testing GWAS-nominated disease risk genes in relevant subtypes and developing more targeted therapeutic strategies. The data is readily accessible without requirement for extensive computational support in a public website, https://brainexp-hykyffa56a-uc.a.run.app/.

Genome-Wide Meta-Analysis of Cerebrospinal Fluid Biomarkers in Alzheimer's Disease and Parkinson's Disease Cohorts.

BACKGROUND: Amyloid-ß, phosphorylated tau (p-tau), and total tau (t-tau) in cerebrospinal fluid are established biomarkers for Alzheimer's disease (AD). In other neurodegenerative diseases, such as Parkinson's disease (PD), these biomarkers have also been found to be altered, and the molecular mechanisms responsible for these alterations are still under investigation. Moreover, the interplay between these mechanisms and the diverse underlying disease states remains to be elucidated. OBJECTIVE: To investigate genetic contributions to the AD biomarkers and assess the commonality and heterogeneity of the associations per underlying disease status. METHODS: We conducted genome-wide association studies (GWASs) for the AD biomarkers on subjects from the Parkinson's Progression Markers Initiative, the Fox Investigation for New Discovery of Biomarkers, and the Alzheimer's Disease Neuroimaging Initiative, and meta-analyzed with the largest AD GWAS. We tested heterogeneity of associations of interest between different disease statuses (AD, PD, and control). RESULTS: We observed three GWAS signals: the APOE locus for amyloid-ß, the 3q28 locus between GEMC1 and OSTN for p-tau and t-tau, and the 7p22 locus (top hit: rs60871478, an intronic variant for DNAAF5, also known as HEATR2) for p-tau. The 7p22 locus is novel and colocalized with the brain DNAAF5 expression. Although no heterogeneity from underlying disease status was observed for the earlier GWAS signals, some disease risk loci suggested disease-specific associations with these biomarkers. CONCLUSIONS: Our study identified a novel association at the intronic region of DNAAF5 associated with increased levels of p-tau across all diseases. We also observed some disease-specific genetic associations with these biomarkers. Published 2023. This article is a U.S. Government work and is in the public domain in the USA.

Genome-wide meta-analysis of CSF biomarkers in Alzheimer's disease and Parkinson's disease cohorts.

Background: Amyloid beta (Aß), phosphorylated tau (p-tau), and total tau (t-tau) in cerebrospinal fluid are established biomarkers for Alzheimer's disease (AD). In other neurodegenerative diseases, such as Parkinson's disease (PD), these biomarkers have also been found to be altered, and the molecular mechanisms responsible for these alterations are still under investigation. Moreover, the interplay between these mechanisms and the diverse underlying disease states remains to be elucidated. Objectives: To investigate genetic contributions to the AD biomarkers and assess the commonality and heterogeneity of the associations per underlying disease status. Methods: We conducted GWAS for the AD biomarkers on subjects from the Parkinson's Progression Markers Initiative (PPMI), the Fox Investigation for New Discovery of Biomarkers (BioFIND), and the Alzheimer's Disease Neuroimaging Initiative (ADNI) and meta-analyzed with the largest AD GWAS.[7] We tested heterogeneity of associations of interest between different disease statuses (AD, PD, and control). Results: We observed three GWAS signals: the APOE locus for Aß, the 3q28 locus between GEMC1 and OSTN for p-tau and t-tau, and the 7p22 locus (top hit: rs60871478, an intronic variant for DNAAF5 , also known as HEATR2 ) for p-tau. The 7p22 locus is novel and co-localized with the brain DNAAF5 expression. While no heterogeneity from underlying disease status was observed for the above GWAS signals, some disease risk loci suggested disease specific associations with these biomarkers. Conclusions: Our study identified a novel association at the intronic region of DNAAF5 associated with increased levels of p-tau across all diseases. We also observed some disease specific genetic associations with these biomarkers.

Application of Aligned-UMAP to longitudinal biomedical studies.

High-dimensional data analysis starts with projecting the data to low dimensions to visualize and understand the underlying data structure. Several methods have been developed for dimensionality reduction, but they are limited to cross-sectional datasets. The recently proposed Aligned-UMAP, an extension of the uniform manifold approximation and projection (UMAP) algorithm, can visualize high-dimensional longitudinal datasets. We demonstrated its utility for researchers to identify exciting patterns and trajectories within enormous datasets in biological sciences. We found that the algorithm parameters also play a crucial role and must be tuned carefully to utilize the algorithm's potential fully. We also discussed key points to remember and directions for future extensions of Aligned-UMAP. Further, we made our code open source to enhance the reproducibility and applicability of our work. We believe our benchmarking study becomes more important as more and more high-dimensional longitudinal data in biomedical research become available.