A cross-sectional study of α-synuclein seed amplification assay in Alzheimer's disease neuroimaging initiative: Prevalence and associations with Alzheimer's disease biomarkers and cognitive function

INTRODUCTION

Alzheimer's disease (AD) pathology is defined by β-amyloid (Aβ) plaques and neurofibrillary tau, but Lewy bodies (LBs; 𝛼-synuclein aggregates) are a common co-pathology for which effective biomarkers are needed.

METHODS

A validated α-synuclein Seed Amplification Assay (SAA) was used on recent cerebrospinal fluid (CSF) samples from 1638 Alzheimer's Disease Neuroimaging Initiative (ADNI) participants, 78 with LB-pathology confirmation at autopsy. We compared SAA outcomes with neuropathology, Aβ and tau biomarkers, risk-factors, genetics, and cognitive trajectories.

RESULTS

SAA showed 79% sensitivity and 97% specificity for LB pathology, with superior performance in identifying neocortical (100%) compared to limbic (57%) and amygdala-predominant (60%) LB-pathology. SAA+ rate was 22%, increasing with disease stage and age. Higher Aβ burden but lower CSF p-tau181 associated with higher SAA+ rates, especially in dementia. SAA+ affected cognitive impairment in MCI and Early-AD who were already AD biomarker positive.

DISCUSSION

SAA is a sensitive, specific marker for LB-pathology. Its increase in prevalence with age and AD stages, and its association with AD biomarkers, highlights the clinical importance of α-synuclein co-pathology in understanding AD's nature and progression.

HIGHLIGHTS

SAA shows 79% sensitivity, 97% specificity for LB-pathology detection in AD. SAA positivity prevalence increases with disease stage and age. Higher Aβ burden, lower CSF p-tau181 linked with higher SAA+ rates in dementia. SAA+ impacts cognitive impairment in early disease stages. Study underpins need for wider LB-pathology screening in AD treatment.

Long-read sequencing unravels the complexity of structural variants in PRKN in two individuals with early-onset Parkinson's disease

Background

PRKN biallelic pathogenic variants are the most common cause of autosomal recessive early-onset Parkinson's disease (PD). However, the variants responsible for suspected PRKN- PD individuals are not always identified with standard genetic testing.

Objectives

Identify the genetic cause in two siblings with a PRKN -PD phenotype using long-read sequencing (LRS).

Methods

The genetic investigation involved standard testing using successively multiple ligation probe amplification (MLPA), Sanger sequencing, targeted sequencing, whole-exome sequencing and LRS.

Results

MLPA and targeted sequencing identified one copy of exon four in PRKN but no other variants were identified. Subsequently, LRS unveiled a large deletion encompassing exon 3 to 4 on one allele and a duplication of exon 3 on the second allele; explaining the siblings' phenotype. MLPA could not identify the balanced rearrangement of exon 3.

Conclusions

This study highlights the potential utility of long-read sequencing in the context of unsolved typical PRKN- PD individuals.

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.

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 (β, 0.3640; standard error [SE], 0.103, P = 4.093e-04), as well as in all samples after adjusting for PD status (β, 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.

GenoTools: An Open-Source Python Package for Efficient Genotype Data Quality Control and Analysis

GenoTools, a Python package, streamlines population genetics research by integrating ancestry estimation, quality control (QC), and genome-wide association studies (GWAS) capabilities into efficient pipelines. By tracking samples, variants, and quality-specific measures throughout fully customizable pipelines, users can easily manage genetics data for large and small studies. GenoTools' "Ancestry" module renders highly accurate predictions, allowing for high-quality ancestry-specific studies, and enables custom ancestry model training and serialization, specified to the user's genotyping or sequencing platform. As the genotype processing engine that powers several large initiatives including the NIH's Center for Alzheimer's and Related Dementias (CARD) and the Global Parkinson's Genetics Program (GP2). GenoTools was used to process and analyze the UK Biobank and major Alzheimer's Disease (AD) and Parkinson's Disease (PD) datasets with over 400,000 genotypes from arrays and 5000 sequences and has led to novel discoveries in diverse populations. It has provided replicable ancestry predictions, implemented rigorous QC, and conducted genetic ancestry-specific GWAS to identify systematic errors or biases through a single command. GenoTools is a customizable tool that enables users to efficiently analyze and scale genotype data with reproducible and scalable ancestry, QC, and GWAS pipelines.

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.

Adaptive Long-Read Sequencing Reveals GGC Repeat Expansion in ZFHX3 Associated with Spinocerebellar Ataxia Type 4

BACKGROUND

Spinocerebellar ataxia type 4 (SCA4) is an autosomal dominant ataxia with invariable sensory neuropathy originally described in a family with Swedish ancestry residing in Utah more than 25 years ago. Despite tight linkage to the 16q22 region, the molecular diagnosis has since remained elusive.

OBJECTIVES

Inspired by pathogenic structural variation implicated in other 16q-ataxias with linkage to the same locus, we revisited the index SCA4 cases from the Utah family using novel technologies to investigate structural variation within the candidate region.

METHODS

We adopted a targeted long-read sequencing approach with adaptive sampling on the Oxford Nanopore Technologies (ONT) platform that enables the detection of segregating structural variants within a genomic region without a priori assumptions about any variant features.

RESULTS

Using this approach, we found a heterozygous (GGC)n repeat expansion in the last coding exon of the zinc finger homeobox 3 (ZFHX3) gene that segregates with disease, ranging between 48 and 57 GGC repeats in affected probands. This finding was replicated in a separate family with SCA4. Furthermore, the estimation of this GGC repeat size in short-read whole genome sequencing (WGS) data of 21,836 individuals recruited to the 100,000 Genomes Project in the UK and our in-house dataset of 11,258 exomes did not reveal any pathogenic repeats, indicating that the variant is ultrarare.

CONCLUSIONS

These findings support the utility of adaptive long-read sequencing as a powerful tool to decipher causative structural variation in unsolved cases of inherited neurological disease. © 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.

Analysis of rare Parkinson's disease variants in millions of people

Although many rare variants have been reportedly associated with Parkinson's disease (PD), many have not been replicated or have failed to replicate. Here, we conduct a large-scale replication of rare PD variants. We assessed a total of 27,590 PD cases, 6701 PD proxies, and 3,106,080 controls from three data sets: 23andMe, Inc., UK Biobank, and AMP-PD. Based on well-known PD genes, 834 variants of interest were selected from the ClinVar annotated 23andMe dataset. We performed a meta-analysis using summary statistics of all three studies. The meta-analysis resulted in five significant variants after Bonferroni correction, including variants in GBA1 and LRRK2. Another eight variants are strong candidate variants for their association with PD. Here, we provide the largest rare variant meta-analysis to date, providing information on confirmed and newly identified variants for their association with PD using several large databases. Additionally we also show the complexities of studying rare variants in large-scale cohorts.

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.

ProtPipe: A Multifunctional Data Analysis Pipeline for Proteomics and Peptidomics

Mass spectrometry (MS) is a technique widely employed for the identification and characterization of proteins, personalized medicine, systems biology and biomedical applications. By combining MS with different proteomics approaches such as immunopurification MS, immunopeptidomics, and total protein proteomics, researchers can gain insights into protein-protein interactions, immune responses, cellular processes, and disease mechanisms. The application of MS-based proteomics in these areas continues to advance our understanding of protein function, cellular signaling, and complex biological systems. Data analysis for mass spectrometry is a critical process that includes identifying and quantifying proteins and peptides and exploring biological functions for these proteins in downstream analysis. To address the complexities associated with MS data analysis, we developed ProtPipe to streamline and automate the processing and analysis of high-throughput proteomics and peptidomics datasets. The pipeline facilitates data quality control, sample filtering, and normalization, ensuring robust and reliable downstream analysis. ProtPipe provides downstream analysis including identifying differential abundance proteins and peptides, pathway enrichment analysis, protein-protein interaction analysis, and MHC1-peptide binding affinity. ProtPipe generates annotated tables and diagnostic visualizations from statistical postprocessing and computation of fold-changes across pairwise conditions, predefined in an experimental design. ProtPipe is well-documented open-source software and is available at https://github.com/NIH-CARD/ProtPipe , accompanied by a web interface.

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.

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.

Large-scale rare variant burden testing in Parkinson's disease

Parkinson's disease has a large heritable component and genome-wide association studies have identified over 90 variants with disease-associated common variants, providing deeper insights into the disease biology. However, there have not been large-scale rare variant analyses for Parkinson's disease. To address this gap, we investigated the rare genetic component of Parkinson's disease at minor allele frequencies <1%, using whole genome and whole exome sequencing data from 7184 Parkinson's disease cases, 6701 proxy cases and 51 650 healthy controls from the Accelerating Medicines Partnership Parkinson's disease (AMP-PD) initiative, the National Institutes of Health, the UK Biobank and Genentech. We performed burden tests meta-analyses on small indels and single nucleotide protein-altering variants, prioritized based on their predicted functional impact. Our work identified several genes reaching exome-wide significance. Two of these genes, GBA1 and LRRK2, have variants that have been previously implicated as risk factors for Parkinson's disease, with some variants in LRRK2 resulting in monogenic forms of the disease. We identify potential novel risk associations for variants in B3GNT3, AUNIP, ADH5, TUBA1B, OR1G1, CAPN10 and TREML1 but were unable to replicate the observed associations across independent datasets. Of these, B3GNT3 and TREML1 could provide new evidence for the role of neuroinflammation in Parkinson's disease. To date, this is the largest analysis of rare genetic variants in Parkinson's disease.

Investigation of the genetic aetiology of Lewy body diseases with and without dementia

Up to 80% of Parkinson's disease patients develop dementia, but time to dementia varies widely from motor symptom onset. Dementia with Lewy bodies presents with clinical features similar to Parkinson's disease dementia, but cognitive impairment precedes or coincides with motor onset. It remains controversial whether dementia with Lewy bodies and Parkinson's disease dementia are distinct conditions or represent part of a disease spectrum. The biological mechanisms underlying disease heterogeneity, in particular the development of dementia, remain poorly understood, but will likely be key to understanding disease pathways and ultimately therapy development. Previous genome-wide association studies in Parkinson's disease and dementia with Lewy bodies/Parkinson's disease dementia have identified risk loci differentiating patients from controls. We collated data for 7,804 patients of European ancestry from Tracking Parkinson's (PRoBaND), The Oxford Discovery Cohort, and AMP-PD. We conducted a discrete phenotype genome-wide association studies comparing Lewy body diseases with and without dementia to decode disease heterogeneity by investigating the genetic drivers of dementia in Lewy body diseases. We found that risk alleles rs429358 tagging APOEe4 and rs7668531 near the MMRN1 and SNCA-AS1 genes, increase the odds of developing dementia and that an intronic variant rs17442721 tagging LRRK2 G2019S, on chromosome 12 is protective against dementia. These results should be validated in autopsy confirmed cases in future studies.

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.

Polygenic risk score for Parkinson's disease and olfaction among middle-aged to older women

INTRODUCTION

Olfactory impairment and Parkinson's disease (PD) may share common genetic and environmental risk factors. This study investigates the association of a PD polygenic risk score (PRS) with olfaction, and whether the associations are modified by environmental exposures of PM2.5, NO2, or smoking.

METHODS

This analysis included 3358 women (aged 50-80) from the Sister Study with genetic data and results from the Brief Smell Identification Test (B-SIT) administered in 2018-2019. PD PRS was calculated using 90 single nucleotide polymorphisms. Olfactory impairment was defined with different B-SIT cutoffs, and PD diagnosis was adjudicated via expert review. We report odds ratios (ORs) and 95% confidence intervals (CIs) from multivariable logistic regression.

RESULTS

As expected, PD PRS was strongly associated with the odds of having PD (OR highest vs. lowest quartile = 3.79 (1.64, 8.73)). The highest PRS quartile was also associated with olfactory impairment, with OR ranging from 1.24 (0.98, 1.56) for a B-SIT cutoff of 9 to 1.42 (1.04, 1.92) for a cutoff of 6. For individual B-SIT items, the highest PRS quartile was generally associated with lower odds of correctly identifying the odorant, albeit only statistically significant for pineapple (0.72 (0.56, 0.94), soap (0.76 (0.58, 0.99)) and rose (0.70 (0.54, 0.92)). The association of PD PRS with olfactory impairment was not modified by airborne environmental exposures or smoking.

CONCLUSION

These preliminary data suggest that high PD genetic susceptibility is associated with olfactory impairment in middle-aged and older women.

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.

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

BACKGROUND

Amyloid-β, 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-β, 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.

Human brain single nucleus cell type enrichments in neurodegenerative diseases

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. 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. 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 Diseases. Subsequently, we identified the major role of 30 fine-mapped loci implicating seven genes in multiple neurodegenerative diseases and their pathogenesis.

Multi-ancestry meta-analysis and fine-mapping in Alzheimer's disease

Genome-wide association studies (GWAS) of Alzheimer's disease are predominantly carried out in European ancestry individuals despite the known variation in genetic architecture and disease prevalence across global populations. We leveraged published GWAS summary statistics from European, East Asian, and African American populations, and an additional GWAS from a Caribbean Hispanic population using previously reported genotype data to perform the largest multi-ancestry GWAS meta-analysis of Alzheimer's disease and related dementias to date. This method allowed us to identify two independent novel disease-associated loci on chromosome 3. We also leveraged diverse haplotype structures to fine-map nine loci with a posterior probability >0.8 and globally assessed the heterogeneity of known risk factors across populations. Additionally, we compared the generalizability of multi-ancestry- and single-ancestry-derived polygenic risk scores in a three-way admixed Colombian population. Our findings highlight the importance of multi-ancestry representation in uncovering and understanding putative factors that contribute to risk of Alzheimer's disease and related dementias.

Genome-wide case-only analysis of gene-gene interactions with known Parkinson's disease risk variants reveals link between LRRK2 and SYT10

The effects of one genetic factor upon Parkinson's disease (PD) risk may be modified by other genetic factors. Such gene-gene interaction (G×G) could explain some of the 'missing heritability' of PD and the reduced penetrance of known PD risk variants. Using the largest single nucleotide polymorphism (SNP) genotype data set currently available for PD (18,688 patients), provided by the International Parkinson's Disease Genomics Consortium, we studied G×G with a case-only (CO) design. To this end, we paired each of 90 SNPs previously reported to be associated with PD with one of 7.8 million quality-controlled SNPs from a genome-wide panel. Support of any putative G×G interactions found was sought by the analysis of independent genotype-phenotype and experimental data. A total of 116 significant pairwise SNP genotype associations were identified in PD cases, pointing towards G×G. The most prominent associations involved a region on chromosome 12q containing SNP rs76904798, which is a non-coding variant of the LRRK2 gene. It yielded the lowest interaction p-value overall with SNP rs1007709 in the promoter region of the SYT10 gene (interaction OR = 1.80, 95% CI: 1.65-1.95, p = 2.7 × 10^-43). SNPs around SYT10 were also associated with the age-at-onset of PD in an independent cohort of carriers of LRRK2 mutation p.G2019S. Moreover, SYT10 gene expression during neuronal development was found to differ between cells from affected and non-affected p.G2019S carriers. G×G interaction on PD risk, involving the LRRK2 and SYT10 gene regions, is biologically plausible owing to the known link between PD and LRRK2, its involvement in neural plasticity, and the contribution of SYT10 to the exocytosis of secretory vesicles in neurons.

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

Background

Amyloid beta (Aβ), 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 Aβ, 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.

Genome-wide association study identifies a new susceptibility locus in PLA2G4C for Multiple System Atrophy

To elucidate the molecular basis of multiple system atrophy (MSA), a neurodegenerative disease, we conducted a genome-wide association study (GWAS) in a Japanese MSA case/control series followed by replication studies in Japanese, Korean, Chinese, European and North American samples. In the GWAS stage rs2303744 on chromosome 19 showed a suggestive association ( P = 6.5 × 10 ^-7 ) that was replicated in additional Japanese samples ( P = 2.9 × 10 ^-6 . OR = 1.58; 95% confidence interval, 1.30 to 1.91), and then confirmed as highly significant in a meta-analysis of East Asian population data ( P = 5.0 × 10 ^-15 . Odds ratio= 1.49; 95% CI 1.35 to 1.72). The association of rs2303744 with MSA remained significant in combined European/North American samples ( P =0.023. Odds ratio=1.14; 95% CI 1.02 to 1.28) despite allele frequencies being quite different between these populations. rs2303744 leads to an amino acid substitution in PLA2G4C that encodes the cPLA2γ lysophospholipase/transacylase. The cPLA2γ-Ile143 isoform encoded by the MSA risk allele has significantly decreased transacylase activity compared with the alternate cPLA2γ-Val143 isoform that may perturb membrane phospholipids and α-synuclein biology.

Genome-Wide Analysis of Structural Variants in Parkinson Disease

OBJECTIVE

Identification of genetic risk factors for Parkinson disease (PD) has to date been primarily limited to the study of single nucleotide variants, which only represent a small fraction of the genetic variation in the human genome. Consequently, causal variants for most PD risk are not known. Here we focused on structural variants (SVs), which represent a major source of genetic variation in the human genome. We aimed to discover SVs associated with PD risk by performing the first large-scale characterization of SVs in PD.

METHODS

We leveraged a recently developed computational pipeline to detect and genotype SVs from 7,772 Illumina short-read whole genome sequencing samples. Using this set of SV variants, we performed a genome-wide association study using 2,585 cases and 2,779 controls and identified SVs associated with PD risk. Furthermore, to validate the presence of these variants, we generated a subset of matched whole-genome long-read sequencing data.

RESULTS

We genotyped and tested 3,154 common SVs, representing over 412 million nucleotides of previously uncatalogued genetic variation. Using long-read sequencing data, we validated the presence of three novel deletion SVs that are associated with risk of PD from our initial association analysis, including a 2 kb intronic deletion within the gene LRRN4.

INTERPRETATION

We identified three SVs associated with genetic risk of PD. This study represents the most comprehensive assessment of the contribution of SVs to the genetic risk of PD to date. ANN NEUROL 2023;93:1012-1022.

Creating the Pick's disease International Consortium: Association study of MAPT H2 haplotype with risk of Pick's disease

Background

Pick's disease (PiD) is a rare and predominantly sporadic form of frontotemporal dementia that is classified as a primary tauopathy. PiD is pathologically defined by argyrophilic inclusion Pick bodies and ballooned neurons in the frontal and temporal brain lobes. PiD is characterised by the presence of Pick bodies which are formed from aggregated, hyperphosphorylated, 3-repeat tau proteins, encoded by the MAPT gene. The MAPT H2 haplotype has consistently been associated with a decreased disease risk of the 4-repeat tauopathies of progressive supranuclear palsy and corticobasal degeneration, however its role in susceptibility to PiD is unclear. The primary aim of this study was to evaluate the association between MAPT H2 and risk of PiD.

Methods

We established the Pick's disease International Consortium (PIC) and collected 338 (60.7% male) pathologically confirmed PiD brains from 39 sites worldwide. 1,312 neurologically healthy clinical controls were recruited from Mayo Clinic Jacksonville, FL (N=881) or Rochester, MN (N=431). For the primary analysis, subjects were directly genotyped for MAPT H1-H2 haplotype-defining variant rs8070723. In secondary analysis, we genotyped and constructed the six-variant MAPT H1 subhaplotypes (rs1467967, rs242557, rs3785883, rs2471738, rs8070723, and rs7521).

Findings

Our primary analysis found that the MAPT H2 haplotype was associated with increased risk of PiD (OR: 1.35, 95% CI: 1.12-1.64 P=0.002). In secondary analysis involving H1 subhaplotypes, a protective association with PiD was observed for the H1f haplotype (0.0% vs. 1.2%, P=0.049), with a similar trend noted for H1b (OR: 0.76, 95% CI: 0.58-1.00, P=0.051). The 4-repeat tauopathy risk haplotype MAPT H1c was not associated with PiD susceptibility (OR: 0.93, 95% CI: 0.70-1.25, P=0.65).

Interpretation

The PIC represents the first opportunity to perform relatively large-scale studies to enhance our understanding of the pathobiology of PiD. This study demonstrates that in contrast to its protective role in 4R tauopathies, the MAPT H2 haplotype is associated with an increased risk of PiD. This finding is critical in directing isoform-related therapeutics for tauopathies.

Variant biomarker discovery using mass spectrometry-based proteogenomics

Genomic diversity plays critical roles in risk of disease pathogenesis and diagnosis. While genomic variants-including single nucleotide variants, frameshift variants, and mis-splicing isoforms-are commonly detected at the DNA or RNA level, their translated variant protein or polypeptide products are ultimately the functional units of the associated disease. These products are often released in biofluids and could be leveraged for clinical diagnosis and patient stratification. Recent emergence of integrated analysis of genomics with mass spectrometry-based proteomics for biomarker discovery, also known as proteogenomics, have significantly advanced the understanding disease risk variants, precise medicine, and biomarker discovery. In this review, we discuss variant proteins in the context of cancers and neurodegenerative diseases, outline current and emerging proteogenomic approaches for biomarker discovery, and provide a comprehensive proteogenomic strategy for detection of putative biomarker candidates in human biospecimens. This strategy can be implemented for proteogenomic studies in any field of enquiry. Our review timely addresses the need of biomarkers for aging related diseases.

Exploring the genetic and genomic connection underlying neurodegeneration with brain iron accumulation and the risk for Parkinson's disease

Neurodegeneration with brain iron accumulation (NBIA) represents a group of neurodegenerative disorders characterized by abnormal iron accumulation in the brain. In Parkinson's Disease (PD), iron accumulation is a cardinal feature of degenerating regions in the brain and seems to be a key player in mechanisms that precipitate cell death. The aim of this study was to explore the genetic and genomic connection between NBIA and PD. We screened for known and rare pathogenic mutations in autosomal dominant and recessive genes linked to NBIA in a total of 4481 PD cases and 10,253 controls from the Accelerating Medicines Partnership Parkinsons' Disease Program and the UKBiobank. We examined whether a genetic burden of NBIA variants contributes to PD risk through single-gene, gene-set, and single-variant association analyses. In addition, we assessed publicly available expression quantitative trait loci (eQTL) data through Summary-based Mendelian Randomization and conducted transcriptomic analyses in blood of 1886 PD cases and 1285 controls. Out of 29 previously reported NBIA screened coding variants, four were associated with PD risk at a nominal p value < 0.05. No enrichment of heterozygous variants in NBIA-related genes risk was identified in PD cases versus controls. Burden analyses did not reveal a cumulative effect of rare NBIA genetic variation on PD risk. Transcriptomic analyses suggested that DCAF17 is differentially expressed in blood from PD cases and controls. Due to low mutation occurrence in the datasets and lack of replication, our analyses suggest that NBIA and PD may be separate molecular entities.

Virus exposure and neurodegenerative disease risk across national biobanks

With recent findings connecting the Epstein-Barr virus to an increased risk of multiple sclerosis and growing concerns regarding the neurological impact of the coronavirus pandemic, we examined potential links between viral exposures and neurodegenerative disease risk. Using time series data from FinnGen for discovery and cross-sectional data from the UK Biobank for replication, we identified 45 viral exposures significantly associated with increased risk of neurodegenerative disease and replicated 22 of these associations. The largest effect association was between viral encephalitis exposure and Alzheimer's disease. Influenza with pneumonia was significantly associated with five of the six neurodegenerative diseases studied. We also replicated the Epstein-Barr/multiple sclerosis association. Some of these exposures were associated with an increased risk of neurodegeneration up to 15 years after infection. As vaccines are currently available for some of the associated viruses, vaccination may be a way to reduce some risk of neurodegenerative disease.

Investigation of Shared Genetic Risk Factors Between Parkinson's Disease and Cancers

BACKGROUND

Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties.

OBJECTIVE

We used results from genome-wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors.

METHODS

We used individual data for participants of European ancestry from the Courage-PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta-Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross-phenotypes polygenic risk score (PRS) analyses.

RESULTS

We confirmed a previously reported positive genetic correlation of PD with melanoma (Gcorr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (Gcorr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven by rs183211 located in an intron of the NSF gene (17q21.31).

CONCLUSIONS

We show evidence in favor of a contribution of pleiotropic genes to the association between PD and specific cancers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

The Foundational Data Initiative for Parkinson Disease: Enabling efficient translation from genetic maps to mechanism

The Foundational Data Initiative for Parkinson Disease (FOUNDIN-PD) is an international collaboration producing fundamental resources for Parkinson disease (PD). FOUNDIN-PD generated a multi-layered molecular dataset in a cohort of induced pluripotent stem cell (iPSC) lines differentiated to dopaminergic (DA) neurons, a major affected cell type in PD. The lines were derived from the Parkinson's Progression Markers Initiative study, which included participants with PD carrying monogenic PD variants, variants with intermediate effects, and variants identified by genome-wide association studies and unaffected individuals. We generated genetic, epigenetic, regulatory, transcriptomic, and longitudinal cellular imaging data from iPSC-derived DA neurons to understand molecular relationships between disease-associated genetic variation and proximate molecular events. These data reveal that iPSC-derived DA neurons provide a valuable cellular context and foundational atlas for modeling PD genetic risk. We have integrated these data into a FOUNDIN-PD data browser as a resource for understanding the molecular pathogenesis of PD.

Genome-wide association study using whole-genome sequencing identifies risk loci for Parkinson's disease in Chinese population

Genome-wide association studies (GWASs) have identified numerous susceptibility loci for Parkinson's disease (PD), but its genetic architecture remains underexplored in populations of non-European ancestry. To identify genetic variants associated with PD in the Chinese population, we performed a GWAS using whole-genome sequencing (WGS) in 1,972 cases and 2,478 controls, and a replication study in a total of 8209 cases and 9454 controls. We identified one new risk variant rs61204179 (Pcombined = 1.47 × 10-9) with low allele frequency, four previously reported risk variants (NUCKS1/RAB29-rs11557080, SNCA-rs356182, FYN-rs997368, and VPS13C-rs2251086), as well as three risk variants in LRRK2 coding region (A419V, R1628P, and G2385R) with genome-wide significance (P < 5 × 10-8) for PD in Chinese population. Moreover, of the reported genome-wide significant risk variants found mostly in European ancestry populations, the correlation coefficient (rb) of effect size accounting for sampling errors was 0.91 between datasets and 63.6% attained P < 0.05 in Chinese population. Accordingly, we estimated a heritability of 0.14-0.18 for PD, and a moderate genetic correlation between European ancestry and Chinese populations (rg = 0.47, se = 0.21). Polygenic risk score (PRS) analysis revealed that individuals with PRS values in the highest quartile had a 3.9-fold higher risk of developing PD than the lowest quartile. In conclusion, the present GWAS identified PD-associated variants in Chinese population, as well as genetic factors shared among distant populations. Our findings shed light on the genetic homogeneity and heterogeneity of PD in different ethnic groups and suggested WGS might continue to improve our understanding of the genetic architecture of PD.

Genome-wide contribution of common short-tandem repeats to Parkinson's disease genetic risk

Parkinson's disease is a complex neurodegenerative disorder with a strong genetic component, for which most known disease-associated variants are single nucleotide polymorphisms (SNPs) and small insertions and deletions (indels). DNA repetitive elements account for >50% of the human genome; however, little is known of their contribution to Parkinson's disease aetiology. While select short tandem repeats (STRs) within candidate genes have been studied in Parkinson's disease, their genome-wide contribution remains unknown. Here we present the first genome-wide association study of STRs in Parkinson's disease. Through a meta-analysis of 16 imputed genome-wide association study cohorts from the International Parkinson's Disease Genomic Consortium (IPDGC), totalling 39 087 individuals (16 642 cases and 22 445 controls of European ancestry), we identified 34 genome-wide significant STR loci (P < 5.34 × 10-6), with the strongest signal located in KANSL1 [chr17:44 205 351:[T]11, P = 3 × 10-39, odds ratio = 1.31 (95% confidence interval = 1.26-1.36)]. Conditional-joint analyses suggested that four significant STRs mapping nearby NDUFAF2, TRIML2, MIRNA-129-1 and NCOR1 were independent from known risk SNPs. Including STRs in heritability estimates increased the variance explained by SNPs alone. Gene expression analysis of STRs (eSTRs) in RNA sequencing data from 13 brain regions identified significant associations of STRs influencing the expression of multiple genes, including known Parkinson's disease genes. Further functional annotation of candidate STRs revealed that significant eSTRs within NUDFAF2 and ZSWIM7 overlap with regulatory features and are associated with change in the expression levels of nearby genes. Here, we show that STRs at known and novel candidate loci contribute to Parkinson's disease risk and have functional effects in disease-relevant tissues and pathways, supporting previously reported disease-associated genes and giving further evidence for their functional prioritization. These data represent a valuable resource for researchers currently dissecting Parkinson's disease risk loci.

Parkinson's Disease Case Ascertainment in the Sister Study: A Cohort for Environmental Health Research

BACKGROUND

Large prospective studies are essential for investigating the environmental causes of Parkinson's disease (PD), but PD diagnosis via clinical exams is often infeasible in such studies.

OBJECTIVE

To present case ascertainment strategy and data collection in a US cohort of women.

METHODS

In the Sister Study (n = 50,884, baseline ages 55.6±9.0), physician-made PD diagnoses were first reported by participants or their proxies. Cohort-wide follow-up surveys collected data on subsequent diagnoses, medication usage and PD-relevant motor and nonmotor symptoms. We contacted self-reported PD cases and their treating physicians to obtain relevant diagnostic and treatment history. Diagnostic adjudication was made via expert review of all available data, except nonmotor symptoms. We examined associations of nonmotor symptoms with incident PD, using multivariable logistic regression models and reported odds ratio (OR) and 95% confidence intervals (CI).

RESULTS

Of the 371 potential PD cases identified, 242 diagnoses were confirmed. Compared with unconfirmed cases, confirmed cases were more likely to report PD diagnosis from multiple sources, medication usage, and motor and nonmotor features consistently during the follow-up. PD polygenic risk score was associated with confirmed PD (ORinter-quartile range = 1.74, 95% CI: 1.45-2.10), but not with unconfirmed cases (corresponding OR = 1.05). Hyposmia, dream-enacting behaviors, constipation, depression, unexplained weight loss, dry eyes, dry mouth, and fatigue were significantly related to PD risk, with ORs from 1.71 to 4.88. Only one of the eight negative control symptoms was associated with incident PD.

CONCLUSION

Findings support our PD case ascertainment approach in this large cohort of women. PD prodromal presentation is likely beyond its well-documented profile.

Regulation of mitophagy by the NSL complex underlies genetic risk for Parkinson's disease at 16q11.2 and MAPT H1 loci

Parkinson's disease is a common incurable neurodegenerative disease. The identification of genetic variants via genome-wide association studies has considerably advanced our understanding of the Parkinson's disease genetic risk. Understanding the functional significance of the risk loci is now a critical step towards translating these genetic advances into an enhanced biological understanding of the disease. Impaired mitophagy is a key causative pathway in familial Parkinson's disease, but its relevance to idiopathic Parkinson's disease is unclear. We used a mitophagy screening assay to evaluate the functional significance of risk genes identified through genome-wide association studies. We identified two new regulators of PINK1-dependent mitophagy initiation, KAT8 and KANSL1, previously shown to modulate lysine acetylation. These findings suggest PINK1-mitophagy is a contributing factor to idiopathic Parkinson's disease. KANSL1 is located on chromosome 17q21 where the risk associated gene has long been considered to be MAPT. While our data do not exclude a possible association between the MAPT gene and Parkinson's disease, they provide strong evidence that KANSL1 plays a crucial role in the disease. Finally, these results enrich our understanding of physiological events regulating mitophagy and establish a novel pathway for drug targeting in neurodegeneration.

Identification and prediction of Parkinson's disease subtypes and progression using machine learning in two cohorts

The clinical manifestations of Parkinson's disease (PD) are characterized by heterogeneity in age at onset, disease duration, rate of progression, and the constellation of motor versus non-motor features. There is an unmet need for the characterization of distinct disease subtypes as well as improved, individualized predictions of the disease course. We used unsupervised and supervised machine learning methods on comprehensive, longitudinal clinical data from the Parkinson's Disease Progression Marker Initiative (n = 294 cases) to identify patient subtypes and to predict disease progression. The resulting models were validated in an independent, clinically well-characterized cohort from the Parkinson's Disease Biomarker Program (n = 263 cases). Our analysis distinguished three distinct disease subtypes with highly predictable progression rates, corresponding to slow, moderate, and fast disease progression. We achieved highly accurate projections of disease progression 5 years after initial diagnosis with an average area under the curve (AUC) of 0.92 (95% CI: 0.95 ± 0.01) for the slower progressing group (PDvec1), 0.87 ± 0.03 for moderate progressors, and 0.95 ± 0.02 for the fast-progressing group (PDvec3). We identified serum neurofilament light as a significant indicator of fast disease progression among other key biomarkers of interest. We replicated these findings in an independent cohort, released the analytical code, and developed models in an open science manner. Our data-driven study provides insights to deconstruct PD heterogeneity. This approach could have immediate implications for clinical trials by improving the detection of significant clinical outcomes. We anticipate that machine learning models will improve patient counseling, clinical trial design, and ultimately individualized patient care.

Genome-wide association study of REM sleep behavior disorder identifies polygenic risk and brain expression effects

Rapid-eye movement (REM) sleep behavior disorder (RBD), enactment of dreams during REM sleep, is an early clinical symptom of alpha-synucleinopathies and defines a more severe subtype. The genetic background of RBD and its underlying mechanisms are not well understood. Here, we perform a genome-wide association study of RBD, identifying five RBD risk loci near SNCA, GBA, TMEM175, INPP5F, and SCARB2. Expression analyses highlight SNCA-AS1 and potentially SCARB2 differential expression in different brain regions in RBD, with SNCA-AS1 further supported by colocalization analyses. Polygenic risk score, pathway analysis, and genetic correlations provide further insights into RBD genetics, highlighting RBD as a unique alpha-synucleinopathy subpopulation that will allow future early intervention.

Analysis of Y chromosome haplogroups in Parkinson's disease

Parkinson's disease is a complex neurodegenerative disorder that is about 1.5 times more prevalent in males than females. Extensive work has been done to identify the genetic risk factors behind Parkinson's disease on autosomes and more recently on Chromosome X, but work remains to be done on the male-specific Y chromosome. In an effort to explore the role of the Y chromosome in Parkinson's disease, we analysed whole-genome sequencing data from the Accelerating Medicines Partnership-Parkinson's disease initiative (1466 cases and 1664 controls), genotype data from NeuroX (3491 cases and 3232 controls) and genotype data from UKBiobank (182 517 controls, 1892 cases and 3783 proxy cases), all consisting of male European ancestry samples. We classified sample Y chromosomes by haplogroup using three different tools for comparison (Snappy, Yhaplo and Y-LineageTracker) and meta-analysed this data to identify haplogroups associated with Parkinson's disease. This was followed up with a Y-chromosome association study to identify specific variants associated with disease. We also analysed blood-based RNASeq data obtained from the Accelerating Medicines Partnership-Parkinson's disease initiative (1020 samples) and RNASeq data obtained from the North American Brain Expression Consortium (171 samples) to identify Y-chromosome genes differentially expressed in cases, controls, specific haplogroups and specific tissues. RNASeq analyses suggest Y-chromosome gene expression differs between brain and blood tissues but does not differ significantly in cases, controls or specific haplogroups. Overall, we did not find any strong associations between Y-chromosome genetics and Parkinson's disease, suggesting the explanation for the increased prevalence in males may lie elsewhere.

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

The Interaction between HLA-DRB1 and Smoking in Parkinson's Disease Revisited

BACKGROUND

Two studies that examined the interaction between HLA-DRB1 and smoking in Parkinson's disease (PD) yielded findings in opposite directions.

OBJECTIVE

To perform a large-scale independent replication of the HLA-DRB1 × smoking interaction.

METHODS

We genotyped 182 single nucleotide polymorphism (SNPs) associated with smoking initiation in 12 424 cases and 9480 controls to perform a Mendelian randomization (MR) analysis in strata defined by HLA-DRB1.

RESULTS

At the amino acid level, a valine at position 11 (V11) in HLA-DRB1 displayed the strongest association with PD. MR showed an inverse association between genetically predicted smoking initiation and PD only in absence of V11 (odds ratio, 0.74, 95% confidence interval, 0.59-0.93, PInteraction  = 0.028). In silico predictions of the influence of V11 and smoking-induced modifications of α-synuclein on binding affinity showed findings consistent with this interaction pattern.

CONCLUSIONS

Despite being one of the most robust findings in PD research, the mechanisms underlying the inverse association between smoking and PD remain unknown. Our findings may help better understand this association. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Genome-wide Association and Meta-analysis of Age at Onset in Parkinson Disease: Evidence From the COURAGE-PD Consortium

BACKGROUND AND OBJECTIVES

Considerable heterogeneity exists in the literature concerning genetic determinants of the age at onset (AAO) of Parkinson disease (PD), which could be attributed to a lack of well-powered replication cohorts. The previous largest genome-wide association studies (GWAS) identified SNCA and TMEM175 loci on chromosome (Chr) 4 with a significant influence on the AAO of PD; these have not been independently replicated. This study aims to conduct a meta-analysis of GWAS of PD AAO and validate previously observed findings in worldwide populations.

METHODS

A meta-analysis was performed on PD AAO GWAS of 30 populations of predominantly European ancestry from the Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease (COURAGE-PD) Consortium. This was followed by combining our study with the largest publicly available European ancestry dataset compiled by the International Parkinson Disease Genomics Consortium (IPDGC).

RESULTS

The COURAGE-PD Consortium included a cohort of 8,535 patients with PD (91.9%: Europeans and 9.1%: East Asians). The average AAO in the COURAGE-PD dataset was 58.9 years (SD = 11.6), with an underrepresentation of females (40.2%). The heritability estimate for AAO in COURAGE-PD was 0.083 (SE = 0.057). None of the loci reached genome-wide significance (p < 5 × 10-8). Nevertheless, the COURAGE-PD dataset confirmed the role of the previously published TMEM175 variant as a genetic determinant of the AAO of PD with Bonferroni-corrected nominal levels of significance (p < 0.025): (rs34311866: β(SE)COURAGE = 0.477(0.203), p COURAGE = 0.0185). The subsequent meta-analysis of COURAGE-PD and IPDGC datasets (Ntotal = 25,950) led to the identification of 2 genome-wide significant association signals on Chr 4, including the previously reported SNCA locus (rs983361: β(SE)COURAGE+IPDGC = 0.720(0.122), p COURAGE+IPDGC = 3.13 × 10-9) and a novel BST1 locus (rs4698412: β(SE)COURAGE+IPDGC = -0.526(0.096), p COURAGE+IPDGC = 4.41 × 10-8).

DISCUSSION

Our study further refines the genetic architecture of Chr 4 underlying the AAO of the PD phenotype through the identification of BST1 as a novel AAO PD locus. These findings open a new direction for the development of treatments to delay the onset of PD.

A CRISPRi/a platform in human iPSC-derived microglia uncovers regulators of disease states

Microglia are emerging as key drivers of neurological diseases. However, we lack a systematic understanding of the underlying mechanisms. Here, we present a screening platform to systematically elucidate functional consequences of genetic perturbations in human induced pluripotent stem cell-derived microglia. We developed an efficient 8-day protocol for the generation of microglia-like cells based on the inducible expression of six transcription factors. We established inducible CRISPR interference and activation in this system and conducted three screens targeting the ‘druggable genome’. These screens uncovered genes controlling microglia survival, activation and phagocytosis, including neurodegeneration-associated genes. A screen with single-cell RNA sequencing as the readout revealed that these microglia adopt a spectrum of states mirroring those observed in human brains and identified regulators of these states. A disease-associated state characterized by osteopontin (SPP1) expression was selectively depleted by colony-stimulating factor-1 (CSF1R) inhibition. Thus, our platform can systematically uncover regulators of microglial states, enabling their functional characterization and therapeutic targeting.

Dräger et al. establish a rapid, scalable platform for iPSC-derived microglia. CRISPRi/a screens uncover roles of disease-associated genes in phagocytosis, and regulators of disease-relevant microglial states that can be targeted pharmacologically.

Heterozygous PRKN mutations are common but do not increase the risk of Parkinson's disease

PRKN mutations are the most common recessive cause of Parkinson's disease and are a promising target for gene and cell replacement therapies. Identification of biallelic PRKN patients at the population scale, however, remains a challenge, as roughly half are copy number variants and many single nucleotide polymorphisms are of unclear significance. Additionally, the true prevalence and disease risk associated with heterozygous PRKN mutations is unclear, as a comprehensive assessment of PRKN mutations has not been performed at a population scale. To address these challenges, we evaluated PRKN mutations in two cohorts with near complete genotyping of both single nucleotide polymorphisms and copy number variants: the NIH-PD + AMP-PD cohort, the largest Parkinson's disease case-control cohort with whole genome sequencing data from 4094 participants, and the UK Biobank, the largest cohort study with whole exome sequencing and genotyping array data from 200 606 participants. Using the NIH-PD participants, who were genotyped using whole genome sequencing, genotyping array, and multi-plex ligation-dependent probe amplification, we validated genotyping array for the detection of copy number variants. Additionally, in the NIH-PD cohort, functional assays of patient fibroblasts resolved variants of unclear significance in biallelic carriers and suggested that cryptic loss of function variants in monoallelic carriers are not a substantial confounder for association studies. In the UK Biobank, we identified 2692 PRKN copy number variants from genotyping array data from nearly half a million participants (the largest collection to date). Deletions or duplications involving exon 2 accounted for roughly half of all copy number variants and the vast majority (88%) involved exons 2, 3, or 4. In the UK Biobank, we found a pathogenic PRKN mutation in 1.8% of participants and two mutations in ∼1/7800 participants. Those with one PRKN pathogenic variant were as likely as non-carriers to have Parkinson's disease [odds ratio = 0.91 (0.58-1.38), P-value 0.76] or a parent with Parkinson's disease [odds ratio = 1.12 (0.94-1.31), P-value = 0.19]. Similarly, those in the NIH-PD + AMP + PD cohort with one PRKN pathogenic variant were as likely as non-carriers to have Parkinson's disease [odds ratio = 1.29 (0.74-2.38), P-value = 0.43]. Together our results demonstrate that heterozygous pathogenic PRKN mutations are common in the population but do not increase the risk of Parkinson's disease.

Deficiency in endocannabinoid synthase DAGLB contributes to early onset Parkinsonism and murine nigral dopaminergic neuron dysfunction

Endocannabinoid (eCB), 2-arachidonoyl-glycerol (2-AG), the most abundant eCB in the brain, regulates diverse neural functions. Here we linked multiple homozygous loss-of-function mutations in 2-AG synthase diacylglycerol lipase β (DAGLB) to an early onset autosomal recessive Parkinsonism. DAGLB is the main 2-AG synthase in human and mouse substantia nigra (SN) dopaminergic neurons (DANs). In mice, the SN 2-AG levels were markedly correlated with motor performance during locomotor skill acquisition. Genetic knockdown of Daglb in nigral DANs substantially reduced SN 2-AG levels and impaired locomotor skill learning, particularly the across-session learning. Conversely, pharmacological inhibition of 2-AG degradation increased nigral 2-AG levels, DAN activity and dopamine release and rescued the locomotor skill learning deficits. Together, we demonstrate that DAGLB-deficiency contributes to the pathogenesis of Parkinsonism, reveal the importance of DAGLB-mediated 2-AG biosynthesis in nigral DANs in regulating neuronal activity and dopamine release, and suggest potential benefits of 2-AG augmentation in alleviating Parkinsonism.

Multi-modality machine learning predicting Parkinson's disease

Personalized medicine promises individualized disease prediction and treatment. The convergence of machine learning (ML) and available multimodal data is key moving forward. We build upon previous work to deliver multimodal predictions of Parkinson's disease (PD) risk and systematically develop a model using GenoML, an automated ML package, to make improved multi-omic predictions of PD, validated in an external cohort. We investigated top features, constructed hypothesis-free disease-relevant networks, and investigated drug-gene interactions. We performed automated ML on multimodal data from the Parkinson's progression marker initiative (PPMI). After selecting the best performing algorithm, all PPMI data was used to tune the selected model. The model was validated in the Parkinson's Disease Biomarker Program (PDBP) dataset. Our initial model showed an area under the curve (AUC) of 89.72% for the diagnosis of PD. The tuned model was then tested for validation on external data (PDBP, AUC 85.03%). Optimizing thresholds for classification increased the diagnosis prediction accuracy and other metrics. Finally, networks were built to identify gene communities specific to PD. Combining data modalities outperforms the single biomarker paradigm. UPSIT and PRS contributed most to the predictive power of the model, but the accuracy of these are supplemented by many smaller effect transcripts and risk SNPs. Our model is best suited to identifying large groups of individuals to monitor within a health registry or biobank to prioritize for further testing. This approach allows complex predictive models to be reproducible and accessible to the community, with the package, code, and results publicly available.

Dairy Intake and Parkinson's Disease: A Mendelian Randomization Study

BACKGROUND

Previous prospective studies highlighted dairy intake as a risk factor for Parkinson's disease (PD), particularly in men. It is unclear whether this association is causal or explained by reverse causation or confounding.

OBJECTIVE

The aim is to examine the association between genetically predicted dairy intake and PD using two-sample Mendelian randomization (MR).

METHODS

We genotyped a well-established instrumental variable for dairy intake located in the lactase gene (rs4988235) within the Courage-PD consortium (23 studies; 9823 patients and 8376 controls of European ancestry).

RESULTS

Based on a dominant model, there was an association between genetic predisposition toward higher dairy intake and PD (odds ratio [OR] per one serving per day = 1.70, 95% confidence interval = 1.12-2.60, P = 0.013) that was restricted to men (OR = 2.50 [1.37-4.56], P = 0.003; P-difference with women = 0.029).

CONCLUSIONS

Using MR, our findings provide further support for a causal relationship between dairy intake and higher PD risk, not biased by confounding or reverse causation. Further studies are needed to elucidate the underlying mechanisms. © 2022 International Parkinson and Movement Disorder Society.

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons.