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

No Bidirectional Causal Relationship Between Traumatic Brain Injury and Parkinson's Disease: A Two-Sample Mendelian Randomization Study

Background

The incidence of Parkinson's disease (PD) is significantly increased in older people who have experienced traumatic brain injury (TBI), suggesting that TBI may be a potential risk factor for PD. However, the causal relationship remains ambiguous.

Objective

To investigate the association between TBI and PD using Mendelian randomization (MR) analyses.

Methods

Four genome-wide association databases were reviewed in detail, including GWAS Catalog, FinnGen, IEU OpenGWAS, and UK Biobank. Genetic data for TBI were obtained from the FinnGen data set, including 7430 clinically diagnosed cases and 404,751 controls, and PD was obtained from a meta-analysis in the GWAS Catalog, including 42,792 cases and 568,693 controls. The bidirectional two-sample MR analyses were used to investigate the causal association between TBI and PD.

Results

There was no evidence of a causal relationship between TBI and an increased risk of PD (IVW; OR = 1.11; 95% CI, 0.91-1.36; p = 0.308). Similarly, genetically predisposed PD was not associated with a high risk of TBI (IVW; OR = 0.96; 95% CI, 0.91-1.02; p = 0.209). Results from MR-Egger regression, weighted mode, and weighted median analyses were consistent with those from the IVW analysis. Additional sensitivity analyses further supported the robustness of our conclusions.

Conclusions

No causal relationship was found between TBI and PD.

Pathogenesis of Parkinson's Disease

Both genetic and environmental factors modulate the risk of Parkinson's disease. In this article, all these pathophysiologic processes that contribute to damages at the tissue, cellular, organelle, and molecular levels, and their effects are talked about.

Comprehensive analysis of SLC17A5 variants in large European cohorts reveals no association with Parkinson's disease risk

BACKGROUND

Parkinson's disease (PD) is a neurodegenerative disorder characterized by dopaminergic neuron loss and α-synuclein aggregation. Aging is the primary risk factor, with both rare and common genetic variants playing a role. Previous studies have implicated lysosomal storage disorder (LSD)-related genes, including SLC17A5, in PD susceptibility.

OBJECTIVE

This study aimed to investigate the association of SLC17A5 variants, including rare and common variants and the FSASD-associated p.Arg39Cys missense variant, with PD risk in large European ancestry cohorts.

METHODS

Rare variant burden analyses were performed at minor allele frequency (MAF) thresholds of ≤1 % and ≤0.1 % in 7,184 PD cases and 51,650 controls using whole-genome and whole-exome sequencing data. Association testing of the p.Arg39Cys variant was conducted across five cohorts, encompassing both Finnish and non-Finnish Europeans. Common variant associations were examined using summary statistics from the largest European GWAS of PD.

RESULTS

No significant association was observed between rare SLC17A5 variants and PD at either MAF threshold. The p.Arg39Cys variant, though enriched in Finnish Europeans, showed no significant association with PD across several cohorts. Similarly, common SLC17A5 variants (MAF ≥1%) were not associated with PD risk.

CONCLUSION

Our findings do not support a role for SLC17A5 variants in PD susceptibility. While lysosomal dysfunction is central to PD pathogenesis, its contribution appears pathway-specific, with SLC17A5 unlikely to influence risk. Larger, multiethnic studies and functional analyses are needed to further investigate sialic acid metabolism in PD and related disorders.

Prioritizing Parkinson's disease risk genes in genome-wide association loci

Many drug targets in ongoing Parkinson's disease (PD) clinical trials have strong genetic links. While genome-wide association studies (GWAS) nominate regions associated with disease, pinpointing causal genes is challenging. Our aim was to prioritize additional druggable genes underlying PD GWAS signals. The polygenic priority score (PoPS) integrates genome-wide information from MAGMA gene-level associations and over 57,000 gene-level features. We applied PoPS to East Asian and European PD GWAS data and prioritized genes based on PoPS, distance to the GWAS signal, and non-synonymous credible set variants. We prioritized 46 genes, including well-established PD genes (SNCA, LRRK2, GBA1, TMEM175, VPS13C), genes with strong literature evidence supporting a mechanistic link to PD (RIT2, BAG3, SCARB2, FYN, DYRK1A, NOD2, CTSB, SV2C, ITPKB), and genes relatively unexplored in PD. Many hold potential for drug repurposing or development. We prioritized high-confidence genes with strong links to PD pathogenesis that may represent our next-best candidates for developing disease-modifying therapeutics.

Alpha-synuclein mutations mislocalize cytoplasmic p300 compromising autophagy, which is rescued by ACLY inhibition

Triplications and certain point mutations in the SNCA gene, encoding alpha-synuclein (α-Syn), cause Parkinson's disease (PD). Here, we demonstrate that the PD-causing A53T α-Syn mutation and elevated α-Syn expression perturb acetyl-coenzyme A (CoA) and p300 biology in human neurons and in the CNS of zebrafish and mice. This dysregulation is mediated by activation of ATP-citrate lyase (ACLY), a key enzyme that generates acetyl-CoA in the cytoplasm, via two mechanisms. First, ACLY activity increases acetyl-CoA levels, which activate p300. Second, ACLY activation increases LKB1 acetylation, which inhibits AMPK, leading to increased cytoplasmic and decreased nuclear p300. This lowers histone acetylation and increases acetylation of cytoplasmic p300 substrates, like raptor, which causes mechanistic target of rapamycin complex 1 (mTORC1) hyperactivation, thereby impairing autophagy. ACLY inhibitors rescue pathological phenotypes in PD neurons, organoids, zebrafish, and mouse models, suggesting that this pathway is a core feature of α-Syn toxicity and that ACLY may be a suitable therapeutic target.

Does COMT Play a Role in Parkinson's Disease Susceptibility Across Diverse Ancestral Populations?

Background

The catechol-O-methyltransferase (COMT) gene is involved in brain catecholamine metabolism, but its association with Parkinson's disease (PD) risk remains unclear.

Objective

To investigate the relationship between COMT genetic variants and PD risk across diverse ancestries.

Methods

We analyzed COMT variants in 2,251 PD patients and 2,835 controls of European descent using whole-genome sequencing from the Accelerating Medicines Partnership-Parkinson Disease (AMP-PD), along with 20,427 PD patients and 11,837 controls from 10 ancestries using genotyping data from the Global Parkinson's Genetics Program (GP2).

Results

Utilizing the largest case-control datasets to date, no significant enrichment of COMT risk alleles in PD patients was observed across any ancestry group after correcting for multiple testing. Among Europeans, no correlations with cognitive decline, motor function, motor complications, or time to LID onset were observed.

Conclusions

These findings emphasize the need for larger, diverse cohorts to confirm the role of COMT in PD development and progression.

Silencer variants are key drivers of gene upregulation in Alzheimer's disease

Alzheimer's disease (AD), particularly late-onset AD, stands as the most prevalent neurodegenerative disorder globally. Owing to its substantial heritability, genetic studies have emerged as indispensable for elucidating genes and biological pathways driving AD onset and progression. However, genetic and molecular mechanisms underlying AD remain poorly defined, largely due to the pronounced heterogeneity of AD and the intricate interactions among AD genetic factors. Notably, approximately 90% of AD-associated genetic variants reside in intronic and intergenic regions, yet their functional significance has remained largely uncharacterized. To address this challenge, we developed a deep learning framework combining bulk and single-cell epigenomic data to evaluate the regulatory potential (i.e., silencing and activating strength) of noncoding AD variants in the dorsolateral prefrontal cortex (DLPFCs) and its major cell types. This model identified 1,457 silencer and 3,084 enhancer AD-associated variants in the DLPFC and binned them into silencer variants only (SL), enhancer variants only (EN), or both variant types (ENSL) classes. Each class exerts distinct cellular and molecular influences on AD pathogenesis. EN loci predominantly regulate housekeeping metabolic processes, whereas SL loci (including the genes MS4A6A , TREM2 , USP6NL , HLA-D ) are selectively linked to immune responses. Notably, 71% of these genes are significantly upregulated in AD and pro-inflammation-stimulated microglia. Furthermore, genes associated with SL loci are, in neuronal cells, often responsive to glutamate receptor antagonists (e.g, NBQX) and anti-inflammatory perturbagens (such as D-64131), the compound classes known for reducing the AD risk. ENSL loci, in contrast, are uniquely implicated in memory maintenance, neurofibrillary tangle assembly, and are also shared by other neurological disorders such as Parkinson's disease and schizophrenia. Key genes in this class of loci, such as MAPT , CR1/2 , and CLU , are frequently upregulated in AD subtypes with hyperphosphorylated tau aggregates. Critically, our model can accurately predict the impact of regulatory variants, with an average Pearson correlation coefficient of 0.54 and a directional concordance rate of 70% between our predictions and experimental outcomes. This model identified rs636317 as a causal AD variant in the MS4A locus, distinguishing it from the 7bp-away allele-neutral variant rs636341. Similarly, rs7922621 was prioritized over its 54-bp-away allele-neutral rs7901634 in the TSPAN14 locus. Additional causal variants include rs6701713 in the CR1 locus, and rs28834970 and rs755951 in the PTK2B locus. Collectively, this work advances our understanding of the regulatory landscape of AD-associated genetic variants, providing a framework to explore their functional roles in the pathogenesis of this complex disease.

Genetic variants associated with idiopathic Parkinson's disease in Latin America: A systematic review

Idiopathic Parkinson's disease (PD) constitutes a complex trait influenced by genetic, environmental, and lifestyle factors, with an estimated heritability of nearly 30%. However, a large proportion of the heritable variation linked to PD remains uncertain, partly due to ancestral bias. Expanding research into Hispanic populations can contribute to address this gap. To review the evidence of genetic variants associated with idiopathic PD in Latin America. A PRISMA-compliant systematic review was conducted in MEDLINE, EMBASE and LILACS, compiling studies published up to February 7, 2025. Nineteen case-control studies were included. Two hypothesis-free studies identified rs525496 near H2BW1 as a protective factor and rs356182 in SNCA as a risk factor through XWAS and GWAS, respectively. Seventeen hypothesis-driven studies examined over three hundred variants, identifying nineteen genetic markers; risk factors included one INDEL in NR4A2, CNV burdens in PRKN, SNCA, and PLA2G6, along with fourteen variants in six loci including GBA, APOEε4, MTHFR, LRRK2, and SNCA. Three SNPs in the PICALM, ALDH1A1, and APOE-ε3 loci were identified as protective factors. Additionally, six SNCA variant haplotypes appear to increase PD risk, while two NR4A2 INDELs haplotypes showed mixed effects. This review summarized genetic loci associated with idiopathic PD in Latin American populations evidencing an overlap with European findings as well as novel loci, although awaiting replication and validation. These observations contribute to the understanding of genetic configuration of the disease and highlight the need for further genomic research in underrepresented groups that include local ancestry analysis within admixed cohorts to guide development of personalized treatments and population-specific interventions.

Large-scale admixture mapping in the All of Us Research Program improves the characterization of cross-population phenotypic differences

Admixed individuals have largely been understudied in medical research due to their complex genetic ancestries. However, the consideration of admixture can help identify ancestry-enriched genetic associations, delineating some of the genetic underpinnings of cross-population phenotypic variation. To this end, we performed local ancestry inference within the All of Us Research Program to identify individuals with recent admixture between African (AFR) and European (EUR) populations (N=48,921). We identified evidence of local AFR ancestry enrichment at the HLA locus, suggestive of putative selection since admixture. Furthermore, we performed the largest admixture mapping (ADM) efforts in AFR-EUR Admixed individuals for 22 traits, identifying 71 associations between inferred local AFR ancestries and a trait. Variants from published GWAS could only account for 18 (25%) of the ADM associations, highlighting novel loci where ancestral haplotypes explained some phenotypic variation. Previous studies likely have not identified these loci due to the low availability of high-powered GWAS in populations genetically similar to AFR. One such loci was 9q21.33, associated with 1.4-fold risk of end-stage kidney disease (ESKD) for carriers of inferred local AFR ancestries at the region. This locus contains the gene SLC28A3, which has previously been linked to kidney function but has never been associated with cross-population ESKD prevalence differences. Together, our results expand upon the existing literature on phenotypic differences between populations, highlighting loci where genetic ancestries play a critical role in the genetic architecture of disease.

Integrated genetic analysis and single cell-RNA sequencing for brain image-derived phenotypes and Parkinson's disease

BACKGROUND

Previous studies have reported Parkinson's disease (PD) patients usually have changes in brain image-derived phenotypes (IDPs). However, the role of genetic factors in their association and biological mechanism remains unclear. We aimed to unveil genetic and biological links between brain IDPs and PD.

METHODS

Using genome-wide association study (GWAS) summary statistics and single-cell RNA sequencing (scRNA-seq) data, we performed a comprehensive analysis between 624 brain IDPs and PD. The genetic correlations and causality were examined by linkage disequilibrium score regression (LDSC), two-sample bidirectional Mendelian randomization (MR) and meta-analysis. Potential shared genes were identified using MAGMA and PLACO. Finally, pathway enrichment using FUMA and Metascape, and scRNA-seq analysis were performed to determine biological mechanisms and gene expression atlas across various cell types in brain tissue.

RESULTS

LDSC revealed that 50 brain IDPs were genetically correlated with PD (P < 0.05), in which 5 IDPs, exhibited putative causality on PD through MR (P < 0.05). For instance, we identified that the increased volume of the right thalamus (IVW: OR = 2.08, 95 % CI: 1.33 to 3.25, PFDR = 0.03) was positively correlated with the risk of PD, which was also supported by replicated MR (IVW: OR = 1.63, 95 % CI: 1.17-2.26, PFDR = 0.02) in FinnGen and meta-analysis (OR = 1.78, 95 % CI: 1.36-2.31, PFDR = 5.00 × 10-4). Additionally, we identified 56 unique pleiotropic genes, such as FAM13A, with notable enrichment in neuronal cells. Biological mechanism analysis revealed these genes were enriched in brain tissues and a variety of pathways such as negative regulation of neuron apoptotic processes.

CONCLUSION

We indicated the shared genetic architecture and biological mechanisms between brain IDPs and PD. These findings might provide insights on the therapeutic intervention and early prediction of PD at the brain imaging level.

Targeting mitophagy in neurodegenerative diseases

Mitochondrial dysfunction is a hallmark of idiopathic neurodegenerative diseases, including Parkinson disease, amyotrophic lateral sclerosis, Alzheimer disease and Huntington disease. Familial forms of Parkinson disease and amyotrophic lateral sclerosis are often characterized by mutations in genes associated with mitophagy deficits. Therefore, enhancing the mitophagy pathway may represent a novel therapeutic approach to targeting an underlying pathogenic cause of neurodegenerative diseases, with the potential to deliver neuroprotection and disease modification, which is an important unmet need. Accumulating genetic, molecular and preclinical model-based evidence now supports targeting mitophagy in neurodegenerative diseases. Despite clinical development challenges, small-molecule-based approaches for selective mitophagy enhancement - namely, USP30 inhibitors and PINK1 activators - are entering phase I clinical trials for the first time.

Genetic Insights into Brain Morphology: a Genome-Wide Association Study of Cortical Thickness and T1-Weighted MRI Gray Matter-White Matter Intensity Contrast

In T1-weighted magnetic resonance imaging (MRI), cortical thickness (CT) and gray-white matter contrast (GWC) capture brain morphological traits and vary with age-related disease. To gain insight into genetic factors underlying brain structure and dynamics observed during neurodegeneration, this genome-wide association study (GWAS) quantifies the relationship between single nucleotide polymorphisms (SNPs) and both CT and GWC in UK Biobank participants (N = 43,002). To our knowledge, this is the first GWAS to investigate the genetic determinants of cortical T1-MRI GWC in humans. We found 251 SNPs associated with CT or GWC for at least 1% of cortical locations, including 42 for both CT and GWC; 127 for only CT; and 82 for only GWC. Identified SNPs include rs1080066 (THSB1, featuring the strongest association with both CT and GWC), rs13107325 (SLC39A8, linked to CT at the largest number of cortical locations), and rs864736 (KCNK2, associated with GWC at the largest number of cortical locations). Dimensionality reduction reveals three major gene ontologies constraining CT (neural signaling, ion transport, cell migration) and four constraining GWC (neural cell development, cellular homeostasis, tissue repair, ion transport). Our findings provide insight into genetic determinants of GWC and CT, highlighting pathways associated with brain anatomy and dynamics of neurodegeneration. These insights can assist the development of gene therapies and treatments targeting brain diseases.

The Neurodegenerative Disease Knowledge Portal: Propelling Discovery Through the Sharing of Neurodegenerative Disease Genomic Resources

Although large-scale genetic association studies have proven useful for the delineation of neurodegenerative disease processes, we still lack a full understanding of the pathologic mechanisms of these diseases, resulting in few appropriate treatment options and diagnostic challenges. To mitigate these gaps, the Neurodegenerative Disease Knowledge Portal (NDKP) was created as an open-science initiative with the aim to aggregate, enable analysis, and display all available genomic datasets of neurodegenerative disease, while protecting the integrity and confidentiality of the underlying datasets. The portal contains 218 genomic datasets, including genotyping and sequencing studies, of individuals across 10 different phenotypic groups, including neurologic conditions such as Alzheimer disease, amyotrophic lateral sclerosis, Lewy body dementia, and Parkinson disease. In addition to securely hosting large genomic datasets, the NDKP provides accessible workflows and tools to effectively use the datasets and assist in the facilitation of customized genomic analyses. Here, we summarize the genomic datasets currently included within the portal, the bioinformatics processing of the datasets, and the variety of phenotypes captured. We also present example use cases of the various user interfaces and integrated analytic tools to demonstrate their extensive utility in enabling the extraction of high-quality results at the source, for both genomics experts and those in other disciplines. Overall, the NDKP promotes open science and collaboration, maximizing the potential for discovery from the large-scale datasets researchers and consortia are expending immense resources to produce and resulting in reproducible conclusions to improve diagnostic and therapeutic care for patients with neurodegenerative disease.

Accumulation of Damaging Lipids in the Arf1-Ablated Neurons Promotes Neurodegeneration through Releasing mtDNA and Activating Inflammatory Pathways in Microglia

Lipid metabolism disorders in both neurons and glial cells have been found in neurodegenerative (ND) patients and animal models. However, the pathological connection between lipid droplets and NDs remains poorly understood. The recent work has highlighted the utility of a neuron-specific Arf1-knockout mouse model and corresponding cells for elucidating the nexus between lipid metabolism disorders and amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS). In this study, it is found that Arf1 deficiency first induced surplus fatty acid synthesis through the AKT-mTORC1-SREBP1-FASN axis, which further triggered endoplasmic reticulum (ER)-mitochondrial stress cascade via calcium flux. The organelle stress cascade further caused mitochondrial DNA (mtDNA) to be released into cytoplasm. Concurrently, the FASN-driven fatty acid synthesis in the Arf1-deficient neurons might also induce accumulation of sphingolipids in lysosomes that caused dysfunction of autophagy and lysosomes, which further promoted lysosomal stress and mitochondria-derived extracellular vesicles (MDEVs) release. The released MDEVs carried mtDNA into microglia to activate the inflammatory pathways and neurodegeneration. The studies on neuronal lipid droplets (LDs) and recent studies of microglial LDs suggest a unified pathological function of LDs in NDs: activating the inflammatory pathways in microglia. This finding potentially provides new therapeutic strategies for NDs.

Epigenome-wide association study, meta-analysis, and multiscore profiling of whole blood in Parkinson's disease

OBJECTIVES

An increasing body of evidence indicates altered DNA methylation in Parkinson's disease, yet the reproducibility and utility of such methylation changes are largely unexplored. We aimed to further elucidate the role of dysregulated DNA methylation in Parkinson's disease and to evaluate the biomarker potential of methylation-based profiling.

METHODS

We conducted an epigenome-wide association study (EWAS) in whole blood, including 280 Parkinson's disease and 279 control participants from Oslo, Norway. Next, we took advantage of data from the Parkinson's Progression Markers Initiative (PPMI) and a previously published EWAS to conduct a whole blood EWAS meta-analysis in Parkinson's disease, incorporating results from a total of 3068 participants. Finally, we generated multiple methylation-based scores for each Oslo and PPMI participant and tested their association with disease status, individually and in a joint multiscore model.

RESULTS

In EWAS meta-analysis, we confirm SLC7A11 hypermethylation and nominate a novel differentially methylated CpG near LPIN1. A joint multiscore model incorporating polygenic risk and methylation-based estimates of epigenetic Parkinson's disease risk, smoking, and leukocyte proportions differentiated patients from control participants with an area under the receiver-operator curve of 0.82 in the Oslo cohort and 0.65 in PPMI.

INTERPRETATION

Our results highlight the power of DNA methylation profiling to capture multiple aspects of disease risk, indicating a biomarker potential for precision medicine in neurodegenerative disorders. The reproducibility of specific differentially methylated CpGs across data sets was limited but may improve if future studies are designed to account for disease stage and incorporate environmental exposure data.

Circular RNAs in neurological conditions - computational identification, functional validation, and potential clinical applications

Non-coding RNAs (ncRNAs) have gained significant attention in recent years due to advancements in biotechnology, particularly high-throughput total RNA sequencing. These developments have led to new understandings of non-coding biology, revealing that approximately 80% of non-coding regions in the genome possesses biochemical functionality. Among ncRNAs, circular RNAs (circRNAs), first identified in 1976, have emerged as a prominent research field. CircRNAs are abundant in most human cell types, evolutionary conserved, highly stable, and formed by back-splicing events which generate covalently closed ends. Notably, circRNAs exhibit high expression levels in neural tissue and perform diverse biochemical functions, including acting as molecular sponges for microRNAs, interacting with RNA-binding proteins to regulate their availability and activity, modulating transcription and splicing, and even translating into functional peptides in some cases. Recent advancements in computational and experimental methods have enhanced our ability to identify and validate circRNAs, providing valuable insights into their biological roles. This review focuses on recent developments in circRNA research as they related to neuropsychiatric and neurodegenerative conditions. We also explore their potential applications in clinical diagnostics, therapeutics, and future research directions. CircRNAs remain a relatively underexplored area of non-coding biology, particularly in the context of neurological disorders. However, emerging evidence supports their role as critical players in the etiology and molecular mechanisms of conditions such as schizophrenia, bipolar disorder, major depressive disorder, Alzheimer's disease, and Parkinson's disease. These findings suggest that circRNAs may provide a novel framework contributing to the molecular dysfunctions underpinning these complex neurological conditions.

Genetic risk for neurodegenerative conditions is linked to disease-specific microglial pathways

Genome-wide association studies have identified thousands of common variants associated with an increased risk of neurodegenerative disorders. However, the noncoding localization of these variants has made the assignment of target genes for brain cell types challenging. Genomic approaches that infer chromosomal 3D architecture can link noncoding risk variants and distal gene regulatory elements such as enhancers to gene promoters. By using enhancer-to-promoter interactome maps for human microglia, neurons, and oligodendrocytes, we identified cell-type-specific enrichment of genetic heritability for brain disorders through stratified linkage disequilibrium score regression. Our analysis suggests that genetic heritability for multiple neurodegenerative disorders is enriched at microglial chromatin contact sites, while schizophrenia heritability is predominantly enriched at chromatin contact sites in neurons followed by oligodendrocytes. Through Hi-C coupled multimarker analysis of genomic annotation (H-MAGMA), we identified disease risk genes for Alzheimer's disease, Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis and schizophrenia. We found that disease-risk genes were overrepresented in microglia compared to other brain cell types across neurodegenerative conditions and within neurons for schizophrenia. Notably, the microglial risk genes and pathways identified were largely specific to each disease. Our findings reinforce microglia as an important, genetically informed cell type for therapeutic interventions in neurodegenerative conditions and highlight potentially targetable disease-relevant pathways.

Blood biomarker profiles in young-onset neurocognitive disorders: A cohort study

INTRODUCTION

Young-onset neurocognitive symptoms result from a heterogeneous group of neurological and psychiatric disorders which present a diagnostic challenge. To identify such factors, we analysed the Biomarkers in Younger-Onset Neurocognitive Disorders cohort, a study of individuals <65 years old presenting with neurocognitive symptoms for a diagnosis and who have undergone cognitive and biomarker analyses.

METHODS

Sixty-five participants (median age at assessment of 56 years, 45% female) were recruited during their index presentation to the Royal Melbourne Hospital Neuropsychiatry Centre, a tertiary specialist service in Melbourne, Australia, and categorized as either early-onset Alzheimer's disease (n = 18), non-Alzheimer's disease neurodegeneration (n = 23) or primary psychiatric disorders (n = 24). Levels of neurofilament light chain, glial fibrillary acidic protein and phosphorylated-tau 181, apolipoprotein E genotype and late-onset Alzheimer's disease polygenic risk scores were determined. Information-theoretic model selection identified discriminatory factors.

RESULTS

Neurofilament light chain, glial fibrillary acidic protein and phosphorylated-tau 181 levels were elevated in early-onset Alzheimer's disease compared with other diagnostic categories. A multi-omic model selection identified that a combination of cognitive and blood biomarkers, but not the polygenic risk score, discriminated between early-onset Alzheimer's disease and primary psychiatric disorders (area under the curve ⩾ 0.975, 95% confidence interval: 0.825-1.000). Phosphorylated-tau 181 alone significantly discriminated between early-onset Alzheimer's disease and non-Alzheimer's disease neurodegeneration causes (area under the curve = 0.950, 95% confidence interval: 0.877-1.00).

DISCUSSION

Discriminating between early-onset Alzheimer's disease, non-Alzheimer's disease neurodegeneration and primary psychiatric disorders causes of young-onset neurocognitive symptoms is possible by combining cognitive profiles with blood biomarkers. These results support utilizing blood biomarkers for the work-up of young-onset neurocognitive symptoms and highlight the need for the development of a young-onset Alzheimer's disease-specific polygenic risk score.

Genomic and epigenomic insights into purkinje and granule neurons in Alzheimer's disease and related dementia using single-nucleus multiome analysis

Although the human cerebellum is known to be neuropathologically impaired in Alzheimer's disease (AD) and AD-related dementias (ADRD), the cell type-specific transcriptional and epigenomic changes that contribute to this pathology are not well understood. Here, we report single-nucleus multiome (snRNA-seq and snATAC-seq) analysis of 103,861 nuclei isolated from both cerebellum and frontal cortex of AD/ADRD patients and normal controls. Using peak-to-gene linkage analysis, we identified 431,834 significant linkages between gene expression and cell subtype-specific chromatin accessibility regions enriched for candidate cis-regulatory elements (cCREs). These cCREs were associated with AD/ADRD-specific transcriptomic changes and disease-related gene regulatory networks, especially for RAR Related Orphan Receptor A (RORA) and E74 Like ETS Transcription Factor 1 (ELF1) in cerebellar Purkinje cells and granule cells, respectively. Trajectory analysis of granule cell populations further identified disease-relevant transcription factors, such as RORA, and their regulatory targets. Finally, we pinpointed two likely causal genes, Seizure Related 6 Homolog Like 2 (SEZ6L2) in Purkinje cells and KAT8 Regulatory NSL Complex Subunit 1 (KANSL1) in granule cells, through integrative analysis of cCREs derived from snATAC-seq, genome-wide AD/ADRD loci, and three-dimensional (3D) genome data. Via CRISPRi experiments, we found that perturbation of rs4788201 and rs62056801 significantly inhibited the expression of their target genes, SEZ6L2 and KANSL1, in human iPSC-derived neurons. This cell subtype-specific regulatory landscape in the human cerebellum identified here offers novel genomic and epigenomic insights into the neuropathology and pathobiology of AD/ADRD and other neurological disorders if broadly applied.

Novel Parkinson's Disease Genetic Risk Factors Within and Across European Populations

Introduction

We conducted a meta-analysis of Parkinson's disease genome-wide association study summary statistics, stratified by source (clinically-recruited case-control cohorts versus population biobanks) and by general European versus European isolate ancestries. This study included 63,555 cases, 17,700 proxy cases with a family history of Parkinson's disease, and 1,746,386 controls, making it the largest investigation of Parkinson's disease genetic risk to date.

Methods

Meta-analyses were performed using standard fixed and random effect models for the European sub-populations, the case-control studies, and the population biobanks separately. Finally, all of the European ancestries for all study types as well as proxy cases were combined in our final cross-European meta-analysis. We estimated heritable risk across ancestry groups, investigated tissue and cell-type enrichment, and prioritized risk genes using public data to facilitate functional follow-up efforts.

Results

The final combined cross-European meta-analysis identified 134 risk loci (59 novel), with a total of 157 independent signals, significantly expanding our understanding of Parkinson's disease risk. Multi-omic data integration revealed that expression of the nominated risk genes are highly enriched in brain tissues, particularly in neuronal and astrocyte cell types. Additionally, we prioritized 33 high-confidence genes across these 134 loci for future follow-up studies.

Conclusions

By integrating diverse European populations and leveraging harmonized data from the Global Parkinson's Genetics Program (GP2), we reveal new insight into the genetic architecture of Parkinson's disease. We identified a total of 134 risk loci, expanding the number of known loci associated with PD by approximately 24%. We also provided an initial layer of biological context to these results through follow-up analyses in an effort to facilitate follow-up studies and precision medicine efforts with the goal of advancing Parkinson's disease research.

Interrogating DNA methylation associated with Lewy body pathology in a cross brain-region and multi-cohort study

Lewy body (LB) diseases are an umbrella term encompassing a range of neurodegenerative conditions all characterized by the hallmark of intra-neuronal α-synuclein associated with the development of motor and cognitive dysfunction. In this study, we have conducted a large meta-analysis of DNA methylation across multiple cortical brain regions, in relation to increasing burden of LB pathology. Utilizing a combined dataset of 1239 samples across 855 unique donors, we identified a set of 30 false discovery rate (FDR) significant loci that are differentially methylated in association with LB pathology, the most significant of which were located in UBASH3B and PTAFR, as well as an intergenic locus. Ontological enrichment analysis of our meta-analysis results highlights several neurologically relevant traits, including synaptic, inflammatory and vascular alterations. We leverage our summary statistics to compare DNA methylation signatures between different neurodegenerative pathologies and highlight a shared epigenetic profile across LB diseases, Alzheimer's disease and Huntington's disease, although the top-ranked loci show disease specificity. Finally, utilizing summary statistics from previous large-scale genome-wide association studies we report FDR significant enrichment of DNA methylation differences with respect to increasing LB pathology in the SNCA genomic region, a gene previously associated with Parkinson's disease and dementia with Lewy bodies.

Genetic Analysis of Retinal Cell Types in Neuropsychiatric Disorders

Importance

As an accessible part of the central nervous system, the retina provides a unique window to study pathophysiological mechanisms of brain disorders in humans. Imaging and electrophysiological studies have revealed retinal alterations across several neuropsychiatric and neurological disorders, but it remains largely unclear which specific cell types and biological mechanisms are involved.

Objective

To determine whether specific retinal cell types are affected by genomic risk for neuropsychiatric and neurological disorders and to explore the mechanisms through which genomic risk converges in these cell types.

Design, Setting, and Participants

This genetic association study combined findings from genome-wide association studies in schizophrenia, bipolar disorder, major depressive disorder, multiple sclerosis, Parkinson disease, Alzheimer disease, and stroke with retinal single-cell transcriptomic datasets from humans, macaques, and mice. To identify susceptible cell types, Multi-Marker Analysis of Genomic Annotation (MAGMA) cell-type enrichment analyses were applied and subsequent pathway analyses performed. The cellular top hits were translated to the structural level using retinal optical coherence tomography (acquired between 2009 and 2010) and genotyping data in the large population-based UK Biobank cohort study. Data analysis was conducted between 2022 and 2024.

Main Outcomes and Measures

Cell type-specific enrichment of genetic risk loading for neuropsychiatric and neurological disorder traits in the gene expression profiles of retinal cells.

Results

Expression profiles of amacrine cells (interneurons within the retina) were robustly enriched in schizophrenia genetic risk across mammalian species and in different developmental stages. This enrichment was primarily driven by genes involved in synapse biology. Moreover, expression profiles of retinal immune cell populations were enriched in multiple sclerosis genetic risk. No consistent cell-type associations were found for bipolar disorder, major depressive disorder, Parkinson disease, Alzheimer disease, or stroke. On the structural level, higher polygenic risk for schizophrenia was associated with thinning of the ganglion cell inner plexiform layer, which contains dendrites and synaptic connections of amacrine cells (B, -0.09; 95% CI, -0.16 to -0.03; P = .007; n = 36 349; mean [SD] age, 57.50 [8.00] years; 19 859 female [54.63%]). Higher polygenic risk for multiple sclerosis was associated with increased thickness of the retinal nerve fiber layer (B, 0.06; 95% CI, 0.02 to 0.10; P = .007; n = 36 371; mean [SD] age, 57.51 [8.00] years; 19 843 female [54.56%]).

Conclusions and Relevance

This study provides novel insights into the cellular underpinnings of retinal alterations in neuropsychiatric and neurological disorders and highlights the retina as a potential proxy to study synaptic pathology in schizophrenia.

Autophagy related genes polymorphisms in Parkinson's Disease; A systematic review of literature

Background

Neurodegenerative diseases are mainly a consequence of degenerated proteins in neurons. Parkinson's disease (PD) is one of the most common neurodegenerative disorders and is characterized by Lewy body deposition. Autophagy is known as one of the cell maintenance mechanisms. Autophagy targets are damaged or degenerated macromolecules and organelles for lysosomal degradation. The role of disrupted autophagy in PD was established earlier. In this regard, the current study aimed to evaluate the frequency and status of the autophagy gene polymorphisms in PD by a systematic review approach.

Materials and methods

In the current study, electronic databases including Scopus, PubMed, and Science Direct were used for the search. The search was performed by using Parkinson's disease, autophagy, autophagy-related gene, ATG, Single-nucleotide polymorphisms, variant, Sequence variants, and with a date limitation of 2010 to 2023. All original research papers in the English language that evaluate the ATG polymorphisms in PD were included in the study.

Results

The conducted search leads to 2626 primary studies screened based on the inclusion criteria. After the screening stage, 8 studies were included. ATG7 rs1375206 and ATG5 rs510432, rs573775 and rs17587319 were associated with PD. However, some other polymorphisms in ATGs that were not associated with PD were listed.

Conclusion

In conclusion, regardless of the critical role of autophagy in PD pathogenesis, it seems that ATG16 and ATG7 polymorphisms are not associated with PD; however, ATG7 rs1375206 needs more evaluation for a clearer conclusion in future studies. ATG5 and ATG12 polymorphisms seem to be more important in PD. More comprehensive studies about all ATG5, 7, 12, and 16 seem to be urgently required for a conclusive judgment about their role in PD or even other neurodegenerative disorders.

Clinical and functional evidence for the pathogenicity of the LRRK2 p.Arg1067Gln variant

LRRK2-related Parkinson's disease (LRRK2-PD) is the most frequent form of monogenic PD worldwide, with important therapeutic opportunities, exemplified by the advancement in LRRK2 kinase inhibition studies/trials. However, many LRRK2 variants, especially those found in underrepresented populations, remain classified as variants of uncertain significance (VUS). Leveraging on Malaysian, Singaporean, and mainland Chinese PD datasets (n = 4901), we describe 12 Chinese-ancestry patients harboring the LRRK2 p.Arg1067Gln variant, more than doubling the number of previously reported cases (total n = 23, 87% East Asian, mean age of onset: 53.9 years). We determine that this variant is enriched in East Asian PD patients compared to population controls (OR = 8.0, 95% CI: 3.0-20.9), and provide supportive data for its co-segregation with PD, albeit with incomplete penetrance. Utilizing established experimental workflows, this variant showed increased LRRK2 kinase activity, by ~2-fold compared to wildtype and higher than the p.Gly2019Ser variant. Taken together, p.Arg1067Gln should be reclassified from a VUS to pathogenic for causing LRRK2-PD.

Deciphering the Genetic Architecture of Parkinson's Disease in India

The genomic landscape of the Indian population, particularly for age-related disorders like Parkinson's disease (PD) remains underrepresented in global research. Genetic variability in PD has been studied predominantly in European populations, offering limited insights into its role within the Indian population. To address this gap, we conducted the first pan-India genomic survey of PD involving 4,806 cases and 6,364 controls, complemented by a meta-analysis integrating summary statistics from a multi-ancestry PD meta-analysis (N=611,485). We further leveraged RNA-sequencing data from lymphoblastoid cell lines of 731 individuals from the 1000 Genomes project to evaluate the expression of key loci across global populations. Our findings reveal a higher genetic burden of PD in the Indian population compared to Europeans, accounting for ∼30% of the previously unexplained heritability. Thirteen genome-wide significant loci were identified, including two novel loci, with an additional three loci uncovered through meta-analysis. Polygenic risk score analysis showed moderate transferability from European populations. Our results highlight the importance of genetic loci in immune function, lipid metabolism and SNCA aggregation in PD pathogenesis, with gene expression variability emphasizing population-specific differences. We also established South Asia's largest PD biobank, providing a foundation for patient-centric approaches to PD research and treatment in India.

Patient-centered brain transcriptomic and multimodal imaging determinants of clinical progression, physical activity, and treatment needs in Parkinson's disease

We continue to lack a clear understanding on how the biological and clinical complexity of Parkinson's disease emerges from molecular to macroscopic brain interactions. Here, we use personalized multiscale spatiotemporal computational brain models to characterize for the first time the synergistic links between genes, several multimodal neuroimaging-derived biological factors, clinical profiles, and therapeutic needs in PD. We identified genes modulating PD-caused brain reorganization in dopamine transporter level, neuronal activity integrity, microstructure, dendrite density and tissue atrophy. Inter-individual heterogeneity in the identified gene-mediated biological mechanisms was associated with five distinct configurations of PD motor and non-motor symptoms. Notably, the protein-protein interaction networks underlying both brain phenotypic and symptom configurations in PD revealed distinct hub genes including MYC, CCNA2, CCDK1, SRC, STAT3 and PSMD4. We also studied the biological mechanisms associated with physical activities performance, observing that leisure and work activities are strongly related to neurotypical cholesterol homeostasis and inflammatory response processes, respectively. Finally, patient-tailored in silico gene perturbations revealed a set of putative disease-modifying drugs with potential to effectively treat PD across different biological levels, most of which are associated with dopamine reuptake and anti-inflammation. Our study constitutes the first self-contained multiscale spatiotemporal computational approach providing comprehensive insights into the complex multifactorial pathogenesis of PD, unraveling key biological modulators of physical and clinical deterioration, and serving as a blueprint for optimum drug selection at personalized level.

EndoMAP.v1, a Structural Protein Complex Landscape of Human Endosomes

Early/sorting endosomes are dynamic organelles that play key roles in proteome control by triaging plasma membrane proteins for either recycling or degradation in the lysosome1,2,3. These events are coordinated by numerous transiently-associated regulatory complexes and integral membrane components that contribute to organelle identity during endosome maturation4. While a subset of the several hundred protein components and cargoes known to associate with endosomes have been studied at the biochemical and/or structural level, interaction partners and higher order molecular assemblies for many endosomal components remain unknown. Here, we combine cross-linking and native gel mass spectrometry5-8 of purified early endosomes with AlphaFold9,10 and computational analysis to create a systematic human endosomal structural interactome. We present dozens of structural models for endosomal protein pairs and higher order assemblies supported by experimental cross-links from their native subcellular context, suggesting structural mechanisms for previously reported regulatory processes. Using induced neurons, we validate two candidate complexes whose interactions are supported by crosslinks and structural predictions: TMEM230 as a subunit of ATP8/11 lipid flippases11 and TMEM9/9B as subunits of CLCN3/4/5 chloride-proton antiporters12. This resource and its accompanying structural network viewer provide an experimental framework for understanding organellar structural interactomes and large-scale validation of structural predictions.

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

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

A Reproducibility Focused Meta-Analysis Method for Single-Cell Transcriptomic Case-Control Studies Uncovers Robust Differentially Expressed Genes

We assessed the reproducibility of differentially expressed genes (DEGs) in previously published Alzheimer's (AD), Parkinson's (PD), Schizophrenia (SCZ), and COVID-19 scRNA-seq studies. While transcriptional scores from DEGs of individual PD and COVID-19 datasets had moderate predictive power for case-control status of other datasets (AUC=0.77 and 0.75), genes from individual AD and SCZ datasets had poor predictive power (AUC=0.68 and 0.55). We developed a non-parametric meta-analysis method, SumRank, based on reproducibility of relative differential expression ranks across datasets, and found DEGs with improved predictive power (AUC=0.88, 0.91, 0.78, and 0.62). By multiple other metrics, specificity and sensitivity of these genes were substantially higher than those discovered by dataset merging and inverse variance weighted p-value aggregation methods. The DEGs revealed known and novel biological pathways, and we validate BCAT1 as down-regulated in AD mouse oligodendrocytes. Lastly, we evaluate factors influencing reproducibility of individual studies as a prospective guide for experimental design.

Genetic Markers of Postmortem Brain Iron

Brain iron (Fe) dyshomeostasis is implicated in neurodegenerative diseases. Genome-wide association studies (GWAS) have identified plausible loci correlated with peripheral levels of Fe. Systemic organs and the brain share several Fe regulatory proteins but there likely exist different homeostatic pathways. We performed the first GWAS of inductively coupled plasma mass spectrometry measures of postmortem brain Fe from 635 Rush Memory and Aging Project (MAP) participants. Sixteen single nucleotide polymorphisms (SNPs) associated with Fe in at least one of four brain regions were measured (p < 5 × 10-8). Promising SNPs (p < 5 × 10-6) were followed up for replication in published GWAS of blood, spleen, and brain imaging Fe traits and mapped to candidate genes for targeted cortical transcriptomic and epigenetic analysis of postmortem Fe in MAP. Results for SNPs previously associated with other Fe traits were also examined. Ninety-eight SNPs associated with postmortem brain Fe were at least nominally (p < 0.05) associated with one or more related Fe traits. Most novel loci identified had no direct links to Fe regulatory pathways but rather endoplasmic reticulum-Golgi trafficking (SORL1, SORCS2, MARCH1, CLTC), heparan sulfate (HS3ST4, HS3ST1), and coenzyme A (SLC5A6, PANK3); supported by nearest gene function and omic analyses. We replicated (p < 0.05) several previously published Fe loci mapping to candidate genes in cellular and systemic Fe regulation. Finally, novel loci (BMAL, COQ5, SLC25A11) and replication of prior loci (PINK1, PPIF, LONP1) lend support to the role of circadian rhythms and mitochondria function in Fe regulation more generally. In summary, we provide support for novel loci linked to pathways that may have greater relevance to brain Fe accumulation; some of which are implicated in neurodegeneration. However, replication of a subset of prior loci for blood Fe suggests that genetic determinants or biological pathways underlying Fe accumulation in the brain are not completely distinct from those of Fe circulating in the periphery.

Exome sequencing in Asian populations identifies low-frequency and rare coding variation influencing Parkinson's disease risk

Parkinson's disease (PD) is an incurable, progressive and common movement disorder that is increasing in incidence globally because of population aging. We hypothesized that the landscape of rare, protein-altering variants could provide further insights into disease pathogenesis. Here we performed whole-exome sequencing followed by gene-based tests on 4,298 PD cases and 5,512 controls of Asian ancestry. We showed that GBA1 and SMPD1 were significantly associated with PD risk, with replication in a further 5,585 PD cases and 5,642 controls. We further refined variant classification using in vitro assays and showed that SMPD1 variants with reduced enzymatic activity display the strongest association (<44% activity, odds ratio (OR) = 2.24, P = 1.25 × 10-15) with PD risk. Moreover, 80.5% of SMPD1 carriers harbored the Asian-specific p.Pro332Arg variant (OR = 2.16; P = 4.47 × 10-8). Our findings highlight the utility of performing exome sequencing in diverse ancestry groups to identify rare protein-altering variants in genes previously unassociated with disease.

Rare SV2C coding variants in Parkinson's disease risk

Genome-wide association studies have identified SV2C as a Parkinson's disease (PD) risk locus, with a common missense variant p.Asp543Asn in the synaptic vesicle glycoprotein 2C (SV2C) protein significantly associated with PD. We examined if other rare SV2C variants also influence PD risk. We analyzed sequencing data of 9810 East Asian individuals comprising 4298 patients and 5512 controls and identified 55 rare nonsynonymous variants. There was no significant association of rare nonsynonymous or loss-of-function variants with PD. Our findings show that besides p.Asp543Asn, other rare coding variants in SV2C do not play a major role in PD susceptibility in East Asia.

Multi-ancestry genome-wide meta-analysis with 472,819 individuals identifies 32 novel risk loci for psoriasis

BACKGROUND

Psoriasis is a common chronic, recurrent, immune-mediated disease involved in the skin or joints or both. However, deeper insight into the genetic susceptibility of psoriasis is still unclear.

METHODS

Here we performed the largest multi-ancestry meta-analysis of genome-wide association study including 28,869 psoriasis cases and 443,950 healthy controls.

RESULTS

We identified 74 genome-wide significant loci for psoriasis. Of 74 loci, 32 were novel psoriasis risk loci. Across 74 loci, 801 likely causal genes are indicated and 164 causal genes are prioritized. SNP-based heritability analyses demonstrated that common variants explain 15% of genetic risk for psoriasis. Gene-set analyses and the genetic correlation revealed that psoriasis-related genes have the positive correlations with autoimmune diseases such as ulcerative colitis, inflammatory bowel diseases, and Crohn's disease. Gene-drug interaction analysis suggested that psoriasis-associated genes overlapped with targets of current medications for psoriasis. Finally, we used the multi-ancestry meta-analysis to explore drug repurposing and the potential targets for psoriasis.

CONCLUSIONS

We identified 74 genome-wide significant loci for psoriasis. Based on 74 loci, we provided new biological insights to the etiology of psoriasis. Of clinical interest, we gave some hints for 76 potential targets and drug repurposing for psoriasis.

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

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder. However, current treatments only manage symptoms and lack the ability to slow or prevent disease progression. We utilized a systems genetics approach to identify potential risk genes and repurposable drugs for PD. First, we leveraged non-coding genome-wide association studies (GWAS) loci effects on five types of brain-specific quantitative trait loci (xQTLs, including expression, protein, splicing, methylation and histone acetylation) under the protein-protein interactome (PPI) network. We then prioritized 175 PD likely risk genes (pdRGs), such as SNCA, CTSB, LRRK2, DGKQ, and CD44, which are enriched in druggable targets and differentially expressed genes across multiple human brain-specific cell types. Integrating network proximity-based drug repurposing and patient electronic health record (EHR) data observations, we identified Simvastatin as being significantly associated with reduced incidence of PD (hazard ratio (HR) = 0.91 for fall outcome, 95% confidence interval (CI): 0.87-0.94; HR = 0.88 for dementia outcome, 95% CI: 0.86-0.89) after adjusting for 267 covariates. In summary, our network-based systems genetics framework identifies potential risk genes and repurposable drugs for PD and other neurodegenerative diseases if broadly applied.

Large-scale genetic characterization of Parkinson's disease in the African and African admixed populations

Elucidating the genetic contributions to Parkinson's disease (PD) etiology across diverse ancestries is a critical priority for the development of targeted therapies in a global context. We conducted the largest sequencing characterization of potentially disease-causing, protein-altering and splicing mutations in 710 cases and 11,827 controls from genetically predicted African or African admixed ancestries. We explored copy number variants (CNVs) and runs of homozygosity (ROHs) in prioritized early onset and familial cases. Our study identified rare GBA1 coding variants to be the most frequent mutations among PD patients, with a frequency of 4% in our case cohort. Out of the 18 GBA1 variants identified, ten were previously classified as pathogenic or likely pathogenic, four were novel, and four were reported as of uncertain clinical significance. The most common known disease-associated GBA1 variants in the Ashkenazi Jewish and European populations, p.Asn409Ser, p.Leu483Pro, p.Thr408Met, and p.Glu365Lys, were not identified among the screened PD cases of African and African admixed ancestry. Similarly, the European and Asian LRRK2 disease-causing mutational spectrum, including LRRK2 p.Gly2019Ser and p.Gly2385Arg genetic risk factors, did not appear to play a major role in PD etiology among West African-ancestry populations. However, we found three heterozygous novel missense LRRK2 variants of uncertain significance overrepresented in cases, two of which - p.Glu268Ala and p.Arg1538Cys - had a higher prevalence in the African ancestry population reference datasets. Structural variant analyses revealed the presence of PRKN CNVs with a frequency of 0.7% in African and African admixed cases, with 66% of CNVs detected being compound heterozygous or homozygous in early-onset cases, providing further insights into the genetic underpinnings in early-onset juvenile PD in these populations. Novel genetic variation overrepresented in cases versus controls among screened genes warrants further replication and functional prioritization to unravel their pathogenic potential. Here, we created the most comprehensive genetic catalog of both known and novel coding and splicing variants potentially linked to PD etiology in an underserved population. Our study has the potential to guide the development of targeted therapies in the emerging era of precision medicine. By expanding genetics research to involve underrepresented populations, we hope that future PD treatments are not only effective but also inclusive, addressing the needs of diverse ancestral groups.

NERINE reveals rare variant associations in gene networks across multiple phenotypes and implicates an SNCA-PRL-LRRK2 subnetwork in Parkinson's disease

Gene networks encapsulate biological knowledge, often linked to polygenic diseases. While model system experiments generate many plausible gene networks, validating their role in human phenotypes requires evidence from human genetics. Rare variants provide the most straightforward path for such validation. While single-gene analyses often lack power due to rare variant sparsity, expanding the unit of association to networks offers a powerful alternative, provided it integrates network connections. Here, we introduce NERINE, a hierarchical model-based association test that integrates gene interactions that integrates gene interactions while remaining robust to network inaccuracies. Applied to biobanks, NERINE uncovers compelling network associations for breast cancer, cardiovascular diseases, and type II diabetes, undetected by single-gene tests. For Parkinson's disease (PD), NERINE newly substantiates several GWAS candidate loci with rare variant signal and synergizes human genetics with experimental screens targeting cardinal PD pathologies: dopaminergic neuron survival and alpha-synuclein pathobiology. CRISPRi-screening in human neurons and NERINE converge on PRL, revealing an intraneuronal α-synuclein/prolactin stress response that may impact resilience to PD pathologies.

SENP1 inhibits aerobic glycolysis in Aβ1-42-incubated astrocytes by promoting PUM2 deSUMOylation

Alzheimer's disease (AD), the most prevalent form of dementia in the elderly, involves critical changes such as reduced aerobic glycolysis in astrocytes and increased neuronal apoptosis, both of which are significant in the disease's pathology. In our study, astrocytes treated with amyloid β1-42 (Aβ1-42) to simulate AD conditions exhibited upregulated expressions of small ubiquitin-like modifier (SUMO)-specific protease 1 (SENP1) and Pumilio RNA Binding Family Member 2 (PUM2), alongside decreased levels of Nuclear factor erythroid 2-related factor 2 (NRF2). SENP1 is notably the most upregulated SUMOylation enzyme in Aβ1-42-exposed astrocytes. Functional assays including Ni2+-Nitrilotriacetic acid (NTA) agarose bead pull-down and co-immunoprecipitation (Co-IP) confirmed SENP1's role in actively deSUMOylating PUM2, thereby enhancing its stability and expression. The interaction between PUM2 and the 3' untranslated region (3'UTR) of NRF2 mRNA reduces NRF2 levels, subsequently diminishing the transcriptional activation of critical glycolytic enzymes, Hexokinase 1 (HK1) and Glucose Transporter 1 (GLUT1). These changes contribute to the observed reduction in glycolytic function in astrocytes, exacerbating neuronal apoptosis. Targeted interventions, such as knockdown of Senp1 or Pum2 or overexpression of NRF2 in APPswe/PSEN1dE9 (APP/PS1) transgenic mice, effectively increased HK1 and GLUT1 levels, decreased apoptosis, and alleviated cognitive impairment. These findings highlight the important roles of the SENP1/PUM2/NRF2 pathway in influencing glucose metabolism in astrocytes, presenting new potential therapeutic targets for AD.

Autophagy, aging, and age-related neurodegeneration

Autophagy is a conserved mechanism that degrades damaged or superfluous cellular contents and enables nutrient recycling under starvation conditions. Many neurodegeneration-associated proteins are autophagy substrates, and autophagy upregulation ameliorates disease in many animal models of neurodegeneration by enhancing the clearance of toxic proteins, proinflammatory molecules, and dysfunctional organelles. Autophagy inhibition also induces neuronal and glial senescence, a phenomenon that occurs with increasing age in non-diseased brains as well as in response to neurodegeneration-associated stresses. However, aging and many neurodegeneration-associated proteins and mutations impair autophagy. This creates a potentially detrimental feedback loop whereby the accumulation of these disease-associated proteins impairs their autophagic clearance, facilitating their further accumulation and aggregation. Thus, understanding how autophagy interacts with aging, senescence, and neurodegenerative diseases in a temporal, cellular, and genetic context is important for the future clinical application of autophagy-modulating therapies in aging and neurodegeneration.

Exploring and validating key genetic biomarkers for diagnosis of Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is a neurological condition characterized by complex genetic basic, and the reliable diagnosis of PD remained limited.

OBJECTIVE

To identify genes crucial to PD and assess their potential as diagnostic markers.

METHODS

Differentially expressed genes (DEGs) were screened from the PD tissue dataset and blood dataset. Two machine learning methods were used to identify key PD-related genes. The genes were validated in an independent dataset. Further validation using 120 peripheral blood mononuclear cells (PBMCs) from PD patients. The clinical significance and the diagnostic value of the genes was determined. The function of genes was analyzed and verified by cells experiments.

RESULTS

Thirteen common upregulated genes were identified between PD tissue dataset and blood dataset. Two machine learning methods identify three key PD-related genes (GPX2, CR1, ZNF556). An independent dataset and PBMCs samples results showed increased expression in PD patients. Clinical analysis showed that GPX2 and CR1 expression correlated with early-stage PD. The validated dataset of blood samples revealed each three gene showed moderate diagnostic potential for PD, with combined analysis outperforming individual gene analysis (AUC:0.701). The PBMCs samples showed similar diagnostic value of each gene, and the combination of the three genes presented better diagnostic value (AUC:0.801). Functional studies highlighted the involvement of these genes in key pathways in PD pathology. The results of SH-SY5Y cells showed that these three genes increased from PD cell model.

CONCLUSIONS

GPX2, CR1, ZNF556 were critical to the development of PD and might serve as diagnostic markers for PD.

Ancient viral DNA in the human genome linked to neurodegenerative diseases

BACKGROUND

Human endogenous retroviruses (HERVs) are sequences in the human genome that originated from infections with ancient retroviruses during our evolution. Previous studies have linked HERVs to neurodegenerative diseases, but defining their role in aetiology has been challenging. Here, we used a retrotranscriptome-wide association study (rTWAS) approach to assess the relationships between genetic risk for neurodegenerative diseases and HERV expression in the brain, calculated with genomic precision.

METHODS

We analysed genetic association statistics pertaining to Alzheimer's disease, amyotrophic lateral sclerosis, multiple sclerosis, and Parkinson's disease, using HERV expression models calculated from 792 cortical samples. Robust risk factors were considered those that survived multiple testing correction in the primary analysis, which were also significant in conditional and joint analyses, and that had a posterior inclusion probability above 0.5 in fine-mapping analyses.

RESULTS

The primary analysis identified 12 HERV expression signatures associated with neurodegenerative disease susceptibility. We found one HERV expression signature robustly associated with amyotrophic lateral sclerosis on chromosome 12q14 (MER61_12q14.2) and one robustly associated with multiple sclerosis on chromosome 1p36 (ERVLE_1p36.32a). A co-expression analysis suggested that these HERVs are involved in homophilic cell adhesion via plasma membrane adhesion molecules.

CONCLUSIONS

We found HERV expression profiles robustly associated with amyotrophic lateral sclerosis and multiple sclerosis susceptibility, highlighting novel risk mechanisms underlying neurodegenerative disease, and offering potential new targets for therapeutic intervention.

Scrutinizing neurodegenerative diseases: decoding the complex genetic architectures through a multi-omics lens

Neurodegenerative diseases present complex genetic architectures, reflecting a continuum from monogenic to oligogenic and polygenic models. Recent advances in multi-omics data, coupled with systems genetics, have significantly refined our understanding of how these data impact neurodegenerative disease mechanisms. To contextualize these genetic discoveries, we provide a comprehensive critical overview of genetic architecture concepts, from Mendelian inheritance to the latest insights from oligogenic and omnigenic models. We explore the roles of common and rare genetic variants, gene-gene and gene-environment interactions, and epigenetic influences in shaping disease phenotypes. Additionally, we emphasize the importance of multi-omics layers including genomic, transcriptomic, proteomic, epigenetic, and metabolomic data in elucidating the molecular mechanisms underlying neurodegeneration. Special attention is given to missing heritability and the contribution of rare variants, particularly in the context of pleiotropy and network pleiotropy. We examine the application of single-cell omics technologies, transcriptome-wide association studies, and epigenome-wide association studies as key approaches for dissecting disease mechanisms at tissue- and cell-type levels. Our review introduces the OmicPeak Disease Trajectory Model, a conceptual framework for understanding the genetic architecture of neurodegenerative disease progression, which integrates multi-omics data across biological layers and time points. This review highlights the critical importance of adopting a systems genetics approach to unravel the complex genetic architecture of neurodegenerative diseases. Finally, this emerging holistic understanding of multi-omics data and the exploration of the intricate genetic landscape aim to provide a foundation for establishing more refined genetic architectures of these diseases, enhancing diagnostic precision, predicting disease progression, elucidating pathogenic mechanisms, and refining therapeutic strategies for neurodegenerative conditions.

Machine learning analysis of population-wide plasma proteins identifies hormonal biomarkers of Parkinson's Disease

As the number of Parkinson's patients is expected to increase with the growth of the aging population there is a growing need to identify new diagnostic markers that can be used cheaply and routinely to monitor the population, stratify patients towards treatment paths and provide new therapeutic leads. Genetic predisposition and familial forms account for only around 10% of PD cases [1] leaving a large fraction of the population with minimal effective markers for identifying high risk individuals. The establishment of population-wide omics and longitudinal health monitoring studies provides an opportunity to apply machine learning approaches on these unbiased cohorts to identify novel PD markers. Here we present the application of three machine learning models to identify protein plasma biomarkers of PD using plasma proteomics measurements from 43,408 UK Biobank subjects as the training and test set and an additional 103 samples from Parkinson's Progression Markers Initiative (PPMI) as external validation. We identified a group of highly predictive plasma protein markers including known markers such as DDC and CALB2 as well as new markers involved in the JAK-STAT, PI3K-AKT pathways and hormonal signaling. We further demonstrate that these features are well correlated with UPDRS severity scores and stratify these to protective and adversarial features that potentially contribute to the pathogenesis of PD.

Comparative mapping of single-cell transcriptomic landscapes in neurodegenerative diseases

INTRODUCTION

Alzheimer's disease (AD), Dementia with Lewy bodies (DLB), and Parkinson's disease (PD) represent a spectrum of neurodegenerative disorders (NDDs). Here, we performed the first direct comparison of their transcriptomic landscapes.

METHODS

We profiled the whole transcriptomes of NDD cortical tissue by snRNA-seq. We used computational analyses to identify common and distinct differentially expressed genes (DEGs), biological pathways, vulnerable and disease-driver cell subtypes, and alteration in cell-to-cell interactions.

RESULTS

The same vulnerable inhibitory neuron subtype was depleted in both AD and DLB. Potentially disease-driving neuronal cell subtypes were present in both PD and DLB. Cell-cell communication was predicted to be increased in AD but decreased in DLB and PD. DEGs were most commonly shared across NDDs within inhibitory neuron subtypes. Overall, we observed the greatest transcriptomic divergence between AD and PD, while DLB exhibited an intermediate transcriptomic signature.

DISCUSSION

These results help explain the clinicopathological spectrum of this group of NDDs and provide unique insights into the shared and distinct molecular mechanisms underlying the pathogenesis of NDDs.

Prioritizing Parkinson's disease risk genes in genome-wide association loci

Recent advancements in Parkinson's disease (PD) drug development have been significantly driven by genetic research. Importantly, drugs supported by genetic evidence are more likely to be approved. While genome-wide association studies (GWAS) are a powerful tool to nominate genomic regions associated with certain traits or diseases, pinpointing the causal biologically relevant gene is often challenging. Our aim was to prioritize genes underlying PD GWAS signals. The polygenic priority score (PoPS) is a similarity-based gene prioritization method that integrates genome-wide information from MAGMA gene-level association tests and more than 57,000 gene-level features, including gene expression, biological pathways, and protein-protein interactions. We applied PoPS to data from the largest published PD GWAS in East Asian- and European-ancestries. We identified 120 independent associations with P < 5×10-8 and prioritized 46 PD genes across these loci based on their PoPS scores, distance to the GWAS signal, and presence of non-synonymous variants in the credible set. Alongside well-established PD genes (e.g., TMEM175 and VPS13C), some of which are targeted in ongoing clinical trials (i.e., SNCA, LRRK2, and GBA1), we prioritized genes with a plausible mechanistic link to PD pathogenesis (e.g., RIT2, BAG3, and SCARB2). Many of these genes hold potential for drug repurposing or novel therapeutic developments for PD (i.e., FYN, DYRK1A, NOD2, CTSB, SV2C, and ITPKB). Additionally, we prioritized potentially druggable genes that are relatively unexplored in PD (XPO1, PIK3CA, EP300, MAP4K4, CAMK2D, NCOR1, and WDR43). We prioritized a high-confidence list of genes with strong links to PD pathogenesis that may represent our next-best candidates for disease-modifying therapeutics. We hope our findings stimulate further investigations and preclinical work to facilitate PD drug development programs.

The Neurodegenerative Disease Knowledge Portal: Propelling Discovery Through the Sharing of Neurodegenerative Disease Genomic Resources

Although large-scale genetic association studies have proven useful for the delineation of neurodegenerative disease processes, we still lack a full understanding of the pathological mechanisms of these diseases, resulting in few appropriate treatment options and diagnostic challenges. To mitigate these gaps, the Neurodegenerative Disease Knowledge Portal (NDKP) was created as an open-science initiative with the aim to aggregate, enable analysis, and display all available genomic datasets of neurodegenerative disease, while protecting the integrity and confidentiality of the underlying datasets. The portal contains 218 genomic datasets, including genotyping and sequencing studies, of individuals across ten different phenotypic groups, including neurological conditions such as Alzheimer's disease, amyotrophic lateral sclerosis, Lewy body dementia, and Parkinson's disease. In addition to securely hosting large genomic datasets, the NDKP provides accessible workflows and tools to effectively utilize the datasets and assist in the facilitation of customized genomic analyses. Here, we summarize the genomic datasets currently included within the portal, the bioinformatics processing of the datasets, and the variety of phenotypes captured. We also present example use-cases of the various user interfaces and integrated analytic tools to demonstrate their extensive utility in enabling the extraction of high-quality results at the source, for both genomics experts and those in other disciplines. Overall, the NDKP promotes open-science and collaboration, maximizing the potential for discovery from the large-scale datasets researchers and consortia are expending immense resources to produce and resulting in reproducible conclusions to improve diagnostic and therapeutic care for neurodegenerative disease patients.

Genetic heterogeneity of early onset Parkinson disease: The dilemma of clinico-genetic correlation

With advances in genetic testing increasing proportion of early onset Parkinson disease (EOPD) are being identified to have an underlying genetic aetiology. This is can be in the form of either highly penetrant genes associated with phenotypes with monogenic or mendelian inheritance patterns or those genes known as risk factor genes which confer an increased risk of PD in an individual. Both of them can modify the phenotypic manifestation in a patient with PD. This improved knowledge has helped in deciphering the intricate role of various cellular pathways in the pathophysiology of PD including both early and late and even sporadic PD. However, the phenotypic and genotypic heterogeneity is a major challenge. Different deleterious alterations in a same gene can result in a spectrum of presentation spanning from juvenile to late onset and typical to atypical parkinsonism manifestation. Similarly, a single phenotype can occur due to abnormality in two or more different genes. This conundrum poses a dilemma in the clinical approach and in understanding the clinico-genetic correlation. Understanding the clinico-genetic correlation carries even more importance especially when genetic testing is either not accessible or affordable or in many regions both. In this narrative review, we aim to discuss briefly the approach to various PARK gene related EOPD and describe in detail the clinico-genetic correlation of individual type of PARK gene related genetic EOPD with respect to their classical clinical presentation, pathophysiology, investigation findings and treatment response to medication and surgery.

An Honest Reckoning With the Amygdala and Mental Illness

Anxiety disorders are a leading source of human misery, morbidity, and premature mortality. Existing treatments are far from curative for many, underscoring the need to clarify the underlying neural mechanisms. Although many brain regions contribute, the amygdala has received the most intense scientific attention. Over the past several decades, this scrutiny has yielded a detailed understanding of amygdala function, but it has failed to produce new clinical assays, biomarkers, or cures. Rising to this urgent public health challenge demands an honest reckoning with the functional-neuroanatomical complexity of the amygdala and a shift from theories anchored on "the amygdala" to models centered on specific amygdala nuclei and cell types. This review begins by examining evidence from studies of rodents, monkeys, and humans for the "canonical model," the idea that the amygdala plays a central role in fear- and anxiety-related states, traits, and disorders. Next, the authors selectively highlight work indicating that the canonical model, while true, is overly simplistic and fails to adequately capture the actual state of the evidentiary record, the breadth of amygdala-associated functions and illnesses, or the complexity of the amygdala's functional architecture. The authors describe the implications of these facts for basic and clinical neuroimaging research. The review concludes with some general recommendations for grappling with the complexity of the amygdala and accelerating efforts to understand and more effectively treat amygdala-related psychopathology.

Ancestry-specific gene expression in peripheral monocytes mediates risk of neurodegenerative disease

It is hypothesised that peripheral immune states responding to regional environmental triggers contribute to central neurodegeneration. Region-specific genetic selection pressures require this hypothesis to be assessed in an ancestry specific manner. Here we utilise genome-wide association studies and expression quantitative trait loci from African, East Asian and European ancestries to show that genes causing neurodegeneration are preferentially expressed in innate rather than adaptive immune cells, and that expression of these genes mediates the risk of neurodegenerative disease in monocytes in an ancestry-specific manner.