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Gibbs, J. R.

Publications and source records attributed to Gibbs, J. R..

At least 19 recordsLinked to original sources

Integration of cell-specific gene expression and chromatin accessibility facilitates localization of neurodegenerative risk in microglia

Genome-wide association studies (GWAS) have identified many loci that contribute to the risk of neurodegenerative diseases. However, a persistent challenge in interpretation of GWAS is to break loci down to specific genes, variants, and cell types, and thus nominate disease mechanisms. Here, we used iPSC-derived cells containing population-level variation to examine GWAS loci across NDDs including Alzheimer's disease, Parkinson's disease and Lewy body dementia. We differentiated a set of 135 iPSC donor lines into two cell types relevant to neurodegeneration, neurons and microglia, and completed single cell gene expression and chromatin accessibility profiling. Meta-analysis of these data with published human brain snRNAseq for QTL mapping identified multiple loci associated with NDDs that are restricted to either neurons or microglia. Colocalization of GWAS and these QTL supports microglia as having a strong contribution to disease risk. We tested peaks nominated at the BIN1 locus for enhancer activity using a perturb-seq-based method in microglia. Our results show one of the nominated peaks controls BIN1 expression in microglia but also modifies expression of other genes at the locus. These results support the hypothesis that common variants affecting gene expression specifically in microglia can contribute directly to NDD risk rather than functioning solely as a secondary response to neurodegeneration. These data also show that iPSC-derived cells are a useful model to experimentally dissect GWAS loci that colocalize with QTL.

genomics↗

Semi-automated annotation refinement accelerates cell type identification in brain spatial and single-cell studies

Backgroundsingle-cell and spatial omic techniques have enabled the investigation of cell type specific alterations in biologically complex tissues. In an effort to map cell taxonomies, large atlas-based studies and multi-laboratory consortia have created sets of annotated cell types. However, application of atlas- or database-level knowledge to individual studies is often resource-limited and computational demands scale with the size of both query and reference datasets. ResultsHere, we report a statistical framework for rapid label transfer using summary statistics and user-defined hyperparameters. Semi-Automated Hand Annotation (SAHA)1 allows the user to investigate magnitude, directionality, and statistical significance of matches between unnamed query clusters and reference cell types using either marker-based or marker-free methodologies. By pre-loading the package with summary statistics from the Allen Brain Cell Atlas of the mouse brain, the SAHA R package is capable of rapid cell type comparisons that closely mimic cell typing by integration-based annotation strategies. Furthermore, this flexible package is capable of comparisons across omic modalities, cluster resolutions, and annotations from any study where summary statistics are available. We demonstrate this flexibility by using multiple single-nuclei studies of the mouse cerebellum, mouse cerebral cortex, human cerebral cortex, human peripheral blood mononuclear cells, and one mouse spatial transcriptomic assay. Importantly, this method avoids privacy concerns as it does not require the sharing or deposition of raw data in a web-based tool. ConclusionsAs a result, SAHA offers a non-deterministic annotation reporting structure with automated html reports and summary statistics for transparency in cell typing decisions. Taken together, this scalable framework implemented as a package in R affords increased biological insight into the annotation of single-cell and spatial datasets. SHORT SUMMARYAcri and colleagues present rapid cell type annotation without the need for dataset integration. This paper outlines the utility of the package, SAHA, in annotating neurological datasets.

bioinformatics↗

Inflammatory signaling differentially changes chromatin accessibility and gene expression of the PD- associated kinase LRRK2 between human and mice

The genomic locus that encodes the Leucine-rich repeat kinase 2 (LRRK2) gene is highly pleiotropic, being associated with both Parkinsons disease (PD) and Crohns disease (CD). Coding variants associated with risk of PD and CD act as gain of function kinase mutations increasing phosphorylation of RAB substrates, and non-coding variants in the promoter region of LRRK2 increase expression of the gene, notably in immune cells. If regulation of LRRK2 expression is a causal contributor to age-related diseases, it is important to understand the mechanism(s) by which LRRK2 is regulated, particularly in the context of inflammation. Here, we show that interferon-{gamma} exposure induces robust LRRK2 activation in human iPSC-derived microglia through signaling of the Janus-activated Kinase complex to phosphorylate STAT1, which then binds to the LRRK2 promoter and is associated with remodeling of chromatin structure in this genomic locus. Additional regulatory mechanisms include the stress-induced transcription factor and long non-coding RNA encoded at the same locus, resulting in increased LRRK2 mRNA levels. We also show evidence of the same effect in acutely cultured human brain slices. While we were unable to demonstrate any induction of Lrrk2 mRNA in the mouse brain, the introduction of a human bacterial artificial chromosome transgene into the mouse genome recapitulated sensitivity to interferon-{gamma} in microglia. A comparative genomic analysis across mammals suggests that these species differences are driven by regulatory regions upstream of LRRK2 that are specific to anthropoid primates. These results demonstrate that there are differences between species in how genes associated with human diseases are regulated and provide important information that should be incorporated in disease modeling.

neuroscience↗

Integrative analysis reveals generalizable human neurodegenerative disease-associated glial states

Glial cells are known to respond transcriptionally in multiple neurodegenerative diseases (NDDs). In particular, microglial states have been characterized in Alzheimers disease and mouse models of amyloidosis as disease-associated microglia. Although single-cell transcriptomic technologies have increased the dimensionality of information available across cell states, few studies have systematically tested for changes in glial transcription across brain regions and disease states. Here, we report a statistical framework for glial annotation, disease association, and transcriptional profiling, which facilitate identification of generalizable glial states that are present across a spectrum of NDDs (Alzheimers disease, Parkinsons disease, amyotrophic lateral sclerosis, and frontotemporal dementia) by re-analyzing data available in four multi-region atlases. We identify seven astrocyte substates, 14 microglia/myeloid substates, and five oligodendrocyte substates where transcriptional variability is attributable to region, disease, or study-specific effects. Regional heterogeneity of astrocytes masked disease associations, even within cortical subregions. We found only limited oligodendrocyte transcriptional heterogeneity, resulting in few substates for further interrogation. Notably, microglia showed the strongest evidence for disease association. We show, for the first time, that this association exists across different NDDs. Using latent factor analysis, we created a consensus human neurodegenerative disease-associated microglia (hnDAM) signature, which we experimentally validated in 11 independent sample series. We demonstrate that the hnDAM signature is a statistically testable biomarker for conserved microglial activation in NDDs by: i) comparing to murine DAM-like signatures, ii) performing transcription factor analysis, and iii) modeling transcriptional reprogramming perturbations in iPSC-derived microglia. Importantly, we find for the first time a way to make direct comparisons between DAM-like activation profiles in separate studies and propose a novel modeling paradigm via PIKfyve inhibition. Taken together, this work broadens our understanding of glial activation across neuropathologies and reveals hnDAM as a putative therapeutic target that can be utilized in any transcriptomic study of patients suffering from NDDs. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/678630v2_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1863095org.highwire.dtl.DTLVardef@dfa6c8org.highwire.dtl.DTLVardef@13e95f1org.highwire.dtl.DTLVardef@1e6165e_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

A genome-wide survey reveals a diverse array of enhancers coordinate the Drosophila innate immune response

To defend against microbes, animals regulate a complex immune response. The Drosophila innate immune system deploys a large transcriptional induction of signaling proteins, anti-microbial effectors, and other critical immune factors. This transcriptional response is encoded in enhancers, cis-regulatory sequences that modulate gene expression by binding transcription factors (TFs). While enhancers and transcription factor binding sites (TFBS) have been identified for several immune responsive genes in Drosophila, most enhancers that regulate immune-induced genes are unknown. By identifying enhancers, we can understand how their composition controls expression and contributes to infection outcome. We employed STARR-seq (Self Transcribing Active Regulatory-Region sequencing) in a hemocyte-like cell line to identify immune-specific enhancers across the D. melanogaster genome and performed ATAC-seq in hemocytes extracted from adult flies to assess the chromatin state of these enhancers before and after immune stimulus. We identified thousands of enhancers responsive to IMD stimulation, one of the two primary immune signaling pathways in Drosophila. As expected, immune enhancers are enriched for motifs of Relish, an NF-{kappa}B factor, and Kay/Jra, a bZip heterodimer pair, involved in the Imd and JNK pathways respectively, compared to enhancers active in unstimulated cells. However, when grouping enhancers by their target genes expression timing or functional role or by the enhancers chromatin accessibility pre- or post-stimulus, different groups of TFBS motifs are enriched, suggesting distinct regulatory logic for different parts of the immune response. Identification and characterization of the diverse array of enhancers that regulate the innate immune response expands our understanding of how animals fight infections.

genomics↗

Long-read sequencing of hundreds of diverse brains provides insight into the impact of structural variation on gene expression and DNA methylation

Structural variants (SVs) drive gene expression in the human brain and are causative of many neurological conditions. However, most existing genetic studies have been based on short-read sequencing methods, which capture fewer than half of the SVs present in any one individual. Long-read sequencing (LRS) enhances our ability to detect disease-associated and functionally relevant structural variants; however, its application in large-scale genomic studies has been limited by challenges in sample preparation and high costs. Here, we leverage a new scalable wet-lab protocol and computational pipeline for whole-genome Oxford Nanopore Technologies sequencing and apply it to neurologically normal control samples from the North American Brain Expression Consortium (NABEC) (European ancestry) and Human Brain Collection Core (HBCC) (African or African admixed ancestry) cohorts. Through this work, we present a publicly available long-read resource from 351 human brain samples (median N50: 27 Kbp and at an average depth of ~40x genome coverage). We discover approximately 234,905 SVs and produce locally phased assemblies that cover 95% of all protein-coding genes in GRCh38. To resolve cis-regulatory effects, we develop ASM-LR, a method for allele-specific methylation analysis from long-read data, revealing both strong and subtle regulatory effects, including numerous novel methylation QTLs masked in unphased models. Our results highlight the power of haplotype-resolved methylation to uncover regulatory mechanisms and establish a foundational resource for exploring how genetic variation shapes gene expression and epigenetic architecture across diverse ancestries.

genomics↗

Characterization of DNA methylation in PBMCs and donor-matched iPSCs shows methylation is reset during stem cell reprogramming

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC="FIGDIR/small/627515v2_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@18cda69org.highwire.dtl.DTLVardef@574c4corg.highwire.dtl.DTLVardef@1522644org.highwire.dtl.DTLVardef@4e799c_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG HighlightsO_LIGeneration of a population-level set of iPSC lines from healthy individuals across the lifespan C_LIO_LIAging-related features were reset based on epigenetic markers of cytosine methylation and telomere length C_LIO_LIBy comparing methQTLs in iPSC vs. their donor PBMCs, we find that detection of methQTLs reflect biological functions of different cell types C_LI DNA methylation is an important epigenetic mechanism that helps define and maintain cellular functions. It is influenced by many factors, including environmental exposures, genotype, cell type, sex, and aging. Since age is the primary risk factor for developing neurodegenerative diseases, it is important to determine if aging-related DNA methylation is retained when cells are reprogrammed to an induced Pluripotent Stem Cell (iPSC) state. Here, we selected peripheral blood mononuclear cells (PBMCs; n = 99) from a cohort of diverse and healthy individuals enrolled in the Genetic and Epigenetic Signatures of Translational Aging Laboratory Testing (GESTALT) study to convert to iPSCs. After reprogramming we evaluated the resulting iPSCs for DNA methylation signatures to determine if they reflect the confounding factors of age and environmental factors. We used genome-wide DNA methylation arrays in both cell types to show that the epigenetic clock is largely reset to an early methylation age after conversion of PBMCs to iPSCs. We further examined the epigenetic age of each cell type using an Epigenome-wide Association Study (EWAS). Finally, we identified a set of methylation Quantitative Trait Loci (methQTL) in each cell type. Our results show that age-related DNA methylation is largely reset in iPSCs, and each cell type has a unique set of methylation sites that are genetically influenced.

molecular biology↗

Decreased SNCA Expression in Whole-Blood RNA Analysis of Parkinson's Disease Adjusting for Lymphocytes

Blood-based RNA transcriptomics offers a promising avenue for identifying biomarkers of Parkinsons Disease (PD) progression and may provide mechanistic insights into the systemic biological processes underlying its pathogenesis beyond the well-defined neurodegenerative features. Previous studies have indicated an age-dependent increase in neutrophil-enriched gene expression, alongside a reduction in lymphocyte counts, in individuals with PD. These immune cell changes can obscure disease-relevant transcriptomic signals. In this study, we performed differential expression (DE) analysis of whole-blood RNA sequencing data from PD cohorts, incorporating a correction for immune cell-enriched gene expression, particularly neutrophil-related pathways, to improve the resolution of PD-associated molecular changes. Using 1,254 Parkinsons Progression Markers Initiative (PPMI) samples with complete blood count (CBC) data, we developed a predictive model to estimate neutrophil percentages in a 6,987 PPMI and Parkinsons Disease Biomarkers Program (PDBP) samples. We mitigated the confounding effects of immune cell-enriched gene expression by integrating predicted neutrophil percentages as a covariate in DE analysis. This approach revealed a consistent and significant downregulation of SNCA across all PD cohorts, a finding previously obscured by immune cell signatures. Lowered SNCA expression was found in individuals with known predisposition genes (e.g., SNCA, GBA, LRRK2) and in non-genetic PD cohorts lacking known pathogenic mutations, suggesting it may represent a key transcriptomic hallmark of the disease.

bioinformatics↗

Single-cell spatial transcriptomics reveals molecular patterns of selective neuronal vulnerability to α-synuclein pathology in a transgenic mouse model of Lewy body disease

In Parkinsons disease and dementia with Lewy bodies, aggregated and phosphorylated -synuclein pathology appears in select neurons throughout cortical and subcortical regions, but little is currently known about why certain populations are selectively vulnerable. Here, using imaging spatial transcriptomics (IST) coupled with downstream immunofluorescence for -synuclein phosphorylated at Ser129 (pSyn) in the same tissue sections, we identified neuronal subtypes in the cortex and hippocampus of transgenic human -synuclein-overexpressing mice that preferentially developed pSyn pathology. Additionally, we investigated the transcriptional underpinnings of this vulnerability, pointing to expression of Plk2, which phosphorylates -synuclein at Ser129, and human SNCA (hSNCA), as key to pSyn pathology development. Finally, we performed differential expression analysis, revealing gene expression changes broadly downstream of hSNCA overexpression, as well as pSyn-dependent alterations in mitochondrial and endolysosomal genes. Overall, this study yields new insights into the formation of -synuclein pathology and its downstream effects in a synucleinopathy mouse model.

neuroscience↗

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

Given that age is a significant risk factor for multiple neurodegenerative diseases, investigating normal brain aging may help identify molecular events that may contribute to increased disease risk over time. Single-nucleus RNA sequencing (snRNA-seq) enables analysis of gene expression changes within specific cell-types, potentially offering insights into the molecular mechanisms underlying aging. However, most brain snRNA-Seq datasets used age-matched controls from studies focused on pathological processes and have largely been limited to cortical regions. Therefore, there is a need to investigate the non-pathological aging process in brain regions that are vulnerable to age-related diseases. Here, we report a snRNA-seq study of 6 young (20-30 years) and 7 aged (60-85 years) encompassing four different brain regions: the entorhinal cortex, middle temporal gyrus, subventricular zone, and putamen. We captured over 150,000 nuclei that represented 10 broad cell-types. While we did not find statistically significant differences in cell-type proportions with age, region- and cell-type-specific differential expression analyses identified over 8,000 age-associated genes. Notably, within a given cell-type, most of these associations were region-specific. Functional enrichment analyses of the gene sets for each cell-type-region combination revealed diverse biological processes, including multiple hallmarks of aging, such as proteostasis, interactions with cytokines, vesicular trafficking, metabolism, inflammation, and metal ion homeostasis. Overall, our findings suggest that unique cell-types exhibit distinct transcriptional aging profiles both at the cell-type level and across different brain regions.

neuroscience↗

The Foundational data initiative for Parkinsons disease (FOUNDIN-PD): enabling efficient translation from genetic maps to mechanism

The FOUNdational Data INitiative for Parkinsons Disease (FOUNDIN-PD) is an international collaboration producing fundamental resources for Parkinsons 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 Parkinsons Progression Markers Initiative study including participants with PD carrying monogenic PD (SNCA) 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 modelling PD genetic risk. We have integrated these data into a FOUNDIN-PD data browser (https://www.foundinpd.org) as a resource for understanding the molecular pathogenesis of PD.

genomics↗

Association of a common genetic variant with Parkinson's disease is propagated through microglia

Studies of the genetic basis of Parkinsons disease (PD) have identified many disease-associated genetic variants, but the mechanisms linking variants to pathogenicity are largely unknown. PD risk is attributed to both coding mutations in the Leucine-rich repeat kinase 2 (LRRK2) gene and to common non-coding variation upstream of the LRRK2 locus. Here we show that the influence of genotype at non-coding variant rs76904798 on LRRK2 expression is propagated specifically through microglia, in contrast to evaluations based on general rather than genotype-dependent expression. We find evidence of microglia-specific regulatory regions that may modulate LRRK2 expression using single nuclei sequencing analyses of human frontal cortex and confirm these results in a human induced pluripotent stem cell-derived microglia model. Our study demonstrates that cell type is an important consideration in interrogation of the role of non-coding variation in disease pathogenesis.

neuroscience↗

The Parkinson's Disease GWAS Locus Browser

Parkinsons disease (PD) is a neurodegenerative disease with an often complex genetic component identifiable by genome-wide association studies (GWAS). The most recent large scale PD GWASes have identified more than 90 independent risk variants for PD risk and progression across 80 loci. One major challenge in current genomics is identifying the causal gene(s) and variant(s) from each GWAS locus. Here we present a GWAS locus browser application that combines data from multiple databases to aid in the prioritization of genes associated with PD GWAS loci. We included 92 independent genome-wide significant signals from multiple recent PD GWAS studies including the PD risk GWAS, age-at-onset GWAS and progression GWAS. We gathered data for all 2336 genes within 1Mb up and downstream of each variant to allow users to assess which gene(s) are most associated with the variant of interest based on a set of self-ranked criteria. Our aim is that the information contained in this browser (https://pdgenetics.shinyapps.io/GWASBrowser/) will assist the PD research community with the prioritization of genes for follow-up functional studies and as potential therapeutic targets.

genetics↗

Common variation at the LRRK2 locus is associated with survival in the primary tauopathy progressive supranuclear palsy

The genetic basis of variation in the rate of disease progression of primary tauopathies has not been determined. In two independent progressive supranuclear palsy cohorts, we show that common variation at the LRRK2 locus determines survival from motor symptom onset to death, possibly through regulation of gene expression. This links together genetic risk in alpha-synuclein and tau disorders, and suggests that modulation of proteostasis and neuro-inflammation by LRRK2 inhibitors may have a therapeutic role across disorders.

genetics↗

Mutations in the SPTLC1 gene are a cause of amyotrophic lateral sclerosis that may be amenable to serine supplementation

Juvenile amyotrophic lateral sclerosis (ALS) is a rare form of childhood motor disorder with a heterogeneous clinical presentation. The underlying causes of this condition are poorly understood, hindering the development of effective therapies. In a whole-exome sequencing trio-family study of three unrelated juvenile patients diagnosed with ALS and failure to thrive, we identified de-novo mutations in SPTLC1 (p.Ala20Ser in two patients and p.Ser331Tyr) not present in their healthy parents or siblings. SPTLC1 encodes a subunit of the serine palmitoyltransferase complex, a key enzyme in sphingolipid biosynthesis. Mutations in this gene are known to cause hereditary sensory autonomic neuropathy, type 1A, with a characteristic increase in plasma levels of neurotoxic deoxymethyl-sphinganine. We found an increase of this metabolite in one of our patients carrying the p.Ala20Ser mutation. Treatment of one of the patients with high dose, oral L-serine led to an increase in body weight, suggesting that serine supplementation may be beneficial among patients carrying mutations in this gene.

genetics↗

A genome-wide genetic pleiotropy approach identified shared loci between multiple system atrophy and inflammatory bowel disease

We aimed to identify shared genetic background between multiple system atrophy (MSA) and autoimmune diseases by using the conjFDR approach. Our study showed significant genetic overlap between MSA and inflammatory bowel disease and identified DENND1B, C7, and RSP04 loci, which are linked to significant changes in methylation or expression levels of adjacent genes. We obtained evidence of enriched heritability involving immune/digestive categories. Finally, an MSA mouse model showed dysregulation of the C7 gene in the degenerating midbrain compared to wildtype mice. The results identify novel molecular mechanisms and implicate immune and gut dysfunction in MSA pathophysiology.

genetics↗

Genetic modifiers of risk and age at onset in GBA associated Parkinson disease and Lewy body dementia

Parkinsons disease (PD) is a genetically complex disorder. Multiple genes have been shown to contribute to the risk of PD, and currently 90 independent risk variants have been identified by genome-wide association studies. Thus far, a number of genes (including SNCA, LRRK2, and GBA) have been shown to contain variability across a spectrum of frequency and effect, from rare, highly penetrant variants to common risk alleles with small effect sizes. Variants in GBA, encoding the enzyme glucocerebrosidase, are associated with Lewy body diseases such as PD and Lewy body dementia (LBD). These variants, which reduce or abolish enzymatic activity, confer a spectrum of disease risk, from 1.4- to >10-fold. An outstanding question in the field is what other genetic factors that influence GBA-associated risk for disease, and whether these overlap with known PD risk variants.\n\nUsing multiple, large case-control datasets, totalling 217,165 individuals (22,757 PD cases, 13,431 PD proxy cases, 622 LBD cases and 180,355 controls), we identified 1,772 PD cases, 711 proxy cases and 7,624 controls with a GBA variant (p.E326K, p.T369M or p.N370S). We performed a genome-wide association study and analysed the most recent PD-associated genetic risk score to detect genetic influences on GBA risk and age at onset. We attempted to replicate our findings in two independent datasets, including the personal genetics company 23andMe, Inc. and whole-genome sequencing data. Our analysis showed that the overall PD genetic risk score modifies risk for disease and decreases age at onset in carriers of GBA variants. Notably, this effect was consistent across all tested GBA risk variants. Dissecting this signal demonstrated that variants in close proximity to SNCA and CTSB (encoding cathepsin B) are the most significant contributors. Risk variants in the CTSB locus were identified to decrease mRNA expression of CTSB. Additional analyses suggest a possible genetic interaction between GBA and CTSB and GBA p.N370S neurons were shown to have decreased Cathepsin B expression compared to controls. These data provide a genetic basis for modification of GBA-associated PD risk and age at onset and demonstrate that variability at genes implicated in lysosomal function exerts the largest effect on GBA associated risk for disease. Further, these results have important implications for selection of GBA carriers for therapeutic interventions.

genetics↗

Penetrance of Parkinson’s disease in LRRK2 p.G2019S carriers is modified by a polygenic risk score

BackgroundWhile the LRRK2 p.G2019S mutation has been demonstrated to be a strong risk factor for Parkinsons Disease (PD), factors that contribute to penetrance among carriers, other than aging, have not been well identified.\n\nObjectivesTo evaluate whether a cumulative genetic risk identified in the recent genome-wide study is associated with penetrance of PD among p.G2019S mutation carriers.\n\nMethodsWe included p.G2019S heterozygote carriers with European ancestry in three genetic cohorts in which the mutation carriers with and without PD were selectively recruited. We also included the carriers from two datasets: one from a case-control setting without selection of mutation carriers, and the other from a population sampling. The associations between PRS constructed from 89 variants reported in Nalls et al. and PD were tested and meta-analyzed. We also explored the interaction of age and PRS.\n\nResultsAfter excluding 8 homozygotes, 833 p.G2019S heterozygote carriers (439 PD and 394 unaffected) were analyzed. PRS was associated with a higher penetrance of PD (OR 1.34, 95% C.I. [1.09, 1.64] per +1 SD, P = 0.005). In addition, associations with PRS and penetrance were stronger in the younger participants (main effect: OR 1.28 [1.04, 1.58] per +1 SD, P = 0.022; interaction effect: OR 0.78 [0.64, 0.94] per +1 SD and +10 years of age, P = 0.008).\n\nConclusionsOur results suggest that there is a genetic contribution for penetrance of PD among p.G2019S carriers. These results have important etiologic consequences and potential impact on the selection of subjects for clinical trials.

genetics↗