Genome-wide structural variant analysis identifies risk loci for non-Alzheimer's dementias.

We characterized the role of structural variants, a largely unexplored type of genetic variation, in two non-Alzheimer's dementias, namely Lewy body dementia (LBD) and frontotemporal dementia (FTD)/amyotrophic lateral sclerosis (ALS). To do this, we applied an advanced structural variant calling pipeline (GATK-SV) to short-read whole-genome sequence data from 5,213 European-ancestry cases and 4,132 controls. We discovered, replicated, and validated a deletion in TPCN1 as a novel risk locus for LBD and detected the known structural variants at the C9orf72 and MAPT loci as associated with FTD/ALS. We also identified rare pathogenic structural variants in both LBD and FTD/ALS. Finally, we assembled a catalog of structural variants that can be mined for new insights into the pathogenesis of these understudied forms of dementia.

The contribution of Neanderthal introgression and natural selection to neurodegenerative diseases.

Humans are thought to be more susceptible to neurodegeneration than equivalently-aged primates. It is not known whether this vulnerability is specific to anatomically-modern humans or shared with other hominids. The contribution of introgressed Neanderthal DNA to neurodegenerative disorders remains uncertain. It is also unclear how common variants associated with neurodegenerative disease risk are maintained by natural selection in the population despite their deleterious effects. In this study, we aimed to quantify the genome-wide contribution of Neanderthal introgression and positive selection to the heritability of complex neurodegenerative disorders to address these questions. We used stratified-linkage disequilibrium score regression to investigate the relationship between five SNP-based signatures of natural selection, reflecting different timepoints of evolution, and genome-wide associated variants of the three most prevalent neurodegenerative disorders: Alzheimer's disease, amyotrophic lateral sclerosis and Parkinson's disease. We found no evidence for enrichment of positively-selected SNPs in the heritability of Alzheimer's disease, amyotrophic lateral sclerosis and Parkinson's disease, suggesting that common deleterious disease variants are unlikely to be maintained by positive selection. There was no enrichment of Neanderthal introgression in the SNP-heritability of these disorders, suggesting that Neanderthal admixture is unlikely to have contributed to disease risk. These findings provide insight into the origins of neurodegenerative disorders within the evolution of Homo sapiens and addresses a long-standing debate, showing that Neanderthal admixture is unlikely to have contributed to common genetic risk of neurodegeneration in anatomically-modern humans.

Functional genomics provide key insights to improve the diagnostic yield of hereditary ataxia.

Improvements in functional genomic annotation have led to a critical mass of neurogenetic discoveries. This is exemplified in hereditary ataxia, a heterogeneous group of disorders characterised by incoordination from cerebellar dysfunction. Associated pathogenic variants in more than 300 genes have been described, leading to a detailed genetic classification partitioned by age-of-onset. Despite these advances, up to 75% of patients with ataxia remain molecularly undiagnosed even following whole genome sequencing, as exemplified in the 100 000 Genomes Project. This study aimed to understand whether we can improve our knowledge of the genetic architecture of hereditary ataxia by leveraging functional genomic annotations, and as a result, generate insights and strategies that raise the diagnostic yield. To achieve these aims, we used publicly-available multi-omics data to generate 294 genic features, capturing information relating to a gene's structure, genetic variation, tissue-specific, cell-type-specific and temporal expression, as well as protein products of a gene. We studied these features across genes typically causing childhood-onset, adult-onset or both types of disease first individually, then collectively. This led to the generation of testable hypotheses which we investigated using whole genome sequencing data from up to 2182 individuals presenting with ataxia and 6658 non-neurological probands recruited in the 100 000 Genomes Project. Using this approach, we demonstrated a high short tandem repeat (STR) density within childhood-onset genes suggesting that we may be missing pathogenic repeat expansions within this cohort. This was verified in both childhood- and adult-onset ataxia patients from the 100 000 Genomes Project who were unexpectedly found to have a trend for higher repeat sizes even at naturally-occurring STRs within known ataxia genes, implying a role for STRs in pathogenesis. Using unsupervised analysis, we found significant similarities in genomic annotation across the gene panels, which suggested adult- and childhood-onset patients should be screened using a common diagnostic gene set. We tested this within the 100 000 Genomes Project by assessing the burden of pathogenic variants among childhood-onset genes in adult-onset patients and vice versa. This demonstrated a significantly higher burden of rare, potentially pathogenic variants in conventional childhood-onset genes among individuals with adult-onset ataxia. Our analysis has implications for the current clinical practice in genetic testing for hereditary ataxia. We suggest that the diagnostic rate for hereditary ataxia could be increased by removing the age-of-onset partition, and through a modified screening for repeat expansions in naturally-occurring STRs within known ataxia-associated genes, in effect treating these regions as candidate pathogenic loci.

Multi-modality machine learning predicting Parkinson's disease.

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

Dissecting the Phenotype and Genotype of PLA2G6-Related Parkinsonism.

BACKGROUND: Complex parkinsonism is the commonest phenotype in late-onset PLA2G6-associated neurodegeneration. OBJECTIVES: The aim of this study was to deeply characterize phenogenotypically PLA2G6-related parkinsonism in the largest cohort ever reported. METHODS: We report 14 new cases of PLA2G6-related parkinsonism and perform a systematic literature review. RESULTS: PLA2G6-related parkinsonism shows a fairly distinct phenotype based on 86 cases from 68 pedigrees. Young onset (median age, 23.0 years) with parkinsonism/dystonia, gait/balance, and/or psychiatric/cognitive symptoms were common presenting features. Dystonia occurred in 69.4%, pyramidal signs in 77.2%, myoclonus in 65.2%, and cerebellar signs in 44.6% of cases. Early bladder overactivity was present in 71.9% of cases. Cognitive impairment affected 76.1% of cases and psychiatric features 87.1%, the latter being an isolated presenting feature in 20.1%. Parkinsonism was levodopa responsive but complicated by early, often severe dyskinesias. Five patients benefited from deep brain stimulation. Brain magnetic resonance imaging findings included cerebral (49.3%) and/or cerebellar (43.2%) atrophy, but mineralization was evident in only 28.1%. Presynaptic dopaminergic terminal imaging was abnormal in all where performed. Fifty-four PLA2G6 mutations have hitherto been associated with parkinsonism, including four new variants reported in this article. These are mainly nontruncating, which may explain the phenotypic heterogeneity of childhood- and late-onset PLA2G6-associated neurodegeneration. In five deceased patients, median disease duration was 13.0 years. Brain pathology in three cases showed mixed Lewy and tau pathology. CONCLUSIONS: Biallelic PLA2G6 mutations cause early-onset parkinsonism associated with dystonia, pyramidal and cerebellar signs, myoclonus, and cognitive impairment. Early psychiatric manifestations and bladder overactivity are common. Cerebro/cerebellar atrophy are frequent magnetic resonance imaging features, whereas brain iron deposition is not. Early, severe dyskinesias are a tell-tale sign. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

MIR-NATs repress MAPT translation and aid proteostasis in neurodegeneration.

The human genome expresses thousands of natural antisense transcripts (NAT) that can regulate epigenetic state, transcription, RNA stability or translation of their overlapping genes1,2. Here we describe MAPT-AS1, a brain-enriched NAT that is conserved in primates and contains an embedded mammalian-wide interspersed repeat (MIR), which represses tau translation by competing for ribosomal RNA pairing with the MAPT mRNA internal ribosome entry site3. MAPT encodes tau, a neuronal intrinsically disordered protein (IDP) that stabilizes axonal microtubules. Hyperphosphorylated, aggregation-prone tau forms the hallmark inclusions of tauopathies4. Mutations in MAPT cause familial frontotemporal dementia, and common variations forming the MAPT H1 haplotype are a significant risk factor in many tauopathies5 and Parkinson's disease. Notably, expression of MAPT-AS1 or minimal essential sequences from MAPT-AS1 (including MIR) reduces-whereas silencing MAPT-AS1 expression increases-neuronal tau levels, and correlate with tau pathology in human brain. Moreover, we identified many additional NATs with embedded MIRs (MIR-NATs), which are overrepresented at coding genes linked to neurodegeneration and/or encoding IDPs, and confirmed MIR-NAT-mediated translational control of one such gene, PLCG1. These results demonstrate a key role for MAPT-AS1 in tauopathies and reveal a potentially broad contribution of MIR-NATs to the tightly controlled translation of IDPs6, with particular relevance for proteostasis in neurodegeneration.

Abrogation of LRRK2 dependent Rab10 phosphorylation with TLR4 activation and alterations in evoked cytokine release in immune cells.

LRRK2 protein is expressed prominently in immune cells, cell types whose contribution to LRRK2-associated genetic Parkinson's disease (PD) is increasingly being recognised. We investigated the effect of inflammatory stimuli using RAW264.7 murine macrophage cells as model systems. A detailed time course of TLR2 and TLR4 stimulation was investigated through measuring LRRK2 phosphorylation at its specific phospho-sites, and Rab8 and Rab10 phosphorylation together with cytokine release following treatment with LPS and zymosan. LRRK2 phosphorylation at Ser935, Ser955 and Ser973 was increased significantly over untreated conditions at 4-24h in both WT-LRRK2 and T1348N-LRRK2 cell lines to similar extents although levels of Ser910 phosphorylation were maintained at higher levels throughout. Importantly we demonstrate that LPS stimulation significantly decreased phospho-Rab10 but not phospho-Rab8 levels over 4-24h in both WT-LRRK2 and T1348N-LRRK2 cell lines. The dephosphorylation of Rab10 was not attributed to its specific phosphatase, PPM1H as the levels remained unaltered with LPS treatment. MAPK phosphorylation occurred prior to LRRK2 phosphorylation which was validated by blocking TLR4 and TLR2 receptors with TAK242 or Sparstolonin B respectively. A significant decrease in basal level of TNFα release was noted in both T1348N-LRRK2 and KO-LRRK2 cell lines at 48h compared to WT-LRRK2 cell line, however LPS and zymosan treatment did not cause any significant alteration in the TNFα and IL-6 release between the three cell lines. In contrast, LPS and zymosan caused significantly lower IL-10 release in T1348N-LRRK2 and KO-LRRK2 cell lines. A significant decrease in phospho-Rab10 levels was also confirmed in human IPS-derived macrophages with TLR4 activation. Our data demonstrates for the first time that LRRK2-dependent Rab10 phosphorylation is modulated by LPS stimulation, and that cytokine release may be influenced by the status of LRRK2. These data provide further insights into the function of LRRK2 in immune response, and has relevance for understanding cellular dysfunctions when developing LRRK2-based inhibitors for clinical treatment.

Pathogenic Huntingtin Repeat Expansions in Patients with Frontotemporal Dementia and Amyotrophic Lateral Sclerosis.

We examined the role of repeat expansions in the pathogenesis of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) by analyzing whole-genome sequence data from 2,442 FTD/ALS patients, 2,599 Lewy body dementia (LBD) patients, and 3,158 neurologically healthy subjects. Pathogenic expansions (range, 40-64 CAG repeats) in the huntingtin (HTT) gene were found in three (0.12%) patients diagnosed with pure FTD/ALS syndromes but were not present in the LBD or healthy cohorts. We replicated our findings in an independent collection of 3,674 FTD/ALS patients. Postmortem evaluations of two patients revealed the classical TDP-43 pathology of FTD/ALS, as well as huntingtin-positive, ubiquitin-positive aggregates in the frontal cortex. The neostriatal atrophy that pathologically defines Huntington's disease was absent in both cases. Our findings reveal an etiological relationship between HTT repeat expansions and FTD/ALS syndromes and indicate that genetic screening of FTD/ALS patients for HTT repeat expansions should be considered.

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies.

BACKGROUND: Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. METHODS: We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. FINDINGS: Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16-36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10-7). INTERPRETATION: These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. FUNDING: The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources).

The human brainome: network analysis identifies HSPA2 as a novel Alzheimer’s disease target.

Our hypothesis is that changes in gene and protein expression are crucial to the development of late-onset Alzheimer’s disease. Previously we examined how DNA alleles control downstream expression of RNA transcripts and how those relationships are changed in late-onset Alzheimer’s disease. We have now examined how proteins are incorporated into networks in two separate series and evaluated our outputs in two different cell lines. Our pipeline included the following steps: (i) predicting expression quantitative trait loci; (ii) determining differential expression; (iii) analysing networks of transcript and peptide relationships; and (iv) validating effects in two separate cell lines. We performed all our analysis in two separate brain series to validate effects. Our two series included 345 samples in the first set (177 controls, 168 cases; age range 65–105; 58% female; KRONOSII cohort) and 409 samples in the replicate set (153 controls, 141 cases, 115 mild cognitive impairment; age range 66–107; 63% female; RUSH cohort). Our top target is heat shock protein family A member 2 (HSPA2), which was identified as a key driver in our two datasets. HSPA2 was validated in two cell lines, with overexpression driving further elevation of amyloid-β40 and amyloid-β42 levels in APP mutant cells, as well as significant elevation of microtubule associated protein tau and phosphorylated-tau in a modified neuroglioma line. This work further demonstrates that studying changes in gene and protein expression is crucial to understanding late onset disease and further nominates HSPA2 as a specific key regulator of late-onset Alzheimer’s disease processes.10.1093/brain/awy215_video1awy215media15824729224001.

NeuroChip, an updated version of the NeuroX genotyping platform to rapidly screen for variants associated with neurological diseases.

Genetics has proven to be a powerful approach in neurodegenerative diseases research, resulting in the identification of numerous causal and risk variants. Previously, we introduced the NeuroX Illumina genotyping array, a fast and efficient genotyping platform designed for the investigation of genetic variation in neurodegenerative diseases. Here, we present its updated version, named NeuroChip. The NeuroChip is a low-cost, custom-designed array containing a tagging variant backbone of about 306,670 variants complemented with a manually curated custom content comprised of 179,467 variants implicated in diverse neurological diseases, including Alzheimer's disease, Parkinson's disease, Lewy body dementia, amyotrophic lateral sclerosis, frontotemporal dementia, progressive supranuclear palsy, corticobasal degeneration, and multiple system atrophy. The tagging backbone was chosen because of the low cost and good genome-wide resolution; the custom content can be combined with other backbones, like population or drug development arrays. Using the NeuroChip, we can accurately identify rare variants and impute over 5.3 million common SNPs from the latest release of the Haplotype Reference Consortium. In summary, we describe the design and usage of the NeuroChip array and show its capability for detecting rare pathogenic variants in numerous neurodegenerative diseases. The NeuroChip has a more comprehensive and improved content, which makes it a reliable, high-throughput, cost-effective screening tool for genetic research and molecular diagnostics in neurodegenerative diseases.

A blood-based gene expression and signaling pathway analysis to differentiate between high and low grade gliomas.

The aims of the present study were to undertake gene expression profiling of the blood of glioma patients to determine key genetic components of signaling pathways and to develop a panel of genes that could be used as a potential blood-based biomarker to differentiate between high and low grade gliomas, non-gliomas and control samples. In this study, blood samples were obtained from glioma patients, non-glioma and control subjects. Ten samples each were obtained from patients with high and low grade tumours, respectively, ten samples from non-glioma patients and twenty samples from control subjects. Total RNA was isolated from each sample after which first and second strand synthesis was performed. The resulting cRNA was then hybridized with the Agilent Whole Human Genome (4x44K) microarray chip according to the manufacturer's instructions. Universal Human Reference RNA and samples were labeled with Cy3 CTP and Cy5 CTP, respectively. Microarray data were analyzed by the Agilent Gene Spring 12.1V software using stringent criteria which included at least a 2-fold difference in gene expression between samples. Statistical analysis was performed using the unpaired Student's t-test with a p<0.01. Pathway enrichment was also performed, with key genes selected for validation using droplet digital polymerase chain reaction (ddPCR). The gene expression profiling indicated that were a substantial number of genes that were differentially expressed with more than a 2-fold change (p<0.01) between each of the four different conditions. We selected key genes within significant pathways that were analyzed through pathway enrichment. These key genes included regulators of cell proliferation, transcription factors, cytokines and tumour suppressor genes. In the present study, we showed that key genes involved in significant and well established pathways, could possibly be used as a potential blood-based biomarker to differentiate between high and low grade gliomas, non-gliomas and control samples.

A genome-wide association study in multiple system atrophy.

OBJECTIVE: To identify genetic variants that play a role in the pathogenesis of multiple system atrophy (MSA), we undertook a genome-wide association study (GWAS). METHODS: We performed a GWAS with >5 million genotyped and imputed single nucleotide polymorphisms (SNPs) in 918 patients with MSA of European ancestry and 3,864 controls. MSA cases were collected from North American and European centers, one third of which were neuropathologically confirmed. RESULTS: We found no significant loci after stringent multiple testing correction. A number of regions emerged as potentially interesting for follow-up at p < 1 × 10-6, including SNPs in the genes FBXO47, ELOVL7, EDN1, and MAPT. Contrary to previous reports, we found no association of the genes SNCA and COQ2 with MSA. CONCLUSIONS: We present a GWAS in MSA. We have identified several potentially interesting gene loci, including the MAPT locus, whose significance will have to be evaluated in a larger sample set. Common genetic variation in SNCA and COQ2 does not seem to be associated with MSA. In the future, additional samples of well-characterized patients with MSA will need to be collected to perform a larger MSA GWAS, but this initial study forms the basis for these next steps.

Next-generation sequencing reveals substantial genetic contribution to dementia with Lewy bodies.

Dementia with Lewy bodies (DLB) is the second most common neurodegenerative dementia after Alzheimer's disease. Although an increasing number of genetic factors have been connected to this debilitating condition, the proportion of cases that can be attributed to distinct genetic defects is unknown. To provide a comprehensive analysis of the frequency and spectrum of pathogenic missense mutations and coding risk variants in nine genes previously implicated in DLB, we performed exome sequencing in 111 pathologically confirmed DLB patients. All patients were Caucasian individuals from North America. Allele frequencies of identified missense mutations were compared to 222 control exomes. Remarkably, ~25% of cases were found to carry a pathogenic mutation or risk variant in APP, GBA or PSEN1, highlighting that genetic defects play a central role in the pathogenesis of this common neurodegenerative disorder. In total, 13% of our cohort carried a pathogenic mutation in GBA, 10% of cases carried a risk variant or mutation in PSEN1, and 2% were found to carry an APP mutation. The APOE ε4 risk allele was significantly overrepresented in DLB patients (p-value <0.001). Our results conclusively show that mutations in GBA, PSEN1, and APP are common in DLB and consideration should be given to offer genetic testing to patients diagnosed with Lewy body dementia.

First effects of rising amyloid-ß in transgenic mouse brain: synaptic transmission and gene expression.

Detecting and treating Alzheimer's disease, before cognitive deficits occur, has become the health challenge of our time. The earliest known event in Alzheimer's disease is rising amyloid-ß. Previous studies have suggested that effects on synaptic transmission may precede plaque deposition. Here we report how relative levels of different soluble amyloid-ß peptides in hippocampus, preceding plaque deposition, relate to synaptic and genomic changes. Immunoprecipitation-mass spectrometry was used to measure the early rise of different amyloid-ß peptides in a mouse model of increasing amyloid-ß ('TASTPM', transgenic for familial Alzheimer's disease genes APP/PSEN1). In the third postnatal week, several amyloid-ß peptides were above the limit of detection, including amyloid-ß40, amyloid-ß38 and amyloid-ß42 with an intensity ratio of 6:3:2, respectively. By 2 months amyloid-ß levels had only increased by 50% and although the ratio of the different peptides remained constant, the first changes in synaptic currents, compared to wild-type mice could be detected with patch-clamp recordings. Between 2 and 4 months old, levels of amyloid-ß40 rose by ∼7-fold, but amyloid-ß42 rose by 25-fold, increasing the amyloid-ß42:amyloid-ß40 ratio to 1:1. Only at 4 months did plaque deposition become detectable and only in some mice; however, synaptic changes were evident in all hippocampal fields. These changes included increased glutamate release probability (P < 0.001, n = 7-9; consistent with the proposed physiological effect of amyloid-ß) and loss of spontaneous action potential-mediated activity in the cornu ammonis 1 (CA1) and dentate gyrus regions of the hippocampus (P < 0.001, n = 7). Hence synaptic changes occur when the amyloid-ß levels and amyloid-ß42:amyloid-ß40 ratio are still low compared to those necessary for plaque deposition. Genome-wide microarray analysis revealed changes in gene expression at 2-4 months including synaptic genes being strongly affected but often showing significant changes only by 4 months. We thus demonstrate that, in a mouse model of rising amyloid-ß, the initial deposition of plaques does not occur until several months after the first amyloid-ß becomes detectable but coincides with a rapid acceleration in the rise of amyloid-ß levels and the amyloid-ß42:amyloid-ß40 ratio. Prior to acceleration, however, there is already a pronounced synaptic dysfunction, reflected as changes in synaptic transmission and altered gene expression, indicating that restoring synaptic function early in the disease progression may represent the earliest possible target for intervention in the onset of Alzheimer's disease.

Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson's disease.

We conducted a meta-analysis of Parkinson's disease genome-wide association studies using a common set of 7,893,274 variants across 13,708 cases and 95,282 controls. Twenty-six loci were identified as having genome-wide significant association; these and 6 additional previously reported loci were then tested in an independent set of 5,353 cases and 5,551 controls. Of the 32 tested SNPs, 24 replicated, including 6 newly identified loci. Conditional analyses within loci showed that four loci, including GBA, GAK-DGKQ, SNCA and the HLA region, contain a secondary independent risk variant. In total, we identified and replicated 28 independent risk variants for Parkinson's disease across 24 loci. Although the effect of each individual locus was small, risk profile analysis showed substantial cumulative risk in a comparison of the highest and lowest quintiles of genetic risk (odds ratio (OR) = 3.31, 95% confidence interval (CI) = 2.55-4.30; P = 2 × 10(-16)). We also show six risk loci associated with proximal gene expression or DNA methylation.

Genome wide assessment of young onset Parkinson's disease from Finland.

In the current study we undertook a series of experiments to test the hypothesis that a monogenic cause of disease may be detectable within a cohort of Finnish young onset Parkinson's disease patients. In the first instance we performed standard genome wide association analyses, and subsequent risk profile analysis. In addition we performed a series of analyses that involved testing measures of global relatedness within the cases compared to controls, searching for excess homozygosity in the cases, and examining the cases for signs of excess local genomic relatedness using a sliding window approach. This work suggested that the previously identified common, low risk alleles, and the risk models associated with these alleles, were generalizable to the Finnish Parkinson's disease population. However, we found no evidence that would suggest a single common high penetrance mutation exists in this cohort of young onset patients.

Comprehensive research synopsis and systematic meta-analyses in Parkinson's disease genetics: The PDGene database.

More than 800 published genetic association studies have implicated dozens of potential risk loci in Parkinson's disease (PD). To facilitate the interpretation of these findings, we have created a dedicated online resource, PDGene, that comprehensively collects and meta-analyzes all published studies in the field. A systematic literature screen of -27,000 articles yielded 828 eligible articles from which relevant data were extracted. In addition, individual-level data from three publicly available genome-wide association studies (GWAS) were obtained and subjected to genotype imputation and analysis. Overall, we performed meta-analyses on more than seven million polymorphisms originating either from GWAS datasets and/or from smaller scale PD association studies. Meta-analyses on 147 SNPs were supplemented by unpublished GWAS data from up to 16,452 PD cases and 48,810 controls. Eleven loci showed genome-wide significant (P < 5 × 10(-8)) association with disease risk: BST1, CCDC62/HIP1R, DGKQ/GAK, GBA, LRRK2, MAPT, MCCC1/LAMP3, PARK16, SNCA, STK39, and SYT11/RAB25. In addition, we identified novel evidence for genome-wide significant association with a polymorphism in ITGA8 (rs7077361, OR 0.88, P  =  1.3 × 10(-8)). All meta-analysis results are freely available on a dedicated online database (www.pdgene.org), which is cross-linked with a customized track on the UCSC Genome Browser. Our study provides an exhaustive and up-to-date summary of the status of PD genetics research that can be readily scaled to include the results of future large-scale genetics projects, including next-generation sequencing studies.