Common genetic variation in the Estrogen Receptor Beta (ESR2) gene and osteoarthritis: results of a meta-analysis

Background: The objective of this study was to examine the relationship between common genetic variation of the ESR2 gene and osteoarthritis.Methods: In the discovery study, the Rotterdam Study-I, 7 single nucleotide polymorphisms (SNPs) were genotyped and tested for association with hip (284 cases, 2772 controls), knee (665 cases, 2075 controls), and hand OA (874 cases, 2184 controls) using an additive model. In the replication stage one SNP (rs1256031) was tested in an additional 2080 hip, 1318 knee and 557 hand OA cases and 4001, 2631 and 1699 controls respectively. Fixed- and random-effects meta-analyses were performed over the complete dataset including 2364 hip, 1983 knee and 1431 hand OA cases and approximately 6000 controls.Results: The C allele of rs1256031 was associated with a 36% increased odds of hip OA in women of the Rotterdam Study-I (OR 1.36, 95% CI 1.08-1.70, p = 0.009). Haplotype analysis and analysis of knee- and hand OA did not give additional information. With the replication studies, the meta-analysis did not show a significant effect of this SNP on hip OA in the total population (OR 1.06, 95% CI 0.99-1.15, p = 0.10). Stratification according to gender did not change the results. In this study, we had 80% power to detect an odds ratio of at least 1.14 for hip OA (α = 0.05).Conclusion: This study showed that common genetic variation in the ESR2 gene is not likely to influence the risk of osteoarthritis with effects smaller than a 13% increase

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)

Severity dependent distribution of impairments in PSP and CBS: Interactive visualizations

BACKGROUND: Progressive supranuclear palsy (PSP) -Richardson's Syndrome and Corticobasal Syndrome (CBS) are the two classic clinical syndromes associated with underlying four repeat (4R) tau pathology. The PSP Rating Scale is a commonly used assessment in PSP clinical trials; there is an increasing interest in designing combined 4R tauopathy clinical trials involving both CBS and PSP. OBJECTIVES: To determine contributions of each domain of the PSP Rating Scale to overall severity and characterize the probable sequence of clinical progression of PSP as compared to CBS. METHODS: Multicenter clinical trial and natural history study data were analyzed from 545 patients with PSP and 49 with CBS. Proportional odds models were applied to model normalized cross-sectional PSP Rating Scale, estimating the probability that a patient would experience impairment in each domain using the PSP Rating Scale total score as the index of overall disease severity. RESULTS: The earliest symptom domain to demonstrate impairment in PSP patients was most likely to be Ocular Motor, followed jointly by Gait/Midline and Daily Activities, then Limb Motor and Mentation, and finally Bulbar. For CBS, Limb Motor manifested first and ocular showed less probability of impairment throughout the disease spectrum. An online tool to visualize predicted disease progression was developed to predict relative disability on each subscale per overall disease severity. CONCLUSION: The PSP Rating Scale captures disease severity in both PSP and CBS. Modelling how domains change in relation to one other at varying disease severities may facilitate detection of therapeutic effects in future clinical trials

Identification of Candidate Parkinson Disease Genes by Integrating Genome-Wide Association Study, Expression, and Epigenetic Data Sets

Importance Substantial genome-wide association study (GWAS) work in Parkinson disease (PD) has led to the discovery of an increasing number of loci shown reliably to be associated with increased risk of disease. Improved understanding of the underlying genes and mechanisms at these loci will be key to understanding the pathogenesis of PD. / Objective To investigate what genes and genomic processes underlie the risk of sporadic PD. / Design and Setting This genetic association study used the bioinformatic tools Coloc and transcriptome-wide association study (TWAS) to integrate PD case-control GWAS data published in 2017 with expression data (from Braineac, the Genotype-Tissue Expression [GTEx], and CommonMind) and methylation data (derived from UK Parkinson brain samples) to uncover putative gene expression and splicing mechanisms associated with PD GWAS signals. Candidate genes were further characterized using cell-type specificity, weighted gene coexpression networks, and weighted protein-protein interaction networks. / Main Outcomes and Measures It was hypothesized a priori that some genes underlying PD loci would alter PD risk through changes to expression, splicing, or methylation. Candidate genes are presented whose change in expression, splicing, or methylation are associated with risk of PD as well as the functional pathways and cell types in which these genes have an important role. / Results Gene-level analysis of expression revealed 5 genes (WDR6 [OMIM 606031], CD38 [OMIM 107270], GPNMB [OMIM 604368], RAB29 [OMIM 603949], and TMEM163 [OMIM 618978]) that replicated using both Coloc and TWAS analyses in both the GTEx and Braineac expression data sets. A further 6 genes (ZRANB3 [OMIM 615655], PCGF3 [OMIM 617543], NEK1 [OMIM 604588], NUPL2 [NCBI 11097], GALC [OMIM 606890], and CTSB [OMIM 116810]) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell types compared with neurons. The weighted gene coexpression performed on the GTEx data set showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes associated with protein ubiquitination and in the ubiquitin-dependent protein catabolic process in the nucleus accumbens, caudate, and putamen. TMEM163 and ZRANB3 were both important in modules in the frontal cortex and caudate, respectively, indicating regulation of signaling and cell communication. Protein interactor analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known mendelian PD and parkinsonism proteins than would be expected by chance. / Conclusions and Relevance Together, these results suggest that several candidate genes and pathways are associated with the findings observed in PD GWAS studies

Identification of sixteen novel candidate genes for late onset Parkinson’s disease

Background Parkinson’s disease (PD) is a neurodegenerative movement disorder affecting 1–5% of the general population for which neither effective cure nor early diagnostic tools are available that could tackle the pathology in the early phase. Here we report a multi-stage procedure to identify candidate genes likely involved in the etiopathogenesis of PD. Methods The study includes a discovery stage based on the analysis of whole exome data from 26 dominant late onset PD families, a validation analysis performed on 1542 independent PD patients and 706 controls from different cohorts and the assessment of polygenic variants load in the Italian cohort (394 unrelated patients and 203 controls). Results Family-based approach identified 28 disrupting variants in 26 candidate genes for PD including PARK2, PINK1, DJ-1(PARK7), LRRK2, HTRA2, FBXO7, EIF4G1, DNAJC6, DNAJC13, SNCAIP, AIMP2, CHMP1A, GIPC1, HMOX2, HSPA8, IMMT, KIF21B, KIF24, MAN2C1, RHOT2, SLC25A39, SPTBN1, TMEM175, TOMM22, TVP23A and ZSCAN21. Sixteen of them have not been associated to PD before, were expressed in mesencephalon and were involved in pathways potentially deregulated in PD. Mutation analysis in independent cohorts disclosed a significant excess of highly deleterious variants in cases (p = 0.0001), supporting their role in PD. Moreover, we demonstrated that the co-inheritance of multiple rare variants (≥ 2) in the 26 genes may predict PD occurrence in about 20% of patients, both familial and sporadic cases, with high specificity (> 93%; p = 4.4 × 10− 5). Moreover, our data highlight the fact that the genetic landmarks of late onset PD does not systematically differ between sporadic and familial forms, especially in the case of small nuclear families and underline the importance of rare variants in the genetics of sporadic PD. Furthermore, patients carrying multiple rare variants showed higher risk of manifesting dyskinesia induced by levodopa treatment. Conclusions Besides confirming the extreme genetic heterogeneity of PD, these data provide novel insights into the genetic of the disease and may be relevant for its prediction, diagnosis and treatment

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

\ua9 2023, Springer Nature Limited. The Global Parkinson’s Genetics Program (GP2) will genotype over 150,000 participants from around the world, and integrate genetic and clinical data for use in large-scale analyses to dramatically expand our understanding of the genetic architecture of PD. This report details the workflow for cohort integration into the complex arm of GP2, and together with our outline of the monogenic hub in a companion paper, provides a generalizable blueprint for establishing large scale collaborative research consortia

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

\ua9 2023, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply. Although over 90 independent risk variants have been identified for Parkinson’s disease using genome-wide association studies, most studies have been performed in just one population at a time. Here we performed a large-scale multi-ancestry meta-analysis of Parkinson’s disease with 49,049 cases, 18,785 proxy cases and 2,458,063 controls including individuals of European, East Asian, Latin American and African ancestry. In a meta-analysis, we identified 78 independent genome-wide significant loci, including 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300 and PPP6R2) and fine-mapped 6 putative causal variants at 6 known PD loci. By combining our results with publicly available eQTL data, we identified 25 putative risk genes in these novel loci whose expression is associated with PD risk. This work lays the groundwork for future efforts aimed at identifying PD loci in non-European populations