Regional overlap of pathologies in Lewy body disorders

Q2Q1Artículo original216-224Paciente adultoLewy body disorders (LBD) are common neurodegenerative diseases characterized by the presence of aggregated a-synuclein in Lewy bodies and Lewy neurites in the central and peripheral nervous systems. The brains of patients with LBD often display other comorbid pathologies, i.e. insoluble tau, b-amyloid aggregates, TAR DNA-binding protein 43 (TDP-43) deposits, and argyrophilic grain disease (AGD). The incidence and physiological relevance of these concurrent pathological findings remain controversial. We performed a semiquantitative detailed mapping of a-synuclein, tau, bamyloid (Ab), TDP-43, and AGD pathologies in 17 areas in 63 LBD cases (44 with Parkinson disease [PD], 28 with dementia, and 19 with dementia with Lewy bodies). APOE and MAPT genetic variants were also investigated. A majority of LBD cases had 2 or 3 concomitant findings, particularly Alzheimer disease-related pathology. Pathological stages of tau, b-amyloid and a-synuclein pathologies were increased in cases with dementia. Ab score was the best correlate of the time to dementia in PD. In addition, b-amyloid deposition correlated with a-synuclein load in all groups. MAPT H1 haplotype did not influence any assessed pathology in PD. These results highlight the common concurrence of pathologies in patients with LBD that may have an impact on the clinical expression of the diseases

Adverse maternal, fetal, and newborn outcomes among pregnant women with SARS-CoV-2 infection: an individual participant data meta-analysis.

INTRODUCTION Despite a growing body of research on the risks of SARS-CoV-2 infection during pregnancy, there is continued controversy given heterogeneity in the quality and design of published studies. METHODS We screened ongoing studies in our sequential, prospective meta-analysis. We pooled individual participant data to estimate the absolute and relative risk (RR) of adverse outcomes among pregnant women with SARS-CoV-2 infection, compared with confirmed negative pregnancies. We evaluated the risk of bias using a modified Newcastle-Ottawa Scale. RESULTS We screened 137 studies and included 12 studies in 12 countries involving 13 136 pregnant women.Pregnant women with SARS-CoV-2 infection-as compared with uninfected pregnant women-were at significantly increased risk of maternal mortality (10 studies; n=1490; RR 7.68, 95% CI 1.70 to 34.61); admission to intensive care unit (8 studies; n=6660; RR 3.81, 95% CI 2.03 to 7.17); receiving mechanical ventilation (7 studies; n=4887; RR 15.23, 95% CI 4.32 to 53.71); receiving any critical care (7 studies; n=4735; RR 5.48, 95% CI 2.57 to 11.72); and being diagnosed with pneumonia (6 studies; n=4573; RR 23.46, 95% CI 3.03 to 181.39) and thromboembolic disease (8 studies; n=5146; RR 5.50, 95% CI 1.12 to 27.12).Neonates born to women with SARS-CoV-2 infection were more likely to be admitted to a neonatal care unit after birth (7 studies; n=7637; RR 1.86, 95% CI 1.12 to 3.08); be born preterm (7 studies; n=6233; RR 1.71, 95% CI 1.28 to 2.29) or moderately preterm (7 studies; n=6071; RR 2.92, 95% CI 1.88 to 4.54); and to be born low birth weight (12 studies; n=11 930; RR 1.19, 95% CI 1.02 to 1.40). Infection was not linked to stillbirth. Studies were generally at low or moderate risk of bias. CONCLUSIONS This analysis indicates that SARS-CoV-2 infection at any time during pregnancy increases the risk of maternal death, severe maternal morbidities and neonatal morbidity, but not stillbirth or intrauterine growth restriction. As more data become available, we will update these findings per the published protocol

Regulatory sites for splicing in human basal ganglia are enriched for disease-relevant information

Genome-wide association studies have generated an increasing number of common genetic variants associated with neurological and psychiatric disease risk. An improved understanding of the genetic control of gene expression in human brain is vital considering this is the likely modus operandum for many causal variants. However, human brain sampling complexities limit the explanatory power of brain-related expression quantitative trait loci (eQTL) and allele-specific expression (ASE) signals. We address this, using paired genomic and transcriptomic data from putamen and substantia nigra from 117 human brains, interrogating regulation at different RNA processing stages and uncovering novel transcripts. We identify disease-relevant regulatory loci, find that splicing eQTLs are enriched for regulatory information of neuron-specific genes, that ASEs provide cell-specific regulatory information with evidence for cellular specificity, and that incomplete annotation of the brain transcriptome limits interpretation of risk loci for neuropsychiatric disease. This resource of regulatory data is accessible through our web server, http://braineacv2.inf.um.es/

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)

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

Whole-genome DNA hyper-methylation in iPSC-derived dopaminergic neurons from Parkinson's disease patients

Background: Parkinson’s disease (PD) is characterized by the loss of midbrain dopaminergic neurons (DAn). Previously, we described the presence of DNA hyper- and hypo-methylation alterations in induced pluripotent stem cells (iPSC)-derived DAn from PD patients using the Illumina 450K array which prominently covers gene regulatory regions. Methods: To expand and contextualize previous findings, we performed the first whole-genome DNA bisulfite sequencing (WGBS) using iPSC-derived DAn from representative PD subjects: one sporadic PD (sPD) patient, one monogenic LRRK2-associated PD patient (L2PD), and one control. Results: At the whole-genome level, we detected global DNA hyper-methylation in the PD which was similarly spread across the genome in both sPD and L2PD and mostly affected intergenic regions. Conclusion: This study implements previous epigenetic knowledge in PD at a whole genome level providing the first comprehensive and unbiased CpG DNA methylation data using iPSC-derived DAn from PD patients. Our results indicate that DAn from monogenic or sporadic PD exhibit global DNA hyper-methylation changes. Findings from this exploratory study are to be validated in further studies analyzing other PD cell models and patient tissues.This work was supported by the Fondo de Investigaciones Sanitarias of the Instituto de Salud Carlos III (ISCIII) to M.E. (grant # PI14/00426), the Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED) to the Movement Disorders Unit of the Neurology Service from the Hospital Clínic de Barcelona to E.T., M.-J.M., R.F.-S., and M.E. (grant # PRI-16-2017). R.F.S. was supported by a Jóvenes Investigadores grant (#SAF2015-73508-JIN) through the Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad (Plan Estatal de I+D+I 2013–2016) of the Spanish Ministry of Economy and Competitiveness (MINECO), and the Agencia Estatal de Investigación (AEI), which is cofunded by FEDER (AEI/FEDER/UE). Other funding included the grants BFU2013-49157-P, BFU2016-80870-P, and the European Research Council (ERC) 2012-StG (311736- PD-HUMMODEL) to A.C; ISCIII/FEDER (RD16/0011/0024) and Generalitat de Catalunya (iPS4BioMed SGR 2017–2019) to A.R.; and ISCIII/FEDER (PIE14/00061) to A.R

Transcriptome analysis in LRRK2 and idiopathic Parkinson's disease at different glucose levels

Type-2 diabetes (T2D) and glucose metabolic imbalances have been linked to neurodegenerative diseases, including Parkinson's disease (PD). To detect potential effects of different glucose levels on gene expression, by RNA-seq we analyzed the transcriptome of dermal fibroblasts from idiopathic PD (iPD) patients, LRRK2-associated PD (L2PD) patients, and healthy controls (total n = 21 cell lines), which were cultured at two different glucose concentrations (25 and 5 mM glucose). In PD patients we identified differentially expressed genes (DEGs) that were related to biological processes mainly involving the plasmatic cell membrane, the extracellular matrix, and also neuronal functions. Such pathway deregulation was largely similar in iPD or L2PD fibroblasts. Overall, the gene expression changes detected in this study were associated with PD independently of glucose concentration.This work was supported by CIBERNED / Instituto de Salud Carlos III (ISCIII) (grant PIE14/00061) (to M.-J.M.), and the Fondo de Investigaciones Sanitarias from ISCIII (grant PIE20/00259) (to M.E.). R.F.-S. was supported by a Jóvenes Investigadores (JIN) grant of the Spanish Ministry of Economy and Competitiveness (MINECO) and the Agencia Estatal de Investigación (AEI) (AEI/FEDER/UE) (grant #SAF2015-73508-JIN), and a Miguel Servet grant from the Instituto de Salud Carlos III (grant #CP19/00048). A.E-C. was funded by ISCIII /MINECO (PT17/0009/0019) and co-funded by FEDER. M.F. was funded through a María de Maeztu grant (#MDM-2017-0729). IDIBAPS receives funding from the CERCA Program from the Generalitat de Catalunya and the FEDER Program from the European Union