8 research outputs found

    A Machine Learning Approach to Predicting Early and Late Reintubation

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    Accurate estimations of surgical risks is important for improving the shared decision making and informed consent processes. Reintubation is a severe postoperative complication that can lead to various other detrimental outcomes. Reintubation can also be broken up into early reintubation (within 72 hours of surgery) and late reintubation (within 30 days of surgery). Using clinical data provided by ACS NSQIP, scoring systems were developed for the prediction of combined, early, and late reintubation. The risk factors included in each scoring system were narrowed down from a set of 37 pre and perioperative factors. The scoring systems demonstrated good performance in terms of both accuracy and discrimination, and these results were only marginally worse than prediction using the full set of risk variables. While more work needs to be done to identify clinically relevant differences between the early and late reintubation outcomes, the scoring systems provided here can be used by surgeons and patients to improve the quality of care overall

    Polygenic Parkinson's Disease Genetic Risk Score as Risk Modifier of Parkinsonism in Gaucher Disease

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    Background: Biallelic pathogenic variants in GBA1 are the cause of Gaucher disease (GD) type 1 (GD1), a lysosomal storage disorder resulting from deficient glucocerebrosidase. Heterozygous GBA1 variants are also a common genetic risk factor for Parkinson's disease (PD). GD manifests with considerable clinical heterogeneity and is also associated with an increased risk for PD. Objective: The objective of this study was to investigate the contribution of PD risk variants to risk for PD in patients with GD1. Methods: We studied 225 patients with GD1, including 199 without PD and 26 with PD. All cases were genotyped, and the genetic data were imputed using common pipelines. Results: On average, patients with GD1 with PD have a significantly higher PD genetic risk score than those without PD (P = 0.021). Conclusions: Our results indicate that variants included in the PD genetic risk score were more frequent in patients with GD1 who developed PD, suggesting that common risk variants may affect underlying biological pathways. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA

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

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    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

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

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    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

    NeuroBooster Array: A Genome-Wide Genotyping Platform to Study Neurological Disorders Across Diverse Populations.

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    Genome-wide genotyping platforms have the capacity to capture genetic variation across different populations, but there have been disparities in the representation of population-dependent genetic diversity. The motivation for pursuing this endeavor was to create a comprehensive genome-wide array capable of encompassing a wide range of neuro-specific content for the Global Parkinson's Genetics Program (GP2) and the Center for Alzheimer's and Related Dementias (CARD). CARD aims to increase diversity in genetic studies, using this array as a tool to foster inclusivity. GP2 is the first supported resource project of the Aligning Science Across Parkinson's (ASAP) initiative that aims to support a collaborative global effort aimed at significantly accelerating the discovery of genetic factors contributing to Parkinson's disease and atypical parkinsonism by generating genome-wide data for over 200,000 individuals in a multi-ancestry context. Here, we present the Illumina NeuroBooster array (NBA), a novel, high-throughput and cost-effective custom-designed content platform to screen for genetic variation in neurological disorders across diverse populations. The NBA contains a backbone of 1,914,934 variants (Infinium Global Diversity Array) complemented with custom content of 95,273 variants implicated in over 70 neurological conditions or traits with potential neurological complications. Furthermore, the platform includes over 10,000 tagging variants to facilitate imputation and analyses of neurodegenerative disease-related GWAS loci across diverse populations. The NBA can identify low frequency variants and accurately impute over 15 million common variants from the latest release of the TOPMed Imputation Server as of August 2023 (reference of over 300 million variants and 90,000 participants). We envisage this valuable tool will standardize genetic studies in neurological disorders across different ancestral groups, allowing researchers to perform genetic research inclusively and at a global scale

    Identification of genetic risk loci and causal insights associated with Parkinson's disease in African and African admixed populations: a genome-wide association study

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    BACKGROUND: An understanding of the genetic mechanisms underlying diseases in ancestrally diverse populations is an important step towards development of targeted treatments. Research in African and African admixed populations can enable mapping of complex traits, because of their genetic diversity, extensive population substructure, and distinct linkage disequilibrium patterns. We aimed to do a comprehensive genome-wide assessment in African and African admixed individuals to better understand the genetic architecture of Parkinson's disease in these underserved populations. METHODS: We performed a genome-wide association study (GWAS) in people of African and African admixed ancestry with and without Parkinson's disease. Individuals were included from several cohorts that were available as a part of the Global Parkinson's Genetics Program, the International Parkinson's Disease Genomics Consortium Africa, and 23andMe. A diagnosis of Parkinson's disease was confirmed clinically by a movement disorder specialist for every individual in each cohort, except for 23andMe, in which it was self-reported based on clinical diagnosis. We characterised ancestry-specific risk, differential haplotype structure and admixture, coding and structural genetic variation, and enzymatic activity. FINDINGS: We included 197 918 individuals (1488 cases and 196 430 controls) in our genome-wide analysis. We identified a novel common risk factor for Parkinson's disease (overall meta-analysis odds ratio for risk of Parkinson's disease 1·58 [95% CI 1·37-1·80], p=2·397 × 10-14) and age at onset at the GBA1 locus, rs3115534-G (age at onset β=-2·00 [SE=0·57], p=0·0005, for African ancestry; and β=-4·15 [0·58], p=0·015, for African admixed ancestry), which was rare in non-African or non-African admixed populations. Downstream short-read and long-read whole-genome sequencing analyses did not reveal any coding or structural variant underlying the GWAS signal. The identified signal seems to be associated with decreased glucocerebrosidase activity. INTERPRETATION: Our study identified a novel genetic risk factor in GBA1 in people of African ancestry, which has not been seen in European populations, and it could be a major mechanistic basis of Parkinson's disease in African populations. This population-specific variant exerts substantial risk on Parkinson's disease as compared with common variation identified through GWAS and it was found to be present in 39% of the cases assessed in this study. This finding highlights the importance of understanding ancestry-specific genetic risk in complex diseases, a particularly crucial point as the Parkinson's disease field moves towards targeted treatments in clinical trials. The distinctive genetics of African populations highlights the need for equitable inclusion of ancestrally diverse groups in future trials, which will be a valuable step towards gaining insights into novel genetic determinants underlying the causes of Parkinson's disease. This finding opens new avenues towards RNA-based and other therapeutic strategies aimed at reducing lifetime risk of Parkinson's disease. FUNDING: The Global Parkinson's Genetics Program, which is funded by the Aligning Science Across Parkinson's initiative, and The Michael J Fox Foundation for Parkinson's Research
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