Genome sequence analyses identify novel risk loci for multiple system atrophy

Multiple system atrophy (MSA) is an adult-onset, sporadic synucleinopathy characterized by parkinsonism, cerebellar ataxia, and dysautonomia. The genetic architecture of MSA is poorly understood, and treatments are limited to supportive measures. Here, we performed a comprehensive analysis of whole genome sequence data from 888 European-ancestry MSA cases and 7,128 controls to systematically investigate the genetic underpinnings of this understudied neurodegenerative disease. We identified four significantly associated risk loci using a genome-wide association study approach. Transcriptome-wide association analyses prioritized USP38-DT, KCTD7, and lnc-KCTD7-2 as novel susceptibility genes for MSA within these loci, and single-nucleus RNA sequence analysis found that the associated variants acted as cis-expression quantitative trait loci for multiple genes across neuronal and glial cell types. In conclusion, this study highlights the role of genetic determinants in the pathogenesis of MSA, and the publicly available data from this study represent a valuable resource for investigating synucleinopathies.

Erratum: Cumulative Genetic Score and C9orf72 Repeat Status Independently Contribute to Amyotrophic Lateral Sclerosis Risk in 2 Case-Control Studies

[This corrects the article DOI: 10.1212/NXG.0000000000200079.].

Cumulative Genetic Score and C9orf72 Repeat Status Independently Contribute to Amyotrophic Lateral Sclerosis Risk in 2 Case-Control Studies

Background and Objectives

Most patients with amyotrophic lateral sclerosis (ALS) lack a monogenic mutation. This study evaluates ALS cumulative genetic risk in an independent Michigan and Spanish replication cohort using polygenic scores.

Methods

Participant samples from University of Michigan were genotyped and assayed for the chromosome 9 open reading frame 72 hexanucleotide expansion. Final cohort size was 219 ALS and 223 healthy controls after genotyping and participant filtering. Polygenic scores excluding the C9 region were generated using an independent ALS genome-wide association study (20,806 cases, 59,804 controls). Adjusted logistic regression and receiver operating characteristic curves evaluated the association and classification between polygenic scores and ALS status, respectively. Population attributable fractions and pathway analyses were conducted. An independent Spanish study sample (548 cases, 2,756 controls) was used for replication.

Results

Polygenic scores constructed from 275 single-nucleotide variation (SNV) had the best model fit in the Michigan cohort. An SD increase in ALS polygenic score associated with 1.28 (95% CI 1.04-1.57) times higher odds of ALS with area under the curve of 0.663 vs a model without the ALS polygenic score (p value = 1 × 10-6). The population attributable fraction of the highest 20th percentile of ALS polygenic scores, relative to the lowest 80th percentile, was 4.1% of ALS cases. Genes annotated to this polygenic score enriched for important ALS pathomechanisms. Meta-analysis with the Spanish study, using a harmonized 132 single nucleotide variation polygenic score, yielded similar logistic regression findings (odds ratio: 1.13, 95% CI 1.04-1.23).

Discussion

ALS polygenic scores can account for cumulative genetic risk in populations and reflect disease-relevant pathways. If further validated, this polygenic score will inform future ALS risk models.

Effect Modification between Genes and Environment and Parkinson's Disease Risk

Parkinson's disease (PD) is a complex neurodegenerative condition in which genetic and environmental factors interact to contribute to its etiology. Remarkable progress has been made in deciphering disease etiology through genetic approaches, but there is limited data about how environmental and genetic factors interact to modify penetrance, risk, and disease severity. Here, we provide insights into environmental modifiers of PD, discussing precedents from other neurological and non-neurological conditions. Based on these examples, we outline genetic and environmental factors contributing to PD and review potential environmental modifiers of penetrance and clinical variability in monogenic and idiopathic PD. We also highlight the potential challenges and propose how future studies might tackle these important questions. ANN NEUROL 2022;92:715-724.

Genomic Characterization of Host Factors Related to SARS-CoV-2 Infection in People with Dementia and Control Populations: The GR@ACE/DEGESCO Study

Emerging studies have suggested several chromosomal regions as potential host genetic factors involved in the susceptibility to SARS-CoV-2 infection and disease outcome. We nested a COVID-19 genome-wide association study using the GR@ACE/DEGESCO study, searching for susceptibility factors associated with COVID-19 disease. To this end, we compared 221 COVID-19 confirmed cases with 17,035 individuals in whom the COVID-19 disease status was unknown. Then, we performed a meta-analysis with the publicly available data from the COVID-19 Host Genetics Initiative. Because the APOE locus has been suggested as a potential modifier of COVID-19 disease, we added sensitivity analyses stratifying by dementia status or by disease severity. We confirmed the existence of the 3p21.31 region (LZTFL1, SLC6A20) implicated in the susceptibility to SARS-CoV-2 infection and TYK2 gene might be involved in COVID-19 severity. Nevertheless, no statistically significant association was observed in the COVID-19 fatal outcome or in the stratified analyses (dementia-only and non-dementia strata) for the APOE locus not supporting its involvement in SARS-CoV-2 pathobiology or COVID-19 prognosis.

Integrating genetic and clinical data to predict impulse control disorders in Parkinson's disease

BACKGROUND AND PURPOSE

Impulse control disorders (ICDs) are frequent in Parkinson's disease (PD), with associated clinical and genetic risk factors. This study was aimed at analyzing the clinical features and the genetic background that underlie ICDs in PD.

METHODS

We included 353 patients with PD in this study (58.9% men, mean age 62.4 ± 10.58 years, mean age at disease onset 52.71 ± 11.94 years). We used the validated Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease for ICDs screening. Motor, nonmotor, and treatment-related features were evaluated according to the presence of ICDs. Twenty-one variants related to dopaminergic, serotonergic, glutamatergic, and opioid neurotransmitter systems were assessed. Association studies between polymorphisms and ICDs were performed. The combination of clinical and genetic variables was analyzed with receiver operating characteristic curves to assess the predictability of experiencing ICDs.

RESULTS

Impulse control disorders appeared in 25.1% of the cases. Patients with ICDs were younger and presented a higher rate of anxiety. Treatment with dopamine agonists increased the risk of ICDs and it was dose dependent (P < 0.05). Genetic association studies showed that the DOPA decarboxylase gene (DDC), rs1451375, might modulate the risk of ICDs. Plotting the clinical-genetic model, the predictability of ICDs increased 11% (area under curve = 0.80; z = 3.22, P = 0.001) when adding the genotype data for single nucleotide polymorphisms.

CONCLUSIONS

Polymorphisms in DDC might act as risk markers for ICDs in PD. The predictability of experiencing ICDs increased by adding genetic factors to clinical features. It is therefore important to assess the patient's genetic background to identify individuals at risk for ICDs.

The Parkinson's Disease Genome-Wide Association Study Locus Browser

BACKGROUND

Parkinson's disease (PD) is a neurodegenerative disease with an often complex component identifiable by genome-wide association studies. The most recent large-scale PD genome-wide association studies have identified more than 90 independent risk variants for PD risk and progression across more than 80 genomic regions. One major challenge in current genomics is the identification of the causal gene(s) and variant(s) at each genome-wide association study locus. The objective of the current study was to create a tool that would display data for relevant PD risk loci and provide guidance with the prioritization of causal genes and potential mechanisms at each locus.

METHODS

We included all significant genome-wide signals from multiple recent PD genome-wide association studies including themost recent PD risk genome-wide association study, age-at-onset genome-wide association study, progression genome-wide association study, and Asian population PD risk genome-wide association study. We gathered data for all genes 1 Mb 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. Multiple databases were queried for each gene to collect additional causal data.

RESULTS

We created a PD genome-wide association study browser tool (https://pdgenetics.shinyapps.io/GWASBrowser/) to assist the PD research community with the prioritization of genes for follow-up functional studies to identify potential therapeutic targets.

CONCLUSIONS

Our PD genome-wide association study browser tool provides users with a useful method of identifying potential causal genes at all known PD risk loci from large-scale PD genome-wide association studies. We plan to update this tool with new relevant data as sample sizes increase and new PD risk loci are discovered. © 2020 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 US Government employees and their work is in the public domain in the USA.