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

International Parkinson's Disease Genomics Consortium, 23andMe Research Team, System Genomics of Parkinson's Disease Consortium

Research output: Contribution to journalArticle

Abstract

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).

Original languageEnglish (US)
Pages (from-to)1091-1102
Number of pages12
JournalThe Lancet Neurology
Volume18
Issue number12
DOIs
StatePublished - Dec 2019

Fingerprint

Genome-Wide Association Study
Parkinson Disease
Meta-Analysis
Random Allocation
Methylation
National Institute on Aging (U.S.)
Inborn Genetic Diseases
Putamen
National Institutes of Health (U.S.)
Brain
Proxy
Single Nucleotide Polymorphism
Smoking
Genome
Phenotype
Gene Expression

ASJC Scopus subject areas

  • Clinical Neurology

Cite this

International Parkinson's Disease Genomics Consortium, 23andMe Research Team, & System Genomics of Parkinson's Disease Consortium (2019). Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies. The Lancet Neurology, 18(12), 1091-1102. https://doi.org/10.1016/S1474-4422(19)30320-5

Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease : a meta-analysis of genome-wide association studies. / International Parkinson's Disease Genomics Consortium; 23andMe Research Team; System Genomics of Parkinson's Disease Consortium.

In: The Lancet Neurology, Vol. 18, No. 12, 12.2019, p. 1091-1102.

Research output: Contribution to journalArticle

International Parkinson's Disease Genomics Consortium, 23andMe Research Team & System Genomics of Parkinson's Disease Consortium 2019, 'Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies', The Lancet Neurology, vol. 18, no. 12, pp. 1091-1102. https://doi.org/10.1016/S1474-4422(19)30320-5
International Parkinson's Disease Genomics Consortium, 23andMe Research Team, System Genomics of Parkinson's Disease Consortium. Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies. The Lancet Neurology. 2019 Dec;18(12):1091-1102. https://doi.org/10.1016/S1474-4422(19)30320-5
International Parkinson's Disease Genomics Consortium ; 23andMe Research Team ; System Genomics of Parkinson's Disease Consortium. / Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease : a meta-analysis of genome-wide association studies. In: The Lancet Neurology. 2019 ; Vol. 18, No. 12. pp. 1091-1102.
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abstract = "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).",
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TY - JOUR

T1 - Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease

T2 - a meta-analysis of genome-wide association studies

AU - International Parkinson's Disease Genomics Consortium

AU - 23andMe Research Team

AU - System Genomics of Parkinson's Disease Consortium

AU - Nalls, Mike A.

AU - Blauwendraat, Cornelis

AU - Vallerga, Costanza L.

AU - Heilbron, Karl

AU - Bandres-Ciga, Sara

AU - Chang, Diana

AU - Tan, Manuela

AU - Kia, Demis A.

AU - Noyce, Alastair J.

AU - Xue, Angli

AU - Bras, Jose

AU - Young, Emily

AU - von Coelln, Rainer

AU - Simón-Sánchez, Javier

AU - Schulte, Claudia

AU - Sharma, Manu

AU - Krohn, Lynne

AU - Pihlstrøm, Lasse

AU - Siitonen, Ari

AU - Iwaki, Hirotaka

AU - Leonard, Hampton

AU - Faghri, Faraz

AU - Gibbs, J. Raphael

AU - Hernandez, Dena G.

AU - Scholz, Sonja W.

AU - Botia, Juan A.

AU - Martinez, Maria

AU - Corvol, Jean Christophe

AU - Lesage, Suzanne

AU - Jankovic, Joseph

AU - Shulman, Lisa M.

AU - Sutherland, Margaret

AU - Tienari, Pentti

AU - Majamaa, Kari

AU - Toft, Mathias

AU - Andreassen, Ole A.

AU - Bangale, Tushar

AU - Brice, Alexis

AU - Yang, Jian

AU - Gan-Or, Ziv

AU - Gasser, Thomas

AU - Heutink, Peter

AU - Shulman, Joshua M.

AU - Wood, Nicholas W.

AU - Hinds, David A.

AU - Hardy, John A.

AU - Morris, Huw R.

AU - Gratten, Jacob

AU - Visscher, Peter M.

AU - Savitt, Joseph

PY - 2019/12

Y1 - 2019/12

N2 - 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).

AB - 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).

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