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Cited by 2,454Parkinson's Disease Mechanisms and TreatmentsGenetic Associations and EpidemiologyNuclear Receptors and Signaling

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

Open access
Nalls, Mike A, Blauwendraat, Cornelis, Vallerga, Costanza L, Heilbron, Karl, Bandres-Ciga, Sara, Chang, Diana, Tan, Manuela, Kia, Demis A +262 more·2019·The Lancet Neurology
DOI 10.1016/s1474-4422(19)30320-5PMC PMC8422160

Published version of a preprint

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Abstract

SUMMARY Background Genome-wide association studies (GWASs) in Parkinson’s disease (PD) have increased the scope of biological knowledge about the disease over the past decade. We sought to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into disease etiology. Methods We performed the largest meta-GWAS of PD to date, involving the analysis of 7.8M SNPs in 37.7K cases, 18.6K UK Biobank proxy-cases (having a first degree relative with PD), and 1.4M controls. We carried out a meta-analysis of this GWAS data to nominate novel loci. We then evaluated heritable risk estimates and predictive models using this data. We also utilized 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 PD and other phenotypes of interest via genetic correlations followed by Mendelian randomization. Findings 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 PD depending on prevalence. Integrating methylation and expression data within a Mendelian randomization framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested PD loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes, smoking status, and educational attainment. Mendelian randomization between cognitive performance and PD risk showed a robust association. Interpretation These data provide the most comprehensive understanding of the genetic architecture of PD to date by revealing many additional PD risk loci, providing a biological context for these risk factors, and demonstrating that a considerable genetic component of this disease remains unidentified.

AI snapshot

Written from the paper’s full text.

TL;DR

This meta-GWAS of Parkinson’s disease identified 90 independent genome-wide significant risk signals across 78 regions, including 38 novel signals, and linked them to brain-enriched neuronal expression and candidate causal genes. It estimated that these variants explain 16–36% of PD heritable risk depending on prevalence, while noting that much genetic risk remains unidentified.

Key findings

  • Identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci, from 37,688 cases, 18,618 UK Biobank proxy-cases, and 1,417,791 controls at 7,784,415 SNPs.
  • The 90 variants explained 16–36% of PD heritable risk depending on prevalence; the 88-variant PRS explained a minimum 16% at 0.5% prevalence, the 1805-variant PRS roughly 26%, and up to 36% at 2% prevalence. Highest-versus-lowest PRS quartile ORs were 3.74 (95% CI 3.35–4.18) in NeuroX-dbGaP and 6.25 (95% CI 4.26–9.28) in HBS.
  • Integrating methylation and expression data via Mendelian randomization identified putatively associated genes at 70 risk signals; 151 of 237 testable genes (63.7%) showed expression or methylation significantly associated with possible causal change in PD risk. PD loci were enriched in brain tissues and neuronal cell types, with strongest enrichment for substantia nigra neurons (P=1.0E-06).
  • Significant genetic correlations included brain volumes, smoking status, and educational attainment; Mendelian randomization showed a robust causal effect of cognitive performance on PD risk (MR effect=0.213, SE=0.041, Bonferroni-adjusted P=8.00E-07).

Methods

  • Design: largest-to-date meta-GWAS of PD using fixed-effects meta-analysis in METAL, followed by conditional and joint analysis (COJO) to nominate independent variants; novelty defined as >1 Mb from previously reported loci.
  • Data: discovery included three previously published studies, 13 new datasets, and UK Biobank proxy-cases; heritability used LD score regression on 11 clinically ascertained datasets; PRS used a two-stage design training in NeuroX-dbGaP (5,851 cases, 5,866 controls) and validating in HBS (527 cases, 472 controls).
  • Main analyses: PRSice2 for polygenic risk profiling, LDSC for heritability and genetic correlations, summary-based Mendelian randomization with brain methylation/expression QTL data, FUMA for tissue/cell/pathway enrichment, and rare coding variant burden tests in IPDGC (17,188 cases, 22,875 controls).

Limitations

  • Stated: no defined external validation dataset was used; external replication of novel associations will be difficult due to required sample sizes; variants with P values between 5E-08 and 5E-9 should be interpreted with greater caution, and 16 risk variants fell in this range.
  • Stated: the study focused on individuals of European ancestry, limiting generalization and ancestry-specific PRS; QTL associations are hampered by small sample size and low cis-SNP density; population-wide screening with the 1805-variant PRS is not feasible, with roughly 14 false positives per true positive at 0.5% prevalence.
  • Evident from the text: the meta-analysis combines heterogeneous datasets, including UK Biobank proxy-cases and self-reported 23andMe cases, which may introduce phenotype misclassification; ancestry restriction also limits fine-mapping and generalizability beyond European populations.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/s1474-4422(19)30320-5

Cites

50 of 50 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 28 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    The 90 identified variants explained 16-36% of the heritable risk of PD depending on prevalence.

    “These 90 variants explained 16–36% of the heritable risk of PD depending on prevalence.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: Disease prevalence is 0.5% (global prevalence) for PRS and power calculations.
  • Findingown data

    Using LDSC on a meta-analysis of all 11 clinically-ascertained datasets, the liability-scale heritability of PD was estimated as 0.22 (95% CI 0.18-0.26).

    “Using LDSC on a meta-analysis of all 11 clinically-ascertained datasets from our GWAS and estimated the liability-scale heritability of PD as 0.22 (95% CI 0.18 – 0.26), only slightly lower than a previous estimate derived using GCTA (0.27, 95% CI 0.17 – 0.38) (2,16,30).”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [2] Polymeropoulos, 1996, Mapping of a gene for Parkinson's disease to chromosome 4q21-q23, Science source

      Not checked in the free run.

    • cites [16] Qi, 2018, Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood, Nat Commun source

      Not checked in the free run.

    • cites [30] Wray, 2010, The genetic interpretation of area under the ROC curve in genomic profiling, PLoS Genet source

      Not checked in the free run.

  • Findingcitation

    In a high-risk population with a prevalence of 2%, the 1805-variant PRS explained a maximum 36% of PD heritable risk.

    “In a high-risk population with a prevalence of 2%, the 1805 variant PRS explained a maximum 36% of PD heritable risk (2,31) (Table S4).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [2] Polymeropoulos, 1996, Mapping of a gene for Parkinson's disease to chromosome 4q21-q23, Science source

      Not checked in the free run.

    • cites [31] Skol, 2006, Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies, Nat Genet source

      Not checked in the free run.

  • Findingown data

    Integrating methylation and expression data within a Mendelian randomization framework identified putatively associated genes at 70 risk signals underlying GWAS loci.

    “Integrating methylation and expression data within a Mendelian randomization framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies.”
    • Also stated in: § RESULTS · hedged
      “Of the 90 PD GWAS risk variants, 70 were in loci containing at least one of these putatively causal genes after multiple test correction (Table 3).”
    Quote in the paperSubstantial claim
  • Findingown data

    The 1805-variant PRS explained roughly 26% of PD heritability.

    “The 1805 variant PRS explained roughly 26% of PD heritability.”
    Quote in the paperSubstantial claim
  • May combine two claims. 18
  • Classified as probably not a substantial claim. 11

  • May combine two claims.

    Findingown data

    The analysis detected 10 loci containing more than one independent risk signal (22 risk SNPs total), of which nine had been identified by previous GWAS, including multi-signal loci near GBA, NUCKS1/RAB29, GAK/TMEM175, SNCA and LRRK2; the novel multi-signal locus comprised rs2269906 (UBTF/GRN) and rs850738 (FAM171A2).

    “We detected 10 loci containing more than one independent risk signal (22 risk SNPs in total across these loci), of which nine had been identified by previous GWAS, including multi-signal loci in the vicinity of GBA, NUCKS1/RAB29, GAK/TMEM175, SNCA and LRRK2. The novel multi-signal locus comprised independent risk variants rs2269906 (UBTF/GRN) and rs850738 (FAM171A2).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Variants in the range 5E-08 < P < 1.35E-03 used in the 1805-variant PRS were rarer and had smaller effect estimates than genome-wide significant variants; sub-significant variants had median minor allele frequency 21.3% and median effect estimate 0.047, while genome-wide significant variants had median minor allele frequency 25.1% and median effect estimate 0.081.

    “Variants in the range of 5E-08 < P < 1.35E-03 (used in the 1805 variant PRS) were rarer and had smaller effect estimates than variants reaching genome-wide significance. These sub-significant variants had a median minor allele frequency of 21.3% and a median effect estimate (absolute value of the log odds ratio of the SNP parameter from regresion) of 0.047.”
    • Also stated in: § RESULTS · plain
      “Genome-wide significant risk variants were more common with a median minor allele frequency of 25.1%, and had a median effect estimate of 0.081.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    PD cases ascertained by clinicians and 23andMe self-reported cases showed strong genetic correlation (rG = 0.85, SE = 0.06), and clinician-ascertained cases and UKB proxy cases showed strong genetic correlation (rG = 0.84, SE = 0.134).

    “Supporting this design, we found strong genetic correlations using PD cases ascertained by clinicians compared to 23andMe self-reported cases (genetic correlation from LDSC (rG) = 0.85, SE = 0.06) and UKB proxy cases (rG = 0.84, SE = 0.134).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The study found significant genetic correlations between PD and brain volumes, smoking status, and educational attainment.

    “We found significant genetic correlations with brain volumes, smoking status, and educational attainment.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Tissue-specific expression enrichment analyses suggested PD loci were heavily brain-enriched, with specific neuronal cell types implicated from single cell data.

    “Tissue-specific expression enrichment analyses suggested PD loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The meta-analysis identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci.

    “We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci.”
    • Also stated in: § RESULTS · plain
      “We identified a total of 90 independent genome-wide significant association signals through our analyses of 37,688 cases, 18,618 UKB proxy-cases and 1,417,791 controls at 7,784,415 SNPs (Figure 2, Table 1, Supplementary Appendices, Table S1, Table S2). Of these, 38 signals are new and more than 1MB from loci described previously (1) (Table S3).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Compared to individuals with PRS values in the lowest quartile, the PD odds ratio for individuals with PRS values in the highest quartile was 3.74 (95% CI 3.35-4.18) in the NeuroX-dbGaP cohort and 6.25 (95% CI 4.26-9.28) in the HBS cohort.

    “Compared to individuals with PRS values in the lowest quartile, the PD odds ratio for individuals with PRS values in the highest quartile was 3.74 (95% CI = 3.35 – 4.18) in the NeuroX-dbGaP cohort and 6.25 (95% CI = 4.26 – 9.28) in the HBS cohort (Table 2, Figure 3, Figure S1).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The study found 10 significantly enriched biological pathways (FDR-adjusted P < 0.05), including four related to vacuolar function and three related to known drug targets.

    “We found 10 significantly enriched pathways (FDR-adjusted P < 0.05, Table S8), including four related to vacuolar function and three related to known drug targets (calcium transporters: ikeda_mir1_targets_dn and ikeda_mir30_targets_up, kinase signaling: kim_pten_targets_dn).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    We identified 90 independent common genetic risk factors for Parkinson's disease, nearly doubling the number of known PD risk variants.

    “We identified 90 independent common genetic risk factors for PD, nearly doubling the number of known PD risk variants.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    After FDR correction, the PD GWAS genes were enriched for expression in seven significant brain cell types, all of which were neuronal.

    “After FDR correction we found seven significant brain cell types, all of which were neuronal (Figure S2B).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The strongest enrichment was for neurons in the substantia nigra at P = 1.0E-06, with additional significant results at P < 5.0E-4 for the globus pallidus, thalamus, posterior cortex, frontal cortex, hippocampus and entopeduncular nucleus.

    “The strongest enrichment was for neurons in the substantia nigra (SN) at P = 1.0E-06, with additional significant results at P < 5.0E-4 for the globus pallidus (GP), thalamus (TH), posterior cortex (PC), frontal cortex (FC), hippocampus (HC) and entopeduncular nucleus (ENT).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The genes highlighted by the PD GWAS were enriched for expression in 13 significant tissues, all of which were brain-derived.

    “We found 13 significant tissues, all of which were brain-derived (Figure S2A), in contrast to what has been seen in Alzheimer’s disease which shows a strong bias towards blood, spleen, lungs and microglial enrichments (39).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    We were able to explain 16%−36% of Parkinson's disease heritability, with the range directly related to prevalence estimates varying from 0.5% to 2%.

    “We were able to explain 16%−36% of PD heritability, the range being directly related to prevalence estimates varying (0.5% to 2%).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    We found 16 risk variants in the P value range 5E-08 to 5E-9, including two known variants near WNT3 (proximal to the MAPT locus) and BIN3.

    “We found 16 risk variants in this range, including two known variants near WNT3 (proximal to the MAPT locus) and BIN3.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    These data provide the most comprehensive understanding of the genetic architecture of PD to date, revealing many additional PD risk loci, providing a biological context for these risk factors, and demonstrating that a considerable genetic component of PD remains unidentified.

    “These data provide the most comprehensive understanding of the genetic architecture of PD to date by revealing many additional PD risk loci, providing a biological context for these risk factors, and demonstrating that a considerable genetic component of this disease remains unidentified.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Alzheimer's disease shows a strong bias towards blood, spleen, lungs and microglial enrichments.

    “in contrast to what has been seen in Alzheimer’s disease which shows a strong bias towards blood, spleen, lungs and microglial enrichments (39)”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [39] Saunders, 2018, Molecular diversity and specializations among the cells of the adult mouse brain, Cell source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Mutations in GRN have been shown to be connected with neuronal ceroid lipofuscinosis, a lysosomal storage disorder.

    “Mutations in GRN have also been shown to be connected with another lysosomal storage disorder, neuronal ceroid lipofuscinosis (35).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [35]

      Not checked in the free run.

  • May combine two claims.

    Interpretationcitation

    The correlation between Parkinson's disease and smoking status may not be independent from the correlation between Parkinson's disease and education, because smoking status and years of education were significantly correlated.

    “The correlation between PD and smoking status may not be independent from the correlation between PD and education as smoking status and years of education were significantly correlated (44).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [44]

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Intracranial volume could not be tested in the MR analysis because its GWAS did not contain any genome-wide significant risk variants.

    “Intracranial volume could not be tested because its GWAS did not contain any genome-wide significant risk variants.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Some of the risk associated with these loci may be due to rare coding variants or these may be pleomorphic risk loci.

    “These results suggest that some of the risk associated with these loci may be due to rare coding variants or that these are pleomorphic risk loci.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.

    Interpretationown data

    Putamen and intracranial volumes may prove to be valuable in future Parkinson's disease biomarker studies.

    “Putamen and intracranial volumes may prove to be valuable in future PD biomarker studies.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    We have previously shown that we will need to incorporate other data sources (e.g. smell tests, family history, age, sex) in order to generate algorithms that have more possible value in population-wide screening.

    “While large-scale genome sequencing and non-linear machine learning methods will likely improve these predictive models, we have previously shown that we will need to incorporate other data sources (e.g. smell tests, family history, age, sex) in order to generate algorithms that have more possible value in population-wide screening (4).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [4] Chang, 2017, A meta-analysis of genome-wide association studies identifies 17 new Parkinson's disease risk loci, Nat Genet source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    GRN is known to be associated with frontotemporal dementia.

    “GRN, a gene known to be associated with frontotemporal dementia (FTD) (34)”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [34] Wang, 2017, WebGestalt 2017: a more comprehensive, powerful, flexible and interactive gene set enrichment analysis toolkit, Nucleic Acids Res source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    Filtering our variants with a secondary random-effects meta-analysis may make our 90 PD GWAS hits somewhat more robust due to the conservative nature of random-effects.

    “To a degree, the fact that we filtered our variants with a secondary random-effects meta-analysis may make our 90 PD GWAS hits somewhat more robust due to the conservative nature of random-effects.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    Risk predictions may not generalize across populations in some cases.

    “Also, risk predictions may not generalize across populations in some cases and ancestry specific PRS should be investigated.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Study design and conductnone given

    Many QTL associations are hampered by both small sample size and low cis-SNP density.

    “Finally, our work utilized state-of-the-art QTL datasets to nominate candidate genes, but many QTL associations are hampered by both small sample size and low cis-SNP density.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Interpretationown data

    Our work suggests that GWASes of increasing size will continue to provide useful biological insights into Parkinson's disease.

    “Our work suggests that GWASes of increasing size will continue to provide useful biological insights into PD.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    No defined external validation dataset was used in this study.

    “No defined external validation dataset was used, which may be seen as a limitation.”
    Quote in the paperNot a substantial claim
28 of 28

  • The authors state this as an assumption.

    In Mendelian randomization analyses, there is no intermediate confounder associated with both the exposure and outcome, and the association is not simply due to linkage disequilibrium.

    “inferring causal associations under the assumption that there is no intermediate confounder associated with both parameters and that the association is not simply due to LD.”

  • The authors state this as an assumption.

    The lower minor allele frequencies and smaller effect size estimates of sub-significant variants are typical and representative of variants contributing to the more inclusive PRS and represent future GWAS hits.

    “Here we assume that the lower minor allele frequencies and smaller effect size estimates are typical and representative of variants contributing to our more inclusive PRS and represent future GWAS hits.”

  • The authors state this as an assumption.

    Disease prevalence is 0.5% (global prevalence) for PRS and power calculations.

    “assuming a global prevalence of 0.5%”
    “Assuming that future data is well-harmonized with current data and that disease prevalence is 0.5%”

  • The authors state this as an assumption.

    Future data is well-harmonized with current data.

    “Assuming that future data is well-harmonized with current data”

  • The paper relies on this without support.

    The academic qualification phenotype 'National Vocational Qualifications (NVQ) or Higher National Diploma (HND) or Higher National Certificate (HNC) or equivalent' is a valid proxy for college education.

    “The negative association with one’s academic qualifications suggests that individuals without a college education may be at less risk of PD.”

  • The paper relies on this without support.

    The genetic variants used as instruments in the MR analyses are valid (associated with the exposure, not associated with confounders, and affect the outcome only through the exposure).

    “We used MR to assess whether there was evidence of a causal relationship between PD and five phenotypes related to academic qualification, smoking, and brain volumes described above (Figure S4).”
6 of 6

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • GWAS have identified several immune-related gene variants in PD, including LRRK2, GBA, PRKN, and PINK1.

    “In addition, GWAS have identified several immune-related gene variants in PD,251 including leucine rich repeat kinase 2 (LRRK2), glucosylceramidase (GBA), parkin RBR E3 ubiquitin protein ligase (PRKN) and PTEN Induced Kinase 1 (PINK1).”

    From Role of neuroinflammation in neurodegeneration development (2023) · cites this paper as [251]

    The Results (page unavailable) identify PD GWAS risk signals near LRRK2 and GBA, but the passages do not identify PRKN or PINK1 as GWAS loci. The Discussion (page unavailable) describes only a possible immune component and says immune-related pathway results warrant caution; it does not establish all four named genes as immune-related GWAS findings. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • The IDUA locus is the third most significant locus in the largest GWAS studying Parkinson's disease risk.

    “The IDUA locus is the third most significant locus in the largest GWAS38 studying PD risk.”

    From Genomic atlas of the proteome from brain, CSF and plasma prioritizes proteins implicated in neurological disorders (2021) · cites this paper as [38]

  • The MED12L locus was identified in the latest PD GWAS.

    “The MED12L locus was identified in the latest PD GWAS50.”

    From Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies (2022) · cites this paper as [50]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • The 16-36% heritability range is attributed to the wrong variants

    Major

    The abstract attributes the full 16-36% range to the 90 genome-wide significant variants. In the results, 16% is attributed to an 88-variant score, while 36% is attributed to a much larger 1,805-variant score.

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Nalls, M. A., Blauwendraat, C., Vallerga, C. L., Heilbron, K., Bandres-Ciga, S., Chang, D., Tan, M., Kia, D. A., Noyce, A. J., Xue, A., Bras, J., Young, E., von Coelln, R., Simón-Sánchez, J., Schulte, C., Sharma, M., Krohn, L., Pihlstrøm, L., Siitonen, A., Iwaki, H., Leonard, H., Faghri, F., Gibbs, J. R., Hernandez, D. G., Scholz, S. W., Botia, J. A., Martinez, M., Corvol, J.-C., Lesage, S., Jankovic, J., Shulman, L. M., Sutherland, M., Tienari, P., Majamaa, K., Toft, M., Andreassen, O. A., Bangale, T., Brice, A., Yang, J., Gan-Or, Z., Gasser, T., Heutink, P., Shulman, J. M., Wood, N. W., Hinds, D. A., Hardy, J. A., Morris, H. R., Gratten, J., Visscher, P. M., Graham, R. R., Singleton, A. B., Adarmes-Gómez, A. D., Aguilar, M., Aitkulova, A., Akhmetzhanov, V., Alcalay, R. N., Alvarez, I., Alvarez, V., Bandres-Ciga, S., Barrero, F. J., Bergareche Yarza, J. A., Bernal-Bernal, I., Billingsley, K., Blauwendraat, C., Blazquez, M., Bonilla-Toribio, M., Botía, J. A., Boungiorno, M. T., Bras, J., Brice, A., Brockmann, K., Bubb, V., Buiza-Rueda, D., Cámara, A., Carrillo, F., Carrión-Claro, M., Cerdan, D., Chelban, V., Clarimón, J., Clarke, C., Compta, Y., Cookson, M. R., Corvol, J.-C., Craig, D. W., Danjou, F., Diez-Fairen, M., Dols-Icardo, O., Duarte, J., Duran, R., Escamilla-Sevilla, F., Escott-Price, V., Ezquerra, M., Faghri, F., Feliz, C., Fernández, M., Fernández-Santiago, R., Finkbeiner, S., Foltynie, T., Gan-Or, Z., Garcia, C., García-Ruiz, P., Gasser, T., Gibbs, J. R., Gomez Heredia, M. J., Gómez-Garre, P., González, M. M., Gonzalez-Aramburu, I., Guelfi, S., Guerreiro, R., Hardy, J., Hassin-Baer, S., Hernandez, D. G., Heutink, P., Hoenicka, J., Holmans, P., Houlden, H., Infante, J., Iwaki, H., Jesús, S., Jimenez-Escrig, A., Kaishybayeva, G., Kaiyrzhanov, R., Karimova, A., Kia, D. A., Kinghorn, K. J., Koks, S., Krohn, L., Kulisevsky, J., Labrador-Espinosa, M. A., Leonard, H. L., Lesage, S., Lewis, P., Lopez-Sendon, J. L., Lovering, R., Lubbe, S., Lungu, C., Macias, D., Majamaa, K., Manzoni, C., Marín, J., Marinus, J., Marti, M. J., Martinez, M., Martínez Torres, I., Martínez-Castrillo, J. C., Mata, M., Mencacci, N. E., Méndez-del-Barrio, C., Middlehurst, B., Mínguez, A., Mir, P., Mok, K. Y., Morris, H. R., Muñoz, E., Nalls, M. A., Narendra, D., Noyce, A. J., Ojo, O. O., Okubadejo, N. U., Pagola, A. G., Pastor, P., Perez Errazquin, F., Periñán-Tocino, T., Pihlstrom, L., Plun-Favreau, H., Quinn, J., R'Bibo, L., Reed, X., Rezola, E. M., Rizig, M., Rizzu, P., Robak, L., Rodriguez, A. S., Rouleau, G. A., Ruiz-Martínez, J., Ruz, C., Ryten, M., Sadykova, D., Scholz, S. W., Schreglmann, S., Schulte, C., Sharma, M., Shashkin, C., Shulman, J. M., Sierra, M., Siitonen, A., Simón-Sánchez, J., Singleton, A. B., Suarez-Sanmartin, E., Taba, P., Tabernero, C., Tan, M. X., Tartari, J. P., Tejera-Parrado, C., Toft, M., Tolosa, E., Trabzuni, D., Valldeoriola, F., van Hilten, J. J., Van Keuren-Jensen, K., Vargas-González, L., Vela, L., Vives, F., Williams, N., Wood, N. W., Zharkinbekova, N., Zharmukhanov, Z., Zholdybayeva, E., Zimprich, A., Ylikotila, P., Shulman, L. M., von Coelln, R., Reich, S., Savitt, J., Agee, M., Alipanahi, B., Auton, A., Bell, R. K., Bryc, K., Elson, S. L., Fontanillas, P., Furlotte, N. A., Huber, K. E., Hicks, B., Jewett, E. M., Jiang, Y., Kleinman, A., Lin, K.-H., Litterman, N. K., McCreight, J. C., McIntyre, M. H., McManus, K. F., Mountain, J. L., Noblin, E. S., Northover, C. A. M., Pitts, S. J., Poznik, G. D., Sathirapongsasuti, J. F., Shelton, J. F., Shringarpure, S., Tian, C., Tung, J., Vacic, V., Wang, X., Wilson, C. H., Anderson, T., Bentley, S., Dalrymple-Alford, J., Fowdar, J., Gratten, J., Halliday, G., Henders, A. K., Hickie, I., Kassam, I., Kennedy, M., Kwok, J., Lewis, S., Mellick, G., Montgomery, G., Pearson, J., Pitcher, T., Sidorenko, J., Silburn, P. A., Vallerga, C. L., Visscher, P. M., Wallace, L., Wray, N. R., Xue, A., Yang, J., & Zhang, F.
Affiliations
  • 23andMe (United States) (US)
  • Genentech (US)
  • University of Maryland, Baltimore (US)
  • National Institutes of Health (US)
  • University of Helsinki (FI)
  • Oslo University Hospital (NO)
  • Centre National de la Recherche Scientifique (FR)
  • Van Andel Institute (US)
  • German Center for Neurodegenerative Diseases (DE)
  • McGill University (CA)
  • UCL Queen Square Institute of Neurology (GB)
  • The University of Queensland (AU)
  • Université Toulouse III - Paul Sabatier (FR)
  • Queen Mary University of London (GB)
  • Baylor College of Medicine (US)
  • Oulu University Hospital (FI)
ORCID
Venue
The Lancet Neurology
Publisher
Elsevier BV
Published
2019-12
Volume
18
Issue
12
Pages
1091-1102
ISSN
1474-4422 (ISSN-L)
DOI
10.1016/s1474-4422(19)30320-5
PMC
PMC8422160
OpenAlex
W2986932567
Semantic Scholar
791b9be9559e6a652048bbaf17f9b2348b40f600
Cited by
2,454
References
50
Citations by year
2026: 291 · 2025: 424 · 2024: 480 · 2023: 338 · 2022: 325 · 2021: 318 · 2020: 222 · 2019: 50 · 2018: 4 · 2017: 1
FWCI
30.81
Type
journal article
Language
en
Open access
Licence
Locations
  • The Lancet Neurology (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • UCL Discovery (University College London) (acceptedVersion)
  • Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
  • HAL (submittedVersion)
  • Leiden Repository (Leiden University) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
  • Työväentutkimus Vuosikirja (submittedVersion, other-oa)
  • University of Canterbury Research Repository (University of Canterbury) (submittedVersion)
  • DZNE Pub (submittedVersion)
  • Queen Mary Research Online (Queen Mary University of London) (submittedVersion, cc-by-nc-nd)
  • Griffith Research Online (submittedVersion, other-oa)
Funders
  • Roche
  • Biogen
  • Agence Nationale de la Recherche
  • H. Lundbeck A/S (PCT/US2014/011014)
  • Division of Human Resource Management
  • Burroughs Wellcome Fund
  • Association France Parkinson
  • Boehringer Ingelheim
  • National Institutes of Health
  • European Commission
  • GE Healthcare
  • Institut de France
  • Adrienne Helis Malvin Medical Research Foundation
  • Sanofi
  • Obstetric Anaesthetists' Association
  • Fondation Roger de Spoelberch
  • Michael J. Fox Foundation for Parkinson's Research
  • Novartis
  • PSP Association
  • School of Public Health, University of California Berkeley
  • Chung Hua University
  • Fédération pour la Recherche sur le Cerveau
  • London Mathematical Society
  • Norges Forskningsråd
  • North Carolina GlaxoSmithKline Foundation
Topics
  • Health Sciences › Medicine › Neurology › Parkinson's Disease Mechanisms and Treatments
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Nuclear Receptors and Signaling
Keywords
Parkinson's disease, genetic susceptibility loci, heritability, genetic correlation, Mendelian randomization, brain volume, smoking, educational attainment, cognitive performance, gene expression, DNA methylation, neuronal cell types, shared genetic risk, causal inference, neurodegeneration, neuroinflammation, brain development, neuroprotection, neuroproliferation, neuroplasticity
MeSH terms
Humans, Parkinson Disease, Risk Factors, Genetic Predisposition to Disease, Databases, Genetic, Genome-Wide Association Study, Genetic Loci

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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