Genome-wide survival study identifies a novel synaptic locus and polygenic score for cognitive progression in Parkinson's disease.
Apolipoprotein E4
/ genetics
Cognition
Cognition Disorders
/ genetics
Disease Progression
Genetic Loci
Genetic Predisposition to Disease
Genome-Wide Association Study
Glucosylceramidase
/ genetics
Humans
Longitudinal Studies
Multifactorial Inheritance
/ genetics
Mutation
/ genetics
Parkinson Disease
/ genetics
Proportional Hazards Models
Risk Factors
Survival Analysis
Synapses
/ genetics
Journal
Nature genetics
ISSN: 1546-1718
Titre abrégé: Nat Genet
Pays: United States
ID NLM: 9216904
Informations de publication
Date de publication:
06 2021
06 2021
Historique:
received:
03
04
2019
accepted:
16
03
2021
pubmed:
8
5
2021
medline:
21
7
2021
entrez:
7
5
2021
Statut:
ppublish
Résumé
A key driver of patients' well-being and clinical trials for Parkinson's disease (PD) is the course that the disease takes over time (progression and prognosis). To assess how genetic variation influences the progression of PD over time to dementia, a major determinant for quality of life, we performed a longitudinal genome-wide survival study of 11.2 million variants in 3,821 patients with PD over 31,053 visits. We discover RIMS2 as a progression locus and confirm this in a replicate population (hazard ratio (HR) = 4.77, P = 2.78 × 10
Identifiants
pubmed: 33958783
doi: 10.1038/s41588-021-00847-6
pii: 10.1038/s41588-021-00847-6
pmc: PMC8459648
mid: NIHMS1684407
doi:
Substances chimiques
Apolipoprotein E4
0
GBA protein, human
EC 3.2.1.45
Glucosylceramidase
EC 3.2.1.45
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
787-793Subventions
Organisme : Medical Research Council
ID : MC_PC_17230
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/R007446/1
Pays : United Kingdom
Organisme : NINDS NIH HHS
ID : U01 NS100603
Pays : United States
Organisme : NINDS NIH HHS
ID : U24 NS095871
Pays : United States
Organisme : NINDS NIH HHS
ID : K23 NS099380
Pays : United States
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : NINDS NIH HHS
ID : U01 NS095736
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS115144
Pays : United States
Investigateurs
Jacobus J van Hilten
(JJ)
Références
Nalls, M. A. et al. Large-scale meta-analysis of genome-wide association data identifies six new risk loci for Parkinson’s disease. Nat. Genet. 46, 989–993 (2014).
pubmed: 25064009
pmcid: 4146673
doi: 10.1038/ng.3043
Chang, D. et al. A meta-analysis of genome-wide association studies identifies 17 new Parkinson’s disease risk loci. Nat. Genet. 49, 1511–1516 (2017).
pubmed: 28892059
pmcid: 5812477
doi: 10.1038/ng.3955
Wijmenga, C. & Zhernakova, A. The importance of cohort studies in the post-GWAS era. Nat. Genet. 50, 322–328 (2018).
pubmed: 29511284
doi: 10.1038/s41588-018-0066-3
Locascio, J. J. & Atri, A. An overview of longitudinal data analysis methods for neurological research. Dement. Geriatr. Cogn. Dis. Extra 1, 330–357 (2011).
pubmed: 22203825
pmcid: 3243635
doi: 10.1159/000330228
Dorsey, E. R. & Bloem, B. R. The Parkinson pandemic—a call to action. JAMA Neurol. 75, 9–10 (2018).
pubmed: 29131880
doi: 10.1001/jamaneurol.2017.3299
Liu, G. et al. Specifically neuropathic Gaucher’s mutations accelerate cognitive decline in Parkinson’s. Ann. Neurol. 80, 674–685 (2016).
pubmed: 27717005
pmcid: 5244667
doi: 10.1002/ana.24781
Liu, G. et al. Prediction of cognition in Parkinson’s disease with a clinical-genetic score: a longitudinal analysis of nine cohorts. Lancet Neurol. 16, 620–629 (2017).
pubmed: 28629879
pmcid: 5761650
doi: 10.1016/S1474-4422(17)30122-9
Aarsland, D. et al. Cognitive decline in Parkinson disease. Nat. Rev. Neurol. 13, 217–231 (2017).
pubmed: 28257128
pmcid: 5643027
doi: 10.1038/nrneurol.2017.27
Schrag, A., Jahanshahi, M. & Quinn, N. What contributes to quality of life in patients with Parkinson’s disease? J. Neurol. Neurosurg. Psychiatry 69, 308–312 (2000).
pubmed: 10945804
pmcid: 1737100
doi: 10.1136/jnnp.69.3.308
Svenningsson, P., Westman, E., Ballard, C. & Aarsland, D. Cognitive impairment in patients with Parkinson’s disease: diagnosis, biomarkers, and treatment. Lancet Neurol. 11, 697–707 (2012).
pubmed: 22814541
doi: 10.1016/S1474-4422(12)70152-7
Braak, H. et al. Staging of brain pathology related to sporadic Parkinson’s disease. Neurobiol. Aging 24, 197–211 (2003).
pubmed: 12498954
doi: 10.1016/S0197-4580(02)00065-9
Langston, J. W. The Parkinson’s complex: parkinsonism is just the tip of the iceberg. Ann. Neurol. 59, 591–596 (2006).
pubmed: 16566021
doi: 10.1002/ana.20834
Williams-Gray, C. H. et al. The CamPaIGN study of Parkinson’s disease: 10-year outlook in an incident population-based cohort. J. Neurol. Neurosurg. Psychiatry 84, 1258–1264 (2013).
pubmed: 23781007
doi: 10.1136/jnnp-2013-305277
Cilia, R. et al. Survival and dementia in GBA-associated Parkinson’s disease: the mutation matters. Ann. Neurol. 80, 662–673 (2016).
pubmed: 27632223
doi: 10.1002/ana.24777
Pang, S., Li, J., Zhang, Y. & Chen, J. Meta-analysis of the relationship between the APOE gene and the onset of Parkinson’s disease dementia. Parkinsons Dis. 2018, 9497147 (2018).
pubmed: 30405900
pmcid: 6204165
Healy, D. G. et al. Phenotype, genotype, and worldwide genetic penetrance of LRRK2-associated Parkinson’s disease: a case-control study. Lancet Neurol. 7, 583–590 (2008).
pubmed: 18539534
pmcid: 2832754
doi: 10.1016/S1474-4422(08)70117-0
Guella, I. et al. alpha-synuclein genetic variability: a biomarker for dementia in Parkinson disease. Ann. Neurol. 79, 991–999 (2016).
pubmed: 27091628
doi: 10.1002/ana.24664
Markopoulou, K. et al. Does alpha-synuclein have a dual and opposing effect in preclinical vs. clinical Parkinson’s disease? Parkinsonism Relat. Disord. 20, 584–589 (2014).
pubmed: 24656894
pmcid: 4723426
doi: 10.1016/j.parkreldis.2014.02.021
Mata, I. F. et al. APOE, MAPT, and SNCA genes and cognitive performance in Parkinson disease. JAMA Neurol. 71, 1405–1412 (2014).
pubmed: 25178429
pmcid: 4227942
doi: 10.1001/jamaneurol.2014.1455
Paul, K. C., Schulz, J., Bronstein, J. M., Lill, C. M. & Ritz, B. R. Association of polygenic risk score with cognitive decline and motor progression in Parkinson disease. JAMA Neurol. 75, 360–366 (2018).
pubmed: 29340614
pmcid: 5885856
doi: 10.1001/jamaneurol.2017.4206
Mata, I. F. et al. Large-scale exploratory genetic analysis of cognitive impairment in Parkinson’s disease. Neurobiol. Aging 56, 211 e1–211 e7 (2017).
doi: 10.1016/j.neurobiolaging.2017.04.009
Locascio, J. J. et al. Association between alpha-synuclein blood transcripts and early, neuroimaging-supported Parkinson’s disease. Brain 138, 2659–2671 (2015).
pubmed: 26220939
pmcid: 4643625
doi: 10.1093/brain/awv202
Pankratz, N. et al. Meta-analysis of Parkinson’s disease: identification of a novel locus, RIT2. Ann. Neurol. 71, 370–384 (2012).
pubmed: 22451204
pmcid: 3354734
doi: 10.1002/ana.22687
Jankovic, J. et al. Variable expression of Parkinson’s disease: a base-line analysis of the DATATOP cohort. The Parkinson Study Group. Neurology 40, 1529–1534 (1990).
pubmed: 2215943
doi: 10.1212/WNL.40.10.1529
Ravina, B. et al. A longitudinal program for biomarker development in Parkinson’s disease: a feasibility study. Mov. Disord. 24, 2081–2090 (2009).
pubmed: 19691116
doi: 10.1002/mds.22690
Winder-Rhodes, S. E. et al. Glucocerebrosidase mutations influence the natural history of Parkinson’s disease in a community-based incident cohort. Brain 136, 392–399 (2013).
pubmed: 23413260
doi: 10.1093/brain/aws318
Marinus, J. et al. A short scale for the assessment of motor impairments and disabilities in Parkinson’s disease: the SPES/SCOPA. J. Neurol. Neurosurg. Psychiatry 75, 388–395 (2004).
pubmed: 14966153
pmcid: 1738938
doi: 10.1136/jnnp.2003.017509
Breen, D. P., Evans, J. R., Farrell, K., Brayne, C. & Barker, R. A. Determinants of delayed diagnosis in Parkinson’s disease. J. Neurol. 260, 1978–1981 (2013).
pubmed: 23572347
doi: 10.1007/s00415-013-6905-3
Rosenthal, L. S. et al. The NINDS Parkinson’s disease biomarkers program. Mov. Disord. 30, 915–923 (2016).
doi: 10.1002/mds.26438
Writing Group for the NINDS Exploratory Trials in Parkinson Disease (NET-PD) Investigators et al. Effect of creatine monohydrate on clinical progression in patients with Parkinson disease: a randomized clinical trial. JAMA 313, 584–593 (2015).
1000 Genomes Project Consortium et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).
Browning, S. R. & Browning, B. L. Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am. J. Hum. Genet. 81, 1084–1097 (2007).
pubmed: 17924348
pmcid: 2265661
doi: 10.1086/521987
Li, Y., Willer, C. J., Ding, J., Scheet, P. & Abecasis, G. R. MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet. Epidemiol. 34, 816–834 (2010).
pubmed: 21058334
pmcid: 3175618
doi: 10.1002/gepi.20533
Marchini, J., Howie, B., Myers, S., McVean, G. & Donnelly, P. A new multipoint method for genome-wide association studies by imputation of genotypes. Nat. Genet. 39, 906–913 (2007).
pubmed: 17572673
doi: 10.1038/ng2088
Visscher, P. M. et al. 10 years of GWAS discovery: biology, function, and translation. Am. J. Hum. Genet. 101, 5–22 (2017).
pubmed: 28686856
pmcid: 5501872
doi: 10.1016/j.ajhg.2017.06.005
Ripatti, S. & Palmgren, J. Estimation of multivariate frailty models using penalized partial likelihood. Biometrics 56, 1016–1022 (2000).
pubmed: 11129456
doi: 10.1111/j.0006-341X.2000.01016.x
Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).
pubmed: 25642630
pmcid: 4495769
doi: 10.1038/ng.3211
Yang, J. et al. Genomic inflation factors under polygenic inheritance. Eur. J. Hum. Genet. 19, 807–812 (2011).
pubmed: 21407268
pmcid: 3137506
doi: 10.1038/ejhg.2011.39
Dubois, B. et al. Diagnostic procedures for Parkinson’s disease dementia: recommendations from the movement disorder society task force. Mov. Disord. 22, 2314–2324 (2007).
pubmed: 18098298
doi: 10.1002/mds.21844
Armstrong, M. J. & Okun, M. S. Diagnosis and treatment of Parkinson disease: a review. JAMA 323, 548–560 (2020).
pubmed: 32044947
doi: 10.1001/jama.2019.22360
Kaeser, P. S. et al. RIM proteins tether Ca2+ channels to presynaptic active zones via a direct PDZ-domain interaction. Cell 144, 282–295 (2011).
pubmed: 21241895
pmcid: 3063406
doi: 10.1016/j.cell.2010.12.029
Liu, C., Kershberg, L., Wang, J., Schneeberger, S. & Kaeser, P. S. Dopamine secretion is mediated by sparse active zone-like release sites. Cell 172, 706–718 e15 (2018).
pubmed: 29398114
pmcid: 5807134
doi: 10.1016/j.cell.2018.01.008
Mechaussier, S. et al. Loss of function of RIMS2 causes a syndromic congenital cone-rod synaptic disease with neurodevelopmental and pancreatic involvement. Am. J. Hum. Genet. 106, 859–871 (2020).
doi: 10.1016/j.ajhg.2020.04.018
Powell, C. M. et al. The presynaptic active zone protein RIM1alpha is critical for normal learning and memory. Neuron 42, 143–153 (2004).
pubmed: 15066271
pmcid: 3910111
doi: 10.1016/S0896-6273(04)00146-1
Nalls, M. A. et al. Identification of novel risk loci, causal insights, and heritable risk for Parkinson’s disease: a meta-analysis of genome-wide association studies. Lancet Neurol. 18, 1091–1102 (2019).
pubmed: 31701892
doi: 10.1016/S1474-4422(19)30320-5
GTEx, Consortium et al. Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017).
doi: 10.1038/nature24277
Dong, X. et al. Enhancers active in dopamine neurons are a primary link between genetic variation and neuropsychiatric disease. Nat. Neurosci. 21, 1482–1492 (2018).
pubmed: 30224808
pmcid: 6334654
doi: 10.1038/s41593-018-0223-0
Jiao, H. F. et al. Transmembrane protein 108 is required for glutamatergic transmission in dentate gyrus. Proc. Natl Acad. Sci. USA. 114, 1177–1182 (2017).
pubmed: 28096412
doi: 10.1073/pnas.1618213114
Mallaret, M. et al. The tumour suppressor gene WWOX is mutated in autosomal recessive cerebellar ataxia with epilepsy and mental retardation. Brain 137, 411–419 (2014).
pubmed: 24369382
doi: 10.1093/brain/awt338
Kunkle, B. W. et al. Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing. Nat. Genet. 51, 414–430 (2019).
pubmed: 30820047
pmcid: 6463297
doi: 10.1038/s41588-019-0358-2
Khera, A. V. et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat. Genet. 50, 1219–1224 (2018).
pubmed: 30104762
pmcid: 6128408
doi: 10.1038/s41588-018-0183-z
Nalls, M. A. et al. Diagnosis of Parkinson’s disease on the basis of clinical and genetic classification: a population-based modelling study. Lancet Neurol. 14, 1002–1009 (2015).
pubmed: 26271532
pmcid: 4575273
doi: 10.1016/S1474-4422(15)00178-7
Lee, J. K., Tran, T. & Tansey, M. G. Neuroinflammation in Parkinson’s disease. J. Neuroimmune Pharmacol. 4, 419–429 (2009).
pubmed: 19821032
pmcid: 3736976
doi: 10.1007/s11481-009-9176-0
Johnson, M. E., Stecher, B., Labrie, V., Brundin, L. & Brundin, P. Triggers, facilitators, and aggravators: redefining Parkinson’s disease pathogenesis. Trends Neurosci. 42, 4–13 (2019).
pubmed: 30342839
doi: 10.1016/j.tins.2018.09.007
Irwin, D. J. et al. Neuropathologic substrates of Parkinson disease dementia. Ann. Neurol. 72, 587–598 (2012).
pubmed: 23037886
pmcid: 3484250
doi: 10.1002/ana.23659
Irwin, D. J. et al. Neuropathological and genetic correlates of survival and dementia onset in synucleinopathies: a retrospective analysis. Lancet Neurol. 16, 55–65 (2017).
pubmed: 27979356
pmcid: 5181646
doi: 10.1016/S1474-4422(16)30291-5
Guerreiro, R. et al. Investigating the genetic architecture of dementia with Lewy bodies: a two-stage genome-wide association study. Lancet Neurol. 17, 64–74 (2018).
pubmed: 29263008
doi: 10.1016/S1474-4422(17)30400-3
Blanche, P., Dartigues, J. F. & Jacqmin-Gadda, H. Estimating and comparing time-dependent areas under receiver operating characteristic curves for censored event times with competing risks. Stat. Med. 32, 5381–5397 (2013).
pubmed: 24027076
doi: 10.1002/sim.5958
Alves, G. et al. Incidence of Parkinson’s disease in Norway: the Norwegian ParkWest study. J. Neurol. Neurosurg. Psychiatry 80, 851–857 (2009).
pubmed: 19246476
doi: 10.1136/jnnp.2008.168211
Parkinson Progression Marker, I. The Parkinson Progression Marker Initiative (PPMI). Prog. Neurobiol. 95, 629–635 (2011).
doi: 10.1016/j.pneurobio.2011.09.005
Verbaan, D. et al. Patient-reported autonomic symptoms in Parkinson disease. Neurology 69, 333–341 (2007).
pubmed: 17646625
doi: 10.1212/01.wnl.0000266593.50534.e8
Beach, T. G. et al. Arizona Study of Aging and Neurodegenerative Disorders and Brain and Body Donation Program. Neuropathology 35, 354–389 (2015).
pubmed: 25619230
pmcid: 4593391
doi: 10.1111/neup.12189
Lucero, C. et al. Cognitive reserve and β-amyloid pathology in Parkinson disease. Parkinsonism Relat. Disord. 21, 899–904 (2015).
pubmed: 26037458
pmcid: 4509801
doi: 10.1016/j.parkreldis.2015.05.020
Corvol, J. C. et al. Longitudinal analysis of impulse control disorders in Parkinson disease. Neurology 91, e189–e201 (2018).
pubmed: 29925549
pmcid: 6059034
doi: 10.1212/WNL.0000000000005816
Parkinson Study Group. DATATOP: a multicenter controlled clinical trial in early Parkinson’s disease. Arch. Neurol. 46, 1052–1060 (1989).
Williams-Gray, C. H. et al. The distinct cognitive syndromes of Parkinson’s disease: 5 year follow-up of the CamPaIGN cohort. Brain 132, 2958–2969 (2009).
pubmed: 19812213
doi: 10.1093/brain/awp245
Hughes, A. J., Daniel, S. E., Ben-Shlomo, Y. & Lees, A. J. The accuracy of diagnosis of parkinsonian syndromes in a specialist movement disorder service. Brain 125, 861–870 (2002).
pubmed: 11912118
doi: 10.1093/brain/awf080
Goetz, C. G. et al. Movement Disorder Society Task Force report on the Hoehn and Yahr staging scale: status and recommendations. Mov. Disord. 19, 1020–1028 (2004).
pubmed: 15372591
doi: 10.1002/mds.20213
Hoops, S. et al. Validity of the MoCA and MMSE in the detection of MCI and dementia in Parkinson disease. Neurology 73, 1738–1745 (2009).
pubmed: 19933974
pmcid: 2788810
doi: 10.1212/WNL.0b013e3181c34b47
van Steenoven, I. et al. Conversion between mini-mental state examination, montreal cognitive assessment, and dementia rating scale-2 scores in Parkinson’s disease. Mov. Disord. 29, 1809–1815 (2014).
pubmed: 25381961
pmcid: 4371590
doi: 10.1002/mds.26062
Uc, E. Y. et al. Incidence of and risk factors for cognitive impairment in an early Parkinson disease clinical trial cohort. Neurology 73, 1469–1477 (2009).
pubmed: 19884574
pmcid: 2779004
doi: 10.1212/WNL.0b013e3181bf992f
Mollenhauer, B. et al. Baseline predictors for progression 4 years after Parkinson’s disease diagnosis in the De Novo Parkinson Cohort (DeNoPa). Mov. Disord. 34, 67–77 (2019).
pubmed: 30468694
doi: 10.1002/mds.27492
Kasten, M. et al. Cohort Profile: a population-based cohort to study non-motor symptoms in parkinsonism (EPIPARK). Int. J. Epidemiol. 42, 128–128k (2013).
pubmed: 23257687
doi: 10.1093/ije/dys202
Bien, S. A. et al. Strategies for enriching variant coverage in candidate disease loci on a multiethnic genotyping array. PLoS ONE 11, e0167758 (2016).
pubmed: 27973554
pmcid: 5156387
doi: 10.1371/journal.pone.0167758
Purcell, S. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).
pubmed: 17701901
pmcid: 1950838
doi: 10.1086/519795
Anderson, C. A. et al. Data quality control in genetic case-control association studies. Nat. Protoc. 5, 1564–1573 (2010).
pubmed: 21085122
pmcid: 3025522
doi: 10.1038/nprot.2010.116
1000 Genomes Project Consortium et al. A map of human genome variation from population-scale sequencing. Nature 467, 1061–1073 (2010).
Price, A. L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).
pubmed: 16862161
doi: 10.1038/ng1847
Das, S. et al. Next-generation genotype imputation service and methods. Nat. Genet. 48, 1284–1287 (2016).
pubmed: 27571263
pmcid: 5157836
doi: 10.1038/ng.3656
McCarthy, S. et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat. Genet. 48, 1279–1283 (2016).
pubmed: 27548312
pmcid: 5388176
doi: 10.1038/ng.3643
Loh, P. R. et al. Reference-based phasing using the Haplotype Reference Consortium panel. Nat. Genet. 48, 1443–1448 (2016).
pubmed: 27694958
pmcid: 5096458
doi: 10.1038/ng.3679
Desikan, R. S. et al. Genetic assessment of age-associated Alzheimer disease risk: development and validation of a polygenic hazard score. PLoS Med. 14, e1002258 (2017).
pubmed: 28323831
pmcid: 5360219
doi: 10.1371/journal.pmed.1002258
Cuellar-Partida, G., Renteria, M. E. & MacGregor, S. LocusTrack: integrated visualization of GWAS results and genomic annotation. Source Code Biol. Med. 10, 1 (2015).
pubmed: 25750659
pmcid: 4351846
doi: 10.1186/s13029-015-0032-8