Full sequencing and haplotype analysis of MAPT in Parkinson disease and REM sleep behavior disorder Jiao Li 1 , 2 , Jennifer A. Ruskey, MSc, 2 , 3 , Isabelle Arnulf, PhD, 4 , Yves Dauvilliers, MD, PhD, 5, Michele T.M. Hu, MBBS, FRCP, PhD, 6,7 , Birgit Högl, MD, 8 , Claire S. Leblond, PhD, 2,9, Sirui Zhou, PhD, 2,3 , Amirthagowri Ambalavanan, PhD, 2,3, , Jay P. Ross, BSc, 2,9 , Cynthia V. Bourassa, MSc, 2 , 3 , Dan Spiegelman, MSc, 2 , 3 , Sandra B Laurent, 2,3 , Ambra Stefani, MD, 8, Christelle Charley Monaca, PhD, 1 0 , Valérie Cochen De Cock, MD, PhD, 1 1 , 1 2 , Michel Boivi PhD, 13,14 , Luigi Ferini-Strambi, MD, PhD, 15 , Giuseppe Plazzi, MD, PhD, 1 6 , 1 7 , Elena Antelmi, MD, PhD, 1 6 , 1 7 , Peter Young, MD, 1 8 , Anna Heidbreder, MD, 18 , Catherine Labbe, PhD 19 , Tanis J. Ferman, PhD 19 , Patrick A. Dion, PhD, 2,3, Dongsheng Fan, MD, PhD, 1, Alex Desautels, MD, PhD, 20,21 , Jean-François Gagnon, PhD, 20,22, Nicolas Dupré, MD, MSc, 23,24 , Edward A. Fon, 2,3 , Jacques Y. Montplaisir, MD, PhD, 20,25 , Bradley F. Boeve, MD, 26 , Ronald B. Postuma, MD, MSc, 2,3,27 , Guy A. Rouleau, MD, PhD, 2,3,9 Owen A. Ross, PhD 28,29 and Ziv Gan-Or, MD, PhD, 2,3,9 . Affiliations : 1 Department of Neurology, Peking University Third Hospital, Beijing
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Full sequencing and haplotype analysis of MAPT in Parkinson disease and REM sleep behavior disorder
Jiao Li1,2, Jennifer A. Ruskey, MSc,2,3, Isabelle Arnulf, MD, PhD,4, Yves Dauvilliers, MD, PhD,5,
Michele T.M. Hu, MBBS, FRCP, PhD,6,7, Birgit Högl, MD,8, Claire S. Leblond, PhD,2,9, Sirui Zhou, PhD,2,3, Amirthagowri Ambalavanan, PhD,2,3,, Jay P. Ross, BSc,2,9, Cynthia V. Bourassa, MSc,2,3, Dan Spiegelman, MSc,2,3, Sandra B Laurent,2,3, Ambra Stefani, MD,8, Christelle Charley Monaca, MD, PhD,10, Valérie Cochen De Cock, MD, PhD,11,12, Michel Boivin, PhD,13,14, Luigi Ferini-Strambi, MD, PhD,15, Giuseppe Plazzi, MD, PhD,16,17, Elena Antelmi, MD, PhD,16,17, Peter Young, MD,18, Anna Heidbreder, MD,18, Catherine Labbe, PhD19, Tanis J. Ferman, PhD19, Patrick A. Dion, PhD,2,3, Dongsheng Fan, MD, PhD,1, Alex Desautels, MD, PhD,20,21, Jean-François Gagnon, PhD,20,22, Nicolas Dupré, MD, MSc,23,24, Edward A. Fon,2,3, Jacques Y. Montplaisir, MD, PhD,20,25, Bradley F. Boeve, MD,26, Ronald B. Postuma, MD, MSc,2,3,27, Guy A. Rouleau, MD, PhD,2,3,9 Owen A. Ross, PhD28,29 and Ziv Gan-Or, MD, PhD,2,3,9.
Affiliations :1Department of Neurology, Peking University Third Hospital, Beijing 100191, People R China 2Montreal Neurological Institute, McGill University, Montréal, QC, H3A 0G4, Canada, 3Department of Neurology and neurosurgery, McGill University, Montréal, QC, H3A 0G4, Canada, 4Sleep Disorders Unit, Pitié Salpêtrière Hospital, Centre de Recherche de l’Institut du Cerveau et de la Moelle Epinière and Sorbonne Universities, UPMC Paris 6 univ, Paris, 75013, France, 5Sleep Unit, National Reference Network for Narcolepsy, Department of Neurology Hôpital-Gui-de Chauliac, CHU Montpellier, INSERM U1061, Montpellier, 34000, France, 6Oxford Parkinson’s Disease Centre (OPDC), University of Oxford, Oxford, OX1 2JD, United Kingdom, 7Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX1 2JD, United Kingdom, 8Sleep Disorders Clinic, Department of Neurology, Medical University of Innsbruck, Innsbruck, 6020, Austria, 9Department of Human Genetics, McGill University, H3A 0G4, Montréal, QC, Canada, 10University Lille north of France, Department of clinical neurophysiology and sleep center, CHU Lille, Lille, 59000, France, 11Sleep and neurology unit, Beau Soleil Clinic, Montpellier, 34070, France, 12EuroMov, University of Montpellier, Montpellier, 34095, France, 13GRIP, École de psychologie, Université Laval, Québec city, QC, G1V 0A6, Canada, 14Institute of Genetic, Neurobiological and Social Foundations of Child Development, Tomsk State University, Tomsk, 634050, Russia, 15Department of Neurological Sciences, Università Vita-Salute San Raffaele, Milan, 20132, Italy, 16Department of Biomedical and Neuromotor Sciences (DIBINEM), Alma Mater Studiorum, University of Bologna, Bologna, 40126, Italy, 17IRCCS, Institute of Neurological Sciences of Bologna, Bologna, 40139, Italy, 18Department of Sleep Medicine and Neuromuscular Disorders, University of Muenster, 48149, Germany, 19Department of Psychiatry and Psychology, Mayo Clinic Jacksonville, FL, USA, 20Centre d’Études Avancées en Médecine du Sommeil, Hôpital du Sacré-Cœur de Montréal, Montréal, QC, H4J 1C5, Canada, 21Department of Neurosciences, Université de Montréal, Montréal, H3T 1J4, Canada, 22Département de psychologie, Université du Québec à Montréal, Montréal, QC, H3C 3P8, Canada, 23Division of Neurosciences, CHU de Québec, Université Laval, Quebec City, QC, Canada, 24Department of Medicine, Faculty of Medicine, Université Laval, Quebec City, QC, Canada, 25Department of Psychiatry, Université de Montréal, Montréal, QC, H3T 1J4, Canada, 26Department of Neurology, Mayo Clinic Rochester,
MN, USA, 27Department of Neurology, Montreal General Hospital, Montréal, QC, H3G 1A4, Canada, 28Department of Neuroscience, Mayo Clinic Jacksonville, FL, USA, 29Department of Clinical Genomics, Mayo Clinic Jacksonville, FL, USA,
Correspondence:Ziv Gan-OrMontreal Neurological Institute, McGill University1033 Pine Avenue, West,Ludmer Pavilion, room 327Montreal, QC, H3A 1A1Phone: +1-514-398-5845e-mail: [email protected]
Word count: 1673 Running title: MAPT in PD and RBDKeywords: REM sleep behavior disorder, Parkinson disease, Genetics, MAPTConflict of interest disclosure: All authors report no conflict of interests.Funding sources: This work was financially supported by the Michael J. Fox Foundation and the Canadian Consortium on Neurodegeneration in Aging (CCNA).
Abstract
Background: MAPT haplotypes are associated with PD, but their association with REM-sleep
behavior disorder (RBD) is unclear.
Methods: Two cohorts were included: A) PD (n=600), RBD (n=613) patients and controls (n=981),
B) DLB patients with RBD (n=271) and controls (n=950). MAPT-associated variants and the entire
coding sequence of MAPT was analyzed. Age-, sex- and ethnicity-adjusted analyses were performed
to examine the association between MAPT, PD and RBD.
Results: MAPT-H2 variants were associated with PD (ORs 0.62-0.65, p=0.010-0.019), but not with
RBD. In PD, the H1 haplotype OR was 1.60 (95%CI 1.12-2.28, p=0.009), and the H2 OR was 0.68
(95%CI 0.48-0.96, p=0.03). The H2/H1 haplotypes were not associated with RBD.
Conclusions: Our results confirm the protective effect of the MAPT-H2 haplotype in PD, and
define its components. Furthermore, our results suggest that MAPT does not play a major role in
RBD, emphasizing different genetic background than in PD in this locus.
Introduction
Rapid eye movement (REM) sleep behavior disorder (RBD) is characterized by loss of muscle
atonia and enactment of dreams during REM sleep. RBD will progress, in most cases, to an overt
synucleinopathy; either Parkinson’s disease (PD), dementia with Lewy bodies (DLB) or, rarely,
multiple system atrophy (MSA).1 Multiple genetic variants have been implicated in PD2, 3 and some
in DLB and MSA,4 yet the potential role of most of them in RBD is still unknown.
Common genetic variation at the MAPT locus represent the second strongest genetic
association in recent genome-wide association studies (GWAS) in PD,2 and may also have a minor
role in DLB.5, 6 Recent studies in MSA also highlighted the MAPT H2 haplotype, although the small
sample size precluded a genome-wide significant p-value.7, 8 Studies in PD focusing on the H1 and
H2 MAPT haplotypes demonstrated that these haplotypes are associated with increased and
decreased risk for PD, respectively, 9-11 and GWAS confirmed that the MAPT H2 haplotype was
strongly associated with PD risk.2
MAPT sub-haplotype analysis and a sequencing study recently performed in DLB, suggested
that a rare sub-haplotype, H1G, and a rare coding variant, p.A152T, were associated with DLB.5, 6
However, a previous study in a large DLB cohort showed no evidence of association of the MAPT
locus with DLB.12 Overall, it seems that MAPT haplotypes play an important role in PD, while their
role in MSA and DLB is still not clear, and could be minor. Since RBD patients may convert to
either PD or DLB, two studies have been recently performed to determine the association between
MAPT and RBD.13, 14 Both studies suggested a possible association, however, both studies were
small and thus underpowered.
In the current study, we aimed to perform a thorough genetic study of the MAPT locus and its
association with RBD (idiopathic RBD and RBD in DLB) and PD, using targeted next generation
sequencing of the entire coding region of MAPT, and in-depth haplotype analysis, in larger cohorts
with RBD.
Methods
Study population
Two Independent cohorts were included (Supplementary Table 1), and more details on their
recruitment and diagnosis is in the Supplementary file: A) The Montreal Neurological Institute
(MNI) cohort included 600 PD patients, 613 RBD patients and 981 controls, all unrelated, of
European ancestry. B) The Mayo cohort included 271 patients with clinical DLB who were
diagnosed with RBD and 950 controls. All participants in both cohorts signed an informed consent
at enrollment to the study, and the respective ethical review boards approved the study protocols.
Genotyping
In cohort A, eight MAPT SNPs were genotyped (Table 1), including six MAPT locus haplotype-
tagging SNPs and two additional MAPT SNP, which were previously reported to be associated with
PD and RBD.13, 14 In cohort B, the six haplotype-tagging SNPs were previously genotyped and
reported. Further details on the genotyping are in the Supplementary file.
Targeted next-generation sequencing
A subset of cohort A, including samples from 525 PD patients, 342 RBD patients and 825 controls
was sequenced using targeted next generation sequencing (NGS). The coding sequences of 51 PD-
related genes (Supplementary Table 2), including MAPT, were captured using molecular inversion
probes (MIPs), as was previously described.15 Further details on alignment, filtering and analysis
are in the Supplementary file.
Statistical analysis
Full details on the statistical analysis can be found in the Supplementary file. To account for
potential bias that may have occurred in cohort A, due to the different populations in patients and
controls (despite all being of European origin), a principal component analysis (PCA) was
performed. Goodness-of-fit chi-square test with one degree of freedom was performed to examine
deviation from Hardy-Weinberg equilibrium (HWE) in the controls for each variant. Adjusted and
unadjusted regression models were performed to examine the association between the tested SNPs
and haplotypes in the MAPT locus and PD or RBD. Burden analysis was done as described in the
Supplementary file. All analyses were performed with PLINK 1.9 or R.
Results
Association of MAPT SNPs with PD and RBD
Data on population stratification and adjustment is in the supplementary file. Genotyping success
rate of the eight selected MAPT SNPs was 100 % in both cohorts, and all variants were in Hardy-
Weinberg equilibrium in the control group. An additional seven common variants with allele
frequencies > 0.05 were identified in the subset of samples from cohort A (525 PD patients, 342
RBD patients and 825 controls) that underwent targeted next generation sequencing of MAPT.
Logistic regression models, with and without adjustment for age, sex and population principal
components, were performed (Table 1).
Of the 15 common variants (Table 1), seven H2-haplotype variants were in almost full LD
(rs12185268, rs8070723, rs1800547, rs62063786, rs62063787, rs17651549, rs10445337), all
associated with a reduced risk for PD (ORs 0.62-0.65, p=0.010-0.019, age, sex and ethnicity
adjusted). The two other H2-haplotye SNPs that were previously reported to be associated with
RBD, rs12185268 and rs1800547,13, 14 were not associated with RBD in the current study, nor were
any of the other MAPT SNPs. In cohort B, rs7521 was nominally associated with DLB-RBD (OR
1.24, 95% CI 1.02-1.52, p=0.035, Supplementary Table 3), however, it was not associated with
RBD in cohort A. Burden analysis did not identify association between rare MAPT variants and PD
or RBD (see Supplementary file).
Analysis of MAPT haplotypes and association with risk for PD and RBD
The H1 haplotype was associated with an increased risk for PD (OR 1.60, 95% CI 1.12-2.28,
p=0.009), and the H2 haplotype was associated with a reduced risk for PD (OR 0.68, 95% CI 0.48-
0.96, p=0.03). However, the H1 and H2 haplotype were not associated with RBD both in cohort A
of idiopathic RBD patients and in cohort B with DLB-RBD. With the data from the targeted NGS,
we demonstrate that the H2 haplotype includes eight coding variants (Supplementary Figure 2)
which are all in full or almost full LD: p.P202L (rs63750417), p.D285N (rs62063786), p.R370W
3. Manuscript Preparation: A. Writing of the first draft – JL, ZGO B. Review and Critique – JL, JAR, IA, YD, MTMH, BH, CSL, SZ, AA, JPR, CVB, DS, SBL, AS, CCM, VCDC, MB, LFS, GP, EA, PY, AH, CL, TJF, PAD, DF, AD, JFG, ND, EAF, JYM, BB, RBP, GAR, OAR, ZGO.
Full financial disclosure for the previous 12 months:JL - nothing to discloseJAR - nothing to discloseIA – Received research funding from FUI (French Investissement Bank)YD - received funds for seminars, board engagements and travel to conferences by UCB Pharma, Jazz, Theranexus, Flamel and Bioprojet.MTMH –received a Parkinson's UK innovation grant “Biomarkers for Dementia and Cognitive decline in Parkinson's disease,” Parkinson's UK Monument Discovery Award “Targeting the earliest pathways to Parkinson's disease,” EU small‐ or medium‐scale focused research project (STREP) Award “Virtual, physiological and computational neuromuscular models for the predictive treatment of Parkinson's Disease‐NoTremor,” and MJFF Biomarker Grant “Development of potential diagnostic biomarkers in Parkinson's disease.”BH – Received funding from the Government of Tyrol translational research funds and from the Austrian Science funds FWF, received honoraria as a consultant from Axovant Mundipahrma and Benevolent Bio, and speaker Honoraria from Otsuka, Janssen Cilag, Lilly, UCB, Abbvie and Nutricia.CSL – nothing to discloseSZ - nothing to disclose AA - nothing to disclose JPR - nothing to disclose CVB - nothing to disclose DS - nothing to disclose SBL - nothing to disclose AS – has received support for research from AxovantCCM – is on the advisory board and received travel and consultancy fees from UCB Pharma.VCDC – has received travel grants from Eole, Orkyn, SOS oxygeneMB – nothing to discloseLFS - nothing to discloseGP – Served on the advisory boards of UCB pharma, Jazz pharmaceuticals and Bioproject.EA – has received a grant from the European Academy of Neurology PY – has received speaker honoraria from Loewenstein Medical GmbH & Co.KG, Neuro Consil, Düsseldorf, UCB Pharma, Genzyme GmbH, Bayer Vital. Served on the advisory boards of Vanda Pharmaceuticals Germany, Genzyme Europe.AH- Has received speaker honoraria from UCB Pharma, Vanda, received travel support from Bioproject. Has served on the advisory board of UCB Pharma CL – nothing to discloseTJF – nothing to disclosePAD - Supported by research grants from CIHR, CCNA, the International Essential Tremor Foundation and ALS Canada-Brain Canada.DF – nothing to discloseAD – nothing to discloseJFG – Supported by research grants from CIHR and Parkinson’s Society Canada.ND - Supported by research grants from Fondation du CHUQ - Kilimandjaro à Québec, CIHR, ALS
Canada & Brain Canada, CQDM/ Brain Canada, FRQS and the W. Garfield Weston Foundation.EAF - Supported by research grants from Canadian Institutes of Health Research (CIHR), Michael J Fox Foundation, ALS Canada-Brain Canada Hudson Team grant, CQDM/ Brain Canada - Focus on Brain Program, Brain Canada, Fonds de Recherche du Québec (FRQS), Canadian Consortium on Neurodegeneration in Aging (CCNA), and National Parkinson Foundation (NPF).JYM - has served on the advisory boards for Sanofi-Aventis, Servier, Merck, Jazz Pharmaceutical, Valeant Pharmaceutical, and Impax Laboratory; has received honoraria from Valeant and Otsuka Pharmaceutical; has received grant support from GlaxoSmithKline and MerckBFB – has received funding from the National Institute on Aging, the National Institute of Neurological Disorders and Stroke, Roivant Sciences, C2N Diagnostics, and Axovant Sciences.RBP – has received personal compensation for travel, speaker fees, and consultation from Boehringer-Ingelheim, GE Health Care, Novartis, Roche, Theranexus and Teva Neurosciences, and is funded by grants from the Fonds de Recherche du Quebec - Sante, the Michael J. Fox Foundation, the W. Garfield Weston Foundation, and the Canadian Institutes of Health Research.GAR – Supported by research grants from CIHR, CCNA, the International Essential Tremor Foundation and ALS Canada-Brain Canada.OAR – has received research support from the National Institutes of Health (P50-NS072187; R01-NS078086), Michael J Fox Foundation and the Department of Defense (W81XWH-17-1-0249).ZGO – has received consultation fees from Genzyme and from Lysosomal Therapeutics Inc. Supported by grants from the Michael J Fox Foundation.
References
1. Postuma RB, Iranzo A, Hogl B, et al. Risk factors for neurodegeneration in idiopathic rapid eye
movement sleep behavior disorder: a multicenter study. Ann Neurol 2015;77(5):830-839.
2. Chang D, Nalls MA, Hallgrimsdottir IB, et al. A meta-analysis of genome-wide association
SNPs, single nucleotide polymorphisms; PD, Parkinson’s disease; RBD, rapid eye movement sleep behavior disorder; OR, odds ratio; CI, confidence interval.a Adjusted for age, sex, and the two major components in the population stratification principal component analysis.
Table 2.Haplotype analysis of MAPT H1 sub-haplotypes in PD and RBD patients.
Allele frequency PD vs. Control RBD vs. ControlHaplotype Haplotype
structure aPD RBD controls OR (95% CI) b p b OR (95% CI) b p b
PD, Parkinson’s disease; RBD, rapid eye movement sleep behavior disorder; OR, odds ratio; CI, confidence interval.a Eight SNPs defining the haplotypes are given in the 5’ to 3’ order as follows: rs12185628, rs1467967, rs242557, rs1800547, rs3785883,
rs2471738, rs8070723, rs7521.b Adjusted for age, sex, and the two major components in the population stratification principal component analysis.
Supplementary material
Full sequencing and haplotype analysis of MAPT in Parkinson disease and REM sleep behavior disorder
Jiao Li1,2, Jennifer A. Ruskey, MSc,2,3, Isabelle Arnulf, MD, PhD,4, Yves Dauvilliers, MD, PhD,5,
Michele T.M. Hu, MBBS, FRCP, PhD,6,7, Birgit Högl, MD,8, Claire S. Leblond, PhD,2,9, Sirui Zhou, PhD,2,3, Amirthagowri Ambalavanan, PhD,2,3,, Jay P. Ross, BSc,2,9, Cynthia V. Bourassa, MSc,2,3, Dan Spiegelman, MSc,2,3, Sandra B Laurent,2,3, Ambra Stefani, MD,8, Christelle Charley Monaca, MD, PhD,10, Valérie Cochen De Cock, MD, PhD,11,12, Michel Boivin, PhD,13,14, Luigi Ferini-Strambi, MD, PhD,15, Giuseppe Plazzi, MD, PhD,16,17, Elena Antelmi, MD, PhD,16,17, Peter Young, MD,18, Anna Heidbreder, MD,18, Catherine Labbe, PhD19, Tanis J. Ferman, PhD19, Patrick A. Dion, PhD,2,3, Dongsheng Fan, MD, PhD,1, Alex Desautels, MD, PhD,20,21, Jean-François Gagnon, PhD,20,22, Nicolas Dupré, MD, MSc,23,24, Edward A. Fon,2,3, Jacques Y. Montplaisir, MD, PhD,20,25, Bradley F. Boeve, MD,26, Ronald B. Postuma, MD, MSc,2,3,27, Guy A. Rouleau, MD, PhD,2,3,9 Owen A. Ross, PhD28,29 and Ziv Gan-Or, MD, PhD,2,3,9.
Supplementary full methods
Study population
Two Independent cohorts were included in the current study (Supplementary Table 1):
A) The Montreal Neurological Institute (MNI) cohort included 600 PD patients, 613 RBD
patients (261 of which were included in a previous study that included analysis of one MAPT
SNP1) and 981 controls, all unrelated, of European ancestry. PD patients and controls were
recruited from clinics across Québec, Canada, including the Quebec Parkinson’s Network
(http://rpq-qpn.ca/) and from Montpellier, France, and were mainly of French-Canadian and
French origin. PD patients were diagnosed by movement disorders specialists from the
participating clinics, based on the UK Parkinson’s Disease Brain Bank Criteria (without
exclusion of patients with familial history of PD). RBD patients were recruited by collaborators
from the International RBD Study Group from Europe and Canada, as part of the International
RBD Genetics Consortium (IRBDGC). RBD diagnosis was confirmed with polysomnography,
according to the International Classification of Sleep Disorders, version 2 (ICSD-2) criteria2. Of
the RBD patients, 342 were of French-Canadian or French origin.
B) The Mayo cohort series consists of 271 patients with clinical DLB who were diagnosed with
RBD (termed hereafter DLB-RBD) confirmed with polysomnography according to the ICSD-2
criteria or diagnosed with probable RBD using the Mayo Sleep Questionnaire (which was
demonstrated to have sensitivity of 98% and specificity of 74% in a cohort of DLB patients 3),
and 950 controls. Further details on this cohort and their recruitment were previously described.4
All participants in both cohorts signed an informed consent at enrollment to the study, and the
respective ethical review boards approved the study protocols.
Genotyping
In cohort A, a total of eight SNPs from the MAPT locus were genotyped, including six MAPT
locus haplotype-tagging SNPs (rs1467967, rs242557, rs3785883, rs2471738, rs8070723, rs7521)
and two additional MAPT SNP (rs12185268, rs1800547), which were previously reported to be
associated with PD and RBD.1, 5 Genotyping was performed using TaqMan SNP genotyping
assays on The Applied Biosystems™ QuantStudio™ 7 Flex Real-Time PCR System (Applied
Biosystems, Foster City, CA) according to the manufacturer's instructions. In cohort B, the six
haplotype-tagging SNPs were previously genotyped and reported, without distinction between
presence or absence of RBD in DLB. Genotyping was performed as previously described.4
Targeted next-generation sequencing
A subset of cohort A, including samples from 525 PD patients, 342 RBD patients and 825
controls was sequenced using targeted next generation sequencing (NGS). The coding sequences
of 51 PD-related genes (Supplementary Table 2), including MAPT, were captured using
molecular inversion probes (MIPs), as was previously described.6 Targeted NGS was performed
using the Illumina HiSeq 2500 platform (Innovation Genome Center, McGill University, and
Genome Quebec). Sequencing data were aligned against the human genome (GRCh37 assembly)
using Burrows-Wheeler Aligner,7 and the variant calling and annotation were done using
Genome Analysis ToolKit (GATK)8 and ANNOVAR9 tools, respectively. For the current study,
data on MAPT was extracted. However, to control for possible population stratification bias, data
on all common variants in these genes was used (see section on principal component analysis). In
the variant analysis, variants with sequencing depth of < 20X or with genotype quality < 60 were
excluded.
Principal component analysis
To account for potential bias that may have occurred in cohort A, due to the different populations
in patients and controls (despite all being of European origin), a principal component analysis
(PCA) was performed. Data on 164 common SNPs from the 51 PD-related genes was extracted
for all 1692 study participants that underwent targeted NGS. These data were compared with the
same variants in the 1000 Genome Project (www.internationalgenome.org) in the CHB (n=103),
CEU (n=99), JPT (n=104) and YRI (n=108) samples (Supplementary Figure 1). Ancestry and
population stratification were assessed using the “smartpca” module implemented in the
EIGENSOFT package10 in R, and the principal components of ancestry were determined.
Statistical analysis
Association of MAPT SNPs with PD and RBD
Goodness-of-fit chi-square test with one degree of freedom was performed to examine deviation
from HWE in the controls for each variant. To examine the association between the tested SNPs
in the MAPT locus and PD or RBD, a binary logistic regression model was performed. To
account for the possible effects of age, sex and ethnicity potential differences, the regression
model was performed with and without age, sex and the 2 first major principal components of
ancestry as covariates. In the combined analysis of RBD patients from cohort A and DLB-RBD
patients from cohort B, the regression model was adjusted for age, sex, and center. This analysis
was performed separately for the PD and RBD cohorts, and all analyses were performed using
PLINK 1.9.11
Association of MAPT haplotypes with PD and BRD risk
Haplotypes were determined, and assignment of the H1/H2 haplotypes and H1 sub-haplotypes
was done as was previously described. Haplotypes with frequency of <0.01 were excluded from
the analysis. Logistic regression over the haplotypes was performed to test for association with
PD and RBD, with and without age, sex and the 2 principal ancestry components as covariates.
This analysis was done separately for PD and RBD from cohort A, and for the RBD vs. controls
from cohort B. In the combined haplotype analysis of RBD patients from cohort A and DLB-
RBD patients from cohort B, the regression model was adjusted for age, sex, and center. All
analyses were performed with PLINK.
Burden analysis of functional MAPT variants in PD and BRD
To examine whether there is a burden effect of coding variants that affect the protein sequence,
an optimized Sequence Kernel Association Test (SKAT-O)12 was performed using R. First, we
examined the burden of all non-synonymous variants, followed by an analysis of all variants
predicted to be deleterious by the SIFT (Sorting Intolerant From Tolerant) algorithm.13
Supplementary Table 1.
Study population. Cohort A Cohort B Population PD RBD Controls DLB-RBD ControlsN 600 613 981 271 950NGS, N 525 342 825 - -Male:Female Ratioa 1.81 3.92 1.11 4.77 0.74Age (Mean±SD)b 65.4±9.8 67.4±8.6 44.1±14.6 63.6±13.3 65.1±12.7Age (Range)c 30.0-91.0 32.0-87.0 19.0-83.0 15.0-91.0 18.0-92.0N, number; NGS, next generation sequencing – number of samples that went through targeted NGS; SD, standard deviation; PD, Parkinson’s disease; RBD, rapid eye movement sleep behavior disorder; DLB-RBD, patients with dementia with Lewy bodies (DLB) and RBD.a Data on sex were not available for 8 PD, 42 RBD and 84 control individualsb Data on age were not available for 16 PD, 17 RBD and 46 control individuals c Data on DLB-RBD age was not available for 13 patients.
Supplementary Table 2. Fifty one genes that were fully sequenced using molecular inversion probes. Common variants in these genes were used to demonstrate ancestry by performance of principal component analysis (see supplementary Figure 1)
ACMSD FGF20
LAMP3
PSAP SREBF1
ATP13A2
GAK LRRK2 RAB25 STK39
BST1 GBA MAPT RAB7L1
STX1B
C18orf8 GCH1 MCCC1
RIT2 SYT11
CCDC62
GIGYF2
NPC1 SCARB2
TMEM163
DDRGK1
GPNMB
PARK2 SETD1A
TMEM175
DGKQ HIP1R PARK7 SIPA1L2
UCHL1
DNAJC13
HTRA2
PINK1 SLC41A1
USP25
EIF4G1 INPP5F
PLA2G6
SMPD1 VPS13C
FAM47E
ITGA8 PM20D1
SNCA VPS35
FBXO7
Supplementary Table 3.Frequencies of MAPT SNPs in patients with DLB and RBD vs. controls, and a combined analysis with RBD patients and controls from cohort A.
Minor allele frequency DLB-RBD vs. controls RBD+DLB-RBD vs. combined controls
DLB-RBD Controls RBD + DLB-RBD Combined controls OR (95% CI) a p a OR (95% CI) b p b
DLB-RBD, patients with dementia with Lewy bodies (DLB) and rapid eye movement sleep behavior disorder (RBD); OR, odds ratio; CI, confidence interval.a Adjusted for age and sex.b Adjusted for age, sex and center.
Supplementary Table 4.Haplotype analysis of MAPT H1 sub-haplotypes in DLB-RBD patients and controls, and combined analysis with RBD patients and controls from cohort A.
Allele frequency DLB-RBD vs. controls RBD+DLB-RBD vs. combined controls
Haplotype Haplotype structure a
DLB-RBD Controls RBD + DLB-RBD Combined controls OR (95% CI) b p b OR (95% CI) c p c
DLB-RBD, patients with dementia with Lewy bodies (DLB) and rapid eye movement sleep behavior disorder (RBD); OR, odds ratio; CI, confidence interval.a Six SNPs defining the haplotypes are given in the 5’ to 3’ order as follows: rs1467967, rs242557, rs3785883, rs2471738, rs8070723, rs7521.b Adjusted for age and sex.c Adjusted for age, sex and center.
Supplementary Figure 1.
To examine our population structure, we extracted on common variants found in the sequencing of the 51 genes detailed in Supplementary Table 2. These variants were used against data from the 1000 genome project to examine the origin of our population. As clearly evident, our PD (pink dots), RBD (orange dots) and control (grey dots) populations segregated with the European ancestry (CEU, red dots, mostly covered by the dots of our population). The two major components were then used as covariates in the regression model.
Supplementary Figure 2.
The structure of the MAPT H2 haplotype, which includes eight coding variants, four of which are amino acid substitutions (p.P202L - rs63750417, p.D285N - rs62063786, p.R370W - rs17651549, p.S447P - rs10445337, p.P493P - rs1052551, p.T540T - rs62063845, p.A562A - rs1052553 and p.N590N - rs17652121). The intronic areas depicted here do not represent their real size. Of note, all four nonsynonymous variants are located in exons 4a and 6, which are probably expressed only in the peripheral nervous system. However, since the periphery, such as the gut nervous system, may be involved in early PD, a role for these variants in PD susceptibility cannot be excluded.
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