Pancreatitis is a complex, progressively destructive inflammatory disorder. Alcohol was long thought to be the primary causative agent, but genetic contributions have been of interest since the discovery that rare PRSS1, CFTR and SPINK1 variants were associated with pancreatitis risk. We now report two associations at genome-wide significance identified and replicated at PRSS1-PRSS2 (P < 1 × 10−12) and X-linked CLDN2 (P < 1 × 10−21) through a two-stage genome-wide study (stage 1: 676 cases and 4,507 controls; stage 2: 910 cases and 4,170 controls). The PRSS1 variant likely affects disease susceptibility by altering expression of the primary trypsinogen gene. The CLDN2 risk allele is associated with atypical localization of claudin-2 in pancreatic acinar cells. The homozygous (or hemizygous in males) CLDN2 genotype confers the greatest risk, and its alleles interact with alcohol consumption to amplify risk. These results could partially explain the high frequency of alcohol-related pancreatitis in men (male hemizygote frequency is 0.26, whereas female homozygote frequency is 0.07).
The exocrine pancreas is a simple digestive gland of only two primary cell types, each with a single function (Supplementary Fig. 1 and Supplementary Note). Recurrent acute pancreatic inflammation can but does not always progress to irreversible damage of the gland, including fibrosis, atrophy, pain and exocrine and endocrine insufficiency1,2,3, known as chronic pancreatitis. Different genetic and environmental factors produce the same clinical phenotype4.
We collected biological samples and phenotypic data from 1,000 individuals with recurrent acute pancreatitis and chronic pancreatitis as well as controls in the North American Pancreatitis Study 2 (NAPS2)5. The primary environmental risk factor identified was heavy alcohol drinking when symptoms of pancreatitis began, defined on the basis of the assessment of the study physician, termed here alcohol-related pancreatitis.
To further define genetic risk, we conducted a two-stage (discovery and replication) genome-wide association study (GWAS). The final data set for the stage 1 cohort included 676 chronic pancreatitis cases and 4,507 controls of European ancestry (Supplementary Figs. 2 and 3) genotyped at 625,739 SNPs (Table 1 and Supplementary Table 1). Associations at genome-wide significance (P < 5 × 10−8) were identified at two loci. The most highly associated SNP fell at Xq23.3, termed the CLDN2 locus, and the other was located at 7q34, termed the PRSS1-PRSS2 locus (Fig. 1, Table 2, Supplementary Figs. 4 and 5 and Supplementary Table 2). CLDN2 encodes the claudin-2 protein, PRSS1 encodes cationic trypsinogen, and PRSS2 encodes anionic trypsinogen.
The stage 2 cohort included 910 cases (331 chronic pancreatitis and 579 recurrent acute pancreatitis; Table 1 and Supplementary Table 1), also genotyped at 625,739 SNPs, and 4,170 controls, most of whom were genotyped previously on the Illumina HumanOmni1_Quad_V1-0_B chip. All subjects were of European ancestry, as determined by genetic analyses. Recurrent acute pancreatitis and chronic pancreatitis were modeled as having common susceptibilities, with chronic pancreatitis occurring over time in the presence of additional disease-modifying factors6. It is possible that this assumption reduces power relative to that of a study comprising solely chronic pancreatitis or recurrent acute pancreatitis cases. Our primary focus in stage 2 was on the PRSS1-PRSS2 and CLDN2 loci, although we also conducted a joint analysis7 of data from stages 1 and 2 to uncover any new risk loci. After controlling for ancestry, these data showed significant effects for the CLDN2 and PRSS1-PRSS2 loci (Fig. 1, Supplementary Figs. 6 and 7 and Supplementary Tables 2 and 3). The quality of the SNP genotypes supported the associations (Supplementary Fig. 8). The frequencies of the putative risk alleles at these two loci were 0.57 for the C allele at rs10273639 (PRSS1-PRSS2 locus), with the minor T allele reducing risk, and 0.26 for the T allele at rs12688220 (CLDN2 locus). No other locus showed association after accounting for SNP genotype quality (Supplementary Figs. 6–8).
PRSS1 gain-of-function mutations, such as the one encoding a p.Arg122His alteration, increase risk for recurrent acute pancreatitis and chronic pancreatitis8, as does increased copy number9,10, whereas rare loss-of-function mutations in PRSS2 are protective11. rs10273639 is in the 5′ promoter region of PRSS1. Because it is the only highly associated SNP in the locus, we validated its genotypes by independent TaqMan genotyping and also genotyped two SNPs in linkage disequilibrium with it (Supplementary Table 4)12,13. We screened PRSS1 for rare variants in 1,138 subjects, 418 with chronic pancreatitis, 350 with recurrent acute pancreatitis and 379 controls. Three known disease-associated variants (encoding p.Ala16Val, p.Asn29Ile and p.Arg122His alterations) were identified in 23 subjects (Supplementary Table 4). These gain-of-function variants occurred almost exclusively in cases (22 out of 23), and 2 of them (encoding p.Ala16Val and p.Arg122His alterations) are likely included on the C or risk haplotype of this locus (Supplementary Table 4). Nonetheless, with only 19 cases harboring alleles encoding p.Ala16Val and p.Arg122His alterations, these rare alleles cannot account for the association observed at this locus.
We genotyped 69 control pancreas tissue samples from 3 sources at rs10273639 and used cDNA to quantify expression of PRSS1 and control genes (Supplementary Table 5). In all three sets of quantitative PCR data, the slope relating the count of the C allele genotype to PRSS1 expression was positive. Taken together, the samples provided evidence that alleles at rs10273639 affect expression of PRSS1 (P = 0.01): expression levels were highest in subjects homozygous for the C allele at rs10273639, intermediate in heterozygotes and lowest in subjects homozygous for the T allele. On the basis of this evidence, we posit that reduced trypsinogen expression protects the pancreas from injury, as has been observed in mouse genetic models14.
CLDN2 is considered the primary candidate gene within the X-linked locus. Claudin-2 is an attractive candidate because it serves as a highly regulated tight junction protein, forming low-resistance, cation-selective ion and water channels between endothelial cells15,16, and is normally expressed at low levels in the tight junction between cells of the pancreatic ducts and in pancreatic islets17,18. The CLDN2 promoter includes a nuclear factor (NF)-κB–binding site19, and CLDN2 expression is enhanced in other cells under conditions associated with injury or stress20,21,22. Claudin-2 can also be expressed by acinar cells when stressed, as reported in porcine models of acute pancreatitis23. Other genes within the CLDN2 locus include MORC4, RIPPLY1 and TBC1D8B. MORC4 is expressed at low levels in most tissues, including the pancreas, with higher levels detected in the placenta and testes24. The MORC4 protein contains a CW four-cysteine zinc-finger motif, nuclear localization signal and nuclear matrix–binding domain, suggesting that it may be a transcription factor24, but its expression does not seem to correlate with pancreatitis (Supplementary Fig. 9). RIPPLY1 and TBC1D8B are not known to be expressed in the pancreas.
To our knowledge, genetic variation in CLDN2 has not previously been associated with disease in humans. We assessed DNA sequence variants around CLDN2 and RNA and protein expression for claudin-2 in control tissue classified by histology and genotype (Supplementary Fig. 10 and Supplementary Table 6). Evaluating 1000 Genomes Project data, we did not identify exonic variation that could explain the association signal. Using similar methods to those described for the analysis of PRSS1 expression, we determined that CLDN2 expression levels in control tissues did not correlate with genotype at the CLDN2 risk locus (P = 0.32). Protein blot analysis of protein extracted from the tissue with antibody to claudin-2 detected only one protein band of the appropriate size, the expression of which correlated with tissue inflammation, as determined by systematic grading of histology in adjacent tissue (Fig. 2a and Supplementary Fig. 10). Immunohistochemical staining with antibody to claudin-2 was verified in normal tissue (Fig. 2b), with kidney, duodenum and bile ducts serving as additional positive controls (data not shown). We assessed protein localization in 12 GWAS cases who underwent pancreatic surgery (6 with the high-risk genotype at CLDN2 and 6 without this genotype). Claudin-2 staining of cytoplasmic granules was markedly higher in both duct and acinar cells in chronic pancreatitis cases as compared with controls. (Fig. 2c–e). Only chronic pancreatitis cases with the high-risk CLDN2 genotype showed moderate-to-strong claudin-2 staining along the basolateral membrane of acinar cells (Fig. 2d,e and Supplementary Table 6). Claudin-2 was also expressed in macrophages, which could contribute to the pathological inflammatory process25 (Fig. 2c,f).
Most studies report excessive alcohol consumption as the major risk factor for adult-onset chronic pancreatitis26,27,28,29. However, only 3% of individuals who are alcoholics develop chronic pancreatitis30, suggesting a pancreas-specific risk factor. We compared genotypes on the basis of whether pancreatitis was alcohol related (yes/no)5,31. Setting control genotype counts as the baseline category against which case genotypes were compared, the jointly estimated odds ratios for cases with positive alcohol-related pancreatitis were greater for both rs10273639 (PRSS1-PRSS2 locus) and rs12688220 (CLDN2 locus) than those estimated for cases with pancreatitis not related to alcohol consumption (Table 3). Thus, the effects of both loci seemed to be amplified by alcohol consumption. In a case-only analysis, both loci seemed to interact with alcohol-related pancreatitis (Table 3), with the association for the CLDN2 locus being more prominent (P = 4 × 10−7).
We conclude that a common allele in the PRSS1-PRSS2 locus is associated with lower PRSS1 gene expression and that this effect is independent of the previously reported rare gain-of-function PRSS1 variants that increase susceptibility to both recurrent acute pancreatitis and chronic pancreatitis8. For this reason and because risk variants at the PRSS1-PRSS2 locus exert a similar effect in subjects with recurrent acute pancreatitis and those with chronic pancreatitis, it is reasonable to conjecture that variation at rs10273639 or variation at sites in linkage disequilibrium with it directly affects risk for chronic pancreatitis and recurrent acute pancreatitis through its impact on trypsinogen expression. Variation at the CLDN2 locus, however, is much more strongly associated with chronic pancreatitis than recurrent acute pancreatitis, suggesting that it probably acts as a disease modifier to accelerate the transition from recurrent acute pancreatitis to chronic pancreatitis. The significant association of the CLDN2 locus with alcohol-related disease suggests that the high-risk allele in the CLDN2 locus may modify risk through a non-trypsin–dependent process. Thus, we have characterized two common genetic risk modifiers for sporadic and alcohol-related chronic pancreatitis.
The Developmental Studies Hybridoma Bank at the University of Iowa, http://dshb.biology.uiowa.edu/Antibody-list.
Details of the recruitment of cases and controls are reported in Supplementary Table 1. All studies were conducted under institutional review board (IRB)-approved protocols. All cases were prospectively ascertained after signing IRB-approved informed consent forms.
Stage 1 samples.
All 758 stage 1 case samples were from the NAPS2 (ref. 5), were diagnosed with chronic pancreatitis and were characterized for alcohol-related pancreatitis (Table 1). Chronic pancreatitis occurs in less than 0.05% of the population, such that a convenience sample provides essentially identical power as a same-sized sample of controls selected for the absence of chronic pancreatitis32. For controls, we used genotypes from 4,076 cases and controls from ADGC and 493 NAPS2 subjects, all genotyped on the same platform as the chronic pancreatitis samples.
Stage 2 samples.
The stage 2 samples consisted of 343 chronic pancreatitis and 627 recurrent acute pancreatitis cases (Table 1 and Supplementary Table 1) as well as 4,191 control subjects (3,986 from NGRC and 205 NAPS2 controls).
All cases and NAPS2 controls were genotyped by the University of Pittsburgh Genomics and Proteomics Core Laboratories using the Illumina HumanOmniExpress BeadChip. Samples were processed and scanned using the manufacturer's recommended protocols with no modifications. ADGC samples33 were also genotyped using Illumina HumanOmniExpress BeadChips, whereas NGRC samples34 were genotyped on the Illumina Human1M-Duo DNA Analysis BeadChip.
Quality control for stage 1.
Quality control was performed for individuals and then SNPs to determine which samples and SNPs should not be included in the analysis. By assessing sex miscalls on the basis of X-chromosome genotypes using PLINK35, we excluded 7 chronic pancreatitis cases and 20 controls (10 NAPS2 and 10 ADGC). On the basis of a requirement for ≥ 95% complete genotypes per individual, 40 cases and 27 controls (20 NAPS2 and 7 ADGC) were excluded. By searching for duplicate or highly related samples using GCTA software36 (defined as those samples with a genetic relationship matrix score (GRM) of >0.4), we excluded 35 cases and 78 controls (2 NAPS2 and 76 ADGC). After applying these quality control filters, 676 cases and 4,507 controls remained for association analysis.
SNP quality control filtering was first performed on NAPS2 and ADGC samples separately. Ancestry was estimated using dacGem37, taking into consideration data from 9,700 SNPs that had genotype completion rates of ≥99.9% and minor allele frequencies (MAFs) of ≥0.05 that were separated by at least 500 kb. Analysis of genotypes from NAPS2 subjects identified one significant dimension of ancestry and clustered subjects into three groups (Supplementary Fig. 1). Groups A and B (shown in Supplementary Fig. 1) delineate 764 and 282 subjects, respectively, of European ancestry (self-identified); SNP quality control filtering by MAF and Hardy-Weinberg equilibrium (HWE) were performed on data from these subjects. Of 731,442 SNPs for which data were available, 633,790 passed quality control filters. SNPs were excluded on the basis of map location (3,165), call rate (11,977), MAF of <0.01 (77,300) and departure from HWE (P < 0.005) (5,219).
ADGC data were available for 3 subsets of 1,763, 1,110 and 1,266 subjects. In the first subset, data were available for 659,224 SNPs, whereas, in the second and third subsets, data were available for 730,525 SNPs. After quality control filtering as described for the chronic pancreatitis cohort, including harmonization with SNPs passing quality control in the chronic pancreatitis cohort, 604,059, 632,761 and 633,023 SNPs remained in each of the three subsets, respectively. After merging cohorts, 30 related subjects were excluded, leaving 4,046 ADGC subjects. Of the 633,615 unique SNPs in this ADGC cohort, quality control filtering excluded 5 for low MAF and 5,316 for departure from HWE, leaving 628,294 SNPs. Combining the ADGC and chronic pancreatitis cohorts and performing another round of quality control yielded 625,739 SNPs for analysis.
Quality control for stage 2.
Quality control for individuals in stage 2 was performed as described for stage 1. These individual-specific quality control filters excluded 60 cases, leaving 331 chronic pancreatitis and 579 recurrent acute pancreatitis cases for analysis; 14 controls were also excluded, leaving 4,177 controls for analysis. We analyzed all SNPs passing quality control in stage 1.
To control confounding due to ancestry, the first ten major eigenvectors from spectral decomposition were used as covariates in stage 1 and stage 2 analyses38, although only one was significant. We contrasted the genotypes of cases and controls via logistic regression and a log-additive (logit) model using PLINK35. Genotypes for any SNPs showing association at P < 5 × 10−7 were manually inspected for valid genotype clustering. SNPs showing poor quality clustering were excluded. We set the overall significance threshold to P = 5 × 10−8, with P = 5 × 10−7 being strongly suggestive of association7.
To determine whether alcohol status interacts with genetic variation to alter risk of pancreatitis, data from cases were fit to a general linear model in which the counts of alleles or genotypes predicted alcohol etiology (yes/no). The test statistic was obtained as a χ2 likelihood ratio. In these analyses and all other analyses other than genome-wide association analysis, we modeled the male genotypes as 0 and 2. In the genome-wide association analysis, PLINK sets the count of minor alleles in males as 0 and 1 and includes a sex effect, but the use of 0 and 2 for the encoding for males is a more powerful approach39,40.
DNA was obtained using standard methods41.
Pancreatic tissue processing.
Tissue was obtained from two sources (Pitt and Pancreatic Adenocarcinoma Gene-Environment Risk (PAGER) from the University of Pittsburgh and PSU from Pennsylvania State University) and processed in three batches: banked (Pitt) and prospectively collected (PAGER) surgical waste from uninvolved pancreas and normal pancreas specimens from the Gift of Life Program that were not used for transplantation (PSU). PAGER samples were snap frozen, placed in RNAlater solution (Ambion) and stored at −80 °C. PSU pancreas samples were also snap frozen and preserved in formalin or placed in RNAlater solution. RNA was isolated using TRIzol reagent (Invitrogen), and its quality was examined by running samples on 1% agarose gels stained with ethidium bromide. cDNA was transcribed using oligo(dT) primers and the Superscript II reverse transcriptase kit (Invitrogen).
Relative expression of PRSS1, PRSS2, CTRC and 18S RNA was determined by analyzing cDNA using TaqMan-based RT-PCR assays (Applied Biosystems). Raw absolute quantitation results were analyzed and converted to relative expression results by software packages SDS V2.3 and DataAssist V1.0 (Applied Biosystems). Assays were repeated in triplicate or quadruplicate. Three sets of samples were assessed, two from Pitt (n = 10 and 22) and one from PSU (n = 37). PSU results were normalized against the levels of 18S RNA, and Pitt results were normalized against the levels of CTRC. From each of these three data sets, mean gene expression per sample was regressed against allele count to obtain an estimated slope, standard error and Z score. We then calculated an overall Z score as a weighted average of the individual Z scores, with weights determined by sample size.
Claudin proteins expression was assessed by protein blot analysis with mouse antibodies to claudin-2 (32-5600, Invitrogen) and claudin-4 (32-9400, Invitrogen), and protein blot analysis with mouse antibody to α-tubulin (AA12.1, The Developmental Studies Hybridoma Bank at the University of Iowa) was used to control for loading. Immunohistochemistry was performed using the antibody to claudin-2 (1:1,000 dilution). Immunoflourescence was performed using the antibody to claudin-2 and goat antibody to human CD68 (sc-7082, Santa Cruz Biotechnology). The secondary antibodies for immunofluorescence were Cy3-conjugated goat antibody to mouse and Cy5-conjugated antibody to goat from Jackson ImmunoResearch.
SDS-PAGE and protein blotting.
Protein homogenates for protein blotting were obtained from snap-frozen tissue that was homogenized and sonicated in lysis buffer (50 mM Tris (pH 7.5), 150 mM NaCl, 0.4 mM EDTA, 1 mM EGTA, 1% sodium-deoxycholate, 1% Triton X-100, 0.1% sodium azide, 0.2 mM Na3VO4) and complete protease inhibitor mixture (Roche Diagnostics). Protein concentration was determined by bicinchoninic acid (BCA) method using a BCA protein assay kit from Thermo Scientific Pierce. Proteins were separated by 12% SDS-PAGE42 and transferred to polyvinylidene difluoride (PVDF) membranes43 for protein blotting44. Immunodetection of bound antibodies on PVDF membrane was performed using enhanced chemiluminescence (ECL) reagents (Amersham Biosciences). All procedures were carried out according to the manufacturer's instructions.
Standard automated immunohistochemistry was performed for claudin-2 on formalin-fixed, paraffin-embedded tissue sections that were 5 μm thick. After deparaffinization in xylene and rehydration in ethanol, antigen retrieval was performed using EDTA buffer, pH 8. Dako Autostainer Plus was used; slides were incubated for 30 min with the primary antibodies and then incubated with the secondary reagent (Mach 2 Mouse HRP Polymer from Biocare Medical) for 30 min. The chromogen was developed (Dako DAB+) for 10 min. Cytoplasmic, granular and membranous staining, predominantly in the lateral cell membranes, was graded on an intensity scale of 0–4 (0, no staining; 1, weak staining; 2, moderate staining; 3, strong staining). The staining intensity was very patchy from lobule to lobule in most samples.
Cryostat sections (5 μm thick) of pancreas were washed three times with PBS and then washed three times with 0.5% BSA in PBS. Sections were blocked with 2% BSA solution for 30 min. Slides were incubated for 1 h at room temperature with primary antibody for claudin-2 (1:100 dilution) and goat antibody to human CD68 in 0.5% BSA solution. Slides were washed three times with BSA solution and incubated for 1 h at 20 °C with Cyr5-conjugated secondary antibody to goat (1:500 dilution) and Cy3-conjugated goat secondary antibody to mouse (1:1,000 dilution) in BSA solution. Nuclei were stained with Hoechst's dye (bisbenzimide, 1 mg in 100 ml of water) for 30 s. After three rinses with PBS, coverslips were applied with Gelvatol mounting medium. Fluorescent images were captured with an Olympus Fluoview 1000 confocal microscope (software version 1.7a). The Cy5 signal (CD68) was pseudocolored green, such that colocalization with the red claudin-2 signal appeared yellow.
Technical support was provided by K. Stello, S. Das, D. Dwyer, A. Rowland, P.A. Blake, M. Ross, C. McGovern, L. Kish, H. Nawaz, S. Solomon, S. Boggiano, R. Ostroff, M. Goss and J. Timm. Data management was provided by L. Silfies and D. Protivnak. Clinical support was provided by S. Boggaino, M. Hendricks, B. Elinoff, L. McHenry, G. Lehman, J. Watkins, E. Fogel and L. Lazzell-Pannell. Additional samples were provided by F. Burton (deceased; St. Louis University School of Medicine); S. Lo (Cedars-Sinai Medical Center, University of California, Los Angeles); M.T. DeMeo (Rush University Medical Center); W.M. Steinberg (Washington Hospital Center); M.L. Kochman (University of Pennsylvania); B. Etemad (Ochsner Medical Center); and H. Zeh, A.J. Moser and K.K. Lee (University of Pittsburgh). This publication was made possible by grants R56DK061451 (D.C.W.), R01DK054709 (D.C.W.), T32DK063922 (D.C.W.), R01MH057881 (B.D. and K.R.), R01CA117926 (J.P.S.), R01DK077906 (D.C.W. and D.Y.), UL1RR024153 and UL1TR000005 from the US National Institutes of Health (NIH). Its contents are solely the responsibility of the authors and do not necessarily represent the official view of the NIH. This project used the University of Pittsburgh Genomics and Proteomics Core Laboratories (UL1RR024153, UL1RR024153 and UL1TR000005) and the University of Pittsburgh Cancer Institute (UPCI) Clinical Genomics Immunoproteomics and Sequencing Facility (NIH P30CA047904). J.L. was supported by Digestive Disease Training Program T32DK063922 (D.C.W.). N.O.Z. was supported by the American Gastroenterology Association John I Isenberg International Scholar Award. The Liverpool cohort was supported by the National Institute for Health Research (NIHR) Biomedical Research Unit award. Additional support was provided by the National Pancreas Foundation (D.C.W.), the Frieda G. and Saul F. Shapira BRCA-Associated Cancer Research Program (D.C.W.) and the Wayne Fusaro Pancreatic Cancer Research Fund (D.C.W.) and Gift of Life Foundation (J.P.S.).
Support for control cohort 1.
Alzheimer's Disease Genetics Consortium (ADGC): The NIH–National Institute on Aging (NIH-NIA) supported this work through the following grants: ADGC, U01AG032984 and RC2AG036528; National Alzheimer's Coordinating Center (NACC), U01AG016976; National Cell Repository for Alzheimer's Disease (NCRAD), U24AG021886; Banner Sun Health Research Institute, P30AG019610; Boston University, P30AG013846, U01AG10483, R01CA129769, R01MH080295, R01AG017173, R01AG025259 and R01AG33193; Columbia University, P50AG008702 and R37AG015473; Duke University, P30AG028377 and AG05128; Emory University, AG025688; Indiana University, P30AG10133; Johns Hopkins University, P50AG005146 and R01AG020688; Massachusetts General Hospital, P50AG005134; Mayo Clinic, P50AG016574; Mount Sinai School of Medicine, P50AG005138 and P01AG002219; New York University, P30AG08051, MO1RR00096 and UL1RR029893; Northwestern University, P30AG013854; Oregon Health & Science University, P30AG008017 and R01AG026916; Rush University, P30AG010161, R01AG019085, R01AG15819, R01AG17917 and R01AG30146; University of Alabama at Birmingham, P50AG016582 and UL1RR02777; University of Arizona, R01AG031581; University of California, Davis, P30AG010129; University of California, Irvine, P50AG016573, P50AG016575, P50AG016576 and P50AG016577; University of California, Los Angeles, P50AG016570; University of California, San Diego, P50AG005131; University of California, San Francisco, P50AG023501 and P01AG019724; University of Kentucky, P30AG028383 and AG05144; University of Michigan, P50AG008671; University of Pennsylvania, P30AG010124; University of Pittsburgh, P50AG005133 and AG030653; University of Southern California, P50AG005142; University of Texas Southwestern, P30AG012300; University of Miami, R01AG027944, AG010491, AG027944, AG021547 and AG019757; University of Washington, P50AG005136; Vanderbilt University, R01AG019085; and Washington University, P50AG005681 and P01AG03991. The Kathleen Price Bryan Brain Bank at the Duke University Medical Center is funded by National Institute of Neurological Disorders and Stroke (NINDS) grant NS39764 and National Institute of Mental Health (NIMH) grant MH60451 and by GlaxoSmithKline. We thank D.S. Snyder and M. Miller who are ex officio ADGC members.
Support for control group 2.
Control group 2 genotypes were obtained from the Genome-Wide Association Study of Parkinson Disease: Genes and Environment, database of Genotypes and Phenotypes (dbGaP) study phs000196.v2.p1. This NeuroGenetics Research Consortium (NGRC) is a gene-environment study of Parkinson's disease. The principal investigator is H. Payami (New York State Department of Health Wadsworth Center, Albany, New York, USA), and the co-investigators are J. Nutt (Oregon Health & Sciences University, Portland, Oregon, USA); C. Zabetian (University of Washington and Puget Sound Veterans Medical Center, Seattle, Washington, USA); S. Factor (Emory University, Atlanta, Georgia, USA); E. Molho (Albany Medical Center, Albany, New York, USA); and D. Higgins (Albany Medical Center and Albany Veterans Medical Center, Albany, New York, USA). Funding was provided by NIH grant R01NS36960. Genotyping was performed by the Genotyping Center at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Funding for genotyping was provided by NIH grant HHSN268200782096C. The NIH contract for the project is entitled 'High throughput genotyping for studying the genetic contributions to human disease'.
Support for the German cohort..
The German cohort was supported by the Alfried-Krupp-von-Bohlen-und-Hahlbach-Foundation (Graduate Schools of Tumour Biology and Free Radical Biology), the Deutsche Krebshilfe/Dr. Mildred-Scheel-Stiftung (109102), the Deutsche Forschungsgemeinschaft (DFG GRK840-E3/E4, MA 4115/1-2/3 and NI 1297/1-1), the Federal Ministry of Education and Research (BMBF GANI-MED 03152061A and BMBF 0314107) and the European Union (EU-FP-7; EPC-TM and EU-FP7-REGPOT-2010-1).
Supplementary Note, Supplementary Tables 1–6 and Supplementary Figures 1–10
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