Susceptibility Loci for Pigmentation and Melanoma in Relation to Parkinson’s disease

Abstract

Growing evidence suggests that Parkinson’s disease (PD) patients have a lower risk for most types of cancer except for melanoma, which has a modest positive association with PD. Pigmentation genes has been hypothesized to contribute to this association. We therefore examined whether genetic susceptibility loci for pigmentation or melanoma were associated with PD risk in two large independent datasets. In the Parkinson’s Genes and Environment (PAGE) Study, we examined 11 SNPs identified from previous GWAS studies of pigmentation or melanoma in relation to PD among 808 PD cases and 1,623 controls; further, we also examined the colors of hair, eye, or skin, and melanoma in relation to PD. In the International Parkinson’s Disease Genomic Consortium (IPDGC), we examined a broader selection of 360 pigmentation or melanoma GWAS SNPs in relation to PD among 5,333 PD cases and 12,019 controls. All participants were non-Hispanic Whites. As expected, in the PAGE study, most SNPs were associated with one or more pigmentation phenotypes. However, neither these SNPs nor pigmentation phenotypes were associated with PD risk after Bonferroni correction with the exception of rs4911414 at the ASIP gene (P=0.001). A total of 18 PD cases (2.2%) and 26 controls (1.6%) had a diagnosis of melanoma with an odds ratio of 1.3 (95% confidence interval: 0.7-2.4). In the IPDGC analysis, none of the 360 SNPs, including rs4911414, were associated with PD risk after adjusting for multiple comparisons. In conclusion, we did not find significant associations between GWAS SNPs of pigmentation or melanoma and the risk for PD.

1. Introduction

Growing evidence suggests that Parkinson’s disease (PD) patients have a lower risk of most types of cancer (Bajaj, et al., 2010). Melanoma is a notable exception in that the risk appears to be higher among PD patients and vice versa (Bertoni, et al., 2010, Ferreira, et al., 2010, Inzelberg and Israeli-Korn, 2009, Liu, et al., 2011). The explanation for this epidemiologic observation remains elusive, but shared genetic or environmental risk factors have been suspected. In particular, it has been hypothesized that pigmentation and genes related to pigmentation and melanoma may contribute to this link (Herrero Hernandez, 2009). We therefore examined susceptibility loci for pigmentation and melanoma in relation to PD risk in the Parkinson’s Genes and Environment (PAGE) study and in the International Parkinson’s disease Genomic Consortium (IPDGC).

2. Methods

The PAGE study was a nested case-control study within the NIH-AARP Diet and Health cohort (Gao, et al., 2011). The current analyses included 808 physician-confirmed PD cases and 1,623 controls that provided saliva samples for genotyping. All subjects are non-Hispanic Whites. Among them, 606 cases and 1,340 controls further provided information on the color of hair, eye, and skin. Further, melanoma cases in the cohort were identified along with cases with other cancers by probabilistic record linkage with state cancer registries.(Lin, et al., 2012). The IPDGC represents an international collaboration of genome-wide association studies (GWAS) to understand the genetic causes of PD with participants from the US, UK, Germany and France (Nalls, et al., 2011). The current analysis used data from the discovery phase of 5,333 cases and 12,019 controls (Nalls, et al., 2011). Details of IPDGC are provided in Supplementary table 1.

In the PAGE study, we successfully genotyped 11 SNPs which were associated with pigmentation phenotypes or the risk of melanoma in previous GWAS (Supplementary Table 1). The genotyping was performed by BioServe Biotechnologies, Ltd (Beltsville, MD), using Sequenom MassARRAY iPLEXTM platform with an average call rate of 95.1% (Supplementary Table 2). All participating cohorts of the IPDGC used Illumina platform for genotyping (Nalls, et al., 2011) and the Markov Chain based haplotyper (MACH; version 1.0.16) to impute genotypes for all participants of European ancestry with haplotypes derived from initial low coverage sequencing of 112 European ancestry samples in the 1000 Genomes Project (as of August, 2009). A total of 7,689,524 SNPs were either genotyped or imputed. In the IPDGC analysis, we included more pigmentation and melanoma susceptiblity SNPs with an updated search for all SNPs that were in high linkage disequilibrium (r² > 0.8) with reported GWAS loci of pigmentation phenotypes of melanoma via SNAP (http://www.broadinstitute.org/mpg/snap/ldsearch.php). A total of 483 SNPs were found and 360 were either genotyped or imputed in the IPDGC (Supplementary Table 3).

In PAGE, we first evaluated the relationships of candidate SNPs with pigmentation phenotypes using linear regression model or with melanoma using logistic regression model, adjusting for year of birth and sex. Pigmentation phenotypes were coded as ordinal variables as did in published studies (Han, et al., 2008). We then evaluated candidate SNPs or related pigmentation phenotypes and melanoma in relation to PD risk. Odds ratios (ORs) and 95% confidence intervals (CIs) were derived from multivariate logistic regression models, adjusting for year of birth, sex, caffeine intake, and smoking status. For the analysis in IPDGC, logit additive genetic effect was first estimated in each cohort and then meta-analyzed, adjusting for sex and the first two principal components of population structure. All statistical analyses were performed using Plink v1.07 and R software (version 2.11.1; The R Foundation for Statistical Computing).

All PAGE study participants provided written consent and the study protocol was approved by the Institutional Review Board of the National Institute of Environmental Health Sciences and the Special Studies Institutional Review Board of the National Cancer Institute. The discovery phase of IPDGC was approved by the institutional review boards of participating cohorts. The detailed Methods section is available in the online Supplementary data.

3. Results

Demographic characteristics of PD cases and controls in the PAGE study are shown in Table 1. As expected, PD patients were less likely to be smokers and drank less coffee as compared to controls.

Table 1.

Characteristics of participants of the Parkinson’s Genes and Environment Study

Variables		Case (%) (n=808)	Control (%) (n=1623)	OR (95%CI)*	P *
Year of Birth (mean± SD)		1932±5	1932±5	-	-
Sex
	Female	189 (23.4%)	346 (21.3%)	-	-
	Male	619 (76.6%)	1277 (78.7%)	-	-
Caffeine intake
≤ median (≤ 216.54 mg)		452 (55.9%)	764 (47.1%)	ref.
> median (> 216.54 mg)		356 (44.1%)	859 (52.9%)	0.72(0.61-0.85)	<0.001
Smoking status
	Never	373 (46.2%)	569 (35.1%)	ref.
	Ever	404 (50.0%)	946 (58.3%)	0.68(0.57-0.81)	<0.001
	Current	31 (3.8%)	108 (6.6%)	0.47(0.31-0.71)	<0.001

^*Adjusted for year of birth, sex, caffeine intake and smoking status as appropriate.

In the PAGE study, most of the selected SNPs from previous GWAS studies were associated with one or more of the pigmentation phenotypes in the directions that were expected, although some did not reach statistical significance (at P<0.05) (Table 2). For both hair color and eye color, rs12896399 at the SLC24A4 showed the strongest association (P=1.07×10⁻¹⁰ for hair color and 7.11×10⁻⁷ for eye color), and for skin color, rs258322 at the CDK10 showed the strongest association (P=1.24×10⁻⁷).

Table 2.

SNPs in relation to pigmentation and melanoma in the Parkinson’s Genes and Environment Study

CHR	Gene	SNP	Minor allele	MAF	Hair color (black to red)			Eye color (blue to black)			Skin color (light to dark)			Melanoma
					beta	s.e.	P	beta	s.e.	P	beta	s.e.	P	OR (95%CI)	P
6	IRF4	rs12203592	T	0.17	−0.26	0.04	1.67×10−10	−0.14	0.05	1.02×10−2	−0.1	0.02	1.51×10−5	2.49 (0.77-0.83)	1.55×10−1
11	TYR	rs1126809	A	0.27	0.07	0.03	4.52×10−2	−0.15	0.05	1.15×10−3	−0.09	0.02	1.22×10−5	1.22 (0.45-3.33)	7.47×10−1
11	TPCN2	rs35264875	T	0.17	0.05	0.04	2.08×10−1	−0.06	0.05	2.39×10−1	0.00	0.02	8.52×10−1	1.73 (0.58-5.22)	3.54×10−1
11	TPCN2	rs3829241	A	0.38	0.09	0.03	6.44×10−3	−0.09	0.04	3.86×10−2	−0.05	0.02	1.09×10−2	0.55 (0.18-1.69)	2.62×10−1
12	KITLG	rs12821256	C	0.09	0.10	0.05	7.28×10−2	0.08	0.07	2.76×10−1	−0.03	0.03	2.68×10−1	1.26 (0.29-5.23)	7.81×10−1
14	SLC24A4	rs12896399	T	0.43	0.2	0.03	1.07×10−10	−0.2	0.04	7.11×10−7	−0.05	0.02	6.53×10−3	0.56 (0.22-1.40)	1.86×10−1
16	MC1R	rs1805008	T	0.07	0.39	0.06	1.60×10−9	−0.08	0.08	3.34×10−1	−0.14	0.04	1.11×10−4	3.79 (0.57-25.06)	2.20×10−1
16	CDK10	rs258322	T	0.10	0.34	0.05	2.00×10−10	0.01	0.07	8.32×10−1	−0.16	0.03	1.24×10−7	1.35 (0.31-5.95)	7.41×10−1
20	ASIP	rs1015362	A	0.28	−0.06	0.03	7.59×10−2	0.00	0.05	9.85×10−1	0.01	0.02	7.96×10−1	4.74 (1.24-18.2)	2.20×10−2
20	ASIP	rs4911414	T	0.33	0.01	0.03	7.19×10−1	−0.05	0.04	2.75×10−1	−0.04	0.02	4.22×10−2	1.97 (0.75-5.18)	1.90×10−1
20	PIGU	rs910873	A	0.07	0.18	0.06	2.53×10−3	−0.06	0.08	4.17×10−1	−0.13	0.03	1.90×10−4	0.55 (0.09-3.35)	5.12×10−1

Adjusted for year of birth and sex.

In the PAGE study, we identified 18 PD cases (2.2%) and 26 (1.6%) controls with first primary melanoma. Several SNPs showed ORs that were consistent with a modest to strong association with melanoma. For example, the minor allele of rs4911414 at the ASIP had an OR of 4.74 (P=0.022), followed by rs1805008 at the MC1R (OR=3.79, P=0.22), and rs12203592 at the IRF4 (OR=2.49, P=0.16). However, with the exception of rs4911414 at the ASIP, none of these SNPs were statistically associated with melanoma due to small sample size.

In the PAGE study, neither pigmentation phenotypes nor melanoma were statistically associated with PD risk. A modest association of melanoma and PD was suggested with an OR of 1.32 (95%CI: 0.71-2.44) that was consistent with the literature; however, this association did not reach statistical significance probably due to the few melanoma cases in the analysis. Further, with the exception of the rs4911414 at the ASIP (P=0.001), none of the SNPs for pigmentation phenotypes or melanoma was associated with PD risk after correcting for multiple comparison (Table 3). However, this SNP was not associated with PD risk in the larger dataset of IPDGC (P=0.43), and none of the other 359 SNPs selected for analysis in the IPDGC dataset showed statistical significance with PD (Table 4 and supplementary Table 3).

Table 3.

Pigmentation / melanoma in relation to Parkinson’s Disease risk in the Parkinson’s Genes and Environment Study

variables		Case	Control	Adjusted OR (95%CI)*	Adjusted P*	P for trend*
Hair color						0.202
	Black	60	156	ref.
	Brown	424	861	1.25 (0.90-1.73)	0.179
	Auburn	19	38	1.28 (0.68-2.44)	0.442
	Blonde	79	236	0.87 (0.58-1.29)	0.475
	Red	14	27	1.36 (0.66-2.79)	0.406
Eye color						0.759
	Blue/Gray	255	585	ref.
	Green	60	124	1.08 (0.77-1.53)	0.654
	Light brown/Hazel	144	316	1.05 (0.82-1.35)	0.691
	Brown/Black	131	292	1.03 (0.80-1.33)	0.819
Skin color						0.088
	Light	244	580	ref.
	Medium	340	704	1.22 (0.99-1.49)	0.057
	Dark	16	36	1.11 (0.60-2.06)	0.736
Melanoma						0.276
	No	790	1597	Ref
	Yes	18	26	1.32 (0.71-2.44)	0.375

^*Adjusted for year of birth, sex, smoking status and caffeine intake.

Table 4.

SNPs in relation to Parkinson’s disease in the Parkinson’s Genes and Environment Study and in the International PD Genomic Consortium

			Parkinson’s Gene Environment Study						International PD Genomic Consortium **
CHR	Gene	SNP	Minor allele	MAF in controls	Case	Control	Adjusted OR (95%CI)*	P *	Meta OR (95%CI)	meta_P
6	IRF4	rs12203592	T	0.16	25/222/539	54/404/1107	1.05 (0.89-1.23)	0.555	0.88 (0.80-0.96)	0.004
11	TYR	rs1126809	A	0.27	62/282/399	123/572/799	1.01 (0.88-1.16)	0.910	1.01 (0.95-1.07)	0.816
11	TPCN2	rs35264875	T	0.17	21/236/526	47/438/1070	1.04 (0.88-1.22)	0.640	0.98 (0.91-1.05)	0.586
11	TPCN2	rs3829241	A	0.38	106/363/302	221/716/601	0.99 (0.87-1.12)	0.825	0.99 (0.94-1.04)	0.615
12	KITLG	rs12821256	C	0.09	10/125/647	22/250/1287	1.00 (0.82-1.23)	0.982	1.02 (0.94-1.11)	0.666
14	SLC24A4	rs12896399	T	0.43	154/368/248	283/746/499	1.04 (0.92-1.17)	0.576	1.00 (0.95-1.05)	0.926
16	MC1R	rs1805008	T	0.06	7/99/671	6/188/1356	1.14 (0.89-1.44)	0.295	0.98 (0.89-1.07)	0.624
16	CDK10	rs258322	T	0.09	8/134/633	22/247/1264	1.03 (0.84-1.27)	0.764	1.10 (1.01-1.20)	0.030
20	ASIP	rs1015362	A	0.29	61/265/432	137/618/789	0.84 (0.73-0.96)	0.011	1.04 (0.98-1.10)	0.195
20	ASIP	rs4911414	T	0.35	86/302/395	190/700/660	0.80 (0.70-0.91)	0.001	1.02 (0.97-1.08)	0.374
20	PIGU	rs910873	A	0.08	5/87/653	8/221/1305	0.82 (0.64-1.05)	0.120	0.90 (0.82-0.99)	0.039

^*Adjusted for year of birth, sex, smoking status and caffeine intake.

^**Other SNPs from the IPDGC were not statistically significantly associated with PD risk.

4. Discussion

In this large and comprehensive analysis, we confirmed the associations of these susceptibility loci with pigmentation phenotypes and/or melanoma; however, we did not identify any association between these SNPs and PD risk. While the statistical power in the PAGE study was limited, the IPDGC had 5,333 cases and 12,019 controls and thus adequate statistical power.

Human pigmentation phenotypes such as the colors of hair, eye, and skin, are polygenic quantitative traits with high heritability, and the link between certain pigmentation phenotypes and susceptibility genes and melanoma have been well-established (Mitra, et al., 2012). Recent GWAS studies (Bishop, et al., 2009, Gudbjartsson, et al., 2008, Han, et al., 2008, Sulem, et al., 2008, Sulem, et al., 2007) identified approximately a dozen susceptibility loci for pigmentation, some shared by phenotypes and others are distinctive. Some of these, such as MC1R and ASIP genes, also confer a higher risk for melanoma. In the PAGE study, we replicated most reported associations between these SNPs and pigmentation phenotypes. The analysis on melanoma was obviously limited by sample size, but the directions and magnitudes of associations with these SNPs were mostly comparable to published reports (Bishop, et al., 2009, Sulem, et al., 2008). Also consistent with previous reports, we found a modest positive association between melanoma and PD (Liu, et al., 2011), but the statistical test was not significant, possibly due to the few melanoma cases in the study.

To the best of our knowledge, only one previous study has directly examined the hypothesis that pigmentation genes may underlie the association between PD and melanoma. The study included 298 PD cases and focused on one SNP (MC1R rs1805007) that encodes red hair (Gao, et al., 2009b). The study reported that compared with the wild type, the homozygous mutant genotype was associated with three-fold higher risk for PD. Correspondingly, participants with red hair were four times more likely to have PD than those with black hair. On the other hand, Meng et al. examined PD susceptibility loci identified from GWAS studies (e.g. SNCA and MAPT) in relation to melanoma in two large GWAS datasets and reported null findings. Three other studies took an indirect approach by examining whether relatives of melanoma patients had a higher risk for PD than individuals without a family history of melanoma or the converse. Two reported positive associations (Gao, et al., 2009a, Kareus, et al., 2012) but the other did not (Olsen, et al., 2011).

The current study directly and comprehensively evaluated multiple pigmentation phenotypes, melanoma, and related SNPs in relation to the risk for PD in two independent datasets. Compared with the previous study (Gao, et al., 2009b), we had a much larger sample size and included many more SNPs and pigmentation phenotypes. In the PAGE study, neither these SNPs nor the pigmentation phenotypes were associated with PD risk. More importantly, the results were also null in a broader analysis of 360 SNPs using the very large dataset of IPDGC. In the IPDGC, rs1805007 at MC1R, the SNP that showed significant association with PD in the previous study (Gao, et al., 2009b) had an OR of 1.06 (95%CI: 0.94-1.19, P=0.37). Our analysis, however, focused on SNPs identified from GWAS and did not include other genetic variations such as mutations in high-penetrance genes (e.g. CDKN2 and CDK4). Thus, we cannot exclude the possibility that other genes may explain the association between melanoma and PD.

Taken together, evidence to date remains elusive on what may be responsible for the link between melanoma and PD. The explanations are likely to be multifactorial and other possibilities, such as environmental factors, should also be considered.

Disclosure statement The authors have no conflicts of interest.

International Parkinson Disease Genomics Consortium members

Mike A Nalls (Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA), Vincent Plagnol (UCL Genetics Institute, London, UK), Dena G Hernandez (Laboratory of Neurogenetics, National Institute on Aging; and Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK), Manu Sharma (Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, and DZNE, German Center for Neurodegenerative Diseases, Tübingen, Germany), Una-Marie Sheerin (Department of Molecular Neuroscience, UCL Institute of Neurology), Mohamad Saad (INSERM U563, CPTP, Toulouse, France; and Paul Sabatier University, Toulouse, France), Javier Simón-Sánchez (Department of Clinical Genetics, Section of Medical Genomics, VU University Medical Centre, Amsterdam, Netherlands), Claudia Schulte (Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research), Suzanne Lesage (INSERM, UMR_S975 [ formerly UMR_S679], Paris, France; Université Pierre et Marie Curie-Paris, Centre de Recherche de l’Institut du Cerveau et de la Moelle épinière, Paris, France; and CNRS, Paris, France), Sigurlaug Sveinbjörnsdóttir (Department of Neurology, Landspítali University Hospital, Reykjavík, Iceland; Department of Neurology, MEHT Broomfield Hospital, Chelmsford, Essex, UK; and Queen Mary College, University of London, London, UK), Sampath Arepalli (Laboratory of Neurogenetics, National Institute on Aging), Roger Barker (Department of Neurology, Addenbrooke’s Hospital, University of Cambridge, Cambridge, UK), Yoav Ben-Shlomo (School of Social and Community Medicine, University of Bristol), Henk W Berendse (Department of Neurology and Alzheimer Center, VU University Medical Center), Daniela Berg (Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research), Kailash Bhatia (Department of Motor Neuroscience, UCL Institute of Neurology), Rob M A de Bie (Department of Neurology, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands), Alessandro Biffi (Center for Human Genetic Research and Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA), Bas Bloem (Department of Neurology, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands), Zoltan Bochdanovits (Department of Clinical Genetics, Section of Medical Genomics, VU University Medical Centre), Michael Bonin (Department of Medical Genetics, Institute of Human Genetics, University of Tübingen, Tübingen, Germany), Jose M Bras (Department of Molecular Neuroscience, UCL Institute of Neurology), Kathrin Brockmann (Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research), Janet Brooks (Laboratory of Neurogenetics, National Institute on Aging), David J Burn (Newcastle University Clinical Ageing Research Unit, Campus for Ageing and Vitality, Newcastle upon Tyne, UK), Gavin Charlesworth (Department of Molecular Neuroscience, UCL Institute of Neurology), Honglei Chen (Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, NC, USA), Patrick F Chinnery (Neurology M4104, The Medical School, Framlington Place, Newcastle upon Tyne, UK), Sean Chong (Laboratory of Neurogenetics, National Institute on Aging), Carl E Clarke (School of Clinical and Experimental Medicine, University of Birmingham, Birmingham, UK; and Department of Neurology, City Hospital, Sandwell and West Birmingham Hospitals NHS Trust, Birmingham, UK), Mark R Cookson (Laboratory of Neurogenetics, National Institute on Aging), J Mark Cooper (Department of Clinical Neurosciences, UCL Institute of Neurology), Jean Christophe Corvol (INSERM, UMR_S975; Université Pierre et Marie Curie-Paris; CNRS; and INSERM CIC-9503, Hôpital Pitié-Salpêtrière, Paris, France), Carl Counsell (University of Aberdeen, Division of Applied Health Sciences, Population Health Section, Aberdeen, UK), Philippe Damier (CHU Nantes, CIC0004, Service de Neurologie, Nantes, France), Jean-François Dartigues (INSERM U897, Université Victor Segalen, Bordeaux, France), Panos Deloukas (Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK), Günther Deuschl (Klinik für Neurologie, Universitätsklinikum Schleswig-Holstein, Campus Kiel, Christian-Albrechts-Universität Kiel, Kiel, Germany), David T Dexter (Parkinson’s Disease Research Group, Faculty of Medicine, Imperial College London, London, UK), Karin D van Dijk (Department of Neurology and Alzheimer Center, VU University Medical Center), Allissa Dillman (Laboratory of Neurogenetics, National Institute on Aging), Jing Dong (Epidemiology Branch, National Institute of Environmental Health Sciences), Frank Durif (Service de Neurologie, Hôpital Gabriel Montpied, Clermont-Ferrand, France), Alexandra Dürr (INSERM, UMR_S975; Université Pierre et Marie Curie-Paris; CNRS; and AP-HP, Pitié-Salpêtrière Hospital), Sarah Edkins (Wellcome Trust Sanger Institute), Jonathan R Evans (Cambridge Centre for Brain Repair, Cambridge, UK), Thomas Foltynie (UCL Institute of Neurology), Michelle Gardner (Department of Molecular Neuroscience, UCL Institute of Neurology), J Raphael Gibbs (Laboratory of Neurogenetics, National Institute on Aging; and Department of Molecular Neuroscience, UCL Institute of Neurology), Alison Goate (Department of Psychiatry, Department of Neurology, Washington University School of Medicine, MI, USA), Emma Gray (Wellcome Trust Sanger Institute), Rita Guerreiro (Department of Molecular Neuroscience, UCL Institute of Neurology), Ómar Gústafsson (deCODE genetics and Department of Psychiatry, Oslo University Hospital, N-0407 Oslo, Norway), Clare Harris (University of Aberdeen), Jacobus J van Hilten (Department of Neurology, Leiden University Medical Center, Leiden, Netherlands), Albert Hofman (Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands), Albert Hollenbeck (AARP, Washington DC, USA), Janice Holton (Queen Square Brain Bank for Neurological Disorders, UCL Institute of Neurology), Michele Hu (Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK), Xuemei Huang (Departments of Neurology, Radiology, Neurosurgery, Pharmacology, Kinesiology, and Bioengineering, Pennsylvania State University– Milton S Hershey Medical Center, Hershey, PA, USA), Heiko Huber (Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research), Gavin Hudson (Neurology M4104, The Medical School, Newcastle upon Tyne, UK), Sarah E Hunt (Wellcome Trust Sanger Institute), Johanna Huttenlocher (deCODE genetics), Thomas Illig (Institute of Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany), Pálmi V Jónsson (Department of Geriatrics, Landspítali University Hospital, Reykjavík, Iceland), Jean-Charles Lambert (INSERM U744, Lille, France; and Institut Pasteur de Lille, Université de Lille Nord, Lille, France), Cordelia Langford (Cambridge Centre for Brain Repair), Andrew Lees (Queen Square Brain Bank for Neurological Disorders), Peter Lichtner (Institute of Human Genetics, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany), Patricia Limousin (Institute of Neurology, Sobell Department, Unit of Functional Neurosurgery, London, UK), Grisel Lopez (Section on Molecular Neurogenetics, Medical Genetics Branch, NHGRI, National Institutes of Health), Delia Lorenz (Klinik für Neurologie, Universitätsklinikum Schleswig-Holstein), Alisdair McNeill (Department of Clinical Neurosciences, UCL Institute of Neurology), Catriona Moorby (School of Clinical and Experimental Medicine, University of Birmingham), Matthew Moore (Laboratory of Neurogenetics, National Institute on Aging), Huw R Morris (MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, UK), Karen E Morrison (School of Clinical and Experimental Medicine, University of Birmingham; and Neurosciences Department, Queen Elizabeth Hospital, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK), Ese Mudanohwo (Neurogenetics Unit, UCL Institute of Neurology and National Hospital for Neurology and Neurosurgery), Sean S O’Sullivan (Queen Square Brain Bank for Neurological Disorders), Justin Pearson (MRC Centre for Neuropsychiatric Genetics and Genomics), Joel S Perlmutter (Department of Neurology, Radiology, and Neurobiology at Washington University, St Louis), Hjörvar Pétursson (deCODE genetics; and Department of Medical Genetics, Institute of Human Genetics, University of Tübingen), Pierre Pollak (Service de Neurologie, CHU de Grenoble, Grenoble, France), Bart Post (Department of Neurology, Radboud University Nijmegen Medical Centre), Simon Potter (Wellcome Trust Sanger Institute), Bernard Ravina (Translational Neurology, Biogen Idec, MA, USA), Tamas Revesz (Queen Square Brain Bank for Neurological Disorders), Olaf Riess (Department of Medical Genetics, Institute of Human Genetics, University of Tübingen), Fernando Rivadeneira (Departments of Epidemiology and Internal Medicine, Erasmus University Medical Center), Patrizia Rizzu (Department of Clinical Genetics, Section of Medical Genomics, VU University Medical Centre), Mina Ryten (Department of Molecular Neuroscience, UCL Institute of Neurology), Stephen Sawcer (University of Cambridge, Department of Clinical Neurosciences, Addenbrooke’s hospital, Cambridge, UK), Anthony Schapira (Department of Clinical Neurosciences, UCL Institute of Neurology), Hans Scheffer (Department of Human Genetics, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands), Karen Shaw (Queen Square Brain Bank for Neurological Disorders), Ira Shoulson (Department of Neurology, University of Rochester, Rochester, NY, USA), Ellen Sidransky (Section on Molecular Neurogenetics, Medical Genetics Branch, NHGRI), Colin Smith (Department of Pathology, University of Edinburgh, Edinburgh, UK), Chris C A Spencer (Wellcome Trust Centre for Human Genetics, Oxford, UK), Hreinn Stefánsson (deCODE genetics), Stacy Steinberg (deCODE genetics), Joanna D Stockton (School of Clinical and Experimental Medicine), Amy Strange (Wellcome Trust Centre for Human Genetics), Kevin Talbot (University of Oxford, Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK), Carlie M Tanner (Clinical Research Department, The Parkinson’s Institute and Clinical Center, Sunnyvale, CA, USA), Avazeh Tashakkori-Ghanbaria (Wellcome Trust Sanger Institute), François Tison (Service de Neurologie, Hôpital Haut-Lévêque, Pessac, France), Daniah Trabzuni (Department of Molecular Neuroscience, UCL Institute of Neurology), Bryan J Traynor (Laboratory of Neurogenetics, National Institute on Aging), André G Uitterlinden (Departments of Epidemiology and Internal Medicine, Erasmus University Medical Center), Daan Velseboer (Department of Neurology, Academic Medical Center), Marie Vidailhet (INSERM, UMR_S975, Université Pierre et Marie Curie-Paris, CNRS, UMR 7225), Robert Walker (Department of Pathology, University of Edinburgh), Bart van de Warrenburg (Department of Neurology, Radboud University Nijmegen Medical Centre), Mirdhu Wickremaratchi (Department of Neurology, Cardiff University, Cardiff, UK), Nigel Williams (MRC Centre for Neuropsychiatric Genetics and Genomics), Caroline H Williams-Gray (Department of Neurology, Addenbrooke’s Hospital), Sophie Winder-Rhodes (Department of Psychiatry and Medical Research Council and Wellcome Trust Behavioural and Clinical Neurosciences Institute, University of Cambridge), Kári Stefánsson (deCODE genetics), Maria Martinez (INSERM U563; and Paul Sabatier University), Nicholas W Wood (UCL Genetics Institute; and Department of Molecular Neuroscience, UCL Institute of Neurology), John Hardy (Department of Molecular Neuroscience, UCL Institute of Neurology), Peter Heutink (DZNE, German Center for Neurodegenerative Diseases), Alexis Brice (INSERM, UMR_S975, Université Pierre et Marie Curie-Paris, CNRS, UMR 7225, AP-HP, Pitié-Salpêtrière Hospital), Thomas Gasser (Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, and DZNE, German Center for Neurodegenerative Diseases), Andrew B Singleton (Laboratory of Neurogenetics, National Institute on Aging).

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