Identification of Genetic Factors that Modify Clinical Onset of ...

Article

Identification of Genetic Factors that Modify Clinical Onset of Huntington’s Disease Graphical Abstract

Authors Genetic Modifiers of Huntington’s Disease (GeM-HD) Consortium

Correspondence [email protected]

In Brief The identification of gene loci that delay or hasten Huntington’s disease onset demonstrates that the disease is modifiable prior to clinical diagnosis and offers a genetic route to targets for treatment prior to disease onset.

Highlights d

GWA signals reveal loci that modify the age at onset of Huntington’s disease

d

Effects at the chr15 locus hasten or delay onset by 6 or 1.4 years, respectively

d

A single effect at the chr8 locus hastens onset by 1.6 years

d

MLH1 association & pathway analysis implicate DNA handling in disease modification

Genetic Modifiers of Huntington’s Disease (GeM-HD) Consortium, 2015, Cell 162, 516–526 July 30, 2015 ª2015 Elsevier Inc. http://dx.doi.org/10.1016/j.cell.2015.07.003

Article Identification of Genetic Factors that Modify Clinical Onset of Huntington’s Disease Genetic Modifiers of Huntington’s Disease (GeM-HD) Consortium* *Correspondence: [email protected] http://dx.doi.org/10.1016/j.cell.2015.07.003

SUMMARY

As a Mendelian neurodegenerative disorder, the genetic risk of Huntington’s disease (HD) is conferred entirely by an HTT CAG repeat expansion whose length is the primary determinant of the rate of pathogenesis leading to disease onset. To investigate the pathogenic process that precedes disease, we used genome-wide association (GWA) analysis to identify loci harboring genetic variations that alter the age at neurological onset of HD. A chromosome 15 locus displays two independent effects that accelerate or delay onset by 6.1 years and 1.4 years, respectively, whereas a chromosome 8 locus hastens onset by 1.6 years. Association at MLH1 and pathway analysis of the full GWA results support a role for DNA handling and repair mechanisms in altering the course of HD. Our findings demonstrate that HD disease modification in humans occurs in nature and offer a genetic route to identifying in-human validated therapeutic targets in this and other Mendelian disorders. INTRODUCTION For the past three decades, a major goal of genetic analysis in humans has been to understand drivers of disease pathogenesis with the hope that these would implicate targets for developing therapeutic interventions. Initially, the primary approaches were linkage analysis and local association, often using multiallelic simple sequence repeat markers, which enabled the identification of a wide range of causative Mendelian mutations, including that underlying Huntington’s disease (HD) (The Huntington’s Disease Collaborative Research Group, 1993). For the past decade, genome-wide association (GWA) analysis with SNPs has extended the power of human genetic studies to complex diseases by identifying a multitude of contributing risk factors, usually of modest or weak effect (Manolio et al., 2009). In this report, aided by visionary HD community efforts to collect phenotypes and biosamples from large numbers of subjects with this disorder (Dorsey, 2012; Li et al., 2003; Orth et al., 2010; Paulsen et al., 2008), we apply GWA not to identify risk factors for disease but to discover genome-wide significant quantitative modifiers of a Mendelian disorder. In HD, a CAG trinucleotide expansion mutation in HTT, the gene encoding the large huntingtin protein, causes a progressive 516 Cell 162, 516–526, July 30, 2015 ª2015 Elsevier Inc.

movement disorder with dementia and behavioral abnormalities (Ross et al., 2014). Unequivocal clinical signs of HD typically emerge in mid-life, but juvenile onset and elderly onset cases are seen. Diagnosis is based upon the presence of characteristic motor signs, but the disorder includes intellectual decline and psychiatric disturbances, with death ensuing a median of 18 years after onset. The expanded CAG tract is the trigger for HD pathogenesis, and its length is the primary determinant of the rate of the pathogenic process that leads to the onset of diagnostic motor signs (referred to here for simplicity as ‘‘motor onset,’’ although more subtle signs may be present before clinical diagnosis) (Lee et al., 2012b). For individuals with 40 or more CAG repeats, the expansion is necessary and sufficient to cause HD, accounting for essentially all of the life-time risk of developing the disorder. Although symptomatic treatment can improve quality of life, there is no disease-modifying intervention to prevent the onset or delay the progression of HD. Because targets validated to impact on the disease process in humans have been lacking for traditional small-molecule approaches to drug development, a current focus for developing an effective disease-modifying therapy is the exploration of cutting-edge nucleic acid manipulation to prevent expression of mutant huntingtin (Aronin and DiFiglia, 2014). However, such strategies remain unproven in humans and pose numerous hurdles, including achieving efficient delivery and avoiding the potential negative effects of reducing normal huntingtin function. Thus, an effective route for identification of in-human validated therapeutic targets for traditional drug development is also needed. Here, we postulated that the presence of the expanded CAG in an individual provides a genetically sensitized background on which to search not for risk alleles but for genetic modifiers of the disease process, which may be common in the population but not have detectable effects in the absence of the HD mutation. Consequently, we applied a GWA strategy to quantitative variations in the disease phenotype in an unbiased search for naturally occurring genetic variations associated with modification of HD pathogenesis prior to emergence of clinical disease. Our findings localize several genome-wide significant genetic modifiers of HD age at onset and already suggest at least one biochemical process that alters HD pathogenesis in humans and can be specifically targeted for traditional drug development. The approach of separating disease risk and disease modification in a Mendelian disorder, merged with the power of modern genetic techniques, is widely applicable and has the potential to implicate new therapeutic pathways in human diseases that are individually not common but that taken together constitute a substantial disease burden.

Definition of the Phenotype for Association Analysis Within a year after the identification of the HD mutation, the inverse relationship between CAG length and age at diagnostic motor onset, which lays the foundation for a genetics-driven approach to understanding HD, was recognized (Gusella and MacDonald, 2006). This relationship establishes that the size of the mutant repeat is the primary determinant of the rate of pathogenesis leading to the emergence of clinical signs of disease (Lee et al., 2012b). The length of the expanded CAG repeat explains much, but not all, of the variation in age at motor onset. We and others have reported that the remaining variance has a large heritable component, implicating the actions of other genetic variations in modifying HD pathogenesis and suggesting that the difference between predicted and observed age of onset could be used in genetic studies to identify modifiers (Djousse´ et al., 2003; Wexler et al., 2004). Haplotype analysis of HTT in HD subjects indicates that common genetic variation at the locus is not a major source of disease modification (Lee et al., 2012a), and the length of the normal CAG repeat in heterozygotes shows no statistically significant modifier influence, either alone or in interaction with the expanded allele (Lee et al., 2012b). Indeed, there is also no effect of a second expanded CAG allele on age at onset, indicating that HD pathogenesis is not HTT dosage dependent but rather reflects the completely dominant effects of a single mutant allele. These stringent analyses generated a robust statistical phenotype model, based upon subjects with 40–53 CAG repeats (Figure S1), which was used to calculate the influence of the CAG repeat on log-transformed age at onset of motor signs of HD subjects in the GWA study (GWAS), thereby generating a residual value for each subject. Residual values from the regression model were transformed back into natural scale values as a phenotype for quantitative association analysis to search the genome for genetic variation that influences age at motor onset. The distribution of residuals was similar to a theoretical normal distribution. This ‘‘residual age at motor onset’’ used as the GWA phenotype thus represents the difference in years between observed age at onset and that expected based upon the individual’s CAG repeat size. We analyzed individuals with 40–55 repeats; however, restricting analysis to individuals with 40–53 repeats did not materially alter our results. Initial Genome-wide Association Studies Over almost three decades of investigating HD, the Massachusetts HD Center Without Walls (MaHDC) accumulated a large collection of DNA samples from HD subjects, including collaborations with the HSG PHAROS (Huntington Study Group PHAROS Investigators, 2006), COHORT (Dorsey, 2012), TREND-HD (Huntington Study Group TREND-HD Investigators, 2008), and PREDICT-HD (Paulsen et al., 2008) studies, and from families for linkage and other genetic studies, including a sib-pair linkage scan for modifiers of HD onset with the HDMAPS collaboration (Li et al., 2003). This collection formed the basis for a collaborative effort that led to generation of two sequential GWA datasets. For the initial dataset (GWA1), 1,089 HD subjects were genotyped with the Affymetrix 6.0 array at the Broad Institute of MIT and Harvard. Data cleaning was carried out using standard quality-control criteria (e.g., SNP call rate > 95%, minor allele frequency [MAF] > 1%, Hardy-Weinberg

equilibrium p value > 1 3 10
6, sample call rate > 95%). After quality-control analysis, multidimensional scaling analysis revealed 977 unique subjects of European ancestry with CAG repeat lengths in the range 40–55. Analysis of GWA1 (after QC: 700,000 typed and 8 million 1000 Genomes-imputed SNPs with MAF > 1%) did not reveal any genome-wide significant signals for association with the phenotype of ‘‘residual of age at motor onset’’ in a linear mixed model with covariates including ancestry characteristics and gender (see Experimental Procedures for details). GWA1 provided the basis for building SNP haplotypes of HTT that revealed that 50% of European HD subjects share a haplotype indicative of a common ancestor, but the rest are consistent with mutation on multiple other chromosome backbones contributing to HD (Lee et al., 2012a). No effect of HTT haplotype on the age at onset phenotype was detected, permitting all HD subjects to be grouped for our GWA analyses. In a second phase of genotyping (GWA2), additional subjects from the MaHDC collection were combined with subjects from the PREDICT-HD natural history study. GWA2 involved 2,874 HD subjects genotyped using the Illumina Omni2.5 array at the Center for Inherited Disease Research (CIDR). Age at onset was known for only a subset of these subjects, mainly those from the MaHDC, as PREDICT-HD enrolled subjects prior to manifestations of diagnostic clinical signs. Data quality-control analysis was similar to GWA1 and yielded 974 unique individuals of European ancestry suitable for our association analysis. Full genotyping data and associated phenotypes for GWA2 have already been deposited into dbGAP, including an extensive and detailed description of the data cleaning steps. Like GWA1, GWA2 (after QC: 1.5 million genotyped and 8.6 million 1000 Genomes-imputed SNPs with MAF > 1%) failed to identify a genome-wide significant signal for association to residual age at motor onset. However, a combined analysis of GWA1+GWA2, which increased the effective sample size to 1,951 unique European HD subjects, revealed a genome-wide significant signal, represented by two SNPs on chromosome 15 (chr15) (best SNP, p = 4.36 3 10
9; rs146353869) (Figure 1A). Follow-up Genome-wide Association Study To confirm the genome-wide significant signal on chr15 in an independent dataset and to implicate new loci through the increased power of a larger combined analysis, we formed the Genetic Modifiers of HD (GeM-HD) Group to carry out GWA3. Genotyping was performed at the Broad Institute using the Illumina Omni2.5 array for 3,447 HD subject samples from the MaHDC collection and from the European Huntington’s Disease Network (EHDN) Registry study (Orth et al., 2010). After QC, GWA3 comprised 2,131 unique individuals of European ancestry suitable for our analysis of association to the residual age at motor onset. GWA3 alone independently confirmed the chr15 locus at a genome-wide significance level (best SNP, p = 1.35 3 10
12; rs146353869). Meta-analysis of the two linear mixed-effect model results (combined GWA1+GWA2 and GWA3; n = 4,082) improved the significance of the best SNP on chr15 to p = 4.3 3 10
20 and also yielded a second genome-wide significant locus on chr8 (p = 2.7 3 10
8, rs1037699) with suggestive trails at other Cell 162, 516–526, July 30, 2015 ª2015 Elsevier Inc. 517

Figure 1. Genome-wide Association Analysis of Residual Age at Motor Onset (A) Manhattan plot of combined GWA1+GWA2 analysis yielding a locus with genome-wide significance on chr15. GWA1 and GWA2 data were combined and tested for association with residual age at onset. Significance of SNPs (
log10[p value], y axis) is plotted against genomic location (x axis). The QQ plot (Figure S1C) did not reveal significant statistical inflation evidenced by an inflation factor of 1.014. (B) Manhattan plot of meta-analysis of GWA1+2 and 3 showing genome-wide significant peaks at chr15 and chr8 and near-significant on chr3, along with other trails. Association analysis was initially performed independently on GWA3 data (not shown), and then a meta-analysis was performed to summarize the overall association findings of the GWA1+GWA2 and GWA3 analyses. The overall inflation factor of 1.009 suggests the absence of statistical inflation in this analysis (Figure S1D). The red dotted lines in (A) and (B) indicate the genome-wide significance level (p value, 5 3 10
8). The GeM-HD Group has developed a web portal through which interested investigators can access the genome-wide SNP association data by SNP, gene, or genomic location of interest. This can be accessed through the HDinHD portal (https:// www.hdinhd.org/). Original data will be made available on request. Please direct inquiries to [email protected] with the words ‘‘GWAS data’’ in the subject line. See also Figure S1 and Table S1.

locations, such as chr3, chr5, and chr21 (Figure 1B). The most significant variants at all locations that achieved a peak p < 1 3 10
6 are given in Table 1, whereas a more extensive list of all SNPs yielding p < 13 10
5 is presented in Table S1. To test the robustness of the quantitative association analysis to outliers with large residuals of age at onset, we also performed a dichotomous analysis. Individuals whose phenotypes fell into the 20% extremes of either earlier or later than expected age at onset were compared for marker allele frequency in a standard ‘‘case:control’’ GWAS design. Logistic regression analysis with ancestry characteristics and gender covariates was implemented using the combined datasets. Results from the genome-wide dichotomous analysis are shown in Figure 2, and details of allele frequency are also provided (in Table S2) for the top SNPs from quantitative analysis. Even though the dichotomous comparison comprised only 40% of the samples, the chr15 region again showed genome-wide significance (best SNP, p = 7.9 3 10
15; rs2140734), and the same secondary peaks on other chromosomes were readily discernible. Thus, detection of these loci does not depend critically on the precise magnitude of the residual of age at onset in the quantitative analysis, as the shift of individuals toward one or the other tail of the distribution creates contrasting allele frequencies between these extremes. Conditional Analysis and Effect Size To determine whether any of the top loci show evidence of more than one functional modifier allele, we carried out conditional as518 Cell 162, 516–526, July 30, 2015 ª2015 Elsevier Inc.

sociation analysis using a fixed-effect model of the combined data as shown in Figure 3A for the chr15 region. The bottom panel shows an expanded view of the chr15 locus association plot. When a fixed-effect model was conditioned by the most significant SNP (rs146353869, red circle), many of the most significant signals disappeared (Figure 3A, top panel), but a large number of SNPs remained above the genome-wide significant level (red dotted line, best SNP = rs2140734, green circle), indicating a second modifier effect independent of that captured by rs146353869. This was confirmed by conditioning the analysis on rs2140734 (Figure 3A, middle panel), whose characteristics are also listed in Table 1. Interestingly, the minor alleles for SNPs detecting these two independent signals are associated with opposing effects. The SNPs with the most significant p values all show a relatively low MAF (1.3%–3.0%), and each minor allele corresponds with up to 6.1 years earlier age at onset than expected based upon CAG length (range
2.9 to
6.1 years/minor allele for 34 SNPs). To avoid any contribution of a ‘‘winner’s curse,’’ we also estimated the effect size in only the GWA3 dataset accumulated after genome-wide significance had already been achieved. In this independent confirmation dataset, the effect size for rs146353869 was
6.2 years/minor allele (in a mixed-effect model). The genome-wide significant SNPs at the chr15 locus that detect the second, independent association signal all display a much higher MAF (27.0%–39.1%) and are associated with a delay in motor onset of up to 1.4 years (rs2140734; range +1.1 to 1.4 for 91 SNPs; +1.4 years/minor allele for rs2140734 in GWA3 alone by mixed-effect model

Table 1. Most Significant Variants Associated with Residual Age at HD Motor Onset SNP

Chr BP (hg19)

MAF in MAF in European Effect Size (Years/ p Value in meta Minor Allele Major Allele Europeans (%)b HD (%) Minor Allele) Analysisa

rs147804330

2

56391203

A

G

8.0

6.3


1.6

7.6 3 10
7

rs72810940

2

75555265

A

G

3.4

2.9

2.4

5.9 3 10
7

rs144287831

3

37068079

C

T

32.5

31.2

0.9

2.2 3 10
7

rs11133929

5

2155168

C

T

9.4

9.3

1.5

2.1 3 10
7

rs1037699

8

103250930

T

C

8.3

9.6


1.6

2.7 3 10
8

rs11061229

12

131389783

C

G

6.9

6.6


1.7

6.7 3 10
7

rs261453

13

82324504

A

C

9.9

11.4


1.3

9.0 3 10
7

GACTCTA

2.0

1.5


3.2

7.5 3 10
7

rs148491145 14

72360176-72360182 —

rs146353869 15

31126401

A

C

1.1

1.7


6.1

4.3 3 10
20

rs2140734

15

31243792

G

T

30.2

30.4

1.4

7.1 3 10
14

rs143367341 21

28348433

G

A

14.6

13.5

1.3

2.5 3 10
7

See also Table S1. a The most significant variant is shown for each independent signal with p < 1 3 10
6. Genome-wide significant signals are shown in bold. See also Table S1. b MAF (%) in Europeans represents the minor allele frequency in 1000 Genomes project data phase 3, except rs143367341 (1000 Genomes Project data, phase 1, release3).

analysis). These two independent modifier effects reflect the presence in the population, on different versions of chr15, of two separate functional variants that likely have opposing impacts on the same gene. Unlike the chr15 region, the other loci listed in Table 1 each suggest only a single modifier allele. Examples are shown in Figures 3B and 3C for chr8 and chr3, where conditioning the analysis on the respective top SNPs (rs1037699 and rs144287831) dramatically reduced other association signals in the corresponding region. We did not detect any significant interaction between the four independent SNPs representing chr15 (rs146353869 and rs2140734), chr8 (rs1037699), and chr3 (rs144287831) in pairwise tests. Furthermore, models directly testing interaction between each SNP and HTT CAG repeat length did not support the significance of CAG:SNP interaction term, suggesting independent effects acting equally across the range of expanded repeats. Genes near Top Association Signals As with any GWA analysis, the location of the significant SNPs does not immediately identify which gene mediates the consequences of the as yet unknown functional variant, but several candidates are evident for the genome-wide significant loci. At the chr15 locus, a recombination frequency peak (cyan line in Figure 3A) on the telomeric side coincides with the loss of both independent significant association signals, which extend proximally in a region containing the two highest priority candidate genes, MTMR10 (myotubularin related protein 10) and FAN1 (Fanconi anemia FANC1/FANCD2-associated [endo] nuclease 1), along with the pseudogene HERC2P10 in a segment that also specifies several putative large intergenic non-coding RNAs (lincRNAs). On chr8 (Figure 3B), the significant association signal also extends across two high-priority candidate genes, RRM2B (a subunit of DNA damage p53-inducible ribonucleotide reductase M2 B) and UBR5 (an HECT domain E3 ubiquitin-protein ligase). The region also contains the microRNA gene MIR5680 and the 50 end of NCALD (neurocalcin delta). Among

the top loci that did not reach genome-wide significance, the most notable is that on chr3 (Figure 3C), which centers on MLH1 (the human homolog of the E. coli DNA mismatch repair gene mutL), whose mouse homolog, Mlh1, was discovered in a genome-wide genetic screen to modify somatic instability of the CAG repeat and the timing of CAG length-dependent phenotypes in the striatum of genetic HD replica CAG knockin mice (Pinto et al., 2013). Pathway Analysis To examine systematically whether variants associated with altered age at onset, extending beyond the most significant hits, cluster in genes with common biological function, we performed pathway analyses using three approaches chosen to have different characteristics: Setscreen, ALIGATOR, and gene-set enrichment analysis (GSEA). Setscreen (Moskvina et al., 2011) combines p values from all SNPs in a pathway, making it advantageous for genes and pathways containing multiple quasi-independent signals of modest size. However, this approach may lose power when the pathways contain a few strong signals with many SNPs showing no association. ALIGATOR (Holmans et al., 2009) defines genes as ‘‘significant’’ based on their most significant SNP and tests whether a pathway contains a higher number of significant genes than would be expected by chance, taking into account gene size and linkage disequilibrium between genes. This gives good power to detect pathways in which there is one strong association signal per gene but has the disadvantage of requiring that a criterion be set for defining significant SNPs and genes. GSEA (Wang et al., 2007) ranks genes in order of a gene-wise significance measure, then tests whether pathway genes have a significantly high rank, weighting by the significance measure. For each analysis, we conservatively assigned SNPs between the start of the first and the end of the last exon of any transcript to the corresponding gene. To avoid making a priori assumptions about the areas of biology involved in the modification of age at motor Cell 162, 516–526, July 30, 2015 ª2015 Elsevier Inc. 519

Figure 2. Dichotomous Association Analysis in Extremes of Age at Motor Onset Association analysis was carried out to compare SNP allele frequencies between the 20% extremes of residual age at motor onset, showing that the modifier effect on chr15 is captured by the allele frequency distribution in addition to quantitative analysis. See also Table S2.

onset, we deliberately chose to use a large pathway set covering as many areas of biology as possible, comprising 14,706 functional gene sets, many with overlapping members, containing between 3 and 500 genes: 10,741 from GO, 265 from KEGG, 1897 from MGI, 119 from PANTHER, 217 from Biocarta, 1248 from Reactome, and 219 from NCI. In the primary Setscreen analysis, 14 pathways were significant after correcting for multiple testing (q < 0.05). These are listed in Table 2, together with their enrichment p values under the ALIGATOR and GSEA analyses. Enrichment p values under all analysis methods are given in Table S3 for the 326 pathways with p < 0.05 in the Setscreen analysis. Figure 4 shows that the 14 significant pathways from Table 2 group into three clusters by gene membership: DNA repair, mitochondrial fission, and oxidoreductase activity. Pathways in the DNA repair cluster also show significant enrichment under the ALIGATOR and GSEA analysis (Table 2), increasing confidence that the enrichments are genuine. Best SNP and gene-wide p values for the genes in these clusters are given in Table S4. Gene-wide p values are calculated using the method of Brown (Brown, 1975), similar to that used in Setscreen. Note that FAN1 (together with ERCC3) is a member only of GO:33683 (nucleotide-excision repair, DNA incision), although it is a member of the broader pathway GO:6281 (DNA repair), which has nominally significant (p = 0.012) evidence for enrichment (see Tables S3 and S5). Thus, the significant enrichments observed in the DNA-repair pathways in Table 2 are achieved independently of the association region on chr15. If genome-wide significant (p < 5 3 10
8) SNPs are removed from the Setscreen analysis, GO:33683 is still significant (p = 8.653 10
5), with the other pathways in Table 2 being unaltered. Genes with gene-wide p < 0.1 from all 326 pathways significantly enriched (p < 0.05) in the Setscreen analysis are shown in Table S5. Effects on Age at Onset of Cognitive and Psychiatric Signs In addition to motor signs, HD subjects also show cognitive difficulties and sometimes exhibit prominent psychiatric disturbance that may precede their movement disorder. The age at onset for cognitive and psychiatric signs was noted for limited subsets of our genotyped subjects of European ancestry. Consequently, we tested the hypothesis that the SNPs showing genome-wide significant association with residual age at motor onset also reveal modification of these non-motor phenotypes. The sample sizes of subjects with CAG 40–55 repeats for these 520 Cell 162, 516–526, July 30, 2015 ª2015 Elsevier Inc.

analyses comprised 843 subjects with a recorded age at onset of cognitive signs and 1,515 with a known age at onset of psychiatric signs, as scored by an expert rater familiar with HD. Each of these phenotypes shows a negative correlation with CAG repeat length, explaining 49.3% and 39.2% of the variance in age at onset, respectively (Figure S2), as compared with 59.4% for the motor phenotype. Both are very significantly correlated (Pearson correlation p value < 2.23 10
16) with age at motor onset (Pearson correlation coefficients of 0.891 and 0.804, respectively), but we sought to assess whether differential effects might be revealed by the actions of the modifier loci. Because stringent phenotype models describing the relationship between age at onset of cognitive or psychiatric onsets and CAG repeat length have not yet been developed, we tested the effects of the independent significant SNPs associated with residual age at motor onset by modeling log-transformed age at onset of cognitive signs or psychiatric signs as a function of CAG repeat length, SNP, gender, and four ancestry covariate values in a combined fixed-effect model analysis framework. For comparison, we also applied this analytical approach to age at motor onset, which yielded p values that were only slightly different than the residual-based analysis above. For both age at cognitive onset and age at psychiatric onset, the independent signals at the chr15 locus both showed a nominally significant association, hastening or delaying cognitive or psychiatric onset in the same direction as the respective effect on motor onset (Table 3). The chr8 modifier was also nominally significant for association with age at cognitive onset and age at psychiatric onset. Interestingly, although the chr3 locus at MLH1 showed near-significance for psychiatric onset, there was no evidence of any effect on cognitive onset, contrasting with the other modifier loci and suggesting that the different modifiers may act on different processes to accomplish their effect on HD pathogenesis. This suggests that not all modifiers of motor onset influence other HD phenotypes and that future analyses of larger HD datasets specifically for cognitive and psychiatric phenotypes may reveal additional modifying genetic variants distinct from those that alter age at motor onset. DISCUSSION Investigation of humans with an expanded HTT CAG allele and studies of model systems in which full-length mutant huntingtin is expressed, including both human cells and CAG knockin mice, support the view that the HD mutation has effects

Figure 3. Conditional Association Analysis at Top Loci (A) Chromosome 15 locus. Bottom panel: The single SNP association analysis of the combined dataset using a fixed-effect model is shown above the recombination rate (cyan line), based upon HapMap samples, and the largest transcript for each annotated gene in the region (blue arrows). The red and green circles represent the most significant independent SNPs that emerged from the conditional analyses shown in the middle and top panels. Middle panel: Single SNP association analysis conditioned by rs2140734 (green in bottom and top panels) revealing a group of SNPs that remain significant after removing the effect associated with rs2140734. Top panel: Single SNP association analysis conditioned by rs146353869 (red in bottom and middle panels) revealing a group of SNPs that remain significant after removing the effect associated with rs146353869. (B) Chromosome 8 locus. Bottom panel: The chr8 locus single SNP association analysis of the combined dataset using a fixed-effect model is shown above the recombination rate (cyan line), based upon HapMap samples, and the largest transcript for each annotated gene in the region (blue arrows). The red circle represents the most significant SNP that was used in the conditional analysis. Top panel: Single SNP association analysis conditioned by rs1037699 (red in bottom panel) revealing that all SNPs that showed association in the original association analysis were no longer significant after removing the effect associated with rs1037699. (C) Chromosome 3 locus. Bottom panel: The chr3 locus single SNP association analysis of the combined dataset using a fixed-effect model is shown above the recombination rate (cyan line), based upon HapMap samples, and the largest transcript for each annotated gene in the region (blue arrows). The red circle represents the most significant SNP that was used in the conditional analysis. Top panel: Single SNP association analysis conditioned by rs144287831 (red in bottom panel) revealing that all SNPs that showed association in the original association analysis were no longer significant after removing the effect associated with rs144287831.

throughout life due to a completely dominant gain-of-function mechanism that leads after decades to onset of clinical signs (Gusella et al., 2014). The precise biological differences distinguishing individuals who possess expanded CAG alleles and will develop HD from those with normal-length CAG alleles who will not are not well understood. However, the proof-of-principle that HD disease modification is possible is demonstrated not by medical treatment but by observations of a heritable

portion of the variance in age at onset that is not explained by either the size of the CAG repeat or other HTT region polymorphisms (Lee et al., 2012a). Instead functional variants exist in the human population that do not themselves confer risk of HD but are capable of modifying the course of the disorder during the long phase that precedes emergence of clinical disease, resulting in earlier or later onset than expected based upon the individual’s expanded CAG repeat length. In essence nature has Cell 162, 516–526, July 30, 2015 ª2015 Elsevier Inc. 521

Table 2. Pathways Significant after Multiple-Testing Correction (q < 0.05) in the Primary Setscreen Analysis and Enrichment p Values For ALIGATOR And GSEA Pathway

p(Set-screen)

q(Set-screen)

p(ALIGATOR)

p(GSEA)

Description

GO:0090200

8.89 3 10
8

0.0007

NA

0.1040

positive regulation of cytochrome c release from mitochondria

GO:0033683

1.69 3 10
6

0.0063

0.0087

0.0030

nucleotide-excision repair, DNA incision

GO:0090141

2.30 3 10
6

0.0063

NA

0.1314

positive regulation of mitochondrial fission

GO:0006298

3.25 3 10
6

0.0066

0.0086

0.0074

mismatch repair

KEGG:3430

6.65 3 10
6

0.0101

0.0732

0.0280

mismatch repair

GO:0030983

7.43 3 10
6

0.0101

0.00254

0.0062

mismatched DNA binding

GO:0090140

1.57 3 10
5

0.0169

NA

0.1560

regulation of mitochondrial fission

GO:0032389

1.66 3 10
5

0.0169

0.00072

0.0382

MutLalpha complex

GO:0004748

2.66 3 10
5

0.0217

NA

0.0380

ribonucleoside-diphosphate reductase activity, thioredoxin disulfide as acceptor

GO:0016728

1.65 3 10
5

0.0217

NA

0.0380

oxidoreductase activity, acting on CH or CH2 groups, disulfide as acceptor

GO:0032300

3.82 3 10
5

0.0283

0.00088

0.0058

mismatch repair complex

GO:0032407

5.74 3 10
5

0.0390

0.00127

0.0062

MutSalpha complex binding

GO:0010822

7.63 3 10
5

0.0478

NA

0.0436

positive regulation of mitochondrion organization

GO:1900063

8.39 3 10
5

0.0488

NA

0.0376

regulation of peroxisome organization

NA means that the pathway contained fewer than two significant genes in the ALIGATOR analysis. Note that many of these pathways contain overlapping sets of genes, allowing them to be clustered as shown in Figure 4. See also Tables S3, S4, and S5.

achieved disease modification, the goal of those seeking therapeutic interventions, and it has remained for investigators to identify the means by which it occurs. Genetic modifiers could lead to a better understanding of the genes and processes that impact on HD pathogenesis and provide in-human validated targets for traditional small-molecule therapies. The significant loci that have emerged from our unbiased genome-wide search for variants associated with altered age at diagnostic motor onset offer a different entre´e into influencing pathogenesis in this long-studied but still intractable disorder. The previous investigation of potential genetic modifiers of HD has largely relied upon biased candidate gene studies, but none has identified a locus of genome-wide significance. The findings have been weak and inconsistent even for the same gene, likely reflecting a lack of power and statistical stringency, variable phenotype definition, and population stratification. Indeed, in our GWAS, none of the previously suggested candidate modifiers achieved p < 1 3 10
5. However, two previous unbiased genetic-linkage modifier searches in HD sib pairs from North America, Europe, and Australia (Li et al., 2003, 2006) or in families limited to Venezuela (Gaya´n et al., 2008) yielded genome-wide significant peaks at 6q23-q24 (LOD = 4.05) or at 2p25 (LOD = 4.29), respectively, with trends in the latter at 2q35 (LOD = 3.39), 5p14 (LOD = 3.31), and 5q32 (LOD = 3.14). None of the most significant association signals and none of the trending SNPs (p < 13 10
5) from our European GWA analysis correspond to any of these linkage regions. The lack of overlap between our GWA and the Venezuela linkage scan could be explained simply by population differences in the modifier alleles present. The difference with the other linkage study, which included subjects expected to be primarily of European 522 Cell 162, 516–526, July 30, 2015 ª2015 Elsevier Inc.

ancestry, more likely represents either a diversity of modifier alleles at the 6q23-q24 locus detectable by linkage but not by association in this sample or inaccuracy in precisely localizing the linkage peak, as there is a nearby association signal at 6q23 (top SNP rs6934819, p = 2.83 10
6). A similar discrepancy between GWA and linkage results has been seen for risk factors in some complex disorders (Weiss et al., 2009). The genome-wide significant loci identified here permit discovery of the specific functional variants responsible for the modifier effects and the genes through which they act. Both the chr15 and chr8 loci offer attractive candidates. On chr15, the presence of two independent genome-wide significant signals in the same region reflects two functional variants, with Occam’s razor arguing that these are likely to affect the same gene. The two strongest locational candidates, FAN1 and MTMR10, are implicated in functions previously suggested in studies of HD pathogenesis: structure-specific DNA handling and inositol-phosphate signaling, respectively. The FAN1 nuclease plays a role in repair of DNA inter-strand cross-links but not of double-strand breaks (Kratz et al., 2010; Liu et al., 2010; MacKay et al., 2010) and has recently been identified as essential for restart of paused replication forks in DNA synthesis (Chaudhury et al., 2014). MTMR10, although catalytically inactive, is thought, like other such myotubularin-related family members, to heterodimerize with an active phosphatase subunit to act on phosphatidylinositol phosphates (Hnia et al., 2012). The top SNPs for each of the two independent signals are located upstream of FAN1 and within MTMR10, respectively, although each is backed by a distinct, extensive set of associated SNPs spanning both genes. FAN1 and MTMR10 lie within a larger 2 Mb region of copy-number variation (CNV) due to non-allelic

Figure 4. Fourteen Significant Pathways (q < 0.05) from the Main Setscreen Analysis Clustered by Gene Membership Thickness of line connecting two pathways is proportional to the number of genes shared between them. The size of the node is proportional to the number of SNPs. The intensity of shading is inversely proportional to the q value; deep shades of red have low q values, and pale shading is close to the 5% threshold. Pathways were assigned to clusters as follows: For each pair of pathways, an overlap measure K was defined as the number of genes common to both pathways divided by the number of genes in the smaller pathway. A pathway was assigned to a cluster if the average K between it and the pathways already in the cluster was greater than 0.4. If it was not possible to assign a pathway to an existing cluster, a new cluster was started. This procedure was carried out recursively, in descending order of enrichment significance. See also Tables S3, S4, and S5.

homologous recombination of flanking repeats. Both deletion and duplication of the region have been associated with intellectual disability, epilepsy, and autism, with the former also associated with schizophrenia. Although no genome-wide significant GWA signal has been reported in this segment for autism, schizophrenia, or other psychiatric disorders, it has been suggested that FAN1 may drive neurodevelopmental susceptibility based upon an increased frequency of rare missense variants (Ionita-Laza et al., 2014). Analysis of our GWA data using (1) the number of CNV segments (p = 0.7819), (2) total CNV size (p = 0.853), and (3) average of CNV segment size (p = 0.5201) did not support a contribution of CNV to our HD modifier association signals, indicating that more subtle but relatively common genetic variants are responsible for the HD modifier effect. Very recent data show that the same 2 Mb segment of 15q13.3 is inverted without change in copy number at low but readily measurable frequency in the normal population (Antonacci et al., 2014). It will be interesting to determine whether SNPs tagging either of the functional effects that we have observed are present on inversion chromosomes. However, in either circumstance, the fact that our genome-wide association signals extend over < 250 kb of the internal region suggests that it will be possible to use haplotyping and sequence analysis to home in on the functional variants, which are likely to act via one of these two genes. The same strategies can apply to the single functional variant implicated on chr8, where the association signals extend over < 250 kb spanning two prime locational candidates, RRM2B and UBR5. These genes are involved in additional func-

tions previously suggested to play a role in HD pathogenesis: mitochondrial energetics and oxidative stress, and proteostasis. As a subunit in quiescent cells of the rate-limiting enzyme in new deoxyribonucleotide triphosphate synthesis (Pontarin et al., 2011), RRM2B has effects on DNA synthesis and repair (Pontarin et al., 2012). It also regulates mitochondrial DNA content (Bourdon et al., 2007) and suppresses activation of the oxidative stress pathway (Kuo et al., 2012). Proteasome-mediated protein degradation due to tagging by E3 ubiquitin ligases like UBR5 is critical to many cellular processes and has been a focus of HD research due to the intracellular accumulation of misfolded polyglutamine fragments of mutant huntingtin (Ortega and Lucas, 2014). Although we believe it most likely that the modifiers act through intersection with the biology of HD pathogenesis, it is formally possible that they act through an independent effect on motor control in aging and modify HD age at onset additively. None of the top SNPs on chr15, chr8, or chr3 SNPs has been associated with any phenotype in previous GWASs, including analysis of age at onset of Parkinson disease, a movement disorder wherein a similar additive effect might be predicted. The effect sizes of
6 to +1.4 years, determined from CAG repeat lengths typically associated with a mean onset range of 20 to 60 years, would indicate a substantial effect in mid-life, but it is conceivable that more detailed phenotyping of normal individuals may reveal HD-independent effects of these loci. Investigation of other movement disorders might also reveal an influence of these loci, particularly if the other disorder shares aspects of pathogenesis with HD. Cell 162, 516–526, July 30, 2015 ª2015 Elsevier Inc. 523

Table 3. Association of Top Loci with Other Phenotypes

SNP rs146353869 rs2140734 rs1037699 rs144287831

Chr 15 15 8 3

Age at Onset of Motor Signs

Age at Onset of Cognitive Signs

Age at Onset of Psychiatric Signs

p value

p value

p value


19

7.0 3 10


13

4.7 3 10


7

1.2 3 10


7

5.1 3 10


3

2.7 3 10
7


3

4.8 3 10
3


4

4.1 3 10
2


1

7.6 3 10
2

7.6 3 10 1.1 3 10 8.7 3 10 9.7 3 10

See also Figure S2.

In HD itself, the effect is substantial, representing 8%–33% of the typical disease duration and as much as 25%–30% of the life span prior to diagnosis. This is most evident in the odds-ratios from extreme dichotomous analysis, which, at 1.8 to 18.1 (Table S2), far exceed those in most disease GWAS where small additive risk effects are the norm. Although larger effect sizes may prove to be more frequent in modifier-based than in risk-based GWAS, they are not a prerequisite for judging a modifier’s value in directing therapeutic development, as pharmaceutical interventions have the potential for stronger effects than naturally occurring human variation on disease-modifying processes. Although not quite achieving genome-wide significance, prior discovery in CAG repeat knockin mouse genetic modifier screen strongly supports the candidacy of MLH1 at the chr3 locus and implicates DNA mismatch repair as a process that modifies HD pathogenesis (Pinto et al., 2013). This proposal receives further support from our pathway analyses. Genes involved in DNA mismatch repair pathways were enriched for association with HD residual age at onset. In humans, inactivation of MLH1 and other mismatch repair genes, predominantly MSH2, MSH6, and PMS2, is associated with dinucleotide repeat instability in certain cancers (Sehgal et al., 2014). By contrast, inactivation of some mismatch repair genes (Msh2, Msh3, Mlh1, Mlh3) eliminates somatic instability of the CAG repeat in Htt CAG knockin mice, and knock out of Mlh1, and other mismatch repair genes, also slows the pathogenic process in these precise genetic HD replicas (Dragileva et al., 2009; Pinto et al., 2013). Given that Mlh1 and other mismatch repair genes influence CAG instability in knockin mice, and longer HTT CAG repeat expansions in HD post-mortem brain are associated with earlier disease onset (Swami et al., 2009), one would predict that MLH1 modifies disease onset in patients as a consequence of an effect on somatic HTT CAG repeat instability. However, although attractive, this assumption should be tested further. The HD knockin mouse studies do not a priori rule out the possibility that DNA repair genes might modify HD pathogenesis via DNA structurespecific functions unrelated to their activities in enhancing CAG instability. The identification of genetic modifier loci that alter the course of HD prior to disease onset opens an entirely new direction for development of therapies to prevent the onset of this devastating disorder. To truly understand the modifier mechanisms, additional work is needed to identify the functional DNA variant and gene(s) responsible for mediating the modifier effect at each 524 Cell 162, 516–526, July 30, 2015 ª2015 Elsevier Inc.

locus. Follow-up to our initial lead is enabled by the ongoing collection of additional well-phenotyped DNA samples from large HD natural history studies and clinical trials. Adding samples will power genome-wide association to detect many more modifiers and to potentially reveal additional pathways by which HD pathogenesis can be altered. Similarly, the analysis of nonEuropean subjects offers the potential for identifying additional alleles at these modifier loci and/or additional loci specific to certain populations. Applying this approach to other HD phenotypes, both before and after disease onset, may, as our findings already suggest, reveal modifiers that distinguish different disease domains. All of these pursuits will accelerate the ability to translate natural disease modification by genetic factors into directed disease modification by human intervention. The genetic modifiers defined here have already identified one pathway, DNA handling, whose manipulation may provide therapeutic benefit in HD. Investigation of the chr15 and chr8 loci is likely to provide additional targets. Even before these modified loci are fully understood and additional modifiers are found, our findings will have a profound impact in a number of areas. As a proof-of-principle, they will spur pursuit of this genetic modifier strategy in other Mendelian disorders with quantitative or discrete qualitative differences in phenotype. In basic research, they will open paths into understanding the pathogenic process in HD by providing human-relevant tools with which to perturb it. In clinical research, they will provide the basis for genotypephenotype studies to more fully explore the phenotypic correlates of each mechanism of disease modification. For clinical trials, stratification of the patient population and/or quantitation of the outcomes in a manner that takes into account the effects of patient genotype at these loci will permit smaller, less costly trials with greater power to detect therapeutic benefit. Finally, for HD families, our findings present the hope of novel in-human validated targets to accelerate development of treatments and represent a validation of their active and willing participation in HD studies that have made such large-scale investigations possible.

EXPERIMENTAL PROCEDURES Subjects and Residual Phenotype Patient consents and the overall study were reviewed and approved by the Partners HealthCare Institutional Review Board. The sources of subjects are described in Supplemental Experimental Procedures. We used age at onset of motor signs and CAG repeat length to derive residual age at onset of motor signs, which we used as the primary phenotype for the GWAS to identify genetic modifiers of HD. In order to subtract the effects of CAG repeats from the age at onset of motor signs, we used a phenotype model previously developed through stringent data analysis (Lee et al., 2012b). This model relates natural log-transformed age at onset of motor signs to CAG repeat length using only normally distributed data points. In the current study, the previously established phenotype model (intercept, 7.01; slope,
0.073) was interrogated with CAG repeat lengths of study subjects of CAG lengths 40–55 to obtain individual predicted age at onset of motor signs, which we transformed into natural scale for calculating the difference between predicted and actual age at motor onset, i.e., the residual age at motor onset. For example, a residual age at onset of
10 for a HD subject indicates that the individual developed motor signs 10 years earlier than expected from his or her CAG repeat length. The distribution of residual age at onset of motor signs of study subjects was very similar to a theoretical normal distribution.

GWA Analysis Quantitative GWA analysis used mixed-effect linear regression analysis, modeling residual age at motor onset as a function of minor allele count of a SNP and gender and ancestry covariates. For extreme dichotomous analysis, we directly compared genome-wide SNP allele frequencies of those individuals whose residual age at motor onset was among the 20% extremes, respectively representing earlier and later than expected onset. As no prior statistical model was available for other onset phenotypes, for these we modeled logtransformed age at onset of cognitive signs or psychiatric signs as a function of CAG repeat length, minor allele count of a test SNP, and gender and ancestry covariates in a linear regression analysis framework to determine the extent to which the test SNP explains the amount of variance in phenotype. Pathway Analysis The primary pathway analysis was performed using Setscreen (Moskvina et al., 2011), with secondary analyses using ALIGATOR (Holmans et al., 2009), and GSEA (Wang et al., 2007) as described in Supplemental Experimental Procedures. SUPPLEMENTAL INFORMATION Supplemental Information includes Supplemental Experimental Procedures, two figures, five tables, and a full list of GeM-HD Consortium Members and can be found with this article online at http://dx.doi.org/10.1016/j.cell.2015. 07.003. CONSORTIA The Genetic Modifiers of Huntington’s Disease (GeM-HD) Consortium was organized into the following groups: GeM Group 1: Jong-Min Lee, Vanessa C. Wheeler, Michael J. Chao, Jean Paul G. Vonsattel, Ricardo Mouro Pinto, Diane Lucente, Kawther Abu-Elneel, Eliana Marisa Ramos, Jayalakshmi Srinidhi Mysore, Tammy Gillis, Marcy E. MacDonald, and James F. Gusella; GeM Group 2: Denise Harold, Timothy C. Stone, Valentina Escott-Price, Jun Han, Alexey Vedernikov, Peter Holmans, and Lesley Jones; GeM Group 3: Seung Kwak and Mithra Mahmoudi; GeM Group 4: Michael Orth and G. Bernhard Landwehrmeyer; Registry Investigators: Jane S. Paulsen; PREDICT-HD Investigators: E. Ray Dorsey and Ira Shoulson; COHORT, PHAROS, and TREND-HD Investigators; Richard H. Myers; and HD-MAPS Investigators. AUTHOR CONTRIBUTIONS Conceptualization, J.-M.L., M.E.M., J.F.G., L.J., and S.K.; resources, R.H.M., J.P.G.V., D.L., M.O., M.M., G.B.L., J.S.P., E.R.D., I.S., and the Registry, PREDICT-HD, COHORT, PHAROS, TREND-HD, and HD-MAPS Investigators; investigation, K.A.-E., E.M.R., J.S.M., and T.G.; data curation, J.-M.L., M.J.C., K.A.-E., D.H., M.O., T.C.S., J.H., A.V., L.J., and P.H.; formal analysis, J.-M.L., P.H., D.H., J.H., M.J.C., T.C.S., and V.E.-P.; writing: J.F.G., J.-M.L., M.E.M., V.C.W., R.M.P., D.H., P.H., L.J., S.K., M.O., and R.H.M.; supervision: J.-M.L., M.E.M., J.F.G., G.B.L., M.O., L.J., P.H., and S.K. ACKNOWLEDGMENTS This work was supported by the CHDI Foundation, by grants X01HG006074, U01NS082079, R01NS091161, R01HG002449, and P50NS016367 from the National Institutes of Health (USA), and by grants G0801418 and MR/ L010305/1 from the Medical Research Council (UK). Although not directly related to this work, E.R.D. has received grant support from Auspex Pharmaceuticals and Prana Biotechnology Ltd, and as of May 12, 2014, after completion of his term leading the Huntington Study Group, I.S. became a compensated non-executive director for Prana Biotechnology Ltd. Received: January 25, 2015 Revised: April 16, 2015 Accepted: June 18, 2015 Published: July 30, 2015

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Supplemental Figures

Figure S1. Description of Phenotype and Q-Q Plots for Quantitative GWA Analyses, Related to Figure 1 (A) A phenotype regression model representing the relationship between expanded CAG repeat length (x axis) and age at onset of diagnostic motor signs (y axis). Each open circle represents a single HD individual. The red line represents the best fit regression model constructed using statistically well-behaved samples with CAG repeat sizes 40–53 as detailed in Lee et al. (2012b). In the current analysis, sufficient subjects were also available at CAG 54 and 55 to meet statistical criteria and were included in the association analysis. Their inclusion or exclusion did not alter the overall association findings. (B) Residual age at onset of subjects. The histogram plot shows the overall distribution for HD individuals in this study of residual age at onset, calculated by subtracting each individual’s predicted age at onset (from the regression model) from their actual age at onset. The red line represents a theoretical normal distribution based on the residuals of study subjects analyzed in this study. (C) Q-Q plot for analysis in Figure 1A. (D) Q-Q plot for analysis in Figure 1B.

Cell 162, 516–526, July 30, 2015 ª2015 Elsevier Inc. S1

Figure S2. Relationship of Age at Cognitive and Age at Psychiatric Onset with CAG Repeat Length, Related to Table 3 Age at onset of cognitive signs (A) and psychiatric signs (B) were available for 843 and 1,515 HD subjects, respectively. Using all data points, log-transformed age at onset of cognitive signs (A) and psychiatric signs (B) were modeled as a function of the size of expanded CAG repeat in linear models. Subsequently, age at onset and statistical models were transformed into natural scale values for plotting. R square values represent the proportion of the variance in log scale age at onset explained by the expanded CAG repeat length. The size of normal HTT CAG allele was not significant in explaining the variance in age at onset of cognitive (p value, 0.583) and psychiatric signs (p value, 0.712), and therefore was excluded from the statistical model models.

S2 Cell 162, 516–526, July 30, 2015 ª2015 Elsevier Inc.

Cell Supplemental Information

Identification of Genetic Factors that Modify Clinical Onset of Huntington’s Disease Genetic Modifiers of Huntington’s Disease (GeM-HD) Consortium

Supplemental Information

The Genetic Modifiers of Huntington’s Disease (GeM-HD) Consortium Investigators GeM Group 1: Jong-Min Lee1,2*, Vanessa C. Wheeler1,2*, Michael J. Chao1,2, Jean Paul G. Vonsattel3, Ricardo Mouro Pinto1,2, Diane Lucente1, Kawther Abu-Elneel1, Eliana Marisa Ramos1, Jayalakshmi Srinidhi Mysore1, Tammy Gillis1, Marcy E. MacDonald1,2,5* and James F. Gusella1,4,5* 1

Center for Human Genetic Research and MGH Research Institute, Massachusetts General

Hospital, Boston, MA 02114, USA 2

Department of Neurology, Harvard Medical School, Boston, MA 02115, USA

3.

Department of Pathology and Cell Biology and the Taub Institute for Research on Alzheimer’s

Disease and the Aging Brain, Columbia University Medical Center, New York, NY 10032, USA. 4

Department of Genetics, Harvard Medical School, Boston, MA 02115, USA

5

Medical and Population Genetics Program, the Broad Institute of M.I.T. and Harvard,

Cambridge, MA 02142, USA GeM Group 2: Denise Harold6+*, Timothy C. Stone6, Valentina Escott-Price6, Jun Han6, Alexey Vedernikov6, Peter Holmans6*, and Lesley Jones6* 6

Medical Research Council (MRC) Centre for Neuropsychiatric Genetics and Genomics,

Institute of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, CF24 4HQ, United Kingdom GeM Group 3: Seung Kwak7* and Mithra Mahmoudi8 7

CHDI Foundation, Princeton, NJ 08540, USA S1

8

CHDI Foundation, Los Angeles, CA 90045, USA

GeM Group 4: Michael Orth9* and G. Bernhard Landwehrmeyer9 representing the European Huntington’s Disease Network (EHDN) Registry investigators^, Jane S. Paulsen10 representing the Huntington Study Group (HSG) PREDICT-HD investigators^, E. Ray Dorsey11 and Ira Shoulson12 representing the HSG COHORT, PHAROS and TREND-HD investigators^, and Richard H. Myers13* representing the HD-MAPS investigators^ 9

Department of Neurology, University of Ulm, Ulm, Germany D-089081

10

Departments of Psychiatry and Neurology, University of Iowa Roy and Lucille Carver College

of Medicine, Iowa City, IA 52242, USA 11

Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642,

USA 12

Program for Regulatory Science & Medicine (PRSM), Georgetown University, Washington,

DC 20007, USA 13

Department of Neurology and Genome Science Institute, Boston University School of

Medicine, Boston, MA 02118, USA * Denotes organizing members of the GeM-HD Consortium + Present address: Neuropsychiatric Genetics Research Group, Department of Psychiatry, Institute of Molecular Medicine, Trinity College, Dublin 8, Ireland ^ Registry, PREDICT-HD, COHORT, PHAROS, TREND-HD and HD-MAPS investigators are listed below as sources of study subjects in the Extended Experimental Procedures

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Extended Experimental Procedures Study Subjects Patient consents and the overall study were reviewed and approved by the Partners HealthCare Institutional Review Board. Subject DNA samples from the HDC-Mod collaboration were collected over the past three decades by investigators from the Massachusetts HD Center Without Walls and by collaborating clinicians and clinical investigators who treat HD patients. Additional subject DNAs were provided by collaborating investigators of the Registry, PREDICTHD, COHORT, PHAROS, TREND-HD and HD-MAPS studies:

European Huntington’s Disease Network REGISTRY Study Registry Steering committee: Anne-Catherine Bachoud-Lévi, Anna Rita Bentivoglio, Ida Biunno, Raphael M Bonelli, Jean-Marc Burgunder, Stephen B Dunnett, Joaquim J Ferreira, Olivia J. Handley, Arvid Heiberg, Torsten Illmann, G Bernhard Landwehrmeyer, Jamie Levey, Maria A. Ramos-Arroyo, Jørgen E Nielsen, Susana Pro Koivisto, Markku Päivärinta, Raymund A.C. Roos, Ana Rojo Sebastián, Sarah J Tabrizi, Wim Vandenberghe, Christine VerellenDumoulin, Tereza Uhrova, Jan Wahlström, Jacek Zaremba Language coordinators: Verena Baake, Katrin Barth, Monica Bascuñana Garde, Sabrina Betz, Reineke Bos, Jenny Callaghan, Adrien Come, Leonor Correia Guedes, Daniel Ecker, Ana Maria Finisterra, Ruth Fullam, Mette Gilling, Lena Gustafsson, Olivia J. Handley, Carina Hvalstedt, Christine Held, Kerstin Koppers, Claudia Lamanna, Matilde Laurà, Asunción Martínez Descals, Saül Martinez-Horta, Tiago Mestre, Sara Minster, Daniela Monza, Lisanne Mütze, Martin Oehmen, Michael Orth, Hélène Padieu, Laurent Paterski, Nadia Peppa, Susana Pro Koivisto, Martina Di Renzo, Amandine Rialland, Niini Røren, Pavla Šašinková, Erika Timewell, Jenny Townhill, Patricia Trigo Cubillo, Wildson Vieira da Silva, Marleen R van Walsem, Carina Whalstedt, Marie-Noelle Witjes-Ané, Grzegorz Witkowski , Abigail Wright, Daniel Zielonka, Eugeniusz Zielonka, Paola Zinzi S3

AUSTRIA Graz (Medizinische Universitäts Graz, Psychiatrie): Raphael M Bonelli, Sabine Lilek, Karen Hecht, Brigitte Herranhof, Anna Holl (formerly Hödl), Hans-Peter Kapfhammer, Michael Koppitz, Markus Magnet, Nicole Müller, Daniela Otti, Annamaria Painold, Karin Reisinger, Monika Scheibl, Helmut Schöggl, Jasmin Ullah Innsbruck (Universitätsklinik Innsbruck, Neurologie): Eva-Maria Braunwarth, Florian Brugger, Lisa Buratti, Eva-Maria Hametner, Caroline Hepperger, Christiane Holas, Anna Hotter, Anna Hussl, Christoph Müller, Werner Poewe, Klaus Seppi, Fabienne Sprenger, Gregor Wenning BELGIUM Bierbeek: Andrea Boogaerts, Godelinde Calmeyn, Isabelle Delvaux, Dirk Liessens, Nele Somers Charleroi (Institut de Pathologie et de Génétique (IPG)): Michel Dupuit, Cécile Minet, Dominique van Paemel, Pascale Ribaï, Christine Verellen-Dumoulin Leuven: (Universitair Ziekenhuis Gasthuisberg,): Andrea Boogaerts, Wim Vandenberghe, Dimphna van Reijen CZECH REPUBLIC Prague (Extrapyramidové centrum, Neurologická klinika, 1. LF UK a VFN): Jiří Klempíř, Veronika Majerová, Jan Roth, Irena Stárková DENMARK Copenhagen (Neurogenetics Clinic, Danish Dementia Research Centre, Rigshospitalet, University of Copenhagen): Lena E. Hjermind, Oda Jacobsen, Jørgen E Nielsen, Ida Unmack Larsen, Tua Vinther-Jensen FINLAND Turku-Suvituuli (Rehabilitation Centre Suvituuli): Heli Hiivola, Hannele Hyppönen, Kirsti Martikainen, Katri Tuuha S4

FRANCE Angers (Centre de référence des maladies neurogénétique- CHU d’Angers): Philippe Allain, Dominique Bonneau, Marie Bost, Bénédicte Gohier, Marie-Anne Guérid, Audrey Olivier, Adriana Prundean, Clarisse Scherer-Gagou, Christophe Verny Bordeaux (Hôpital CHU Pellegrin): Blandine Babiloni, Sabrina Debruxelles, Charlotte Duché, Cyril Goizet, Laetitia Jameau, Danielle Lafoucrière, Umberto Spampinato Lille-Amiens: Lille (CHRU Roger Salengro) : Rekha Barthélémy, Christelle De Bruycker, Maryline Cabaret, Anne-Sophie Carette, Eric Decorte Luc Defebvre, Marie Delliaux, Arnaud Delval, Alain Destee, Kathy Dujardin, Marie-Hélène Lemaire, Sylvie Manouvrier, Mireille Peter, Lucie Plomhouse, Bernard Sablonnière, Clémence Simonin, Stéphanie Thibault-Tanchou, Isabelle Vuillaume Amiens (CHU Nord) : Marcellin Bellonet, Hassan Berrissoul, Stéphanie Blin, Françoise Courtin, Cécile Duru, Véronique Fasquel, Olivier Godefroy, Pierre Krystkowiak, Béatrice Mantaux, Martine Roussel, Sandrine Wannepain Marseille (Hôpital La Timone) : Jean-Philippe Azulay, Marie Delfini, Alexandre Eusebio, Frédérique Fluchere, Laura Mundler Strasbourg (Hôpital Civil) : Mathieu Anheim, Celine Julié, Ouhaid Lagha Boukbiza, Nadine Longato, Gabrielle Rudolf, Christine Tranchant, Marie-Agathe Zimmermann GERMANY Aachen (Universitätsklinikum Aachen, Neurologische Klinik): Christoph Michael Kosinski, Eva Milkereit, Daniela Probst, Kathrin Reetz, Christian Sass, Johannes Schiefer, Christiane Schlangen, Cornelius J. Werner Berlin (Klinik und Poliklinik für Neurologie - Charité - Universitätsmedizin Berlin): Harald Gelderblom, Josef Priller, Harald Prüß, Eike Jakob Spruth

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Bochum (Huntington-Zentrum (NRW) Bochum im St. Josef-Hospital): Gisa Ellrichmann, Lennard Herrmann, Rainer Hoffmann, Barbara Kaminski, Peter Kotz, Christian Prehn, Carsten Saft Dinslaken (Reha Zentrum in Dinslaken im Gesundheitszentrums Lang): Herwig Lange, Robert Maiwald Dresden (Universitätsklinikum Carl Gustav Carus an der Technischen Universität Dresden, Klinik und Poliklinik für Neurologie): Matthias Löhle, Antonia Maass, Simone Schmidt, Cecile Bosredon, Alexander Storch, Annett Wolz, Martin Wolz Freiburg (Universitätsklinik Freiburg, Neurologie): Philipp Capetian, Johann Lambeck, Birgit Zucker Hamburg (Universitätsklinikum Hamburg-Eppendorf, Klinik und Poliklinik für Neurologie): Kai Boelmans, Christos Ganos, Walburgis Heinicke, Ute Hidding, Jan Lewerenz, Alexander Münchau, Michael Orth, Jenny Schmalfeld, Lars Stubbe, Simone Zittel Hannover (Neurologische Klinik mit Klinischer Neurophysiologie, Medizinische Hochschule Hannover): Gabriele Diercks, Dirk Dressler, Heike Gorzolla, Christoph Schrader, Pawel Tacik Itzehoe (Schwerpunktpraxis Huntington, Neurologie und Psychiatrie): Michael Ribbat Marburg KPP (Klinik für Psychiatrie und Psychotherapie Marburg-Süd): Bernhard Longinus Marburg Uni (Universität Marburg, Neurologie): Katrin Bürk, Jens Carsten Möller, Ida Rissling München (Huntington-Ambulanz im Neuro-Kopfzentrum - Klinikum rechts der Isar der Neurologischen Klinik und Poliklinik der Technischen Universität München): Mark Mühlau, Alexander Peinemann, Michael Städtler, Adolf Weindl, Juliane Winkelmann, Cornelia Ziegler

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Münster (Universitätsklinikum Münster, Klinik und Poliklinik für Neurologie): Natalie Bechtel, Heike Beckmann, Stefan Bohlen, Eva Hölzner, Herwig Lange, Ralf Reilmann, Stefanie Rohm, Silke Rumpf , Sigrun Schepers, Natalia Weber Taufkirchen (Isar-Amper-Klinikum - Klinik Taufkirchen (Vils)): Matthias Dose, Gabriele Leythäuser, Ralf Marquard, Tina Raab, Alexandra Wiedemann Ulm (Universitätsklinikum Ulm, Neurologie): Katrin Barth, Andrea Buck, Julia Connemann, Daniel Ecker, Carolin Geitner, Christine Held, Andrea Kesse, Bernhard Landwehrmeyer, Christina Lang, Jan Lewerenz, Franziska Lezius, Solveig Nepper, Anke Niess, Michael Orth, Ariane Schneider, Daniela Schwenk, Sigurd Süßmuth, Sonja Trautmann, Patrick Weydt ITALY Bari Clinica Neurologica - Neurophysiopatology of Pain Unit UNIVERSITA' DI BARI): Claudia Cormio, Vittorio Sciruicchio, Claudia Serpino, Marina de Tommaso Bologna (DIBINEM - Alma Mater Studiorum - Università di Bologna; IRCCS Istituto delle Scienze Neurologiche di Bologna): Sabina Capellari, Pietro Cortelli, Roberto Galassi, Rizzo Giovanni, Roberto Poda, Cesa Scaglione Florence (Dipartimento di Scienze Neurologiche e Psichiatriche Universita' degli Studi di Firenze-Azienda Ospedaliera Universitaria Careggi): Elisabetta Bertini, Elena Ghelli, Andrea Ginestroni, Francesca Massaro, Claudia Mechi, Marco Paganini, Silvia Piacentini, Silvia Pradella, Anna Maria Romoli, Sandro Sorbi Genoa (Dipartimento di Neuroscienze, Riabilitazione, Oftalmologia, Genetica e Scienze Materno-Infantili, Università di Genova): Giovanni Abbruzzese, Monica Bandettini di Poggio, Giovanna Ferrandes, Paola Mandich, Roberta Marchese Milan (Fondazione IRCCS Istituto Neurologico Carlo Besta): Alberto Albanese, Daniela Di Bella, Anna Castaldo, Stefano Di Donato, Cinzia Gellera, Silvia Genitrini, Caterina Mariotti, Daniela Monza, Lorenzo Nanetti, Dominga Paridi, Paola Soliveri, Chiara Tomasello S7

Naples (Dipartimento di Neuroscienze, Scienze Riproduttive e Odontostomatologiche, Università Federico II): Giuseppe De Michele, Luigi Di Maio, Marco Massarelli, Silvio Peluso, Alessandro Roca, Cinzia Valeria Russo, Elena Salvatore, Pierpaolo Sorrentino Pozzilli (IS) (Centro di Neurogenetica e Malattie Rare - IRCCS Neuromed): Enrico Amico, Mariagrazia Favellato, Annamaria Griguoli, Irene Mazzante, Martina Petrollini, Ferdinando Squitieri and Rome (Lega Italiana Ricerca Huntington e malattie correlate - onlus / www.LIRH.it): Barbara D'Alessio, Chiara Esposito Rome (Istituto di Farmacologia Traslazionale & Istituto di Scienze e Tecnologie della Cognizione /CNR, Istituto di Neurologia Università Cattolica del Sacro Cuore): Anna Rita Bentivoglio, Marina Frontali, Arianna Guidubaldi, Tamara Ialongo, Gioia Jacopini, Carla Piano, Silvia Romano, Francesco Soleti, Maria Spadaro, Paola Zinzi NETHERLANDS Enschede (Medisch Spectrum Twente): Monique S.E. van Hout, Marloes E. Verhoeven, Jeroen P.P. van Vugt, A. Marit de Weert Groningen (Polikliniek Neurologie): J.J.W. Bolwijn, M. Dekker, B. Kremer, K.L. Leenders, J.C.H. van Oostrom Leiden (Leiden University Medical Centre (LUMC)): Simon J. A. van den Bogaard, Reineke Bos, Eve M. Dumas, Ellen P. ‘t Hart, Raymund A.C. Roos Nijmegen (Universitair Medisch Centrum St. Radboud, Neurology): Berry Kremer, C.C.P. Verstappen NORWAY Oslo University Hospital (Rikshospitalet, Dept. of Medical Genetics and Dept. of Neurology): Olaf Aaserud, Jan Frich C., Arvid Heiberg, Marleen R. van Walsem, Ragnhild Wehus

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Oslo University Hospital (Ulleval, Dept. of Medical Genetics and Dept.of Neurorehabilitation): Kathrine Bjørgo, Madeleine Fannemel, Per F. Gørvell, Eirin Lorentzen, Susana Pro Koivisto, Lars Retterstøl, Bodil Stokke Trondheim (St. Olavs Hospital): Inga Bjørnevoll, Sigrid Botne Sando POLAND Gdansk (St. Adalbert Hospital, Gdansk, Medical University of Gdansk, Neurological and Psychiatric Nursing Dpt.): Artur Dziadkiewicz, Malgorzata Nowak, Piotr Robowski, Emilia Sitek, Jaroslaw Slawek, Witold Soltan, Michal Szinwelski Katowice (Medical University of Silesia, Katowice): Magdalena Blaszcyk, Magdalena Boczarska-Jedynak, Ewelina Ciach-Wysocka, Agnieszka Gorzkowska, Barbara Jasinska-Myga, Gabriela Kłodowska–Duda, Gregorz Opala, Daniel Stompel Krakow (Krakowska Akademia Neurologii): Krzysztof Banaszkiewicz, Dorota Boćwińska, Kamila Bojakowska-Jaremek, Małgorzata Dec, Malgorzata Krawczyk, Monika Rudzińska, Elżbieta Szczygieł, Andrzej Szczudlik, Anna Wasielewska, Magdalena Wójcik Poznan (Poznan University of Medical Sciences, Poland): Anna Bryl, Anna Ciesielska, Aneta Klimberg, Jerzy Marcinkowski, Husam Samara, Justyna Sempołowicz, Daniel Zielonka Warsaw-MU (Medical University of Warsaw, Neurology): Anna Gogol (formerly Kalbarczyk), Piotr Janik, Hubert Kwiecinski, Zygmunt Jamrozik Warsaw-IPiN (Institute of Psychiatry and Neurology Dep. of Genetics, First Dep. of Neurology): Jakub Antczak, Katarzyna Jachinska, Wioletta Krysa, Maryla Rakowicz, Przemyslaw Richter, Rafal Rola, Danuta Ryglewicz, Halina Sienkiewicz-Jarosz, Iwona Stępniak, Anna Sułek, Grzegorz Witkowski, Jacek Zaremba, Elzbieta Zdzienicka, Karolina ZieoraJakutowicz PORTUGAL Coimbra (Hospital Universitário de Coimbra): Cristina Januário, Filipa Júlio

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Lisbon (Clinical Pharmacology Unit, Instituto de Medicina Molecular, Faculty of Medicine, University of Lisbon): Joaquim J Ferreira, Miguel Coelho, Leonor Correia Guedes, Tiago Mendes, Tiago Mestre, Anabela Valadas Porto (Hospital de São João, (Faculdade de Medicina da Universidade do Porto)): Carlos Andrade, Miguel Gago, Carolina Garrett, Maria Rosália Guerra. SPAIN Badajoz (Hospital Infanta Cristina): Carmen Durán Herrera, Patrocinio Moreno Garcia Barcelona-Hospital Mútua de Terrassa : Miquel Aguilar Barbera, Dolors Badenes Guia, Laura Casas Hernanz , Judit López Catena, Pilar Quiléz Ferrer, Ana Rojo Sebastián, Gemma Tome Carruesco Barcelona-Bellvitge (Hospital Universitari de Bellvitge): Jordi Bas, Núria Busquets, Matilde Calopa Barcelona-Merced (Hospital Mare de Deu de La Merced): Misericordia Floriach Robert, Celia Mareca Viladrich, Jesús Miguel Ruiz Idiago, Antonio Villa Riballo Burgos (Servicio de Neurología Hospital General Yagüe): Esther Cubo, Cecilia Gil Polo, Natividad Mariscal Perez, Jessica Rivadeneyra Granada (Hospital Universitario San Cecilio, Neurología): Francisco Barrero, Blas Morales Madrid-Clinico (Hospital Clínico Universitario San Carlos): María Fenollar, Rocío GarcíaRamos García, Paloma Ortega, Clara Villanueva Madrid RYC (Hospital Ramón y Cajal, Neurología): Javier Alegre, Mónica Bascuñana, Juan Garcia Caldentey, Marta Fatás Ventura, Guillermo García Ribas, Justo García de Yébenes, José Luis López-Sendón Moreno, Patricia Trigo Cubillo Madrid FJD (Madrid-Fundación Jiménez Díaz): Javier Alegre, Fernando Alonso Frech, Justo García de Yébenes, Pedro J García Ruíz, Asunción Martínez-Descals, Rosa Guerrero, María José Saiz Artiga, Vicenta Sánchez

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Murcia (Hospital Universitario Virgen de la Arrixaca): María Fuensanta Noguera Perea, Lorenza Fortuna, Salvadora Manzanares, Gema Reinante, María Martirio Antequera Torres, Laura Vivancos Moreau Oviedo (Hospital Central de Asturias): Sonia González González, Luis Menéndez Guisasola, Carlos Salvador, Esther Suaréz San Martín Palma de Mallorca (Hospital Universitario Son Espases): Inés Legarda Ramirez, Aranzazú Gorospe, Mónica Rodriguez Lopera, Penelope Navas Arques, María José Torres Rodríguez, Barbara Vives Pastor Pamplona (Complejo Hospitalario de Navarra): Itziar Gaston, Maria Dolores MartinezJaurrieta, Maria A. Ramos-Arroyo Sevilla ("Hospital Virgen Macarena"): Jose Manuel Garcia Moreno, Carolina Mendez Lucena, Fatima Damas Hermoso, Eva Pacheco Cortegana, José Chacón Peña, Luis Redondo Sevilla (Hospital Universitario Virgen del Rocío): Fátima Carrillo, María Teresa Cáceres, Pablo Mir, María José Lama Suarez, Laura Vargas-González Valencia (Hospital la Fe): Maria E. Bosca, Francisco Castera Brugada, Juan Andres Burguera, Anabel Campos Garcia, Carmen Peiró Vilaplana SWEDEN Göteborg (Sahlgrenska University Hospital): Peter Berglund, Radu Constantinescu, Gunnel Fredlund, Ulrika Høsterey-Ugander, Petra Linnsand, Liselotte Neleborn-Lingefjärd, Jan Wahlström, Magnus Wentzel Umeå (Umeå University Hospital): Ghada Loutfi, Carina Olofsson, Eva-Lena Stattin, Laila Westman, Birgitta Wikström SWITZERLAND Bern: Jean-Marc Burgunder, Yanik Stebler (Swiss HD Zentrum), Alain Kaelin, Irene Romero, Michael Schüpbach, Sabine Weber Zaugg (Zentrum für Bewegungsstörungen, Neurologische Klinik und Poliklinik, Universität Bern) S11

Zürich (Department of Neurology, University Hospital Zürich): Maria Hauer, Roman Gonzenbach, Hans H. Jung, Violeta Mihaylova, Jens Petersen UNITED KINGDOM Aberdeen (NHS Grampian Clinical Genetics Centre & University of Aberdeen): Roisin Jack, Kirsty Matheson, Zosia Miedzybrodzka, Daniela Rae, Sheila A Simpson, Fiona Summers, Alexandra Ure, Vivien Vaughan Birmingham (The Barberry Centre, Dept of Psychiatry): Shahbana Akhtar, Jenny Crooks, Adrienne Curtis, Jenny de Souza (Keylock), John Piedad, Hugh Rickards, Jan Wright Bristol (North Bristol NHs Trust, Southmead hospital): Elizabeth Coulthard, Louise Gethin, Beverley Hayward, Kasia Sieradzan, Abigail Wright Cambridge (Cambridge Centre for Brain Repair, Forvie Site): Matthew Armstrong, Roger A. Barker, Deidre O’Keefe, Anna Di Pietro, Kate Fisher, Anna Goodman, Susan Hill, Ann Kershaw, Sarah Mason, Nicole Paterson, Lucy Raymond, Rachel Swain, Natalie Valle Guzman Cardiff (Schools of Medicine and Biosciences, Cardiff University): Monica Busse, Cynthia Butcher, Jenny Callaghan, Stephen Dunnett, Catherine Clenaghan, Ruth Fullam, Olivia Handley, Sarah Hunt, Lesley Jones, Una Jones, Hanan Khalil, Sara Minster, Michael Owen, Kathleen Price, Anne Rosser, Jenny Townhill Edinburgh (Molecular Medicine Centre, Western General Hospital, Department of Clinical Genetics): Maureen Edwards, Carrie Ho (Scottish Huntington´s Association), Teresa Hughes (Scottish Huntington´s Association), Marie McGill, Pauline Pearson, Mary Porteous, Paul Smith (Scottish Huntington´s Association) Fife (Scottish Huntington's Association Whyteman's Brae Hospital): Peter Brockie, Jillian Foster, Nicola Johns, Sue McKenzie, Jean Rothery, Gareth Thomas, Shona Yates Gloucester (Department of Neurology Gloucestershire Royal Hospital): Liz Burrows, Carol Chu, Amy Fletcher, Deena Gallantrae, Stephanie Hamer, Alison Harding, Stefan Klöppel, Alison

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Kraus, Fiona Laver, Monica Lewis, Mandy Longthorpe, Ivana Markova, Ashok Raman, Nicola Robertson, Mark Silva, Aileen Thomson, Sue Wild, Pam Yardumian Hull (Castle Hill Hospital): Carol Chu, Carole Evans, Deena Gallentrae, Stephanie Hamer, Alison Kraus, Ivana Markova, Ashok Raman Leeds (Chapel Allerton Hospital, Department of Clinical Genetics): Leeds (Chapel Allerton Hospital, Clinical Genetics): Carol Chu, Stephanie Hamer, Emma Hobson, Stuart Jamieson, Alison Kraus, Ivana Markova, Ashok Raman, Hannah Musgrave, Liz Rowett, Jean Toscano, Sue Wild, Pam Yardumian Leicester (Leicestershire Partnership Trust, Mill Lodge): Colin Bourne, Jackie Clapton, Carole Clayton, Heather Dipple, Dawn Freire-Patino, Janet Grant, Diana Gross, Caroline Hallam, Julia Middleton, Ann Murch, Catherine Thompson Liverpool (Walton Centre for Neurology and Neurosurgery): Sundus Alusi, Rhys Davies, Kevin Foy, Emily Gerrans, Louise Pate London (Guy's Hospital): Thomasin Andrews, Andrew Dougherty, Charlotte Golding, Fred Kavalier, Hana Laing, Alison Lashwood, Dene Robertson, Deborah Ruddy, Alastair Santhouse, Anna Whaite London (The National Hospital for Neurology and Neurosurgery): Thomasin Andrews, Stefania Bruno, Karen Doherty, Charlotte Golding, Salman Haider, Davina Hensman, Nayana Lahiri, Monica Lewis, Marianne Novak, Aakta Patel, Nicola Robertson, Elisabeth Rosser, Sarah Tabrizi, Rachel Taylor, Thomas Warner, Edward Wild Manchester (Genetic Medicine, University of Manchester, Manchester Academic Health Sciences Centre and Central Manchester University Hospitals NHS Foundation Trust): Natalie Arran, Judith Bek, Jenny Callaghan, David Craufurd, Ruth Fullam, Marianne Hare, Liz Howard, Susan Huson, Liz Johnson, Mary Jones, Helen Murphy, Emma Oughton, Lucy Partington-Jones, Dawn Rogers, Andrea Sollom, Julie Snowden, Cheryl Stopford, Jennifer Thompson, Iris Trender-Gerhard, Nichola Verstraelen (formerly Ritchie), Leann Westmoreland S13

Oxford (Oxford University Hospitals NHS Trust, Dept. of Neurosciences, University of Oxford): Richard Armstrong, Kathryn Dixon, Andrea H Nemeth, Gill Siuda, Ruth Valentine Plymouth (Plymouth Huntington Disease Service, Mount Gould Hospital): David Harrison, Max Hughes, Andrew Parkinson, Beverley Soltysiak Sheffield (The Royal Hallamshire Hospital– Sheffield Children’s Hospital): Oliver Bandmann, Alyson Bradbury, Paul Gill, Helen Fairtlough, Kay Fillingham, Isabella Foustanos, Mbombe Kazoka, Kirsty O’Donovan, Nadia Peppa, Cat Taylor, Katherine Tidswell, Oliver Quarrell EHDN’s associate site in Singapore: National Neuroscience Institute Singapore: JeanMarc Burgunder, Puay Ngoh Lau, Emmanul Pica, Louis Tan

Huntington Study Group PREDICT-HD Study Investigators, Coordinators, Motor Raters, Cognitive Raters: Peg Nopoulos, MD, Robert Rodnitzky, MD, Ergun Uc, MD, BA, Leigh J. Beglinger, PhD, Vincent A. Magnotta, PhD, Stephen Cross, BA, Nicholas Doucette, BA, Andrew Juhl, BS, Jessica Schumacher, BA, Mycah Kimble, BA, Pat Ryan, MS, MA, Jessica Wood, MD, PhD, Eric A. Epping, MD, PhD, Thomas Wassink, MD, and Teri Thomsen, MD (University of Iowa Hospitals and Clinics, Iowa City, Iowa, USA); David Ames, MD, Edmond Chiu, MD, Phyllis Chua, MD, Olga Yastrubetskaya, PhD, Joy Preston, Anita Goh, D.Psych, and Angela Komiti, BS, MA (The University of Melbourne, Kew, Victoria, Australia); Lynn Raymond, MD, PhD, Rachelle Dar Santos, BSc, Joji Decolongon, MSC, and David Weir, BSc (University of British Columbia, Vancouver, British Columbia, Canada); Adam Rosenblatt, MD, Christopher A. Ross, MD, PhD, Barnett Shpritz, BS, MA, OD, and Claire Welsh (Johns Hopkins University, Baltimore, Maryland, USA);

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William M. Mallonee, MD and Greg Suter, BA (Hereditary Neurological Disease Centre, Wichita, Kansas, USA); Ali Samii, MD, Hillary Lipe, ARNP, and Kurt Weaver, PhD (University of Washington and VA Puget Sound Health Care System, Seattle, Washington, USA); Randi Jones, PhD, Cathy Wood-Siverio, MS, Stewart A. Factor, DO, and Claudia Testa, MD, PhD (Emory University School of Medicine, Atlanta, Georgia, USA); Roger A. Barker, BA, MBBS, MRCP, Sarah Mason, BSC, Anna Goodman, PhD, and Anna DiPietro (Cambridge Centre for Brain Repair, Cambridge, UK); Elizabeth McCusker, MD, Jane Griffith, RN, and Kylie Richardson, PhD (Westmead Hospital, Sydney, Australia); Bernhard G. Landwehrmeyer, MD, Daniel Ecker, MD, Patrick Weydt, MD, Michael Orth MD, PhD, Sigurd Süβmuth, MD, RN, Katrin Barth, RN, and Sonja Trautmann, RN (University of Ulm, Ulm, Germany); Kimberly Quaid, PhD, Melissa Wesson, MS, and Joanne Wojcieszek, MD (Indiana University School of Medicine, Indianapolis, IN); Mark Guttman, MD, Alanna Sheinberg, BA, Adam Singer, and Janice Stober, BA, BSW (Centre for Addiction and Mental Health, University of Toronto, Markham, Ontario, Canada); Susan Perlman, MD and Arik Johnson, PsyD (University of California, Los Angeles Medical Center, Los Angeles, California, USA); Michael D. Geschwind, MD, PhD and Jon Gooblar, BA (University of California San Francisco, California, USA); Tom Warner, MD, PhD, Stefan Klöppel, MD, Maggie Burrows, RN, BA, Marianne Novak, MD, Thomasin Andrews, MD, BSC, MRCP, Elisabeth Rosser, MBBS, FRCP, and Sarah Tabrizi, BSC, PhD (National Hospital for Neurology and Neurosurgery, London, UK); Anne Rosser, MD, PhD, MRCP and Kathy Price, RN (Cardiff University, Cardiff, Wales, UK);

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Amy Chesire, LCSW-R, MSG, Frederick Marshall, MD, and Mary Wodarski, BA (University of Rochester, Rochester, New York, USA); Oksana Suchowersky, MD, FRCPC (now at University of Alberta, Edmonton), Sarah Furtado, MD, PhD, FRCPC, and Mary Lou Klimek, RN, BN, MA (University of Calgary, Calgary, Alberta, Canada); Peter Panegyres, MB, BS, PhD, Carmela Connor, BP, MP, DP, and Elizabeth Vuletich, BSC (Neurosciences Unit, Graylands, Selby-Lemnos & Special Care Health Services, Perth, Australia); Joel Perlmutter, MD and Stacey Barton, MSW, LCSW (Washington University, St. Louis, Missouri, USA); Sheila A. Simpson, MD, Daniela Rae, RN, and Zosia Miedzybrodzka, PhD (Clinical Genetics Centre, Aberdeen, Scotland, UK); David Craufurd, MD, Ruth Fullam, BSC, and Elizabeth Howard, MD (University of Manchester, Manchester, UK) Pietro Mazzoni, MD, PhD, Karen Marder, MD, MPH, Carol Moskowitz, MS, and Paula Wasserman, MA (Columbia University Medical Center, New York, New York, USA); Diane Erickson, RN, Dawn Miracle, BS, MS, and Rajeev Kumar, MD (Colorado Neurological Institute, Englewood, Colorado, USA); Vicki Wheelock, MD, Terry Tempkin, RNC, MSN, Nicole Mans, BA, MS, and Kathleen Baynes, PhD (University of California Davis, Sacramento, California, USA); Joseph Jankovic, MD, Christine Hunter, RN, CCRC, and William Ondo, MD (Baylor College of Medicine, Houston, Texas, USA); Justo Garcia de Yebenes, MD, Monica Bascunana Garde, Marta Fatas, BA, and Jose Luis Lópenz Sendon, MD (Hospital Ramón y Cajal, Madrid, Spain); Martha Nance, MD, Dawn Radtke, RN, and David Tupper, PhD (Hennepin County Medical Center, Minneapolis, Minnesota, USA); S16

Wayne Martin, MD, Pamela King, BScN, RN, and Satwinder Sran, BSC (University of Alberta, Edmonton, Alberta, Canada); Anwar Ahmed, PhD, Stephen Rao, PhD, Christine Reece, BS, Janice Zimbelman, PhD, PT, Alexandra Bea, BA, and Emily Newman, BA (Cleveland Clinic Foundation, Cleveland, Ohio, USA); Steering Committee Jane Paulsen, PhD, Principal Investigator, Eric A. Epping, MD, PhD, Douglas Langbehn, MD, PhD, Hans Johnson, PhD, Megan Smith, PhD, Janet Williams, PhD, RN, FAAN (University of Iowa Hospitals and Clinics, Iowa City, IA); Elizabeth Aylward, PhD (Seattle Children's Research Institute, WA); Kevin Biglan, MD (University of Rochester, Rochester, NY); Blair Leavitt, MD (University of British Columbia, Vancouver, BC, Canada); Marcy MacDonald, PhD (Massachusetts General Hospital); Martha Nance, MD (Hennepin County Medical Center, Minneapolis, MN); Jean Paul Vonsattel, PhD (Columbia University Medical Center, New York, NY). Scientific Sections Bio Markers: Blair Leavitt, MDCM, FRCPC (Chair) and Michael Hayden, PhD (University of British Columbia); Stefano DiDonato, MD (Neurological Insitute “C. Besta,” Italy); Ken Evans, PhD (Ontario Cancer Biomarker Network); Wayne Matson, PhD (VA Medical Center, Bedford, MA); Asa Peterson, MD, PhD (Lund University, Sweden), Sarah Tabrizi, PhD (National Hospital for Neurology and Neurology and Neurosurgery, London). Cognitive: Deborah Harrington, PhD (Chair, University of California, San Diego), Tamara Hershey, PhD (Washington University Cognitive Science Battery Development); Holly Westervelt, PhD (Chair, Quality Control and Training, Alpert Medical School of Brown University), Jennifer Davis, PhD, Pete Snyder, PhD, and Geoff Tremont, PhD, MS (Scientific Consultants, Alpert Medical School of Brown University); Megan Smith, PhD (Chair, Administration), David J. Moser, PhD, Leigh J. Beglinger, PhD (University of Iowa); Lucette S17

Cysique, PhD (St. Vincent’s/University of Melbourne, Australia); Carissa Gehl, PhD (VA Medical Center, Iowa City, IA); Robert K. Heaton, PhD, David Moore, PhD, Joanne Hamilton, PhD, and David Salmon, PhD (University of California, San Diego); Kirsty Matheson (University of Aberdeen); Paula Shear, PhD (University of Cincinnati); Karen Siedlecki, PhD (Fordham University); Glenn Smith, PhD (Mayo Clinic); and Marleen Van Walsem (EHDN). Functional Assessment: Janet Williams, PhD (Co-Chair), Leigh J. Beglinger, PhD, Anne Leserman, MSW, LISW, Justin O’Rourke, MA, Bradley Brossman, MA, Eunyoe Ro, MA (University of Iowa); Rebecca Ready, PhD (University of Massachusetts); Anthony Vaccarino, PhD (Ontario Cancer Biomarker Network); Sarah Farias, PhD (University of California, Davis); Noelle Carlozzi, PhD (Kessler Medical Rehabilitation Research & Education Center); and Carissa Gehl, PhD (VA Medical Center, Iowa City, IA). Genetics: Marcy MacDonald, PhD (Co-Chair), Jim Gusella, PhD, and Rick Myers, PhD (Massachusetts General Hospital); Michael Hayden, PhD (University of British Columbia); Tom Wassink, MD (Co-Chair) and Eric A. Epping, MD, PhD (University of Iowa). Imaging: Administrative: Ron Pierson, PhD (Chair), Kathy Jones, BS, Jacquie Marietta, BS, William McDowell, AA, Steve Dunn, BA, Greg Harris, BS, Eun Young Kim, MS, and Yong Qiang Zhao, PhD (University of Iowa); John Ashburner, PhD (Functional Imaging Lab, London); Vince Calhoun, PhD (University of New Mexico); Steve Potkin, MD (University of California, Irvine); Klaas Stephan, MD, PhD (University College of London); and Arthur Toga, PhD (University of California, Los Angeles). Striatal: Elizabeth Aylward, PhD (Chair, Seattle Children's Research Institute) and Kurt Weaver, PhD (University of Washington and VA Puget Sound Health Care System, Seattle, Washington). Surface Analysis: Peg Nopoulos, MD (Chair), Eric Axelson, BSE, and Jeremy Bockholt, BS (University of Iowa). S18

Shape Analysis: Christopher A. Ross (Chair), MD, PhD, Michael Miller, PhD, and Sarah Reading, MD (Johns Hopkins University); Mirza Faisal Beg, PhD (Simon Fraser University). DTI: Vincent A. Magnotta, PhD (Chair, University of Iowa); Karl Helmer, PhD (Massachusetts General Hospital); Kelvin Lim, MD (University of Ulm, Germany); Mark Lowe, PhD (Cleveland Clinic); Sasumu Mori, PhD (Johns Hopkins University); Allen Song, PhD (Duke University); and Jessica Turner, PhD (University of California, Irvine). fMRI: Steve Rao, PhD (Chair), Erik Beall, PhD, Katherine Koenig, PhD, Mark Lowe, PhD, Michael Phillips, MD, Christine Reece, BS, and Jan Zimbelman, PhD, PT (Cleveland Clinic). Motor: Kevin Biglan, MD (University of Rochester), Karen Marder, MD (Columbia University), and Jody Corey-Bloom, MD, PhD (University of California, San Diego) all Co-Chairs; Michael Geschwind, MD, PhD (University of California, San Francisco); and Ralf Reilmann, MD (Muenster, Germany). Psychiatric: Eric A. Epping, MD, PhD (Chair), Nancy Downing, RN, MSN, Jess Fiedorowicz, MD, Robert Robinson, MD, and Megan Smith, PhD (University of Iowa); Karen Anderson, MD (University of Maryland); David Craufurd, MD (University of Manchester); Mark Groves, MD (Columbia University); Anthony Vaccarino, PhD and Ken Evans, PhD (Ontario Cancer Biomarker Network); Hugh Rickards, MD (Queen Elizabeth Psychiatric Hospital); and Eric van Duijn, MD (Leiden University Medical Center, Netherlands). Core Sections Statistics: Douglas Langbehn, MD, PhD (Chair) and James Mills, MEd, MS (University of Iowa); and David Oakes, PhD (University of Rochester). Recruitment/Retention: Martha Nance, MD (Chair, University of Minnesota); Anne Leserman, MSW, LISW, Stacie Vik, BA, Christine Anderson, BA, Nick Doucette, BA, Kelly Herwig, BA, MS, Mycah Kimble, BA, Pat Ryan, MSW, LISW, MA, Jessica Schumacher, BA, Kelli Thumma, BA, and Elijah Waterman, BA (University of Iowa); and Norm Reynolds, MD (University of Wisconsin, Milwaukee). S19

Ethics: Cheryl Erwin, JD, PhD, (Chair, McGovern Center for Health, Humanities and the Human Spirit); Eric A. Epping, MD, PhD and Janet Williams, PhD (University of Iowa); and Martha Nance, MD (University of Minnesota). IT/Management: Hans Johnson, PhD (Chair), R.J. Connell, BS, Paul Allen, AASC, Sudharshan Reddy Bommu, MS, Karen Pease, BS, Ben Rogers, BA, BSCS, Jim Smith, AS, Kent Williams, BSA, MCS, MS, Shuhua Wu, MCS, and Roland Zschiegner (University of Iowa). Program Management Administrative: Chris Werling-Witkoske (Chair), Karla Anderson, BS, Kristine Bjork, BA, Ann Dudler, Jamy Schumacher, Sean Thompson, BA (University of Iowa). Financial: Steve Blanchard, MSHA (Co-Chair), Machelle Henneberry, and Kelsey Montross, BA (University of Iowa).

Huntington Study Group COHORT (Cooperative Huntington Observational Research Study) Study Steering Committee: University of Rochester, Rochester, NY: Ira Shoulson, MD (principal investigator), Massachusetts General Hospital, Boston, MA: James Gusella, PhD (co–principal investigator), Indiana University School of Medicine, Indianapolis IN: Tatiana Foroud, PhD (coprincipal investigator), CHDI Foundation Inc., Princeton NJ: Irina Antonijevic, MD (member), Dan van Kammen, MD (member). Publications & Data Use Committee: Indiana University School of Medicine, Indianapolis IN: Tatiana Foroud, PhD (Chair), Johns Hopkins University, Baltimore MD: Ray Dorsey, MD (CoChair); CHDI Foundation Inc., Princeton NJ: John Warner, PhD (member), Joe Giuliano, BSN (member); Huntington’s Disease Society of America, New York NR: Louise Vetter (member); University of Alberta, Edmonton AB: Oksana Suchowersky, MD (member); University of Rochester, Rochester NY: Christopher Beck, PhD (member), David Oakes, PhD (member);

S20

Participating Investigators and Coordinators: University of Rochester, NY: Fred Marshall, MD (investigator); Columbia University Medical Center, New York NY: Karen Marder, MD (investigator), Steven Frucht, MD (investigator), Carol Moskowitz, MS (coordinator), Ronda Clouse, RN (coordinator) , Paula Wasserman, MA (coordinator); Rush University Medical Center, Chicago IL: Kathleen Shannon, MD (investigator), Jeana Jaglin, RN (coordinator); Baylor College of Medicine: Joseph Jankovic, MD (investigator), Alicia Palao, MA; University of Virginia, Charlottesville VA: Madaline Harrison, MD (investigator) ; University of Miami, Miami FL: Carlos Singer, MD (investigator), Monica Quesada (coordinator); Massachusetts General Hospital: Steven Hersch, MD (investigator), Diana Rosas, MD (investigator), Kalo Tanev, MD (investigator), Keith Malarick, BA (coordinator); University of Pennsylvania, Philadelphia PA: Amy Colcher, MD (investigator); University of South Florida, Tampa FL: Juan Sanchez-Ramos, MD (investigator); Ohio State University, Columbus OH: Sandra Kostyk, MD (investigator); University of Iowa, Iowa City IA: Jane Paulsen, PhD (investigator); Washington University, St Louis MO: Joel Perlmutter, MD (investigator), Samer Tabbal (investigator), MD; Johns Hopkins University, Baltimore MD: Christopher Ross, MD (investigator), Ray Dorsey (investigator), Frederick Nucifora, DO (investigator); University of Kansas Medical Center, Kansas City KS: Richard Dubinsky, MD (investigator), Hilary Dubinsky, BA (coordinator); University of Calgary, Calgary AB: Oksana Suchowersky, MD (investigator, now at University of Alberta, Edmonton), Sarah Furtado, MD (investigator), Mary Lou Klimek, MA (coordinator); Emory University School of Medicine, Atlanta GA: Randi Jones, PhD (investigator), Claudia Testa, MD (investigator), Stewart Factor, DO (investigator); Institute for Neurogenerative Disorders, New Haven CT: Dana Jennings, MD (investigator); Medical College of Georgia, Augusta GA: John Morgan, MD (investigator); Albany Medical College, Albany NY: Don Higgins, MD (investigator), Eric Mohlo, MD (investigator); The Centre for Addiction and Mental Health, Toronto ON: John Adams, MD (investigator); Boston University, Boston MA: Sam Frank, MD (investigator), Marie Saint-Hilaire, MD (investigator), Melissa Diggin, MS (coordinator); Wake Forest University School of S21

Medicine, Winston-Salem NC: Francis Walker, MD (investigator), Christine O’Neill, BS (coordinator), Victoria Hunt, RN (coordinator); Indiana University School of Medicine, Indianapolis IN: Kim Quaid, PhD (investigator); University of Tennessee Health Science Center, Memphis TN: Mark LeDoux, MD (investigator); University of British Columbia, Vancouver BC: Lynn Raymond, MD (investigator), Blair Leavitt, MD (investigator), Joji Decolongon, MSC (coordinator); University of California, Los Angeles CA: Susan Perlman, MD; University of California, San Diego CA: Jody Corey-Bloom, MD (investigator), Guerry Peavy, PhD (neuropsych rater), Jody Goldstein, BS (coordinator); Colorado Neurological Institute, Englewood CO: Rajev Kumar, MD (investigator); Westmead Hospital, Sydney NSW, Australia: Elizabeth McCusker, MD (investigator), Jane Griffith, RN (coordinator), Clemet Loy, MD (investigator); University of California Davis, Sacramento CA: Vicki Wheelock, MD (investigator), Teresa Tempkin, MSN (coordinator), Amanda Martin (coordinator); Hennepin County Medical Center, Minneapolis MN: Martha Nance, MD (investigator); University of Chicago, Chicago IL: Un Jung Kang, MD (investigator); Hereditary Neurological Disease Center, Wichita KS: William Mallonee, MD (investigator), Greg Suter, BA (coordinator); University of Cincinnati/Cincinnati Children’s Hospital, Cincinnati OH: Fredy Revilla, MD (investigator), Maureen Gartner, RN (coordinator); University of Connecticut, Farmington CT: Carolyn Drazinic, MD (investigator), Mary Jane Fitzpatrick, MS (coordinator); Hôtel-Dieu Hôpital-CHUM, Montreal QC: Michel Panisset, MD (investigator); University of Utah, Salt Lake City UT: Kevin Duff, PhD (investigator); Duke University Medical Center, Durham NC: Burton Scott, MD(investigator); University of Maryland School of Medicine, Baltimore MD: William Weiner, MD (investigator), Bradley Robottom, MD (investigator); St Vincent's Aged Mental Health Service (SVAMHS) Melbourne VC, Australia: Edmond Chiu, MD (investigator), Olga Yastrubetskaya, PhD (investigator), Andrew Churchyard, MD (investigator); University of Pittsburgh, Pittsburgh PA: Timothy Greenamyre, MD (investigator); Booth Gardner Parkinson's Care Center, Kirkland WA: Pinky Agarwal, MD (investigator). S22

Biostatistics/Coordination Center: University of Rochester, Rochester NY: David Oakes, PhD (biostatistician), Christopher Beck, PhD (biostatistician), Suzanne Robertson, PhD (project manager), Ken Eaton (database program manager), Pat Lindsay (information analyst), Lisa Deuel, BA (research assistant); DNA Genotyping Center: Center for Human Genetic Research, Massachusetts General Hospital, Boston MA: Marcy E. MacDonald, PhD (scientist). Contributors: University of Rochester, NY: Charlyne Hickey, MS (coordinator); Columbia University Medical Center, New York NY: Lisa Muratori, EDD (neuropsych rater), Elan Louis, MD (investigator); University of Iowa: Anne Leserman, MSW, Nick Doucette, BA (neuropsych rater), Eurgen Uc, MD (investigator), Robert Rodnitzky, MD (investigator), Stacie Vik, BA (neuropsych rater); University of Virginia, Charlottesville VA: Robert Davis, MSN (coordinator), Susan Dietrich (coordinator); Colorado Neurological Institute, Englewood CO: Vicki Segro, MS, Diane Erickson, RN (coordinator); University of Pittsburgh, Pittsburgh PA: Nancy Lucarelli, MA (coordinator); University of Kansas Medical Center, Kansas City KS: Janice Broyles, RN (coordinator); University of Texas, Galveston TX: Jeanene DeLaRosa (coordinator); Neurodegenerative Disorders Research, Subiaco WA, Australia: Peter Panegyres, MD (investigator); Washington University, St Louis MO: Amy Schmidt (coordinator), Stacy Barton, MSW (coordinator); Emory University School of Medicine, Atlanta GA: Elaine Sperin, LPN (coordinator); University of California, Los Angeles CA: Curtis Thiede, BS; Indiana University School of Medicine, Indianapolis IN: Elizabeth Zauber, MD (motor rater), Melissa Wesson, MS (coordinator); Massachusetts General Hospital: Robert McInnis, BA; Johns Hopkins University, Baltimore MD: Claire Welsh (coordinator); University of British Columbia, Vancouver BC: Allison Coleman, BSC (coordinator)

S23

Huntington Study Group PHAROS Study Steering Committee: Ira Shoulson, MD (principal investigator), Karl Kieburtz, MD, MPH (director, Clinical Trials Coordination Center), David Oakes (chief biostatistician), Elise Kayson, MS, RNC (project coordinator), Hongwei Zhao, ScD, M. Aileen Shinaman, JD (Huntington Study Group executive director), Megan Romer, MS, University of Rochester, Rochester, New York; Anne Young, MD, PhD (co-principal investigator), Steven Hersch, MD, PhD, Jack Penney, MD (deceased), Massachusetts General Hospital, Charlestown; Kevin Biglan, MD (medical monitor), The Johns Hopkins University, Baltimore, Maryland; Karen Marder, MD, MPH, Columbia University Medical Center, New York, New York; Jane Paulsen, PhD, University of Iowa, Iowa City; Kimberly Quaid, PhD, Indiana University School of Medicine, Indianapolis; Eric Siemers, MD, Lilly Corporate Center, Indianapolis, Indiana; Caroline Tanner, MD, The Parkinson’s Institute, Sunnyvale, California. Participating Investigators and Coordinators: William Mallonee, MD, David Palmer, MD (deceased), Greg Suter, BA, Hereditary Neurological Disease Centre, Wichita, Kansas; Richard Dubinsky, MD, Gary Gronseth, MD, R. Neil Schimke, MD, Carolyn Gray, RN, University of Kansas Medical Center, Kansas City; Martha Nance, MD, Scott Bundlie, MD, Dawn Radtke, RN, Hennepin County Medical Center/Minneapolis, Minnesota; Sandra Kostyk, MD, PhD, George W. Paulson, MD, Karen Thomas, DO, Nonna Stepanov, MD, Corrine Baic, BS, Ohio State University, Columbus; James Caress, MD, Francis Walker, MD, Vicki Hunt, RN, Wake Forest University School of Medicine, Winston-Salem, North Carolina; Sylvain Chouinard, MD, Guy Rouleau, MD, PhD, Hubert Poiffaut, RN, Brigitte Rioux (deceased), Hotel-Dieu Hospital-Centre hospitalier de l’universite de Montreal, Montreal, Quebec, Canada; Claudia Testa, MD, PhD, Timothy Greenamyre, MD, PhD, Joan Harrison, RN, Emory University School of Medicine, Atlanta, Georgia; Jody Corey-Bloom, MD, PhD, David Song, MD, Guerry Peavy, PhD, Jody Goldstein, BS, University of California, San Diego, LaJolla; Jane Paulsen, PhD, Henry Paulson, MD, Robert L. Rodnitzky, MD, Ania Mikos, BA, Becky Reese, BS, Laura Stierman, BS, Katie Williams, BA, Lynn Vining, RN, MSN, University of Iowa; S24

Karen Marder, MD, MPH, Elan Louis, MD, MSc, Carol Moskowitz, RN, Columbia University Medical Center; Kimberly Quaid, PhD, Joanne Wojcieszek, MD, Melissa Wesson, MS, Indiana University School of Medicine; Ali Samii, MD, Thomas Bird, MD, Hillary Lipe, ARNP, University of Washington & VA Puget Sound Health Care System, Seattle; Norman Reynolds, MD, Karen Blindauer, MD, Jeannine Petit, ANP, Medical College of Wisconsin, Milwaukee; Peter Como, PhD, Frederick Marshall, MD, Timothy Counihan, MD, Kevin Biglan, MD, Carol Zimmerman, RN, University of Rochester; Penelope Hogarth, MD, John Nutt, MD, Pamela Andrews, BS, CCRC, Oregon Health & Science University, Portland; Steven Hersch, MD, PhD, Leslie Shinobu, MD, PhD, Diana Rosas, MD, Yoshio Kaneko, BA, Sona Gevorkian, MS, Paula Sexton, BA, CCRA, Massachusetts General Hospital; John Caviness, MD, Charles Adler, MD, PhD, Mayo Clinic Scottsdale, Scottsdale, Arizona; Vicki Wheelock, MD, David Richman, MD, Teresa Tempkin, RNC, MSN, University of California Davis, Sacramento; Chuang-Kuo Wu, MD, PhD, Hubert Fernandez, MD, Joseph H. Friedman, MD, Margaret Lannon, RN, MS, Brown University (Memorial Hospital of Rhode Island), Pawtucket; Lauren Seeberger, MD, Christopher O’Brien, MD, Sherrie Montellano, MA, Colorado Neurological Institute, Englewood; Ninith Kartha, MD, Sharin Sakurai, MD, PhD, Susan Hickenbottom, MD, PhD, Roger Albin, MD, PhD, Kristine Wernette, RN, MS, University of Michigan, Ann Arbor; Brad Racette, MD, Joel S. Perlmutter, MD, Laura Good, BA, Washington University, St Louis, Missouri; George Jackson, MD, PhD, Susan Perlman, MD, Shelley Segal, MD, Russell Carroll, MA, Laurie Carr, BS, UCLA Medical Center, Los Angeles, California; Wayne Martin, MD, Ted Roberts, MD, Marguerite Wieler, BSC, PT, University of Alberta, Edmonton, Alberta, Canada; Blair Leavitt, MD, Lorne Clarke, MD, CM, Lynn Raymond, MD, PhD, Joji Decolongon, MSC, Vesna Popovska, MD, Elisabeth Almqvist, RN, PhD, University of British Columbia, Vancouver, British Columbia, Canada; William Ondo, MD, Madhavi Thomas, MD, Tetsuo Ashizawa, MD, Joseph Jankovic, MD, Baylor College of Medicine, Houston, Texas; Robert Hauser, MD, Juan Sanchez-Ramos, MD, PhD, Karen Price, MA, Holly Delgado, RN, University of South Florida, Tampa; Sarah Furtado, MD, PhD, Anne S25

Louise LaFontaine, MD, Oksana Suchowersky (now at University of Alberta, Edmonton), MD, Mary Lou Klimek, RN, MA, University of Calgary, Calgary, Alberta, Canada; Rustom Sethna, MD, Mark Guttman, MD, Sandra Russell, BSW, RSW, Sheryl Elliott, RN, Centre for Addiction and Mental Health, Markham, Ontario, Canada; Marc Mentis, MB, CHB, Andrew Feigin, MD, Marie Cox, RN, BSN, Barbara Shannon, RN, North Shore University Hospital, Manhasset, New York; Alan Percy, MD, Leon Dure, MD, Donna Pendley, RN, Jane Lane, RN, BSN, University of Alabama at Birmingham; Madaline Harrison, MD, Elke Rost-Ruffner, RN, BSN, University of Virginia, Charlottesville; William Johnson, MD, University of Medicine and Dentistry of New Jersey Robert Wood Johnson Medical Center, Stratford; Amy Colcher, MD, Andrew Siderowf, MD, Mary Matthews, RN, University of Pennsylvania, Philadelphia; Danna Jennings, MD, Kenneth Marek, MD, Karen Caplan, MSW, Institute for Neurodegenerative Disorders, New Haven, Connecticut; Stewart Factor, DO, Donald Higgins, MD, Eric Molho, MD, Constance Nickerson, LPN, Sharon Evans, LPN, Diane Brown, RN (deceased), Albany Medical College, Albany, New York; Douglas Hobson, MD, Paul Shelton, MD, Shaun Hobson, RN, Winnipeg Clinic, Winnipeg, Manitoba, Canada; Carlos Singer, MD, Nestor Galvez-Jimenez, MD, William Koller, MD (deceased), Doris Martin, DDS, Kelly Lyons, PhD, Dinorah Rodriguez, RN, University of Miami, Miami, Florida; Kathleen Shannon, MD, Cynthia Comella, MD, Jean Jaglin, RN, CCRC, Rush Presbyterian–St Luke’s Medical Center, Chicago, Illinois; Karen Anderson, MD, William Weiner, MD (deceased), Kelly Dustin, RN, BSN, University of Maryland School of Medicine; Adam Rosenblatt, MD, Christopher Ross, MD, PhD, Deborah Pollard, The Johns Hopkins University; Marie H. Saint-Hilaire, MD, Peter Novak, MD, J. Stephen Fink, MD, PhD (deceased), Bonnie Hersh, MD, Melissa Diggin, MS, RN, Leslie Vickers, RN, MS, Boston University, Botson; Wallace Deckel, PhD, James Duffy, MD, Mary Jane Fitzpatrick, APRN, University of Connecticut, Hartford. Participating NIH Authors: Elizabeth Thomson, PhD, National Human Genome Research Institute, Bethesda, Maryland; National Institute of Neurological Disorders and Stroke, Bethesda. Event Monitoring Committee: Steven Hersch, S26

MD, PhD (cochair), Massachusetts General Hospital; Julie Stout, PhD (co-chair), James Calhoun, Indiana University; William Coryell, MD, Cheryl Erwin, JD, PhD, University of Iowa; Vicki Hunt, RN, Wake Forest University School of Medicine; Christopher Ross, MD, PhD, The Johns Hopkins University; Dorothy Vawter, PhD, Minnesota Center for Health Care Ethics. Ethics Committee: Lori Andrews, JD, Debbie Bury, James Calhoun, Chicago-Kent College of Law, Chicago, Illinois; Steven Hersch, MD, PhD (chair), Massachusetts General Hospital; Vicki Hunt, RN, Carl Leventhal, MD, Wake Forest University School of Medicine; Kimberly Quaid, PhD, Indiana University School of Medicine; Aileen Shinaman, JD, University of Rochester; Dorothy Vawter, PhD, Minnesota Center for Health Care Ethics; Nancy Wexler, PhD, Columbia University, New York. Biostatistics and Clinical Trials Coordination Center: Alicia Brocht, BA, Susan Daigneault, Karen Gerwitz, BS, Connie Orme, BA, Ruth Nobel, Victoria Ross, MA, Mary Slough, Arthur Watts, BS, Joe Weber, BS, Christine Weaver, Elaine Julian-Baros, University of Rochester. Genetic/ Environmental Modifiers Committee: Anne Young, MD, PhD (chair), Massachusetts General Hospital; Karen Marder, MD (co-chair), Columbia University Medical Center; Tatiana Foroud, PhD, Indiana University School of Medicine; James Gusella, PhD, Massachusetts General Hospital; David Housman, PhD, Massachusetts Institute of Technology, Boston; Marcy MacDonald, PhD, Massachusetts General Hospital; Richard Myers, PhD, Boston University; Caroline Tanner, MD, The Parkinson’s Institute; Rudolph Tanzi, PhD, Massachusetts General Hospital. Independent Monitoring Committee: Stanley Fahn, MD, Columbia University; Michael Conneally, PhD (deceased), Indiana University; Weiu-Yann Tsai, PhD, Columbia University. Scientific Advisory Committee: Flint Beal, MD, New York Hospital Department of Neurology, New York; David Housman, PhD, Massachusetts Institute of Technology, Boston; Christopher Ross, MD, PhD, The Johns Hopkins University; Rudolph Tanzi, PhD, Anne Young, MD, PhD, Massachusetts General Hospital; Claudia Kawas, MD, University of California, Irvine; Marie Francoise-Chesselet, MD, PhD, University of California Los Angeles. DNA Oversight Committee: Michael Conneally, PhD (deceased), Indiana University Medical Center; Martha S27

Nance, MD, University of Minnesota/ Minnesota VA Medical Center; Clifford Shults, MD (deceased), University of California, San Diego; Caroline Tanner, MD, The Parkinson’s Institute. Independent Rater Video Committee: Penelope Hogarth, MD, Oregon Health & Science University; Diana Rosas, MD, Massachusetts General Hospital; Hongwei Zhao, ScD, University of Rochester.

Huntington Study Group TREND-HD Study Steering Committee: E. Ray Dorsey (medical monitor), Ira Shoulson (principal investigator), Blair Leavitt (coprincipal investigator), Christopher Ross (coprincipal investigator), C. A. Beck, Elizabeth A. de Blieck, John. T. Greenamyre, Steven M. Hersch, Karl. Kieburtz, Karen Marder, Colleen McCallum (project manager), Carol Moskowitz, David Oakes, Adam Rosenblatt, and Aileen Shinaman. Participating Site Investigators/Coordinators: Steven. Frucht, Karen Marder, and Carol Moskowitz (Columbia University Medical Center, New York, New York); Russell Margolis (The Johns Hopkins University, Baltimore, Maryland); Kathleen Shannon and Jeanna Jaglin (Rush University Medical Center, Chicago, Illinois); Juan Sanchez-Ramos (University of South Florida, Tampa); Mark Guttman (The Centre for Addiction and Mental Health, Toronto, Ontario, Canada); Lynn A. Raymond and Jogi Decolongon (University of British Columbia, Vancouver, Canada); Peter Como, Richard Barbano, and Carol. Zimmerman (University of Rochester); Allison Seward (The Ohio State University, Columbus); Oksana Suchowersky (University of Calgary, Calgary, Alberta, Canada); Donald Higgins (Albany Medical College, Albany, New York); Joanne Wojcieszek (Indiana University School of Medicine, Indianapolis); Mandar Jog and Cheryl Horn (London Health Sciences Centre, Toronto); Richard M. Dubinsky (University of Kansas Medical Center, Kansas City); Wayne Martin (University of Alberta, Edmonton, Alberta, Canada); Andrew Feigin and Barbara Shannon (North Shore–Long Island Jewish Health System, Manhasset, New York); Martha Nance (Struthers Parkinson’s Center, Minneapolis, S28

Minnesota); Ninith Kartha (University of Michigan, Ann Arbor); Carlos Singer and Monica Quesada (University of Miami, Miami, Florida); Leigh Beglinger and Hank Paulson (The University of Iowa, Iowa City); John C. Morgan and Buff Dill (Medical College of Georgia, Augusta); Samuel Frank (Boston University, Boston, Massachusetts); Michael D. Geschwind (University of California, San Francisco); Madeline B. Harrison (University of Virginia, Charlottesville); Mark S. LeDoux (University of Tennessee Health Science Center, Memphis); Jody Corey-Bloom, Jody Goldstein (University of California, San Diego); and Herbert Fernandez (University of Florida, Gainesville). Biostatistics/Coordination Center: Christopher A. Beck, Keith Bourgeois, Elizabeth A. de Blieck, Colleen McCallum, Nichole McMullen, David Oakes, Victoria Ross, Lisa Rumfola, Art Watts, Christine. Weaver, and Tina Winebrenner (University of Rochester). Medical Monitoring: E. Ray. Dorsey (Clinical Trials Coordination Center, University of Rochester) and Bim Strausser (Bridge Biomedical Research and Consulting, San Francisco, California).

HD-MAPS Collaboration MA HD Center Without Walls: Jong-Min Lee, Diane Lucente, Vanessa Wheeler, Marcy E. MacDonald, James F. Gusella (Massachusetts General Hospital, Boston, MA) and Tiffany Hadzi, Audrey E. Hendricks, Richard H. Myers (Boston University School of Medicine, Boston, MA) Collaborating Investigators: Michael R. Hayden and Chris Kay (University of British Columbia, Vancouver, BC), Patrick J. Morrison (Belfast HSC Trust, Belfast, and University of Ulster, Coleraine, UK), Martha Nance (Hennepin County Medical Center, Minneapolis, MN), Christopher A. Ross and Russell L. Margolis (Johns Hopkins University, Baltimore, MD), Ferdinando Squitieri (IRCCS Neuromed , Pozzilli (IS), Italy), Cinzia Gellera and Stefano Di Donato (Istituto Nazionale Neurologico C. Besta, Milan, Italy), Estrella Gomez-Tortosa and S29

Carmen Ayuso (Fundación Jiménez Diaz, Madrid, Spain), Oksana Suchowersky (University of Alberta, Edmonton, AB), Ronald J. Trent (University of Sydney, New South Wales, Australia), Elizabeth McCusker (Westmead Hospital, Westmead Sydney, New South Wales, Australia), Andrea Novelletto (University Tor Vergata, Rome, Italy), Marina Frontali (Institute of Neurobiology and Molecular Medicine, Rome, Italy), Randi Jones (Emory University School of Medicine, Atlanta, GA), Tetsuo Ashizawa (University of Florida, Gainesville, FL), Samuel Frank and Marie-Helene Saint-Hilaire (Boston University School of Medicine, Boston, MA), Steven M. Hersch and Herminia D. Rosas (Massachusetts General Hospital, Charlestown, MA), Madaline B. Harrison (University of Virginia, Charlottesville, VA), Andrea Zanko (University of California, San Francisco, CA), Ruth K. Abramson (University of South Carolina School of Medicine, Columbia, SC), Karen Marder (Columbia University Medical Center, New York, NY), Jorge Sequeiros (Universidade do Porto, Portugal).

Clinical data and GWA Age at onset data were recorded by raters expert in HD, often through completion of the Unified Huntington's Disease Rating Scale (UHDRS) (Huntington Study Group, 1996). DNA samples from the EHDN Registry study were obtained from the BioRep Inc. repository (Milan, Italy) and phenotypic data recorded from each of the EHDN Registry sites were provided from the central EHDN database. The HTT CAG repeats of DNA samples were determined by a standard PCRsequencing method at the Massachusetts General Hospital (Perlis et al., 2010; Warner et al., 1993). DNA samples were genotyped in three phases (GWA1, GWA2, and GWA3) involving 1,089 (Affymetrix 6.0; Broad Institute), 2,874 (Illumina Omni 2.5; CIDR), and 3,447 subjects (Illumina Omni2.5; Broad Institute). After a series of quality control analyses, study subjects with European ancestry (based on genome-wide SNP data in comparison with the CEU and TSI HapMap populations) were identified for genotype imputation. Subsequently, a total of 4,082

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unique HD subjects were analyzed (GWA1, 977; GWA2, 974; GWA3, 2,131) to test effects of SNPs on residual age at onset of motor signs.

Quality control and genotype imputation Each genotype data set was independently subjected to a standard quality control pipeline. Briefly, SNPs with genotyping call rate >95%, minor allele frequency >1%, Hardy-Weinberg Equilibrium p-value >1E-6, and samples with genotyping call rate >95% were identified for subsequent genotype imputation. In addition, when data were available, samples with ambiguous gender, DNA contamination, and significant discordant genotype between fingerprint data and full data were excluded. Genotype imputation for all 3 GWA data sets was performed using the same programs and parameters to minimize the introduction of bias. Briefly, we used the MACH program (http://www.sph.umich.edu/csg/abecasis/MACH/tour/imputation.html) for haplotype phasing and MINIMAC program (http://genome.sph.umich.edu/wiki/Minimac) for genotype imputation. Each chromosome was split into fragments of 2500 SNPs with 500 overlapping SNPs for haplotype phasing (parameters; rounds 20, states 500 and default parameters for others). Then, imputation was carried out (parameters; rounds 20, state 500, and default parameters for others) using 1000 Genome Project data (phase 1, release 3; http://www.sph.umich.edu/csg/abecasis/MACH/download/1000G.2012-03-14.html). Resulting dosage data were transformed into PLINK program compatible genotype data. Subsequently, SNPs with imputation quality score (i.e., Rsq) >0.5 were used for subsequent association analysis. Only autosomes were imputed.

Association analysis and meta-analysis of continuous phenotype The GWA data sets were generated sequentially so when the first two GWA data sets were available they were combined to perform mixed effect model linear regression analysis. Residual age at onset of motor signs was modeled as a function of minor allele count of a SNP S31

and a set of covariates including gender and 4 ancestry characteristic values calculated by the PLINK program (i.e., MDS values). In addition, a relationship matrix was derived from actually typed SNP data to be included as a random effect in the univariate mixed effect model context by the GEMMA program (http://www.xzlab.org/software.html). Combined analysis of GWA1+GWA2 analysis revealed genome-wide significant signals on Chr15. For confirmation, GWA3 genotyping and analysis was performed. After genotyping and genotype imputation, a linear mixed effect model analysis was performed for GWA3 data and meta-analysis was carried out for the two sets of results (GWA1+GWA2 combined analysis and GWA3 analysis). We used the METAL program (http://genome.sph.umich.edu/wiki/METAL_Documentation; sample size-weighted analysis) to summarize the two results files.

Estimation of effect sizes In order to estimate effect sizes for associated SNPs, we performed univariate mixed effect model linear regression analysis using all 3 data sets combined by modeling residual age at onset as a function of SNP and a set of covariates of gender and ancestry characteristics. Effect sizes represent years of delay or hastening of age at onset of motor signs per minor allele of the tested SNP.

Extreme dichotomous analysis To confirm the association signals discovered using the continuous phenotype variable using an alternative analytical approach, we performed association analysis using the dichotomous extremes of age at onset after correcting for CAG repeat length. In principle, genetic modifiers with measurable effect sizes should be enriched in groups of individuals representing phenotypic extremes, an enrichment that can be assessed by comparing SNP allele frequency. This approach requires an initial phenotype model for determining extreme samples, but does not rely on the specific residual age at onset values for association analysis making it more S32

resistant to misestimates of age at onset although it does suffer loss of power due to the reduced sample size. We directly compared genome-wide SNP allele frequencies between extreme early and extreme late HD subjects, chosen based on the residual age at onset of motor signs of study subjects with CAG 40-55. We used the top and bottom 20% of the residual values based upon combined sorted data (816 extreme late and 816 extreme early subjects, respectively) and compared the two groups for allele counts of SNPs using logistic regression analysis using gender and 4 MDS values as covariates.

Conditional analysis Linkage disequilibrium between SNPs and the high density of markers in 1000 Genome Project imputed data contributes to discovery of a cluster of correlated SNPs in associated regions. In order to dissect independent association signals, we performed conditional analysis. Briefly, for a given region, the SNP with the most significant p-value in meta-analysis was included in the linear regression association analysis model as a covariate with other covariates (gender and 4 MDS values) to assess the extent to which association between the test SNP and the phenotype is determined by linkage disequilibrium with the covariate SNP. By comparing the significance for a given SNP in two models (one with and the other without the most significant SNP covariate), we identified SNPs whose association signals were minimally affected by the presence of the most significant SNP. When such signals were present, we took the most significant SNP in the first conditional analysis as a covariate SNP to condition the model to determine whether SNPs that are correlated with the most significantly associated SNP are independent of the covariate SNP.

Interaction analysis To test statistically for interaction between CAG repeat length and SNP genotype, actual age at onset in natural log scale (i.e., not residual age at onset) was modeled as a function of CAG S33

repeat length, genotype of a SNP, interaction between CAG and SNP, sex, and 4 ancestry characteristics covariates in a fixed model framework. Four SNPs representing independent association signals (rs146353869, rs2140734, rs1037699, and rs144287831) were tested independently. Although the p-values of CAG length and SNP in this analysis strongly supported the significant main effect of CAG and SNP on age at onset, none of the SNPs showed nominally significant interaction p-values with the CAG repeat length variable. Subsequently, the significance of interaction was determined between all pairs of SNPs from among these top 4 SNPs by modeling residual age at onset as a function of main effects of two SNPs, interaction term of two SNPs, sex, and ancestry characteristics covariates. None of the statistical models involving any of the 6 possible SNP pairs showed significant interaction by nominal p-value of 0.05. All variables used in the interaction analysis were centered.

Other phenotype analysis For selected SNPs with highly significant p-values in the meta-analysis of the continuous residual data, we performed association analysis using age at onset of cognitive signs and age at onset of psychiatric signs where the rater had recorded such data. As the UHDRS questionnaire requests onset age only for the first observed clinical sign, many of our subjects had only one measure of onset. Age at onset of cognitive signs was based on the rater's estimate of disrupted executive function while age at onset of psychiatric signs was based on the rater's estimation of age at appearance of chronic severe depression, irritability, violent/aggressive behaviors, apathy, perseverative/obsessive behaviors, or psychosis. Unlike motor and cognitive disruptions, not all HD subjects will suffer a discrete psychiatric onset. In contrast to the analysis of motor onset, stringent phenotype models for age at onset of cognitive signs and of psychiatric signs have not yet been developed. Therefore, instead of using residuals, we modeled log transformed age at onset of cognitive signs or psychiatric signs as a function of CAG repeat length, minor allele count of a test SNP, gender, and 4 MDS variables in S34

a linear regression analysis framework to determine the extent to which the test SNP explains the amount of variance in phenotype. 843 and 1515 subjects were used for cognitive onset and psychiatric onset analysis, respectively. We applied exactly the same approach to age at onset of motor signs analysis as a comparison, with results comparable but not identical to the primary residual analysis.

Pathway analysis To avoid making a priori assumptions about the areas of biology involved in the modification of age at motor onset, we deliberately chose to use a large pathway set, covering as many areas of biology as possible. This set comprised 1) Gene Ontology (GO) (Harris et al., 2004) (http://www.geneontology.org/), downloaded 7/26/2013), 2) Kyoto Encyclopedia of Genes and Genomes (KEGG) (Kanehisa et al., 2012) (http://www.genome.jp/kegg/; downloaded 6/4/2013), 3) PANTHER v8.1 (Mi et al., 2013), (downloaded 6/4/2013), 4) Mouse Genome Informatics (MGI) (Bult et al., 2008) (http://www.informatics.jax.org; downloaded 8/9/2013), 5) Reactome pathways (Croft et al., 2014) (http://www.reactome.org, downloaded 7/27/2013), 6) Biocarta pathways; downloaded from the Molecular Signatures Database v4.0 (MsigDB) (http://www.broadinstitute.org/gsea/msigdb/index.jsp; accessed on 7/28/2013), 7) the NCI pathway interaction database (Schaefer et al., 2009) (http://pid.nci.nih.gov/download.shtml) (accessed on 7/28/2013)

The primary pathway analysis was performed using Setscreen (Moskvina et al., 2011), which combines p-values across all SNPs in a pathway using the method proposed by Brown (Brown, 1975), a version of Fisher’s method which takes into account dependence between SNPs due to linkage disequilibrium. Correction for multiple testing of pathways in the Setscreen analysis was performed using the q-value method (Storey and Tibshirani, 2003). As secondary analyses, we applied ALIGATOR (Holmans et al., 2009) which defines genes as “significant” based on S35

their most significant SNP. It then tests whether a pathway contains a higher number of significant genes than would be expected by chance, taking into account gene size and linkage disequilibrium between genes. A drawback of ALIGATOR is that it requires that a p-value criterion for SNPs be specified in order to define significant genes. We chose a criterion of p=1.05E-3, resulting in the top 5% of genes being deemed significant, but also ran analyses using other criteria ranging from p=0.01 to p=0.000001 (see Table S3). We also ran gene-set enrichment (GSEA) analysis (Wang et al., 2007) which ranks genes in order of a gene-wise significance measure, then tests whether pathway genes have a significantly high rank, weighting by the significance measure. In order to allow for varying numbers of SNPs per gene, the gene-wide statistic used was the Simes-corrected single-SNP p-value (Simes, 1986). SNPs were assigned to genes if they were located within the genomic sequence lying between the start of the first and the end of the last exon of any transcript corresponding to that gene, as defined by NCBI (using build 37.3). Analysis was restricted to known protein-coding genes, as defined by the NCBI gene_info file. The chromosome and location for all currently known human SNPs was taken from the dbSNP132 database. In total, 3,396,556 SNPs were annotated to 17,963 unique genes.

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Supplemental Tables Table S2 – Dichotomous Extreme Analysis Of Loci Identified By Quantitative Analysis, Related to Figure 2

SNP

Chr

MAF in early

MAF in late

group (%)

group (%)

Odds Ratio*

P-value*

rs147804330

2

7.7

4.7

1.719

3.7E-4

rs72810940

2

1.8

4.3

0.432

2.3E-4

rs144287831

3

27.6

36.0

0.688

1.5E-6

rs11133929

5

6.9

11.1

0.629

2.1E-4

rs1037699

8

11.8

6.7

1.881

8.1E-7

rs11061229

12

9.3

4.4

2.133

5.3E-7

rs261453

13

13.5

8.6

1.699

5.2E-6

rs148491145

14

2.6

1.0

2.700

7.0E-4

rs146353869

15

4.0

0.2

18.100

2.3E-8

rs2140734

15

25.8

38.8

0.540

7.9E-15

rs143367341

21

10.7

16.9

0.559

1.3E-7

*Similar odds ratios can be associated with quite different P-values based upon MAF (minor allele frequency).

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Table S4- Best Single-SNP And Gene-wide p-values For The Genes In Pathway Clusters With Gene-wide p