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American Journal of Human Genetics logoLink to American Journal of Human Genetics
. 2007 Mar 8;80(4):769–778. doi: 10.1086/513320

Identification of a Novel Risk Locus for Progressive Supranuclear Palsy by a Pooled Genomewide Scan of 500,288 Single-Nucleotide Polymorphisms

Stacey Melquist 1,*, David W Craig 1,*, Matthew J Huentelman 1, Richard Crook 1, John V Pearson 1, Matt Baker 1, Victoria L Zismann 1, Jennifer Gass 1, Jennifer Adamson 1, Szabolcs Szelinger 1, Jason Corneveaux 1, Ashley Cannon 1, Keith D Coon 1, Sarah Lincoln 1, Charles Adler 1, Paul Tuite 1, Donald B Calne 1, Eileen H Bigio 1, Ryan J Uitti 1, Zbigniew K Wszolek 1, Lawrence I Golbe 1, Richard J Caselli 1, Neill Graff-Radford 1, Irene Litvan 1, Matthew J Farrer 1, Dennis W Dickson 1, Mike Hutton 1, Dietrich A Stephan 1
PMCID: PMC1852701  PMID: 17357082

Abstract

To date, only the H1 MAPT haplotype has been consistently associated with risk of developing the neurodegenerative disease progressive supranuclear palsy (PSP). We hypothesized that additional genetic loci may be involved in conferring risk of PSP that could be identified through a pooling-based genomewide association study of >500,000 SNPs. Candidate SNPs with large differences in allelic frequency were identified by ranking all SNPs by their probe-intensity difference between cohorts. The MAPT H1 haplotype was strongly detected by this methodology, as was a second major locus on chromosome 11p12-p11 that showed evidence of association at allelic (P<.001), genotypic (P<.001), and haplotypic (P<.001) levels and was narrowed to a single haplotype block containing the DNA damage-binding protein 2 (DDB2) and lysosomal acid phosphatase 2 (ACP2) genes. Since DNA damage and lysosomal dysfunction have been implicated in aging and neurodegenerative processes, both genes are viable candidates for conferring risk of disease.


Progressive supranuclear palsy (PSP [MIM 601104]) is the second-most-common form of parkinsonism, with a population prevalence rate of 6–6.4 per 100,000.1,2 Clinical features include vertical-gaze palsy and postural instability.3,4 PSP is characterized neuropathologically by neuronal and glial inclusions composed of aggregated microtubule associated protein tau (MAPT) in the basal ganglia and brain stem.5,6 Mutations in the MAPT (MIM 157140) gene have been identified in patients with a clinical presentation of PSP.714 A recent report also described linkage to chromosome 1q31.1 in a family with autosomal dominant PSP.15 However, only the MAPT locus has been consistently associated with increased risk for idiopathic PSP.1620 The MAPT locus exists as two major haplotype groups, termed “H1” and “H2”16 in European populations, with the H2 haplotype defined by >100 SNPs that are inherited in strong linkage disequilibrium (LD) with each other, reflecting the total absence of H1-H2 recombination.21 Inheritance of two copies of the H1 haplotype (H1/H1) is a major genetic risk factor for PSP.16 A large collection of pathologically confirmed PSP samples was used recently to fine map PSP risk on H1 chromosomes in PSP cases and controls. 22,23 PSP risk was associated with an extended subhaplotype, and narrowing the region for PSP risk to a 22-kb region in intron 0 of MAPT was accomplished by examining younger patients with, presumably, a larger genetic component to their disease.22,23 The most likely explanation of the association with the MAPT H1 haplotype and PSP is that variants in the H1 (and H2) haplotypes confer risk of (protect against) disease by altering expression at the locus, with the risky H1 haplotypes expressing higher levels of MAPT.2226

Calculations of population-attributable risk suggest that only ∼68% of the risk of PSP can be accounted for by the MAPT H1 haplotype, suggesting there may be additional risk genes involved in PSP. We hypothesized that additional genetic loci involved in conferring risk of PSP could be identified through genomewide association (GWA) methods. The cost of performing an association study that involved individual genotyping of thousands of SNPs for a series this size was prohibitive, so, instead, we used a pooled-DNA approach to identify additional risk factors. Whereas a pooling-based genomewide scan of thousands of SNPs has been proposed in principle, in large part, these studies have not been used for the discovery of genes predisposing to complex diseases,27,28 likely because of technical concerns or lack of technology and analysis tools.

The patients used in the initial pooling study, the “original” series, were largely derived from pathologically confirmed subjects collected by the PSP Society and sent to D.W.D. for brain autopsy. As described elsewhere, the patient samples in this brain bank were donated from the United States and Canada.29 The patient series is similar to the one that we employed in previous studies to fine map the H1 genetic risk,22 with 288 subjects with a primary pathological diagnosis of PSP used to create the pool of PSP-affected patients. A total of 344 age- and sex-matched cognitively normal control individuals were obtained through the Normal and Pathological Aging protocol at the Mayo Clinic (Scottsdale),30,31 to create the pool of control individuals. All patient and control individuals were white from the United States and Canada, and institutional review board (IRB)–approved protocols were used in the collection of all samples.

Replicate pools of patients with PSP and control individuals were created as described elsewhere.32 Samples were genotyped on 20 replicate Affymetrix 500K arrays and 20 Affymetrix 100K, in accordance with the Affymetrix protocols, whereby each of the five replicate pools was genotyped on two replicate arrays. This design therefore yielded probe-intensity data for both platforms on 10 replicate arrays per cohort. Data were analyzed using GenePool software (TGen Bioinformatics Research Unit).32 In brief, probe-intensity data were directly read from cell-intensity (CEL) files, and relative allele signal (RAS) values were calculated for each quartet. These values yield independent measures of different hybridization events and are consequently treated as individual data points. We used a silhouette statistic to rank all genotyped SNPs,33 because it avoids introducing unnecessary variance by averaging probe-intensity data from probes with different hybridization properties. Silhouette scores range from 1, where significant separation between data points has been achieved and cluster assignment can be made with confidence, to −1, where differences in allelic frequencies are less reliable. Poorly performing SNPs were identified by Affymetrix as unreliable in the transition to Mendel3 libraries or exhibited high variance between replicate arrays and were removed from the analysis; 428,867 SNPs remained. SNPs were ranked on the basis of silhouette score, whereby the SNP with the highest score was ranked 1 and the SNP with the lowest score was ranked 428,867, with use of Affymetrix’s Mendel3 libraries for the Affymetrix 500K arrays and HindIII and XbaI libraries for the Affymetrix 100K arrays, then were sorted by chromosome and physical position. With this ranking, it is assumed that SNPs approaching a rank of 1 will have larger differences in allelic frequency. With each sample ranked by silhouette score, we calculated a sliding-window statistic of the mean rank for consecutively neighboring SNPs across a fixed window size. Window sizes from 2 to 31 were used.

Since the MAPT H1 haplotype is associated with disease with a haplotypic odds ratio (OR) of ∼3–4,16,22,23,34 it served as an internal positive control for the study. For analysis, we used the 500K data to identify chromosomal regions of interest (i.e., those with small mean-rank scores). The 100K data were then used to confirm that a region identified in the 500K analysis contained SNPs with large allelic frequency differences. The SNP with the single best statistical rank on the 500K chip was rs901746 on chromosome 11p12, and the second-best SNP was rs17662235, near MAPT. The top 1,000 SNPs, based on individual statistical rank, are given in table 1. Multimarker statistics also identified both chromosome 11p12 and chromosome 17q21 (MAPT) regions with sliding windows of multiple sizes. Although we recognize that this type of statistic is biased because of genomewide LD, it allowed us to identify clusters of high-ranking SNPs that neighbor one another, which reduced the possibility of technical errors influencing the results. Shown in figure 1A, the MAPT locus, labeled as having the #2 SNP overall, showed the greatest evidence of differences between case and control pools with use of the sliding-window analysis, largely because of 38 SNPs within the top 1,000 SNPs overall and a total of 75 SNPs in the region with a rank score of <10,000 (fig. 1B and table 1). Examination of the individual SNPs with high rank scores over this locus showed SNPs that were derived from a region covering the full extent of the MAPT H1 haplotype, spanning nearly 1 Mb (fig. 1B).36 All of the 75 SNPs with genotype-frequency data in the database resembled MAPT H2 variants (which differentiate between H1 and H2 MAPT haplotypes) rather than H1 variants (which differentiate between H1 subhaplotypes); this is because, in white populations, the SNP minor-allele frequency was ∼0.2, whereas the minor allele of the SNP was absent or rare in Asian populations and African populations.36,37 In addition, two of the SNPs with low rank scores (rs12150111 and rs807072) were identified definitively as MAPT H2 variants from prior MAPT genomic sequencing efforts.22

Table 1. .

Predicted Allelic Frequencies for the Top 1,000 SNPs

Frequencyc (SD) of Predicted Allele
SNP Ranka dbSNP Number Chromosome Positionb Case Control
1 rs901746 11 47216895 61.3 (.042) 81.1 (.027)
2 rs17662235 17 41589553 2.7 (.019) 15.3 (.028)
3 rs2699808 7 26175747 60.5 (.039) 45.2 (.043)
4 rs17662853 17 41604625 26.7 (.068) 14.0 (.039)
5 rs11898241 2 115847267 75.6 (.057) 61.0 (.042)
6 rs17563501 17 41157478 96.4 (.050) 79.9 (.021)
7 rs2141299 17 41596763 94.7 (.035) 77.7 (.023)
8 rs17574228 17 41460355 12.4 (.016) 24.8 (.035)
9 rs2732706 17 41707463 8.5 (.036) 22.1 (.044)
10 rs7139545 13 24677429 74.2 (.022) 85.7 (.039)
11 rs6450530 5 59095265 30.6 (.047) 51.3 (.041)
12 rs2668695 17 41647903 13.3 (.034) 27.3 (.038)
13 rs3759297 12 32029119 63.6 (.033) 80.0 (.030)
14 rs10798036 1 182784619 45.0 (.045) 61.1 (.046)
15 rs10213502 4 11624923 93.7 (.023) 79.4 (.039)
16 rs7700506 5 56032355 65.5 (.029) 85.5 (.031)
17 rs7198242 16 68205996 24.0 (.083) 5.9 (.048)
18 rs2532286 17 41597441 96.6 (.045) 89.6 (.048)
19 rs7534271 1 47406001 55.7 (.035) 68.6 (.051)
20 rs9649052 7 134311099 49.4 (.012) 58.6 (.034)
21 rs17604700 15 29922129 51.6 (.053) 34.6 (.078)
22 rs11623728 14 96882409 27.6 (.019) 18.6 (.018)
23 rs1557996 7 7430544 93.4 (.039) 77.9 (.054)
24 rs2202445 5 7381176 57.7 (.047) 74.5 (.056)
25 rs1527036 23 3215185 50.3 (.035) 63.7 (.039)
26 rs2035515 8 107825837 92.1 (.025) 82.4 (.019)
27 rs11745421 5 168123644 11.8 (.044) 0.7 (.017)
28 rs429988 3 41081069 63.2 (.033) 74.0 (.028)
29 rs10838681 11 47231640 67.6 (.030) 80.8 (.041)
30 rs10517938 4 168729149 77.6 (.044) 84.9 (.028)
31 rs12918956 16 70781836 42.0 (.070) 57.0 (.059)
32 rs9567416 13 43806741 36.3 (.100) 15.2 (.044)
33 rs2107699 7 49367808 19.6 (.082) 45.4 (.182)
34 rs4794984 17 29333048 66.1 (.037) 78.8 (.037)
35 rs8088596 18 72620941 65.2 (.032) 50.1 (.049)
36 rs2116457 8 129876983 53.9 (.039) 67.3 (.029)
37 rs762038 14 20304608 71.0 (.028) 83.3 (.035)
38 rs1336433 10 113348065 32.8 (.038) 46.2 (.039)
39 rs7620394 3 55206368 36.1 (.035) 23.8 (.039)
40 rs6590039 11 123446989 72.7 (.029) 57.0 (.040)
41 rs10824896 10 51463093 81.7 (.046) 89.2 (.018)
42 rs354636 1 91184514 86.2 (.044) 95.7 (.051)
43 rs13020820 2 33892179 48.8 (.042) 59.9 (.039)
44 rs520605 1 181527436 68.8 (.021) 84.7 (.058)
45 rs11926691 3 83064778 64.6 (.027) 55.1 (.011)
46 rs16936441 9 18201655 70.9 (.068) 88.7 (.045)
47 rs8036777 15 48208710 46.8 (.060) 66.3 (.030)
48 rs1299704 3 108688432 32.0 (.022) 42.7 (.047)
49 rs1550532 2 234046848 58.4 (.042) 69.4 (.038)
50 rs9394550 6 38960939 56.3 (.059) 41.7 (.035)
51 rs12717171 6 112800652 53.2 (.027) 62.0 (.032)
52 rs2548879 16 77200307 54.7 (.081) 27.9 (.077)
53 rs10256927 7 125167859 71.8 (.021) 79.4 (.022)
54 rs7407281 18 55756601 67.4 (.045) 82.4 (.032)
55 rs1122452 3 144910038 77.7 (.039) 63.4 (.029)
56 rs12962651 18 56476045 47.9 (.052) 61.0 (.040)
57 rs2070929 1 47395627 30.0 (.045) 17.0 (.028)
58 rs2036535 17 28775126 47.9 (.046) 38.8 (.022)
59 rs11211670 2 1346042 42.7 (.041) 29.4 (.024)
60 rs4372225 1 211830838 75.3 (.070) 92.3 (.048)
61 rs17660065 17 41518102 97.2 (.045) 82.1 (.081)
62 rs1725604 7 101507570 51.8 (.035) 41.7 (.017)
63 rs2194711 5 154994268 17.8 (.043) 7.2 (.044)
64 rs6753459 2 190890259 25.0 (.041) 14.2 (.039)
65 rs1041834 21 41841892 40.9 (.034) 31.7 (.012)
66 rs6847349 4 13717192 27.6 (.040) 45.2 (.061)
67 rs6101206 20 59050033 59.8 (.040) 41.0 (.032)
68 rs2732675 17 41635965 1.6 (.048) 16.9 (.046)
69 rs7396713 11 88020266 39.0 (.073) 27.5 (.030)
70 rs11835314 12 106412032 75.3 (.034) 57.2 (.062)
71 rs1520961 15 35523947 85.5 (.056) 71.8 (.067)
72 rs4740919 9 7844892 38.0 (.042) 20.2 (.039)
73 rs8088963 18 57198294 48.5 (.057) 37.6 (.017)
74 rs695271 22 32327285 59.2 (.050) 47.9 (.057)
75 rs9377831 6 58761209 14.3 (.037) 6.3 (.013)
76 rs9955849 18 3052581 84.2 (.042) 70.0 (.027)
77 rs10791979 11 55916546 77.2 (.068) 55.7 (.079)
78 rs2805386 9 110761555 69.4 (.018) 56.6 (.072)
79 rs4845237 1 187114452 82.1 (.062) 61.3 (.061)
80 rs4440119 3 61936314 40.0 (.092) 60.2 (.080)
81 rs1289951 1 117625061 87.2 (.021) 76.5 (.061)
82 rs4669550 2 10273437 15.3 (.055) 7.2 (.016)
83 rs6712370 2 69766745 35.7 (.072) 20.3 (.057)
84 rs6469264 8 110594779 20.0 (.089) 6.4 (.041)
85 rs323376 8 30851071 15.5 (.071) 39.5 (.084)
86 rs916793 17 41310477 95.3 (.068) 78.9 (.027)
87 rs210069 20 52162352 62.5 (.022) 71.8 (.016)
88 rs1826763 4 177179201 27.1 (.059) 46.4 (.062)
89 rs12427267 12 90826440 49.4 (.079) 70.7 (.035)
90 rs2442497 8 6314156 11.5 (.052) 22.7 (.046)
91 rs2583513 4 116275788 71.1 (.023) 64.0 (.029)
92 rs2191265 7 12678307 42.2 (.039) 56.7 (.040)
93 rs2163385 18 38452575 8.5 (.021) 0.5 (.022)
94 rs11071075 15 29550901 68.0 (.042) 80.2 (.037)
95 rs12819116 12 12537788 59.2 (.036) 70.2 (.028)
96 rs7940239 11 55880498 19.4 (.056) 35.1 (.067)
97 rs1400174 3 52174 36.6 (.050) 23.4 (.048)
98 rs17563787 17 41169023 6.9 (.064) 22.4 (.022)
99 rs10829618 10 131380410 72.8 (.067) 89.9 (.064)
100 rs9710693 2 239504258 34.1 (.033) 20.7 (.040)
101 rs11157865 14 51436825 52.1 (.063) 67.9 (.041)
102 rs1678719 6 38901529 77.5 (.043) 95.5 (.033)
103 rs1692506 18 24511864 61.7 (.030) 73.5 (.037)
104 rs10928098 2 141715827 42.1 (.046) 23.8 (.046)
105 rs10975882 9 689065 43.1 (.034) 50.4 (.024)
106 rs578987 1 17948686 38.3 (.041) 25.2 (.042)
107 rs2274403 13 94645021 61.8 (.047) 48.4 (.024)
108 rs3807404 7 38325866 61.0 (.062) 77.7 (.036)
109 rs2532275 17 41602774 95.7 (.033) 84.0 (.048)
110 rs6920684 6 8306390 66.6 (.044) 56.3 (.054)
111 rs3911781 10 67516022 77.9 (.046) 89.6 (.036)
112 rs1304527 21 35459060 94.4 (.048) 77.0 (.067)
113 rs10021851 4 40209776 85.4 (.058) 58.0 (.109)
114 rs1445517 4 138159604 40.1 (.034) 48.7 (.056)
115 rs11119752 1 208064160 65.9 (.041) 54.1 (.015)
116 rs17577094 17 41543275 2.7 (.098) 28.7 (.093)
117 rs2532316 17 41569489 90.6 (.043) 80.2 (.021)
118 rs7177316 15 48209122 43.6 (.049) 58.8 (.059)
119 rs2696600 17 41572003 89.8 (.036) 79.7 (.031)
120 rs5751592 22 21822228 75.7 (.047) 91.0 (.019)
121 rs9354193 6 65733294 59.6 (.047) 47.7 (.041)
122 rs6581596 12 63670237 31.8 (.059) 46.1 (.037)
123 rs722979 10 83952201 66.8 (.051) 54.6 (.038)
124 rs4943389 13 36008899 36.4 (.049) 51.8 (.048)
125 rs10931378 2 189420130 29.9 (.049) 40.1 (.047)
126 rs919262 5 151246277 38.9 (.045) 26.1 (.044)
127 rs1399564 8 76646411 37.1 (.034) 49.7 (.052)
128 rs12043736 1 215866548 57.0 (.047) 72.5 (.057)
129 rs17353336 3 134155679 54.1 (.032) 39.8 (.024)
130 rs9371835 6 155327752 39.1 (.038) 48.7 (.030)
131 rs1635216 23 3214080 57.9 (.075) 80.9 (.053)
132 rs1159788 4 103664727 35.5 (.049) 25.0 (.030)
133 rs153518 5 142937957 46.4 (.021) 40.3 (.037)
134 rs17074118 13 29420217 17.8 (.026) 4.3 (.043)
135 rs206034 23 39291012 56.2 (.032) 74.3 (.066)
136 rs9287986 2 176312475 51.9 (.027) 36.9 (.046)
137 rs1562495 3 144910247 31.1 (.025) 43.8 (.051)
138 rs1993329 6 68992781 43.9 (.062) 28.3 (.068)
139 rs6060965 20 29869759 29.5 (.032) 18.1 (.030)
140 rs1957779 14 62739400 62.5 (.027) 43.1 (.059)
141 rs10745813 12 96767932 11.6 (.033) 24.0 (.055)
142 rs2064855 20 59058742 35.4 (.048) 16.9 (.045)
143 rs7321718 13 72257693 52.6 (.036) 66.2 (.025)
144 rs1220627 5 72906819 29.9 (.033) 20.0 (.029)
145 rs1952251 1 180714144 36.5 (.079) 23.8 (.040)
146 rs4420176 10 127666188 51.2 (.032) 40.7 (.061)
147 rs338565 1 181508758 22.5 (.112) 7.8 (.034)
148 rs776965 8 107768142 47.9 (.066) 30.1 (.052)
149 rs4132608 13 109898267 68.4 (.030) 80.8 (.021)
150 rs1841043 4 69889478 10.9 (.034) 30.4 (.058)
151 rs11259272 10 6586077 34.3 (.058) 61.5 (.106)
152 rs7901651 10 85617227 49.3 (.048) 63.1 (.057)
153 rs7999230 13 106749278 27.0 (.033) 39.2 (.039)
154 rs12144146 1 151338046 40.1 (.081) 22.3 (.038)
155 rs10842885 12 27291048 63.8 (.054) 47.7 (.056)
156 rs17173853 7 149243724 81.3 (.037) 93.4 (.026)
157 rs1547597 7 147404398 39.5 (.096) 2.3 (.064)
158 rs1549411 12 29684407 75.5 (.070) 92.6 (.070)
159 rs586457 10 6537428 41.6 (.042) 25.6 (.042)
160 rs10894846 11 133954025 23.6 (.074) 10.7 (.048)
161 rs10459826 16 5680786 87.5 (.070) 70.6 (.039)
162 rs256447 5 79375707 1.6 (.029) 9.7 (.064)
163 rs476906 3 177685396 68.6 (.040) 78.8 (.017)
164 rs4633144 9 32494294 52.3 (.058) 71.6 (.065)
165 rs694444 13 63372180 73.3 (.066) 83.3 (.018)
166 rs332735 2 119167473 79.3 (.056) 90.6 (.028)
167 rs12424367 12 90826168 55.4 (.079) 73.1 (.048)
168 rs12281742 11 68060205 30.8 (.050) 16.1 (.060)
169 rs2809658 1 42719489 35.8 (.047) 53.7 (.049)
170 rs1249426 2 141775551 67.9 (.039) 88.3 (.060)
171 rs2709733 7 20728610 56.7 (.052) 37.6 (.096)
172 rs1878248 10 113311751 32.1 (.060) 21.1 (.028)
173 rs4730720 7 115489186 34.1 (.048) 16.2 (.053)
174 rs9321395 6 133642955 8.3 (.057) 24.2 (.042)
175 rs2167287 12 61068734 85.2 (.040) 92.7 (.014)
176 rs973406 2 176935238 76.4 (.047) 63.9 (.041)
177 rs10795321 10 15901281 14.4 (.061) 30.4 (.044)
178 rs10832515 11 15725228 33.6 (.038) 24.8 (.034)
179 rs6538018 9 135465832 50.3 (.044) 75.4 (.095)
180 rs1692507 18 24511941 63.6 (.042) 75.2 (.027)
181 rs798544 7 2536343 32.9 (.048) 19.3 (.025)
182 rs11708068 3 63429650 68.9 (.055) 86.0 (.038)
183 rs2399547 10 10719044 62.2 (.055) 78.2 (.020)
184 rs2059741 2 218719965 26.2 (.067) 11.9 (.053)
185 rs7610580 3 179446096 59.9 (.017) 50.9 (.045)
186 rs4705890 5 130882899 28.3 (.071) 14.4 (.050)
187 rs6949651 7 68983791 82.2 (.045) 72.1 (.070)
188 rs10944721 6 94937693 91.5 (.051) 80.5 (.062)
189 rs4865206 4 53047922 13.1 (.073) 26.6 (.026)
190 rs2532292 17 41592845 93.2 (.029) 81.3 (.078)
191 rs807339 14 98483425 21.4 (.057) 5.0 (.051)
192 rs2830191 21 26664758 1.8 (.049) 12.6 (.044)
193 rs980214 6 116996269 57.8 (.073) 77.1 (.057)
194 rs1868629 14 80117727 37.5 (.043) 16.1 (.045)
195 rs2589559 10 9101376 94.9 (.084) 76.3 (.081)
196 rs402642 1 18332121 56.8 (.038) 70.1 (.021)
197 rs10823706 10 72678863 40.6 (.028) 54.3 (.032)
198 rs2227072 22 33662312 47.3 (.054) 33.1 (.030)
199 rs1460167 8 80402202 33.9 (.054) 24.7 (.026)
200 rs6470355 8 126529717 74.1 (.032) 89.1 (.034)
201 rs4877253 9 83194004 58.2 (.050) 73.5 (.049)
202 rs17641413 5 177706306 65.7 (.025) 52.6 (.048)
203 rs11869264 17 28135096 45.7 (.035) 63.8 (.051)
204 rs17617724 8 40283622 74.0 (.029) 89.7 (.057)
205 rs4795653 17 27163735 6.8 (.043) 18.0 (.050)
206 rs2053844 4 64740967 61.3 (.056) 76.3 (.050)
207 rs7649638 3 61936012 40.5 (.094) 66.5 (.104)
208 rs2916755 8 6356758 80.3 (.069) 61.6 (.066)
209 rs1257669 14 98561945 52.6 (.026) 42.8 (.027)
210 rs1635217 23 3214104 32.7 (.077) 16.5 (.077)
211 rs11241644 5 121831417 73.1 (.034) 80.3 (.009)
212 rs594731 1 178226185 21.3 (.048) 13.5 (.028)
213 rs7750190 6 67325355 45.5 (.058) 33.6 (.028)
214 rs10826304 10 60940671 43.3 (.035) 55.1 (.038)
215 rs13419861 2 139837545 23.0 (.031) 14.0 (.018)
216 rs12936006 17 2628917 71.8 (.026) 61.9 (.035)
217 rs12434898 14 100831794 15.1 (.018) 22.0 (.031)
218 rs17100010 14 62022876 18.6 (.068) 37.0 (.031)
219 rs307022 4 124375261 38.0 (.105) 15.6 (.080)
220 rs4945261 11 77667908 21.9 (.042) 8.0 (.042)
221 rs11609955 12 641938 73.5 (.024) 79.4 (.047)
222 rs7270791 20 42558543 86.3 (.028) 94.3 (.025)
223 rs228832 20 49493555 69.5 (.047) 78.2 (.044)
224 rs5770111 22 47957002 74.2 (.036) 84.2 (.030)
225 rs11596456 10 120562236 20.4 (.041) 5.1 (.040)
226 rs796459 3 119980825 42.9 (.073) 28.7 (.036)
227 rs4537652 1 213626581 37.4 (.047) 46.2 (.055)
228 rs5755439 22 33662286 51.1 (.031) 38.7 (.029)
229 rs741245 12 4097509 44.2 (.082) 28.3 (.028)
230 rs2128404 3 65075198 65.9 (.058) 48.0 (.042)
231 rs4276705 8 131631298 6.7 (.030) 19.9 (.048)
232 rs2532276 17 41602401 4.9 (.059) 19.9 (.029)
233 rs17098942 1 76590177 24.5 (.034) 16.6 (.048)
234 rs9320784 6 121334748 95.9 (.021) 89.2 (.028)
235 rs17650063 17 41358383 95.8 (.032) 82.3 (.051)
236 rs17659881 17 41513416 89.8 (.038) 77.4 (.035)
237 rs9296268 6 39007463 76.1 (.029) 64.8 (.025)
238 rs12708283 9 107956429 35.2 (.057) 20.8 (.054)
239 rs9372465 6 116968576 56.5 (.034) 69.4 (.036)
240 rs11043827 12 18109374 87.7 (.103) 68.4 (.072)
241 rs1760931 14 20017108 71.5 (.046) 54.8 (.068)
242 rs2037276 15 60349273 70.2 (.047) 80.5 (.033)
243 rs1178355 7 17978051 67.7 (.055) 82.2 (.044)
244 rs10892044 11 116272109 15.6 (.069) 5.5 (.031)
245 rs1356266 12 37689848 56.0 (.051) 40.0 (.040)
246 rs4358170 2 42027555 62.3 (.061) 77.4 (.060)
247 rs241212 1 4541639 39.2 (.053) 26.7 (.026)
248 rs1902408 10 33913367 20.5 (.059) 8.1 (.047)
249 rs17040424 3 14882981 16.7 (.046) 3.3 (.055)
250 rs7491764 13 113618608 49.0 (.041) 38.0 (.034)
251 rs7849137 9 18132898 36.9 (.126) 9.2 (.067)
252 rs5934262 23 15451678 50.1 (.037) 36.3 (.064)
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936 rs2280732 2 28730018 78.8 (.042) 88.1 (.037)
937 rs7233739 18 6718488 37.7 (.046) 50.9 (.033)
938 rs11131719 4 68357286 41.1 (.043) 17.8 (.061)
939 rs7994224 13 49450185 18.2 (.076) 4.5 (.042)
940 rs1446893 2 72731680 88.0 (.040) 99.1 (.024)
941 rs7401404 14 62684209 29.0 (.028) 35.6 (.036)
942 rs4851854 2 105842256 51.5 (.027) 44.8 (.041)
943 rs1467616 10 102631681 38.6 (.050) 26.6 (.045)
944 rs9822959 3 185681145 37.8 (.051) 26.9 (.022)
945 rs8021814 14 46735752 50.6 (.032) 61.6 (.039)
946 rs12921623 16 16003634 87.8 (.070) 63.2 (.073)
947 rs4961688 9 16252191 46.7 (.062) 33.8 (.041)
948 rs2837297 21 40225051 23.3 (.038) 13.0 (.037)
949 rs4309752 3 136416314 49.3 (.055) 38.2 (.046)
950 rs500586 1 40744302 59.7 (.030) 70.6 (.047)
951 rs2577001 15 94555158 75.9 (.099) 88.3 (.026)
952 rs2662389 5 58162103 50.4 (.021) 40.5 (.021)
953 rs264705 3 65839896 34.2 (.047) 27.6 (.053)
954 rs275838 19 53558026 28.6 (.033) 21.0 (.033)
955 rs17345528 3 102777520 35.3 (.071) 14.2 (.072)
956 rs7541193 1 150485320 34.6 (.079) 53.0 (.064)
957 rs960537 2 124629747 14.6 (.077) 5.6 (.023)
958 rs1332011 6 39016289 25.1 (.052) 15.6 (.033)
959 rs875964 14 95802744 77.8 (.135) 95.1 (.087)
960 rs10016578 4 17742615 22.7 (.048) 3.3 (.041)
961 rs6056754 20 9540598 45.5 (.035) 36.9 (.015)
962 rs2480490 9 89387779 44.2 (.052) 32.3 (.034)
963 rs3857501 6 92348639 63.8 (.057) 74.3 (.033)
964 rs2084414 8 481735 72.6 (.034) 85.2 (.039)
965 rs2909824 5 116091320 69.2 (.087) 86.7 (.063)
966 rs1954916 6 162418023 91.1 (.055) 78.6 (.061)
967 rs17755177 2 187794592 71.0 (.054) 79.9 (.043)
968 rs7965234 12 126595604 62.1 (.086) 78.7 (.034)
969 rs6131684 20 15572156 56.2 (.062) 46.6 (.057)
970 rs17712923 11 39149865 16.6 (.172) 52.6 (.158)
971 rs2252550 6 38649462 29.2 (.040) 39.6 (.046)
972 rs6908475 6 22680777 67.1 (.032) 58.8 (.041)
973 rs11176031 12 64763239 71.5 (.132) 53.3 (.146)
974 rs3770536 2 216664326 69.7 (.029) 57.4 (.052)
975 rs10027488 4 187482998 29.2 (.059) 44.7 (.048)
976 rs2218248 3 179591920 64.5 (.091) 79.3 (.090)
977 rs17077348 5 173699036 71.0 (.044) 87.0 (.061)
978 rs974491 14 24835423 76.1 (.040) 62.1 (.070)
979 rs7751500 6 37697775 32.3 (.078) 14.7 (.060)
980 rs11127608 3 78033812 82.2 (.044) 68.6 (.042)
981 rs975974 2 43851917 15.4 (.048) 26.6 (.040)
982 rs3845948 3 37798704 75.6 (.043) 85.5 (.034)
983 rs611052 7 68601918 70.2 (.031) 62.0 (.039)
984 rs7930841 11 38466276 56.0 (.053) 68.9 (.039)
985 rs12433343 14 46617494 7.7 (.036) 17.8 (.023)
986 rs1281978 6 153565346 38.5 (.051) 51.1 (.047)
987 rs7077548 10 113350071 76.6 (.083) 58.8 (.036)
988 rs7127507 11 27671460 25.2 (.059) 38.3 (.076)
989 rs4971342 2 926687 88.8 (.076) 67.8 (.056)
990 rs1683119 14 96572498 33.5 (.040) 22.5 (.041)
991 rs2482527 9 25554648 81.6 (.057) 72.5 (.054)
992 rs6894312 5 18712040 13.7 (.044) 24.3 (.030)
993 rs4716908 7 155060486 77.2 (.054) 96.5 (.039)
994 rs1900455 10 55266508 50.5 (.043) 62.9 (.060)
995 rs2391870 7 30314272 77.4 (.102) 58.3 (.079)
996 rs771443 6 83452859 72.3 (.055) 57.4 (.090)
997 rs3091260 7 76475046 22.9 (.032) 34.4 (.053)
998 rs10878366 12 64708641 79.6 (.055) 68.7 (.112)
999 rs255026 5 178717241 48.6 (.035) 56.2 (.039)
1,000 rs5750373 22 35749531 73.5 (.064) 59.6 (.036)
a

The rank order of the SNPs is based on a silhouette-test statistic calculated on probe intensity measures from replicate arrays, implemented in GenePool 0.81 (TGen Bioinformatics Research Unit). Only SNPs for which allelic frequencies could be calculated using the k-correction method35 from a training database of 1,000 individually genotyped samples are included.

b

Chromosomal positions for each SNP are based on National Center for Biotechnology Information build 35.1.

c

Frequencies are expressed as percentages. Predicted allelic frequencies are the median frequency of all replicate arrays and refer to the A allele as defined by Affymetrix 500K. The median value is used, since an extreme outlier is occasionally observed.

d

SNP has no rs number, only an Affymetrix identification number.

Figure 1. .

Figure  1. 

Two loci showing strong support for association by pooled analysis. A, Genomewide plot of the mean rank of five consecutive SNPs, calculated to identify clusters of high-ranking SNPs. The single best region was on chromosome 17, neighboring MAPT, and the second best region was on chromosome 11p12. Chromosome 11p12 also harbored the SNP that ranked #1 overall by single-marker statistics. B, Single-marker rank statistics for SNPs over the MAPT (left) and DDB2/ACP2 (right) loci. SNPs deemed less reliable or showing high variability among replicates were removed, and the remaining SNPs were ranked in order from 1 (showing the greatest difference between cases and controls) to 428,867 (showing the least difference between cases and controls) with use of a silhouette-test statistic in GenePool software (TGen Bioinformatics Research Unit). Rank scores are plotted versus chromosomal position. Genes within the plotted chromosomal region are shown below. SNPs on the Affymetrix 500K platform are shown above, and SNPs on the Affymetrix 100K platform are shown below. EA = Early Access.

The chromosome 11p12 region that showed the highest rank SNP by single-marker statistics and multimarker sliding-window analysis was a novel locus and therefore was examined in greater detail (fig. 1B). The top overall ranked SNP, rs901746, a SNP in intron 9 of the DNA damage-binding protein 2 (DDB2 [MIM 600811]) gene, was chosen for follow-up in the individual samples comprising the pooled DNA. A significant increase of 10% in the G allele frequency was seen in cases versus controls (P=.0002) (table 2). The SNP was then genotyped in a second U.S. series to confirm the association. This “replication” sample (n=161) was made up of both pathologically confirmed (n=97) and clinically defined PSP case individuals (n=64), as described in Rademakers et al.22 A total of 165 age- and sex-matched cognitively normal control individuals were obtained from the Normal and Pathological Aging Protocol at the Mayo Clinic (Scottsdale).30,31 In addition, for the rs901746 and rs2167079 analysis, additional pathologically confirmed cases (n=41) and clinically defined PSP case indivuals (n=22) were genotyped, and 252 age- and sex-matched cognitively normal control individuals collected at Mayo Clinic Jacksonville were used as a second source of controls.22 All case and control individuals in this set were white from the United States and Canada, and IRB-approved protocols were used in the collection of all samples.

Table 2. .

Association Analysis of rs901746 in Original and Replication Series

No. (%) of
Alleles
Genotypes
GG versus AG and AA
Population n A G AA AG GG OR 95% CI P
Control combined 735 1,011 (75) 335 (25) 377 (56) 257 (38) 39 (6)
Control original 344 438 (78) 126 (22) 166 (58) 106 (37) 10 (4)
Control replication 391 573 (73) 209 (27) 211 (54) 151 (39) 29 (7)
PSP combined 501 661 (68) 317 (32) 231 (47) 199(41) 59 (12) 2.2 1.5–3.4 .0001
PSP original 288 374 (68) 178 (32) 131 (47) 112 (41) 33 (12) 4.0 1.9–8.3 .0001
PSP replication 213 287 (67) 139 (33) 100 (47) 87 (41) 26 (12) 1.7 1.0–3.0 .05

When allele frequencies at rs901746 were examined in the replication sample set, a 6% increase in the frequency of the G allele in subjects with PSP was observed; however, because of the smaller sample size, this allele frequency difference is borderline significant (P=.05). When genotype distributions were examined in both PSP case-control series, the frequencies were very similar, with an increase from 4% to 12% in the GG genotype in the original population and an increase from 7% to 12% in the replication set. The allelic frequency difference in both series is explained by an apparent doubling of the GG frequency in subjects with PSP compared with controls, suggesting that risk at this locus acts in a recessive manner. We explicitly tested dominant, recessive, and additive models at this locus, and the model that best fit the data was a recessive one (P<.0001). The OR for harboring an rs901746 GG genotype versus all other genotypes in the original series was 3.7 (95% CI 1.2–3.9) and was 1.7 (95% CI 1.0–3.0) for the replication series. When these individuals in both of these series were combined and analyzed, the combined OR for the GG genotype compared with all other genotypes in the series was 2.2 (95% CI 1.4–3.4). To confirm that the rs901746 association observed is not a control frequency artifact, we examined allele frequencies for rs901746 in 250 cognitively normal controls recently published in a Parkinson disease (PD [MIM 168600]) GWA study.38 We found that the frequency of the rs901746 G allele in this independent control series was 0.27, consistent with our observed control frequencies (0.22 and 0.27).

The genomic context near rs901746 was examined by downloading the CEPH-from-Utah SNP genotypes for 100 kb around rs901746 from the HapMap genome browser and by examining the LD patterns and haplotype-block structure of the region with use of the Haploview software.39 rs901746 lies in the middle of a haplotype block encompassing at least two genes—the DDB2 gene and the lysosomal acid phosphatase 2 (ACP2 [MIM 171650]) gene—and can extend into the 3′ of another gene, nuclear receptor subfamily 1, group H, member 3 (NR1H3 [MIM 602423]), depending on the type of haplotype-block definition used.39 Variation in this 100-kb region could be fully described by 16 additional tag SNPs. These tag SNPs were genotyped in all PSP series, and both single and multimarker analysis was performed on the combined series (table 3). Single-marker analysis showed that nine tag SNPs showed significant allelic association. Of these, five tag SNP associations were highly significant (P values ⩽.003), with rs10501320 showing the greatest association after rs901746 (P<.0001).

Table 3. .

Single-Marker Analysis of Tag SNPs in the Combined Series and in Both Young and Old Patient Populations[Note]

All Cases(n=448)
Youngb Cases(n=162)
Oldb Cases(n=182)
tagIDa (SNP),
and Allele
No. (%) of
Alleles in
Controls
(n=532)
No. (%)
of Alleles
P No. (%)
of Alleles
P No. (%)
of Alleles
P
1 (rs11039130): .003 .02 .25
 C 600 (69) 614 (75) 224 (76) 245 (72)
 T 274 (31) 202 (25) 72 (24) 95 (28)
2 (rs4647709): .5 .57 .88
 C 806 (91) 787 (90) 292 (90) 331 (91)
 T 78 (9) 85 (10) 32 (10) 31 (9)
3 (rs2291120): .0004 .003 .006
 T 781 (92) 859 (87) 280 (86) 317 (87)
 C 67 (8) 115 (13) 44 (14) 47 (13)
4 (rs10742797): .81 .72 .98
 A 591 (81) 572 (81) 212 (82) 243 (80)
 T 143 (19) 134 (19) 48 (18) 59 (20)
5 (rs1685404): .72 .97 .96
 G 598 (68) 560 (67) 213 (68) 237 (68)
 C 282 (32) 274 (33) 101 (32) 111 (32)
6 (rs7395581): .03 .02 .07
 A 378 (71) 437 (65) 157 (63) 180 (65)
 G 152 (29) 233 (35) 93 (37) 96 (35)
7 (rs11039138): .01 .02 .37
 G 470 (56) 442 (62) 168 (64) 173 (59)
 A 372 (44) 268 (38) 94 (36) 121 (41)
8 (rs2957873): .22 .52 .28
 A 728 (83) 679 (81) 257 (81) 281 (80)
 G 150 (17) 163 (19) 59 (19) 69 (20)
9 (rs4647736): .03 .04 .12
 C 807 (91) 736 (88) 273 (88) 305 (89)
 T 75 (9) 98 (12) 39 (13) 39 (11)
10 (rs2013867): .004 .006 .02
 T 657 (74) 549 (66) 206 (66) 236 (67)
 C 229 (26) 279 (34) 106 (34) 114 (33)
11 (rs901746): <.0001 .003 .004
 A 659 (76) 570 (67) 204 (65) 242 (68)
 G 213 (24) 282 (33) 110 (35) 116 (32)
12 (rs1050244): .53 .89 .44
 C 851 (97) 823 (96) 307 (97) 343 (96)
 T 29 (3) 33 (4) 11 (3) 15 (4)
13 (rs11039143): .87 .64 .52
 T 830 (98) 782 (98) 293 (98) 319 (98)
 G 18 (2) 16 (2) 5 (2) 5 (2)
14 (rs7118396): .16 .27 .13
 C 741 (86) 688 (84) 253 (84) 287 (83)
 T 117 (14) 132 (16) 49 (16) 59 (17)
15 (rs12577530): .0009 .005 .04
 G 784 (88) 701 (82) 260 (82) 296 (84)
 C 106 (12) 149 (18) 58 (18) 58 (16)
16 (rs7114704): .01 .3 .0006
 C 813 (93) 803 (96) 288 (95) 343 (98)
 T 61 (7) 35 (4) 16 (5) 7 (2)
17 (rs10501320): <.0001 .003 .16
 G 609 (70) 641 (78) 230 (79) 255 (74)
 C 265 (30) 179 (22) 62 (21) 91 (26)

Note.— Significant P values are shown in bold.

a

Tag SNPs were chosen on the basis of the tagging algorithm in Haploview v3.32 software,39 with the “Pairwise Tagging Only” option selected and the r2 threshold set at .8.

b

Subjects aged <76 years were classified as “young”; subjects aged ⩾76 were classified as “old.”

We examined the DDB2/ACP2 tag SNP data set in different age groups in our combined series of cases and controls to see whether looking at younger cases might help further refine the associated region, as it had for the MAPT locus, where younger cases show a stronger association with the H1/H1 genotype.22 Pathologically confirmed cases were divided into “young” and “old” groups on the basis of median age at death (75 years), and single-marker allelic association statistics were calculated using 2×2 contingency tables and were examined using χ2 tests. On the whole, all of the SNPs that show significant association in the combined PSP case set also show significant association (P<.05) with the younger case subset, whereas there is less-significant association observed for the older cases.

To refine the disease-associated region, we performed haplotype-inference analysis in the young cases versus all controls, using a sliding-window approach.40 As described elsewhere, this type of approach was key in refining the associated region on the MAPT H1 haplotype.22 However, as figure 2 displays, when data from all the tag SNPs were included in the analysis, there was no obvious resolution of the associated region when the young cases were considered separately. This may reflect the fact that the contribution to the overall signal of the association at this locus was not as great with the younger cases as had been seen with the MAPT locus; therefore, the sample size and/or the number of informative SNPs was inadequate to detect a smaller associated region.

Figure 2. .

Figure  2. 

Haplotype sliding window–analysis results. The haplotype score–based method of Schaid et al.40 was used to investigate evidence of association of haplotypes with case-control status. Only haplotypes with an estimated overall frequency of ⩾5% were considered for these analyses. Reported P values are based on asymptotic assumptions but were verified by simulating P values derived from 1,000 permutations of case and control labels and were found to be consistent. Global P values for each 4-marker haplotype are denoted as lines at the −log10P. Only young pathologically confirmed PSP cases (death at age <76 years) were used for the analysis. All individuals in the control group were used in all analyses, since no single SNP showed significantly different allelic frequency distribution in controls when stratified by age. Global P=.01 is denoted by a dashed line. SNP numbers are as noted in table 3.

Since a haplotype-inference approach was unsuccessful in narrowing the associated region, we decided to identify additional novel SNPs that may represent functional variant(s) accounting for increased risk of disease by sequencing a series of 18 subjects with PSP who had the various genotypes at rs901746, the majority of whom carried the risky GG genotype (n=11 GG, n=5 AG, and n=2 AA) (table 4). Primers were designed to fully sequence coding exons of both DDB2 and ACP2. Only one SNP, found 63 bp downstream of exon 3 in ACP2, was not already in the dbSNP database; however, this SNP appeared to be in near-complete LD with nearby rs10838677 in exon 5 of ACP2, encoding a silent change (L165L). Interestingly, a number of SNPs identified through sequencing appeared to be in near-complete LD with rs901746, including rs2167079, a coding SNP in ACP2 in which the minor allele changes the amino acid at position 29 from an arginine to a glutamine (R29Q). This converts the protein sequence to the mouse amino acid residue at the equivalent position. Interestingly, this position in ACP2 is predicted to encode the signal peptidase cleavage site,41 suggesting that carriers of the minor allele encoding glutamine at position 29 may have altered cleavage of the signal peptide compared with those encoding arginine at that position. Since this SNP could affect function of the protein, we genotyped it through the combined series. Results from this analysis are shown in table 5. Overall, the LD between rs901746 and rs2167079 was high (cases r2=0.97; controls r2=0.94). As expected, significant allelic association was observed with rs2167079 (P=.002); however, this was not any greater than the association observed with rs901746, suggesting that rs2167079 is unlikely to fully explain the association at the DDB2/ACP2 locus. We tested the R29Q variant for dominant, recessive, and additive models, and the additive model best fit the data (P<.0001).

Table 4. .

SNP Discovery Results from Sequencing DDB2 and ACP2 in 18 Subjects with PSP

Genotype at DDB25′→3′
Genotype at ACP23′→5′
Intron 8
Intron 9
3′ UTR
Intron 6
Exon 5
Intron 3
Exon 1
Sample rs326222 rs901746 rs1050244 rs11039146 rs2242261 rs10838677a ss68362654b rs4752973 rs2167079c
1 GG GG CT CT AA AG AG AG AA
2 GG GG CC CC AA GG GG AA AA
3 GG GG CC CC CC GG GG GG AA
4 GG GG CC CC AC GG GG AG AA
5 GG GG CC CC AC GG GG AG AA
6 GG GG CC CC CC GG GG GG AA
7 GG GG CC CC AA GG GG AA AA
8 GG GG CT CT AA AG AG AG AA
9 AG AG CC CC AA GG GG AA AG
10 GG GG CC CC AC GG GG AG AA
11 GG GG CC CC AC GG GG AG AA
12 GG GG CC CC AC GG GG AG AA
13 AG AG CC CC AA GG GG AA AG
14 AG AG CC CC AA GG GG AA GG
15 AG AG CC CC AA GG GG AA AG
16 AG AG CC CC AA GG GG AA AG
17 AA AA CC CC AA GG GG AA GG
18 AA AA CC CC AA GG GG AA GG
a

Encodes synonymous change L165L.

b

No rs number; submitted to dbSNP.

c

Encodes nonsynonymous change R29Q.

Table 5. .

Association Analysis of rs2167079 in the Combined Series[Note]

No. (%) of Alleles
SNP and
Allele
All Controls
(n=735)
All Patients
(n=501)
P
rs901746: <.0001
 A 1,011 (75) 661 (68)
 G 335 (25) 317 (32)
rs2167079: .002
 G 918 (73) 598 (67)
 A 332 (27) 292 (33)

Note.— Results include the additional cases and controls used in the replication series.

In an alternative method for determining the gene responsible for disease risk at this locus, expression analysis was performed on the DDB2 and ACP2 genes. Analysis was performed, using real-time Taqman expression assays (Applied Biosystems), on mRNA extracted from the cerebella of 20 rs901746 AA and 20 rs901746 GG genotype carriers, to determine whether risk variants at the DDB2/ACP2 locus have a direct effect on gene expression. Unfortunately, although DDB2 transcript levels are slightly increased in cases with a GG genotype, no significant differences were observed between the cases with AA and GG genotypes for either DDB2 or ACP2 mRNA levels (for DDB2, P=.29; for ACP2, P=.48) (fig. 3).

Figure 3. .

Figure  3. 

Relative mRNA expression with TATA-binding protein as an endogenous control. Plotted are relative levels of glyceraldehyde-3-phosphate dehydrogenase (GAPDH); tyrosine 3-monooxygenase/tryptophan 5-mono-oxygenase activation protein, zeta polypeptide (YWHAZ); ACP2 (assay Hs00155636_m1 [Applied Biosystems]); and DDB2 (assay Hs00172068_m1 [Applied Biosystems]) for 20 carriers of the rs901746 AA (neutral) genotype and 20 carriers of the rs901746 GG (risky) genotype. SE is denoted by the error bars. None of the comparisons between AA and GG carriers reach the level of statistical significance (P values noted below each graph). Similar results are seen when GAPDH or YWHAZ was used as the endogenous control (data not shown). RQ = relative quantity.

GWA studies are appealing because of their lack of bias, in that they represent a model-free approach for identification of new and novel genes that are involved in a disease process that may never be identified using other methodologies. However, even now, individually genotyping hundreds of individuals to perform a “traditional” GWA is not feasible for many rarer diseases, including PSP, because of the lack of available funding. Therefore, this type of pooled genomewide approach potentially represents a fast and economical initial solution to this problem. Pooling methods lack the analytical flexibility inherent in a traditional genomewide study because it is not possible to reanalyze the data with use of subgroups of cases or controls or to perform true haplotype-scanning analyses. However, there is still some uncertainty about how best to analyze the large amounts of individual genotype data used in GWA studies. An early GWA study of the PD showed problems in replication of results, potentially because of problems in study design.4247

Although pooling methods clearly have limitations, the analysis procedures we used in the GenePool software (TGen Bioinformatics Research Unit) were developed using individual genotype data from samples that were also pooled, thereby allowing the algorithms to be adjusted until they predicted SNP ranks on the basis of what was known from the individual genotype data.32 In the present analysis, we had prior knowledge that the MAPT H1 haplotype is associated with disease, so it could serve as a positive control for the genomewide analysis.

The identification of a new risk locus for PSP on chromosome 11 from the pooled genomewide approach was confirmed in a second U.S. PSP case-control series, with similar allele and genotype frequencies. Closer examination of this locus by dense SNP genotyping suggests that the association spans the entire haplotype block containing the DDB2 and ACP2 genes. Examination of potential functional variants yielded no definitive explanation for the observed association.

Both ACP2 and DDB2 are reasonable candidate genes that highlight previously implicated pathways for neurodegenerative disease. There are many lines of evidence suggesting a role for lysosomes and autophagic processes in neurodegeneration. Autophagy has been implicated in the clearance of protein aggregates, a common feature of many neurodegenerative disorders.48,49 Interestingly, patients with lysosomal-storage disorders often exhibit neurological phenotypes with pathology similar to that seen in PSP.5052 Two lines of evidence implicate ACP2 in neurodegeneration. First, it has been reported that, in brains of subjects with Alzheimer disease (AD [MIM 104300]), microglia surrounding the amyloid plaques stain strongly for ACP2.53 In addition, cerebrospinal fluid from half of the examined subjects with AD showed evidence of ACP2 activity, whereas patients not affected with AD showed no activity.53 These results leave open the question of whether ACP2 in AD is just a secondary marker of neurodegeneration or perhaps plays a more active role in the neurodegenerative process. Second, knockouts and mutations of Acp2 in mice have neurological phenotypes.54,55 Neuropathology of Acp2−/− tissue showed increased lysosomal staining (as detected by lamp-1 and cathepsin D immunoreactivity), primarily in glial cells. Interestingly, ∼7% of these Acp2−/− mice presented with generalized seizures after age 8 wk, and it has been suggested that this phenotype may be correlated with the defective lysosomal storage observed in glial cells.54 The observation that loss of Acp2 causes deficits in glial lysosomal storage in the Acp2−/− mice may also be significant, given that, in PSP, there is abundant MAPT-inclusion pathology within glia (astrocytes and olgodendroglia), as well as in neurons.56

Mutations in the DDB2 gene are responsible for xeroderma pigmentosum (XP) complementation group E (XPE [MIM 278740]). Interestingly, some mutations in the nucleotide excision–repair pathway that cause the diseases XP and Cockayne syndrome (MIM 216400) present with neurological phenotypes; however, XPE does not seem to be one of them.57,58 DDB2 forms a ubiquitin E3-ligase complex, with DNA damage-binding protein 1 (DDB1 [MIM 600045]) and Cullin 4a (CUL4A [MIM 603137]), that binds damaged DNA. Both histone H2A (H2AA [MIM 603137]) and XP complementation group C (XPC [MIM 278720]) proteins have been implicated as substrates for the DDB1/DDB2/CUL4A complex upon activation.59,60 Ubiquitination of histone H2A may change local chromatin configuration at the damage site, thereby allowing access to other DNA-repair proteins farther down the pathway.60 The accumulation of damaged DNA in aging brain suggests that DNA-repair capacity is reduced as we age and appears to be selective to genes important in learning and memory. Interestingly, there is evidence of brain-specific alternatively spliced forms of DDB2 that splice out either exons 4–7 or exons 4 and 6 alone.61 The proteins encoded by these alternatively spliced transcripts act as dominant negative inhibitors of DNA repair, when tested in an in vitro system.61 It will be interesting to tease apart which gene or genes at this locus are involved in conferring risk of PSP, but functional studies, rather than genetic ones, will probably be required to address these issues.

Given the size of the association seen at the DDB2/ACP2 locus, the fact that the described PSP series represents the largest collection of PSP-affected subjects worldwide, and the fact that our U.S. replication series is underpowered to detect changes with an OR <2.0, we may be at the limit of what can be consistently detected and confirmed using the case-control populations available. Six additional weaker loci were identified in the genomewide screen that still need to be analyzed in detail, and it will be interesting to examine this potential power issue in closer detail. This genomewide analysis has identified a novel second locus implicated in PSP risk, accelerating research and the hope of identifying effective therapeutics for this devastating disease.

Acknowledgments

We are grateful to the patients and their families for their cooperation in this project. We also thank the Society for Progressive Supranuclear Palsy brain bank for providing samples. We thank John Gonzalez and Monica Castanedes-Casey in the Neuropathology Laboratory at Mayo Clinic Jacksonville for technical assistance. This research was funded by National Institutes of Aging grant PO1 AG 17216 (to M.H., D.W.D., and M.J.F.); the Mayo Foundation, USA; The Society for Progressive Supranuclear Palsy; and a Robert and Clarice Smith Fellowship. S.M. was funded by the National Research Service Award postdoctoral fellowship AG24030. Funding was also provided by a foundation grant from the Stardust Foundation (to D.W.C.) and the National Institutes of Health Neuroscience Blueprint grant 1U24NS043571 (to D.A.S.).

Web Resources

The URLs for data presented herein are as follows:

  1. dbSNP, http://www.ncbi.nlm.nih.gov/SNP/
  2. Online Mendelian Inheritance in Man (OMIM), http://www.ncbi.nlm.nih.gov/Omim/ (for PSP, MAPT, DDB2, PD, ACP2, NR1H3, AD, XPE, Cockayne syndrome, DDB1, CUL4A, H2AA, and XPC)
  3. TGen Bioinformatics Research Unit, http://bioinformatics.tgen.org/ (for the GenePool source code)

References

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