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Am J Hum Genet. Jan 2006; 78(1): 78–88.
Published online Nov 15, 2005. doi:  10.1086/498851
PMCID: PMC1380225

A Scan of Chromosome 10 Identifies a Novel Locus Showing Strong Association with Late-Onset Alzheimer Disease

Abstract

Strong evidence of linkage to late-onset Alzheimer disease (LOAD) has been observed on chromosome 10, which implicates a wide region and at least one disease-susceptibility locus. Although significant associations with several biological candidate genes on chromosome 10 have been reported, these findings have not been consistently replicated, and they remain controversial. We performed a chromosome 10–specific association study with 1,412 gene-based single-nucleotide polymorphisms (SNPs), to identify susceptibility genes for developing LOAD. The scan included SNPs in 677 of 1,270 known or predicted genes; each gene contained one or more markers, about half (48%) of which represented putative functional mutations. In general, the initial testing was performed in a white case-control sample from the St. Louis area, with 419 LOAD cases and 377 age-matched controls. Markers that showed significant association in the exploratory analysis were followed up in several other white case-control sample sets to confirm the initial association. Of the 1,397 markers tested in the exploratory sample, 69 reached significance (P<.05). Five of these markers replicated at P<.05 in the validation sample sets. One marker, rs498055, located in a gene homologous to RPS3A (LOC439999), was significantly associated with Alzheimer disease in four of six case-control series, with an allelic P value of .0001 for a meta-analysis of all six samples. One of the case-control samples with significant association to rs498055 was derived from the linkage sample (P=.0165). These results indicate that variants in the RPS3A homologue are associated with LOAD and implicate this gene, adjacent genes, or other functional variants (e.g., noncoding RNAs) in the pathogenesis of this disorder.

Alzheimer disease (AD [MIM 104300]) is the most significant cause of dementia in developed countries and is clinically characterized by memory loss of subtle onset followed by a slowly progressive dementia that has a course of several years. The risk of AD has a genetic component, as evidenced by an increased risk of AD among first-degree relatives of affected individuals. So far, three genes have been identified that lead to the rare autosomal dominant early-onset form of AD. Mutations in the three genes—β-amyloid precursor protein (APP [MIM 104760]) (Goate et al. 1991), presenilin 1 (PSEN1 [MIM 104311]) (Sherrington et al. 1995), and presenilin 2 (PSEN2 [MIM 600759]) (Levy-Lahad et al. 1995)—lead to an increase in the production of long amyloid β peptide (Aβ42), the main component in amyloid plaques. The great majority of AD cases are of late onset (age at onset >65 years) and show complex, non-Mendelian patterns of inheritance. Late-onset AD (LOAD [MIM 606626]) probably results from the combined effects of variation in a number of genes as well as from environmental factors. Early genetic studies of LOAD demonstrated that the epsilon4 variant of APOE (MIM 107741) is associated with increased risk of LOAD and with lower age at disease onset in a dose-dependent manner (Corder et al. 1993).

Genomewide linkage screens in patients with LOAD have identified several other chromosomal regions (reviewed by Pastor and Goate [2004]), implying that genetic risk factors other than APOE must exist. Putative LOAD-susceptibility loci on chromosomes 9, 10, and 12 have been reported in two or more sample sets by different groups (Pericak-Vance et al. 1997, 2000; Rogaeva et al. 1998; Kehoe et al. 1999; Myers et al. 2000, 2002; Blacker et al. 2003). Perhaps the most prominent among them is the linkage to chromosome 10, observed in a number of nonoverlapping samples from studies employing distinct approaches, including linkage analysis based on a genomewide screen, a candidate gene–based limited genome screen, and a genome screen that used plasma Aβ levels as a quantitative phenotype (Kehoe et al. 1999; Bertram et al. 2000; Ertekin-Taner et al. 2000; Myers et al. 2000; Blacker et al. 2003; Farrer et al. 2003). Several candidate genes that are under or near the chromosome 10 linkage peaks have been tested for association with LOAD, but none has been consistently replicated (Alzheimer Disease Forum).

To identify the genes and mutations for LOAD, we undertook a screen of putative functional SNPs in 677 genes under the linkage peak, using a powerful set of unrelated cases and controls. A similar approach was used to identify the glyceraldehyde-3-phosphate dehydrogenase gene (GAPD [MIM 138400]), located on the short arm of chromosome 12, as a putative LOAD risk gene (Li et al. 2004). Here, we report the findings from this scan of 1,412 SNPs on chromosome 10.

Material and Methods

Sample-Set Characteristics

Three white clinical case-control series were used in this study: (1) the WU series (422 cases; 382 controls), collected through the Washington University Alzheimer’s Disease Research Center (ADRC) patient registry; (2) the UK series (368 cases; 404 controls), collected as part of the Medical Research Council (MRC) Late-Onset AD Genetic Resource, including those from the Cardiff University Wales School of Medicine and from King’s College London; and (3) the UCSD series (217 cases; 409 controls), collected through the ADRC of the University of California–San Diego. In total, 1,007 AD cases and 1,195 controls were analyzed. Cases in these series had received a clinical diagnosis of dementia of the Alzheimer type (DAT), with use of criteria equivalent to NINCDS-ADRDA (National Institute of Neurological and Communicative Diseases and Stroke/Alzheimer's Disease and Related Disorders Association) (McKhann et al. 1984) but modified slightly to include AD as a diagnosis for individuals aged >90 years (Berg et al. 1998). The minimum age at onset of DAT was 60 years. Controls were nondemented individuals aged >60 years at assessment who were screened for dementia through use of neuropsychological tests and clinical interviews. Controls were matched with cases for age and sex. These samples all show an expected age and APOE epsilon4–genotype distribution and do not appear to have evidence of population stratification (Li et al. 2004). More-detailed information about these samples can be found elsewhere (Li et al. 2005).

A fourth case-control series was generated by selecting one case per family from our genetic linkage sample (Myers et al. 2002) and matching each of them to an equal number of white, nondemented controls collected in St. Louis (these controls are independent of the controls used in the exploratory sample above). There were 429 cases and 321 controls in this series (mean age at onset for the case series is 73.6 years; mean age at assessment for controls is 75.0 years). The linkage pedigrees from the National Institute of Mental Health (NIMH) series and the NIA series (292 pedigrees; 624 affected individuals) (Myers et al. 2002) were also genotyped for the single SNP significant in all case-control series.

Two small series that consisted of neuropathologically confirmed white cases and controls were derived from the U.S. ADRCs (contributing centers are listed in the Acknowledgments) and from Newcastle upon Tyne, United Kingdom. Of the samples in the U.S. series, 40% were assessed as being at either Braak and Braak stage 5 or 6 (cases) or Braak stage 2 or less (controls). The remaining samples (cases) met neuropathological criteria for AD. Both the controls and cases were selected to be largely free of such complicating pathologies as Lewy bodies and vascular events. The combined series included 360 cases (age range 65–97 years; 220 women) and 252 controls (age range 65–100 years; 123 women).

SNP Selection and Genotyping

Genotyping of all samples was performed with written informed consent/assent from the participating individuals and their caregivers and approval from the participating institutions. Polymorphisms used for genotyping were identified from either the Celera human genome database that includes publicly available SNP data or the Applera Genome Sequencing Initiative database. For this study, we chose gene-based SNPs, with a preference for putative functional mutations, as predicted in the Celera or public SNP databases, with the aim to screen as many predicted genes with at least one variant as possible (table A1 and fig. A1 [online only]). Thus, these SNPs consist of 367 missense/nonsense mutations, 1 donor splice-site variant, 172 putative transcription factor binding site mutations, 9 exon-skipping site variants, 109 variants in the UTR, and 739 variants of other types (intronic, silent, and unknown types [SNPs of unknown and silent types were annotated as functional variants in previous genome assemblies]). They cover a total of 677 of 1,270 annotated genes on chromosome 10. All genomic positions for all SNPs and genes are from the Celera Genome Assembly R27. All SNPs had a minor-allele frequency (MAF) of >2% in either cases or controls. The MAF was 2%–5% for 80 exploratory markers and 5%–10% for 165 markers. The remaining markers had MAFs of 10%–50%, with approximately equal numbers of SNPs in each 10% interval.

Genotyping of SNPs was undertaken by allele-specific real-time PCR for individual samples, by use of primers designed and validated in-house (Germer et al. 2000). Cases and controls were always run on the same plate in a blind fashion. Assay quality was scored by an individual who had no access to the sample phenotypes, before the genotyping results were subjected to statistical analysis. Overall, the accuracy of our genotyping was >99%, as determined by internal comparisons of differentially designed assays for the same marker and by comparisons of the same marker across different groups.

Genotyping was performed in stages—markers were first genotyped in one sample set, the exploratory set. Generally, the WU sample set was used as the exploratory sample set. However, when markers were tested for replication in another sample set, we also genotyped that sample set with novel assays that had passed our assay-validation step. Overall, we used the UK sample (105 assays) and the UCSD sample (1 assay) as exploratory sets for <8% of all tested assays. Significant exploratory markers (P<.05) were then genotyped in two additional clinical case-control series. After replication in at least one of these other sample sets, additional fine-mapping markers were genotyped near the replicated SNPs. When additional assays for markers near significant exploratory markers were immediately available, they were genotyped in the exploratory sample in parallel with attempting to replicate in the validation samples. Significant markers were followed up as described above. Five SNPs that showed some level of replication in one or both of the additional case-control series were genotyped in a case-control series derived from the families originally used for our genomewide linkage scan. One of these SNPs (rs498055) was also genotyped in the case-control series that was composed of neuropathologically confirmed AD cases and controls.

Statistical Analysis

To help exclude assays with possible genotyping errors from the analysis, Hardy-Weinberg equilibrium tests were first performed in both the case and the control samples. Assays with significant deviation from Hardy-Weinberg equilibrium in controls were then examined for genotyping quality (P<.05; 63 markers in the exploratory stage). As a result, two assays were dropped from our analysis. One remaining assay with an MAF <10% was significant in the exploratory set but did not validate in the other sample sets and was in Hardy-Weinberg equilibrium.

Pearson’s χ2 test was used to calculate P values for the association of an allele with disease status within a single study. This test of association was performed on the basis of the frequency counts of a 2×2 contingency table of allele and disease status. Two-sided P values are presented for the exploratory study. In the validation stage, one-sided P values were calculated if the odds ratios (ORs) were in the direction observed in the exploratory stage. P values were not adjusted for multiple comparisons unless otherwise stated. ORs and the 95% CIs for an allelic effect were also estimated. ORs and P values for meta-analyses that combine results of multiple sample sets were calculated using the Cochran-Mantel-Haenszel test, and were controlled for the sample set (Agresti 1990). Evidence of replication, rather than multiple testing corrections, was used to evaluate the significance of associated SNPs.

Linkage Analysis

To determine whether rs498055 contributed to our linkage signal on chromosome 10, we stratified families on the basis of the presence or absence of the risk allele of rs498055 in the proband of each family. The families used in this analysis were the NIMH and the National Cell Repository for Alzheimer's Disease families from our linkage screen (Myers et al. 2002). The analysis was performed in Mapmaker/SIBS (“All pairs, UNWEIGHTED”). For the “proband” analysis, the (numerically) first individual with the SNP genotype was identified as the proband.

Haplotype Analysis

Several studies have shown that placing individual SNPs into the context of a haplotype increases biological information (Balciuniene et al. 2002; Knoblauch et al. 2002; Van Eerdewegh et al. 2002). Similarly, placing haplotypes into their evolutionary context also increases biological information (Templeton et al. 2005). For the haplotype analysis, we used SNPs that were typed in all three series and were located within ~40 kb of rs498055. These criteria resulted in a data set of 11 SNPs in 1,159 controls and 974 cases from the WU, UK, and UCSD case-control samples.

Haplotypes were estimated using the software PHASE (Stephens et al. 2001; Stephens and Donnelly 2003). A set of 95%-plausible haplotype trees was estimated using statistical parsimony in the program TCS (Clement et al. 2000; Templeton et al. 2000).

Association with LOAD was tested by tree scanning (Templeton et al. 2005), which was modified to manage case-control data (Nowotny et al. 2005). A tree scan uses the haplotype network to define tests that are based on each branch of the tree. Each branch represents an a priori defined pooling of haplotypes: haplotypes on one side of the branch are pooled together and define an allele, whereas the haplotypes on the other side are pooled to define a separate allele. This results in a biallelic locus that can be tested for association with the phenotype. A permutation-based analog of the sequential Bonferroni (Westfall and Young 1993) was used to obtain nominal and multiple-test–corrected significance values with the parametric P value used as the test statistic. This permutation method takes into account the correlation structure between tests while correcting for multiple tests.

Results

To identify genetic variation associated with LOAD on chromosome 10, we performed a SNP-based association study with three well-characterized LOAD case-control series. Our strategy was to test markers in one sample set (exploratory sample) and to follow up significant markers in the two remaining sample sets (validation samples). Using this paradigm, we first scanned a relatively large number of gene-based putative functional SNPs across chromosome 10, with the highest SNP density in regions directly under the linkage peak reported above. Significant markers were then genotyped in the other two sample sets to attempt replication of the initial association. Regions with markers showing strong association with the exploratory sample and replication in at least one other sample set were then tested with additional markers. Specifically, we genotyped a total of 1,397 SNPs by allele-specific PCR in the exploratory stage (fig. 1), targeting 674 genes. From these, we genotyped 408 genes with 1 marker, 141 with 2 markers, 57 with 3 markers, 47 with 4–7 markers, and the remainder with [gt-or-equal, slanted]8 markers. The majority of exploratory markers (1,291) were tested in the WU sample set. In the UK sample set, 105 markers were genotyped, and 1 marker was genotyped in the UCSD sample set. Of the 1,397 tested SNPs, 69 were significantly associated with LOAD in the exploratory sample (P<.05). These markers were scattered across the chromosome, as would be expected because of the high probability of false-positive associations due to the large number of SNPs analyzed (fig. 1). We subsequently genotyped the 69 markers in the two validation sample sets and found 5 that replicated in a meta-analysis combining the two validation sample sets (one-sided P<.05) (table 1). One marker, rs498055, located in LOC439999, a gene with high homology to RPS3A (MIM 180478), was significant (P<.05) in each of the three sample sets and was the most significant (P=.00004) marker in the three-sample meta-analysis (table 1). One other marker, rs4417206, located in a neighboring gene ALDH18A1 (or PYCS [MIM 138250]), was also significant in the combined validation study (P=.013). Markers rs4417206 in ALDH18A1 and rs498055 in LOC439999 are ~41 kb apart and are in strong linkage disequilibrium (LD) with one another (D=0.98; r2=0.43).

Figure  1
Allelic P values of 1,397 exploratory markers from the exploratory sample (middle), with a bar graph showing the distribution of annotated genes across chromosome 10 (bottom). Marker rs498055 is noted with an arrow, and a P value of .05 is marked with ...
Table 1
Allelic Tests of Replicated Markers and LOAD

To determine whether any of the five SNPs that replicated in the meta-analysis (rs1057971, rs498055, rs4417206, rs600879, and rs1903908) were also associated with risk for LOAD in our original linkage study sample (Myers et al. 2002), we genotyped the entire series and performed two analyses. First, we used a case-control approach by selecting one case (proband) per family, and we matched each of them to an equal number of unrelated controls. We chose to use a case-control analysis rather than a discordant–sib-pair analysis because of the greater power in the case-control design and because discordant siblings were available for only a proportion of the cases. A one-sided χ2 test demonstrated significant evidence of association in the case-control sample with the same allele as in the other case-control series for rs498055 (P=.0165); all other SNPs failed to show any evidence of association (table 2). The ORs observed in the linkage series for rs498055 were similar to those observed in the other case-control series (OR=1.26; 95% CI 1.02–1.54).

Table 2
Allelic Association in Linkage Case-Control Series[Note]

Marker rs498055 was also examined in two small series (183 cases/127 controls; 160 cases/106 controls) of neuropathologically confirmed cases and controls. The SNP was not associated with AD risk in these samples (P=.63 and P=.21, respectively). However, power to replicate our finding in these samples was low (40% and 36%, respectively; 60% power in the combined sample sets).

To further estimate the effect of rs498055 in the linkage sample, we performed a stratified linkage analysis of the stage II linkage data, on the basis of the genotype of the proband of each pedigree. We performed stratified linkage analyses using the pedigrees in which the proband had a copy of allele A and pedigrees in which the proband had a copy of allele G (table 3). We also considered pedigrees in which the proband was a homozygote for the A allele and in which the proband was a homozygote for the G allele. The results did not show an increase in LOD score in probands with the risk allele. In fact, although the first two groups were roughly the same size, the LOD score was substantially smaller in pedigrees in which the proband had a copy of the risk allele. This suggests that the rs498055 polymorphism (at 91.1 Mb) may have little direct effect on the linkage findings, which have their peak near D10S1211 (at 59.9 Mb), and that other loci contributing to disease have yet to be found in this region.

Table 3
Linkage Analysis of Pedigrees Stratified by rs498055

These findings prompted us to focus further follow-up on the region flanking these two genes. A total of 53 markers, covering a 1.49-Mb region, were typed in the exploratory sample, and association of these SNPs was examined. Ten of the markers resulted in a P value <.1 in the exploratory sample, and five were significant at P<.05 (fig. 2). After genotyping these markers in the validation samples, rs498055 remained the only marker that was significantly associated with LOAD in each of the three sample sets.

Figure  2
Allelic P values of markers around the RPS3A homologue region (LOC43999) in both exploratory and validation samples, along with a gene map of the region and Celera assembly coordinates (in Mbp). Blue diamonds indicate two-sided explatory sample P values; ...

We examined LD structure in this region, using genotypes from the UK and the WU sample sets. We observed a block of high LD extending from rs500470 to rs1418709, covering at least 190 kb of the genomic region that includes the most-significant markers, rs498055 and rs4417206. Although the D′ values among neighboring SNPs were high, the r2 values were generally low (table 4). The LD structure was comparable between cases and controls. The five significant markers with a P value <.05 (rs500470, rs533343, rs495998, rs498055, and rs4417206) were all located within this block and exhibited higher r2 values with rs498055 than with other neighboring SNPs. (All had r2>0.43 with rs498055.) Comparison of these results with data in the HapMap project indicates that the block containing rs498055 extends 419 kb and contains seven genes, LOC439999, ALDH18A1 (MIM 138250), C10orf61, ENTPD1 (MIM 601752), hCG2023951, hCG1781136, and C10orf130.

Table 4
Measures of Pairwise D′ and r2 in UK Controls[Note]

The tree-scan analysis of 11 SNPs in the region surrounding rs498055 identified significant results across many branches of the haplotype network. However, the results of the conditional tests suggest that the association observed at these branches is due to their location in the network relative to a single branch. This branch was significant in both the original (P=.0008) and the conditional (P=.03) analyses (fig. 3). It is marked by mutations creating the SNPs rs498055 and rs495998.

Figure  3
Haplotype networks. Each oval contains the haplotype identification number, the state at each locus, and the number of times it was inferred to occur in this sample set. To simplify the presentation of the network, haplotypes that appear only once in ...

Discussion

Genetic variants in several biological candidate genes under or near the chromosome 10 linkage peaks—including mutations in CTNNA3 (MIM 607667), PLAU (MIM 191840), IDE (MIM 146680), and others—have been reported to be associated with LOAD. However, none of the associations in these candidate genes has been consistently replicated (Alzheimer Disease Forum). Indeed, our own studies in the case-control series used in the present study showed no evidence of association with any of these genes (Myers et al. 2004; Nowotny et al. 2005). These findings suggest that the reported association may be false, although it remains possible that the lack of consistent replication may be due to type 1 error, genetic heterogeneity, population stratification, and/or a small genetic effect confounded by sample sizes insufficient to replicate the initial reports. With the technology that was available to us, we performed a broadly scaled and nonbiased genotyping program. This approach would inevitably be burdened by a requirement of multiple-testing corrections to assess potential associations. To mitigate this, we designed a two-step process in which we genotyped ~1,400 SNPs in the exploratory sample set but only 69 markers in the subsequent validation sample sets. This strategy led us to identify five SNPs, located in five genes on chromosome 10, that are associated with LOAD. Although our genotyping scan covers the entire chromosome 10, these significant SNPs are located relatively close to linkage peaks identified in other studies (Bertram et al. 2000). Our analysis included 12 SNPs in IDE, 2 SNPs in PLAU, and 32 SNPs in CTNNA3, but none was significantly associated with LOAD (Busby et al. 2004; Nowotny et al. 2005).

The most consistently associated marker among the five significant SNPs is rs498055, which is significant in each of the three initially tested clinical case-control series employed here, with an allelic P value of .00004 in the meta-analysis of the three sample sets. The replication P value of .00021 is significant even after Bonferroni correction for 69 markers (P=.014), and the meta-analysis of these three case-control series used in the screening paradigm is marginally significant even after adjustment for 1,397 SNPs (P=.051). The linkage sample–derived case-control series replicates these results, whereas the smaller combined neuropathologically confirmed case-control sample set is not significant. The meta-analysis of all six sample sets maintains that rs498055 is significantly associated with AD risk (P=.0001).

The tree-scan analysis identified a single branch in the network that is significantly associated with LOAD. This branch is marked by mutations at rs498055 and rs495998. Marker rs498055 is the most significant SNP in the single-marker association tests (see table 1), and rs495998 is in high LD with rs498055 (r2=0.98) (table 4). This suggests that the observed effect is a mutation on the background shared and defined by these SNPs. It is also interesting to note that rs498055 is homoplasious, with mutations inferred on four different haplotypic backgrounds (one major and three minor haplotypes). In some cases, the haplotype structure of a population allows for tests to be conducted at each branch that is marked by a particular SNP, which provides some evidence as to the “causal” nature of the polymorphism. Although no association was detected at the other transitions marked by rs498055 (a result that suggests that the SNP is not causal), the sample sizes for these tests are too small to provide strong evidence regarding the causality of this SNP. Inclusion of all the associated SNPs in this region in a logistic regression analysis by use of sequential regression (type 1) indicates that the significance derives only from LD with rs498055; that is, no other significant association is observed after first including the effect of rs498055.

Marker rs498055 is located in a gene annotated as an RPS3A homologue in the Entrez Gene database. Although the function of the RPS3A homologue is unknown, it appears that RPS3A itself is a strong biological candidate gene for AD. It has been reported that RPS3A mediates the interaction between BCL2 (encoded by BCL2 [MIM 151430]) and PARP—poly(ADP-ribose) polymerase—(PARP1 [MIM 173870]) and that BCL2 and RPS3A together prevent apoptosis by inhibiting PARP activity (Hu et al. 2000; Song et al. 2002). Thus, RPS3A is an important player in the early phase of apoptosis, a feature observed in AD-affected brains. However, we have been unable to detect transcripts of the RPS3A gene by RT-PCR in RNA from multiple tissues, including brain (data not shown). This may be due to constraints in transcript-specific primer design if a gene has multiple paralogues, as is the case with RPS3A. Alternatively, the annotated gene may not be expressed, and this SNP or variants that are in LD are located in a noncoding expressed sequence, such as a microRNA. It is also possible that this SNP, or variants that are in LD, modulate the transcription of neighboring genes. The SORBS1 (MIM 605264) coding sequence is located 33.7 kb downstream from this SNP and can be considered a strong biological candidate gene. It is involved in insulin signaling and was recently reported to be up-regulated in the hippocampus of AD-affected brains compared with controls (Blalock et al. 2004). ALDH18A1 (at 91.1 Mb and in tight LD with SNPs in RPS3A) encodes a member of the aldehyde dehydrogenase family, which is involved in proline biosynthesis via catalyzing the conversion of l-glutamate to l-glutamate 5-phosphate.

On the basis of the results in the combined validation sample sets, three other markers of interest were also identified, but they are not significant in all three individual samples. The power to replicate the original observation in the exploratory sample for these markers is relatively low in each of the validation samples (table 1). These markers are located in four different genes. PCGF5 (at 86.7 Mb) encodes polycomb group (PcG) ring finger 5, a component of a multimeric, chromatin-associated PcG protein complex, which is involved in stable repression of gene activity. SORCS1 (MIM 606283) (at 102.7 Mb) encodes a type 1 receptor containing a Vps10p-domain and a leucine-rich domain that is involved in endocytosis and intracellular sorting. It is most abundantly expressed in the brain (Hermey et al. 1999), and its expression can be differentially affected by neuronal activity (Hermey et al. 2004). hCG2039140 (at 102.9 Mb) is a predicted gene in the Celera Genome Assembly, encoding a 41-aa polypeptide with no apparent homology to any other known proteins. The potential relevance of these genes with LOAD remains to be examined. Moreover, it is possible that neighboring genes might have a role in AD, since the significant SNPs we identified or variants that are in LD may affect their function.

Although the association with rs498055 was replicated in the case-control series from the linkage sample, the pedigree analyses suggest that this association did not significantly contribute to the original linkage signal on chromosome 10. Although the power of this analysis is low, it suggests that there may be more than one AD susceptibility gene on chromosome 10.

In our screen, we did not attempt to systematically genotype chromosome 10; rather, we used an opportunistic approach to identify functionally relevant gene-based variants that show significant association with AD in at least two independently collected case-control sample sets. Therefore, we cannot exclude the majority of nonsignificant chromosome 10 genes from those that might contribute to the genetic risk of AD. This would require high-density SNP genotyping incorporating an LD-based approach to SNP selection in the case of the common disease–common variant hypothesis and, ultimately, deep resequencing of all genes, to exclude rare pathogenic variants. However, the results outlined above highlight five SNPs—particularly rs498055, which was replicated in four independent case-control series—and corresponding genes as likely AD risk factors on chromosome 10. These findings require functional experiments to validate potential links of the genes and genetic variation to pathways related to disease mechanisms for AD.

Acknowledgments

Some of the authors are employed by Celera Diagnostics, have personal financial interests in the company, or receive research funding from Celera Diagnostics. Funding for this work was partly provided by National Institutes of Health (NIH) ADRC grants P50 AG05681 (to J.C.M.), P50 AG05131 (to L.T.), RO1 AG16208 (to A. Goate), and PO1 AG03991 (to J.C.M.); the MRC UK (to J.W., M. Owen, S.L. M. O'Donovan, and L. Jones); and the Alzheimer Research Trust (to J.W., M. Owen, and S.L.). J.H. and A.M. were supported by the NIH intramural program and by the VERUM Foundation (DIADEM project). J.S.K.K. is supported by NIH training grant T32 HG000045, and T.J.M. is supported by MICORTEX and NIH grant GM065509. We acknowledge Mary Coats and Elizabeth Grant for coordinating the Washington University material, Mary Sundsmo for coordinating the UCSD case material, and Pamela Moore and Dragana Turic for providing clinical/DNA samples from MRC UK Genetic Resource for LOAD. Many data and biomaterials were collected in three projects that participated in the NIMH Alzheimer’s Disease Genetics Initiative. From 1991 to 1998, the research centers, grant numbers, and principal investigators and coinvestigators were as follows: Massachusetts General Hospital, Boston, U01 MH46281, Marilyn S. Albert and Deborah Blacker; Johns Hopkins University, Baltimore, U01 MH46290, Susan Bassett, Gary A. Chase, and Marshal F. Folstein; University of Alabama, Birmingham, U01 MH46373, Rodney C. P. Go and Lindy E. Harrell. Samples for this study also came from the National Cell Repository for Alzheimer’s Disease, which is supported by cooperative agreement NIA grant U24 AG021886. The neuropathological series were collected largely from several NIA–National Alzheimer's Coordinating Center–funded sites. Marcelle Morrison-Bogorad, Tony Phelps, and Walter Kukull are thanked for helping to coordinate this collection. The research centers, directors, pathologist, and technicians involved include: NIA, Bethesda, Ruth Seemann; Johns Hopkins ADRC, Baltimore (NIA grant AG 05146), Juan C. Troncoso and Olga Pletnikova; University of California–Los Angeles (NIA grant P50 AG16570), Harry Vinters and Justine Pomakian; the Kathleen Price Bryan Brain Bank, Duke University Medical Center, Durham, NC (NIA grant AG05128, National Institute of Neurological Disorders and Stroke grant NS39764, NIMH grant MH60451, and support from GlaxoSmithKline), Christine Hulette; Stanford University, La Jolla, Dikran Horoupian and Ahmad Salehi; New York Brain Bank, Taub Institute, Columbia University, New York, Jean Paul Vonsattel; Massachusetts General Hospital, Boston, E. Tessa Hedley-Whyte and Karlotta Fitch; University of Michigan, Ann Arbor (NIH grant P50-AG08671), Roger Albin, Lisa Bain, and Eszter Gombosi; University of Kentucky, Lexington, William Markesbery and Sonya Anderson, Mayo Clinic Jacksonville, Jacksonville, FL, Dennis W. Dickson and Natalie Thomas; University of Southern California, Los Angeles, Carol A. Miller, Jenny Tang, and Dimitri Diaz; ADRC, Washington University, St. Louis, Dan McKeel, John C. Morris, Eugene Johnson Jr., Virginia Buckles, and Deborah Carter; University of Washington, Seattle, Thomas Montine and Aimee Schantz. A.J.M. is a resident research associate of the National Academy of Sciences (U.S.A.).

Appendix A

Figure A1

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Object name is AJHGv78p78fg4.jpg

Count of markers used in the exploratory samples by SNP types. Note that the categorization of the unknown (intergenic) and silent mutation SNPs is based on the most current genome assembly (Celera Genome Assembly R27). In previous genome assemblies, these SNPs belonged to functional categories as well.

Table A1

Markers Genotyped as Part of the LOAD Screen of Chromosome 10[Note]

Gene
Sample
Marker123WUUCSCUKSNP Sequence
hCV1007164hCG1811021XTGTGTGTACGGGTGTGGTTGTGAAAGAGARAAGGAAGTCATTTTGTAGAGCTGTTTATTT
hCV11194331IDEXCCCGGCTCAAGCAATCCTCCCGCCTCAGCMTCTGGAATAGTTGAGATTACTGGCACGTGC
hCV11196784LOC119587XGGGCAACCTGGAAAGGACAATGCTTGTTAWAAACAACGACAGATGCTGAAAGGGATGAGT
hCV11205455MAT1AXAAGTTGCTGCTTCTGCTCCAGGAAGCCCASATAGGACTGGACTGGACTTAGACCACTTAC
hCV11208397DMBT1XAAGGATTCTTGTGTTCCCCTGTAGGATCTRAATCCAGTTTGGCCCTGAGGCTGGTGAATG
hCV11276238PTPREXTACCAGTTCATAATACCCATTTGTTGATGWCCTCAGGGGCTGACGGTGGCCGTTATGGTT
hCV11304669SAMD8XGAGGGTGGGAGGATCATTTCAAAAATATGWGATGTATGGTCCCTGTCCTCAGGAATATTA
hCV11374977NAXCTTATTAGGTCTTCCACGATAACTATTTTRTTGCCTCATACACCACCTCTTTATCCTGTT
hCV11476780VCLXTACTGTGGGCTATCAGGCTGCCTATATTTRGTGGGTGCCTTCATTTCTTTGGGTAGGCTC
hCV11568071MRC1XTACGCTACTAGGCAATGCCAATGGAGCAAYCTGTGCATTCCCGTTCAAGTTTGAAAACAA
hCV11568148hCG1660695XTGGGACCCCAGGAGCCCTCCTGTGACTCCRGAATCCTGAGAATGATGTCCCGGCGAGATG
hCV11596131JMJD1CXGGGAATTATAAACTGTTTTTTCTGTGCTGKTTTTTTTTTTTTTTTCTGAGACACAGTCTC
hCV11640694RSU1XGCAACCAAAAGGGAAACGCGGGTTCCCCCYGTCAGGCAGAAAACTTCCCAGACAGACTAC
hCV11640699CUBNXTTAGAAAGGGTAGCAGCAAGACCTACCACSAAGTAATCCCCCTGGTTGCAAGAAGAATCT
hCV11647845CALML3XCCTCCACGGCATGGCATCAGCTACTCTGAYTCAGTTCACCCACGGCAGTGAGTGTGTCCT
hCV11652239KINXCATACATACTATCTGTCCTAGTAAGAAAAYAGATCAACGCTGAGTAGAAACTATGGATGA
hCV11756797HTR7XAATGGGAAGTTGGACACACTTCCTGATACYCCCACCTTCAGGGGAGCCATCAGGCTTTCC
hCV11779483ASAH2XATATAAACCCCAAACCCCCAGCTCCACAARCAGACAAGGAGATGAACAGAAAAGCAGAAT
hCV11877867NCOA4XTTGAGCCAAGGAGTTTAACACCAGCCTGGSCAACATACAGAGACCCTGTCTGTACAAAAA
hCV11880347GALNAC4S-6STXTTTTGTTTTCTCCTTTGCACGTGGGGCACRCCTGGTGACCGTGATGGGGGCCCCCTTGGC
hCV12014288NAXACCCACTGACACCGGTGATAGGGGCCTCTYTTCCACTGGACTGACAGCTACAAGGATGTA
hCV1213173hCG1781406TACC2XACAAAGTGAGCATGGGGTGTAACATGTCCRTTTGCTTACTATGCATGCACGCCCCTCTTC
hCV1229739ADAMTS14XCTAGTGAGGTGTTTTGTATTCATAAACAARGTTATTTAAAACAAAAAAGCTGGAGTATCC
hCV1251183hCG1820432XGAGCAAGAATGTGATGCTTTAGAAGAAAGRAATGAATGAAAGGCCAGGCTGGTTAAGCTG
hCV1345812PKD2L1XXXGGGAAGCCATCAGCTCCTGTTCTATCACCYACTCTACTGGGATCTCAGGACCAAGGCTCA
hCV1407029hCG2041916XCAGAACACAAATTATTATTATGATTCCTAWTATGAGCAATAGCTTCTGCCACCAAGTTCC
hCV1531925SUPV3L1XGCCAGCGGAGACTCCTTTTAGGATTCTTTRTCATTGAGGAGGCGCCGACTCATACCACGC
hCV1548908hCG1643384XTGAAGATGCTTCAGATTCAATCCGAGAAAKGTATCACTGCAGAGTTTATAGAAAATGAAG
hCV15792242C10orf30XGTTCGCTGGGAGCATATAAGGGAAATTGGRGGTTGTTGTCTGTTTTGAGTTCCAACTGCG
hCV15825497NAXCTGGTTAATCGCAGGAGGCACTTTCAGCCMCTTATAGAGGATGGCTCTCTGCCGCTGCAA
hCV15834772MKI67XGGTCTCCCCTGACGTCCGTGTGAACTTGCYGACTGCTAGGAGCTCTTCTTTCACACCTAC
hCV16167035hCG1655317XTGATCTCATCCATCTTACTAAAGTTTGTGSAGTCTTGATCATTCCCCATTCCCCCAACAT
hCV16192725C10orf35XACAGGTAGGTACTCATTTCCTGTGGAGTGRGACAGATGGCCTCCTGTGTACTGGCTACTC
hCV16264597NAXCTCAGACTCCAGTTATGGCTCAACCCAAARAAGATGAAGAGGAAGATGATGATGTAGTGG
hCV1709930LHPPXGACTTGGCCCAGGGCAGCCTCATAAAGCARTTCCCACCCAGGACCGCCCCGATCGATCGG
hCV1720473C10orf7XGCAGGTACAACATTTTTAAGACAGATACARTGTAAACCTTTCCAGTCTACTGACTGACTG
hCV1893544JMJD1CXCATCCTACAAGATGTGGTAAATTTGAAAAKAATAACCCTGATCTTTACTTAAAGGAGTTG
hCV1912681hCG39169XCAGCGTCTGGTACAGCCACCTGTTCTTCCRGTACAGATGGAAGTGGAATTGACTATCTGT
hCV1974596LOXL4XTGGGCTTGAGCCGCACCTCCTCCAGCCGCYGGCCCTGCGGGGTGCACAGTCACCTGTGGG
hCV2008818SORBS1XACAGCAGCTGAGGCACAGGCATTGAAAACRAATTTTGCCTACCTGTAAAGACTCTAGACT
hCV2009356hCG2041919XTTTTGTAGAAAGTATTTGAGGTGACGCTCWCAATTCAAGGAGATATCTCAGGGTGTAAGA
hCV2041328hCG2041421XTTTCAACTGAGAGGATAACAAAGAACATGRTAGGAGTTGGACTACATAAAAGTTAGTTTC
hCV204710hCG23640XTCTTTGACAAGTTTGAGTGTTGCTGGAACRGTTCGGATAGGTAAGGCCTGCGTGGAGATG
hCV21898RPP30XGAAGTTTGAATTTGTCTGTCAAGCCTGTAYACACTAGCATTGTCAGTAAGCTTTGTTTTT
hCV2376176hCG1811015XGATTCCTAGAGGGAACCTCCCTCCCCCCCWCAAGGGTGACACGCATGCTCGTGGGGTGAT
hCV2432147TXNL2XAGCGACATGCATCTAGTGGCTCCTTCCTAYCCAGCGCTAATGAACATCTTAAAGAAGATC
hCV247567LOC220929XACACATGCATGTTTTCACTGAGAGCTGTAYTTGAAGAACAGCCTATATTCTGCTAAATTT
hCV25592823CWF19L1XCATAGGGCTCAAAGTCTTTCCGGAAGCGGYGAGCCAGGGTCTCCTCGTCTTCCTTGCTGA
hCV25595249SYNPO2LXCCTGCTTGGGTGTTGCCCGAGGCCCCTGGKATTGGGCCTTAGGGAGAGTTCGGGCCGCCT
hCV25595681NAXAACCAGAACAATGTCTTTTGACTTGCAGARATCCAGCAGTTTGCTCTGGTTGAGGTAAGG
hCV25596066RGRXTCTATACGCAGTCATCGCAGACGTGACTTYCATCTCCCCCAAACTGCAGATGGTACAGAT
hCV25599810MMRN2XACCCTTCTGCAGCTCAGCCATGGCAAAGASCGTTGCTGTGCTTCCACTCCCCTGCCCAGT
hCV25600248ADAMTS14XCGGGCCCCAACCCTGGCCCAGACCCTGGCYCAACCTCACTGCCCCCCTTCTCCACTCCTG
hCV25602992DNTTXGTTTCAGAACTCTGAGTAAAGTAAGGTCGSACAAAAGCCTGAAATTTACACGAATGCAGA
hCV25603384INAXCCAATCCAAGTTACCTGCTCCCACCTAGAMTCCTCAGTGCTACAACCTCCAAAGTCTCAT
hCV25603850hCG23635XGTCTTAGGTTTTAGTCTCTATGGAAAGCAYTGTGAAGTTAAAGTGCTTAATATTCACATA
hCV25603990hCG23635XGAGGTATTTTCTTAACAGGCACTGTGGGCRGCAATCTGTCAACAGAGAAAATAAAACTAT
hCV25604328PPRC1XAAACACCCCTTGAGATTTGCCTTGTGCCTRTAGGTCCCAGCCCTGCTTCTCCTAGTCCTG
hCV25604457ITIH2XGGACTATGATTTTTTGAAGAGACTGTCCARTGAAAACCATGGAATTGCACAAAGGATTTA
hCV25604675ARHGAP19XCAGCTCTCTCAGTGCCTCTTCCGTATGGTRCTGGGTCTCCTCCTGGTGAGGGCAGGAATC
hCV25605409C10orf28XCGAAGAGTTCAAAACAGAAGAGCAAGATGMCTCAGGGAGTATAGAATTTGGTGTATCTTT
hCV25606322C10orf64XCCTGGAGAGAGGGAAGTGAAGATTGAAGASGTCACACCGCTCTGGGAGGAGACGATGCTC
hCV25614719OGDHLXGAGCTGGCCACACTGCCGATGTGGGTGAGSATGTCCTCAGGGATCCCCGTGGCTGGGCAT
hCV25624518PNLIPRP2XCTGTAAAATTACTTCCCTGGTCCCCCGAGSACATTGACACCCGCTTTCTTCTGTACACAA
hCV25624843MCM10XGAACCAAGAGGGTGGCTCGAACACCAAAGSCTTCACCTCCAGGTGTAGTACTTGCGGTCT
hCV25625205JMJD1CXTATACCTTTTGAAGAAATTCCCTTATCTTSTCAACATCTTTCCCAGCATAAATATGCCAC
hCV25626240FER1L3XTTTCCCTGCATAAGGGTCACAGCGAAAGCRGTCCAGGCGCTCGATGGTGCACTGGCCGAC
hCV25626404C10orf3XAGAAATGTTACAACGATCTCTTGGCAAGTSCAAAAAAAGATCTTGAGGTTGAACGACAAA
hCV25638641hCG1641533XTACTGTTCGGTTCTGGTTCTACATGATTGWTCCCAGGAGTATGGGAATATTAAAGGTACA
hCV25639102hCG1643351XTATCAAAAGTATGCACGTATTTTATGTATRAGGTTCGCTACCCTAACAGCTCCACCGAGG
hCV25644235hCG1655308XTTTGACATTGATAGACTAGGAGAGGAAATYATCTCCAGGAAAAATGCCATGCATGACCAG
hCV25650689MGC16186XGAAGGAGGCCTTGAAGCAGGAATTCCTGCSAGGTACTTCCAGTCTGATTCCAGGAATGCC
hCV25651247AMSH-LPXTGCGAAGTCAGCAAACCTCAGGGCTGTCARAGCAGATTGATGGGAGCGCTTTGTCCTGCT
hCV25651790THNSL1XGCCTGAAGACTGTGAACAGAAGGTTTCAGMAAAATTCTTTAGTGAAGCTGTAATTGAGGG
hCV25651880NEBLXTGACCTTCCTTTAATCTCCTTCTCAAAATSCTCTTTGTAAACTTTCTGTTAAATAAGACC
hCV25652036hCG1792626XGCCTGACGTTCGTTCATCAGCTCCTGGTAMTCACGCCGCTGCCGCGCCATGTCCTGCTTG
hCV25652141TCF7L2XGTTAAAGAACATTAAATAAATTATATAAGKATGCCTACCTGTAACACTTTTATAAGGCAA
hCV25652286SORCS3XAGCAGAGGCCGTAAAAAAAAGTTTAAAGCRTGAAGCGAAATTCCACACCCATCCAGCGCT
hCV25767316HECTD2XAATTACTATTTACAAGATCTATAAACTTCRGAAGCAAAAATATCTTGCCTTGGCAGGAAA
hCV25921991hCG2018011XCTTACTGGGAAGGTTACGTTATGTAATATXTGCCAGCCATTTTTGCAAAGTGCTGTATAC
hCV25923481hCG2023484XATTGAAAGCCATGGGAGAGGCTAAAGGAASAAGAGCCTCCAGATAACTTTCCTGAAAACA
hCV25930703hCG1648656hCG2042804XTCCTTCTGACACTGGGTCCCTGTCACTTCYGAGGGAACAGGACCGTAGGATGATGTTTCC
hCV25931135hCG1803570XAAGCTGTGGAGAGCCACGAAGGTGGCAGGRGGCATTAGAGGGGCTGTAAAGGGACCGATG
hCV25932561MGC32871XATTCAAATTAGTTTATCATTTACCTGCAAWCTTTTTCTTTGGTTCTGCAAGTCCGTGACT
hCV25933604KNDC1XTGACCCAGCCTCCTCGGCCGTGCTGACGAYGAGAATGCAGGTCAGTCCCCACCTCCGCCC
hCV25936294NAXCGCGCCGGCACGAGGGTGTTTTCGACGTTRGCTGTGGGGAAACAGCAAGCGGCGTGGACG
hCV25943811C10orf61XXCGGGTCCGACGTAGGCCTCCGCGGTCTCCMATCGCATTGCCAGAGCGTGGGTGGGAGGAG
hCV25953510hCG2024410XCTTTGGTCACCCTGTGGTAGAAAGCCTTCRAAAGCAGCTAGGCCAGGACCCTTTCTTTGA
hCV25953694hCG2017698XGTGTCAGCCTGGACAACATAGCAAGACTCYATCTCTGAAAAAAAAACAACAACAAACTTT
hCV25966142GPR123XGGCGGGGTCACTTCGGTACCCCCAGTGACYTCATGTGGCAGATGGGCCCCCCACTCTGCT
hCV25971922NUDT13XCTGTTTCTTAGAGTTGGAAAGGCTCCTGGRTAAATTTGGACAGGATGCACAAAGAATAGA
hCV25990430NAXTTCTCCTCTTGTAGCACCCAGTGACTGTGSGGGCCACTACACAGATGAATATGGCAGGAT
hCV29522RPP30XTTAAGCACAGATCTTAATTTTGTCACGATKTGGGCCCTTTTCTTTGGTTGTGGTGAAAAG
hCV3010735hCG1993574XGGGGAAAATGTCTGGGAAGAAGCTTTTCGKGACCAATGGTGAGCGGATGCCTTTCTCCAA
hCV3033543NAXGCCTGAAGGGGAAAGCCACCTCGGAGGACMCCCTCAATCTAAGGTAATGGCGGGTAGCCA
hCV3061051NAXGCTGGCAAGGCTGCGGAGAAAAGGGAATGYTTACACACTGTTGGTGGGAATGTAAATTTG
hCV3261312KIAA1754XCCCCCTCTGTCGGCAGCCATCTCCGACACRGCTCCTCCGAGCTCGCGCTCTCCATCGCGC
hCV382705BTRCXCCAGGCCTCAGCTGGTAGTGTAGTTATTTMAAATAATATTTAATACAATAAATTCTATGG
hCV385555hCG1657676XCCCGAACAGAGGTAGATACCATGTGTAGAKAGAAACAGGCAGAGAAATAGGAGAGTTGAA
hCV7432608KCNMA1XCTTACCACGACCCAAAGAGCCTCACAGAAYAGATTTCGGAAAGTACGTGTGCGTGTGTGT
hCV7534313hCG2041498XTTGGTACAGGTAAGACCATCAGAGTGATTRCTGACATCTGGAATGTTGTTGTTCTTTTCA
hCV7548937hCG25651XACAGTACATAAGAGAACACACAGAGGGGAKAAATCTTATTACTGTAATAAATGTGGGAAA
hCV8040921CTNNA3XCTATTGCATGATTGCTCGTACACATGTCTMTTCCTGGGTAATGAGCTCCATTATAGGAGG
hCV8171810ABLIM1XAATATCCTTGGGATTTAGCTCCGTAGCTAYACTTATGTTACATTCTCCATCTCTCCCACC
hCV9580408CACNB2XTTTATTTTTTCCCAGAGATGTTTTTATCTRTCTTTTGTGCCTTGTGACTTTGATAAGGTT
hDV60100216NAXCTTGTCACAGCCGACAGGCTGAGGCCAGAKGTGAGGTCAGTGGGAGGAGGCTCCCCTGCC
hDV60100219NAXTAACTGAAACCACAGAACTTGTATATCCTYAGGATTGAGTTGATGAAGGTCATAAAAGGT
hDV68531048NAXCGCCCCCTGGCACTACCGCGGGTCCGCACYCCACGCCGGGCTGATTCCGGCGCTCGCTCA
hDV68531050PYCSXCCTAAAGTCTGAAGGCTCACAGGCCTGCTSGAGTGTCAAGTCTGCTTGTAGTAGTGTCTT
rs1004256CBARA1X
rs10082391MKI67X
rs10082466MBL2X
rs1017822ATRNL1hCG2042431X
rs1021362SORCS3X
rs10242RPP38X
rs1027190SORCS3X
rs1029074LIPAX
rs1029077ARHGAP12X
rs10409HNRPFX
rs1042454RGRX
rs1043009hCG2041852X
rs1043098EIF4EBP2X
rs1044258C10orf76X
rs1044261IDI2X
rs1044563PPP1R3CX
rs1044612CAMK2GX
rs1044795ARHGAP12X
rs10450321hCG2017076hCG25653X
rs1045170WDR11X
rs1046399LDB1X
rs1046528hCG1640346X
rs10466026CDH23X
rs10466280SEC61A2X
rs1047100FGFR2X
rs1047991PAPD1X
rs1048828NAX
rs1049125PNLIPRP1X
rs1049455NOLC1X
rs1049632RSU1X
rs1050767MKI67XXX
rs10508773EPC1X
rs10509343CBARA1X
rs10509571IFIT4LIPAXXX
rs10509612RPP30X
rs10509613RPP30X
rs1051338LIPAX
rs1051509ARHGAP22X
rs1051723TLX1X
rs1052289SEC23IPX
rs1052420hCG24072X
rs1052895hCG1781727X
rs1053266CCDC6X
rs1053905PYCSX
rs1054053hCG1993574X
rs1057108CREMX
rs1057234hCG1803442X
rs1057910CYP2C9XXX
rs1057971RNF159XXX
rs1061135HPS1X
rs1061159hCG1781474X
rs1062465MPHOSPH1X
rs1063535MKI67X
rs10727PANK1X
rs10736069KIF11X
rs10736889LOC399818X
rs10740118JMJD1CX
rs10745302GPR123X
rs10751331hCG2006747ZNF32X
rs10751904hCG2039878hCG2041856X
rs10752157hCG2041860XXX
rs10761471ANK3X
rs10761733JMJD1CX
rs10761739JMJD1CXXX
rs10762179NAX
rs10762231CXXC6X
rs10762360LRRC20X
rs10762430hCG1818231UNC5BX
rs10762732hCG1793822X
rs10762760KCNMA1X
rs10764048C10orf9X
rs10764734PTPREX
rs10764882hCG1796762X
rs10764899MGMTX
rs10764921hCG41189X
rs10765037TCERG1LX
rs10776682hCG1803640X
rs10786050KIF11X
rs10786122C10orf4X
rs10786211SORBS1X
rs10786740hCG2040253X
rs10786775OBFC1X
rs10786783C10orf78X
rs10787227SMNDC1X
rs10787428GPAMX
rs10787728hCG1792255X
rs10787879hCG39777X
rs10795417RSU1X
rs10795446CUBNX
rs1079610OPN4X
rs10821668ANK3X
rs10821675ANK3X
rs10821937hCG41574X
rs10822156JMJD1CX
rs10822160JMJD1CX
rs10822988CTNNA3X
rs10823333HK1X
rs10823345HK1X
rs10823365TACR2X
rs10823435COL13A1X
rs10823935CBARA1X
rs10824119ADKX
rs10826793hCG1789973X
rs10827628hCG1641533X
rs10828317PIP5K2AX
rs10828395ARMC3X
rs10828833GPR158X
rs10829163hCG25239XXX
rs10829529hCG1654004X
rs10829970TCERG1LX
rs10857625C10orf64X
rs10882617SORBS1X
rs10882645PYCSX
rs10882993ZFYVE27X
rs10883100HPSE2X
rs10883565C10orf6X
rs10883841NT5C2X
rs10883974C10orf79hCG23142X
rs10883979C10orf79hCG23143X
rs10885330hCG1811160X
rs10885789ATRNL1X
rs10887621KIAA0261X
rs10887666BMPR1AX
rs10901542hCG1793036X
rs10901614hCG1660574X
rs10903752ZMYND11X
rs10906818THEDC1X
rs10994860ACFX
rs10997762CTNNA3XXX
rs10997795hCG1786927X
rs10997818DNAJC12X
rs10997823DNAJC12X
rs10998112RUFY2X
rs10998268hCG1787108X
rs10999147TYSND1X
rs10999212GPR147X
rs10999426PRF1X
rs10999511MYST4X
rs11000566TTC18X
rs11000911ADKX
rs11001296SAMD8X
rs11001359hCG1643166X
rs11001456NAXXX
rs11002528hCG2041497X
rs11006122UBE2D1X
rs11006128TFAMX
rs11007349hCG1820823X
rs11008020hCG1643739X
rs11008032hCG1643738X
rs11009218NAX
rs11010082CUL2hCG2040100X
rs11011216hCG1817887hCG1817888X
rs11011224hCG25652X
rs11013233ARMC3X
rs11015624hCG1648219X
rs11015640ARMC4XXX
rs11016076MKI67X
rs11016944hCG1796998X
rs11068NET-7X
rs1108616RAI17X
rs11101202CHATX
rs11106MKI67X
rs1111350TLX1X
rs1113394NRAPXXX
rs11146301NAX
rs11186275hCG1787893X
rs11186361NAX
rs11186426hCG1641715X
rs11187265CYP26C1X
rs11187825PLCE1X
rs11187952hCG1811021X
rs11188410ALDH18A1X
rs11189211KIAA0690X
rs11189705HPSE2X
rs11190190SLC25A28X
rs11190780SEMA4GX
rs11190812KAZALD1X
rs11191283PSDX
rs11191865OBFC1X
rs11193438hCG2039140X
rs11196200hCG1776259TCF7L2X
rs11196400NRAPX
rs11196686NAX
rs11199005RGS10X
rs11199755hCG2040383X
rs11200999KIAA1128X
rs11204210ZNF488X
rs11239851hCG2040417X
rs1124013hCG1641930X
rs11245007hCG2023484XXX
rs11245366LOC399818X
rs11248366ACADSBX
rs11253042AKR1C4X
rs11253185NET1X
rs11254232CUBNX
rs11254238CUBNX
rs11256802RBM17X
rs11257462UPF2X
rs1125798hCG1781035X
rs1129614GDI2XXX
rs1132816PIP5K2AX
rs1139943DNMBPX
rs1148274hCG25654X
rs1148275hCG25654X
rs11509438GSTO1X
rs1152659CTBP2X
rs11541237NAX
rs11542131PEO1X
rs11553577C10orf61X
rs11572080CYP2C8X
rs11591349SEMA4GX
rs11592052CCDC7hCG2017386X
rs11592502hCG1781166X
rs11592567hCG2040099hCG2040100X
rs11592612ACADSBX
rs11593766CASP7X
rs11594687NAX
rs11594962C10orf79X
rs11595081hCG1818441X
rs11595114SORBS1X
rs11595603LRRC20X
rs11595684ZNF248X
rs11596193HK1X
rs11596235SUFUX
rs11596518HTR7X
rs11597349PRKG1X
rs11597471HTR7X
rs11597812hCG2041859X
rs11597888hCG2041374X
rs11598232ADKX
rs11598673hCG24137X
rs11599164ANK3X
rs11599210ADAMTS14X
rs11599234PTPLAX
rs11600hCG1643971X
rs11601CSTF2TX
rs1162759HNRPH3X
rs1171614SLC16A9X
rs11812465hCG2040270X
rs11812708HTR7X
rs11816811COL13A1X
rs11816967C10orf59X
rs11872PDLIM1X
rs1200814ANKRD30AhCG1789874X
rs1208606ZNF25X
rs1211373hCG1745367X
rs12217414C10orf68X
rs12221STAMX
rs12221039hCG32858X
rs12240276AKR1CL2X
rs12241995NRAPX
rs12243497ANXA7X
rs12244832C10orf68X
rs12247541RSU1XXX
rs12248786BMPR1AhCG1994049X
rs12251014ADAM12X
rs12253226hCG1643166X
rs12253240CTNNA3X
rs12254856AMSH-LPX
rs12255505USP54X
rs12256352HTR7X
rs12256617hCG1787893X
rs12256853VPS26X
rs12261515hCG32744X
rs12262099LRRC21XXX
rs12263503hCG1649846X
rs12263945hCG2040383XXX
rs12266925CCDC7X
rs12268745CUL2hCG2040100X
rs12268910ADD3X
rs1227049CDH23X
rs1227065CDH23X
rs1227236hCG1640361X
rs1228187LIPFX
rs1229406LIPFX
rs12354886ZNF485X
rs12356978C10orf92X
rs12357316VCLX
rs12359728hCG2040358X
rs12359843KAZALD1X
rs12359948hCG25653X
rs1240373hCG1994053X
rs12412095hCG1642404X
rs12412249IDEX
rs12413153NAX
rs12414281HERC4X
rs12414693SORBS1X
rs12415681SORBS1X
rs12415976SARA1X
rs12416239hCG40968X
rs1244229hCG1774090XXX
rs1244422ATP5C1X
rs1244471hCG2017949X
rs1245560SPOCK2X
rs1247441SVILX
rs1247755KCNMA1X
rs1247766KCNMA1X
rs1248623DLG5X
rs1248634DLG5X
rs1248636DLG5X
rs1248638DLG5X
rs1248653DLG5X
rs1248674DLG5X
rs1248678DLG5X
rs1248688DLG5X
rs1248689DLG5X
rs1248690DLG5XXX
rs1248696DLG5X
rs1250533RAI17X
rs1250541RAI17X
rs1250556RAI17X
rs1250565RAI17X
rs1250580RAI17X
rs1250600RAI17X
rs1251363KIF5BX
rs12570211hCG24887X
rs12570967PPX
rs12570974P4HA1X
rs12572012MPHOSPH1X
rs12572520C10orf70X
rs12573590ADKX
rs12573841hCG2024499X
rs1258184OGDHLX
rs1264781ATRNL1X
rs1268514DLG5X
rs1268956DLG5X
rs1270911DLG5X
rs12761105HTR7X
rs12761705hCG24649X
rs12765373C10orf107X
rs12765826hCG1744837X
rs12766523RPP30XXX
rs12766938hCG1643166X
rs12767046ARL8X
rs12767142ANXA11X
rs12769629hCG2036818X
rs12769766PCBDX
rs12770335SGPL1X
rs12770830hCG25567HSPA14X
rs12771333hCG1646071X
rs12771404hCG1648653hCG41189X
rs12772251DOCK1X
rs12772980hCG2041102X
rs12773574SORBS1X
rs12773592hCG1646071X
rs12774010C10orf64hCG1642860XXX
rs12774061CTNNA3X
rs12774070ADAMTS14X
rs12776792NAX
rs12779919ABI1X
rs12780826NAX
rs12781453hCG2040330X
rs12782946hCG1781474X
rs12782963PKD2L1X
rs12784524hCG40467X
rs12784975PIK3AP1X
rs12915hCG2040497X
rs12917MGMTX
rs13088C10orf72XXX
rs13134ALOX5X
rs1316312PPIFX
rs1316313PPIFX
rs1317894C10orf64X
rs1320496LIPAX
rs1321934PAPSS2X
rs1322319ZNF248X
rs1324693NAX
rs1326331SEC15L1X
rs1328323SVILX
rs1331326NRP1X
rs1334891FRAT1X
rs1336459C10orf130X
rs1338565ZNF239X
rs1338864NAX
rs1339746hCG1644292X
rs1339907hCG2038611X
rs1340380LOC143241MGC16186X
rs1341667NAX
rs1341676NAX
rs1342273MXI1XXX
rs1344089CTNNA3X
rs1344967NAX
rs13500LIPAX
rs1356090KCNMA1X
rs1359281PARD3X
rs1359511RAI17X
rs1359849SHOC2X
rs1360456NRP1X
rs1367024NAX
rs1370562hCG1781753X
rs1374471C10orf76X
rs1380555FAM13C1X
rs1397617EIF3S10X
rs1403629VCLX
rs1407696PDCD4X
rs1409313CUEDC2PSDX
rs1409322PRPF18X
rs1409354PANK1X
rs1410304ATRNL1X
rs1413772ARMC4X
rs1413835FAM13C1X
rs1417000hCG25163X
rs14177LZTS2X
rs1418362MXI1X
rs1418709ENTPD1X
rs1436186PIK3AP1X
rs1436214hCG1745369X
rs1439031hCG1815393X
rs1441735ACTA2AMSH-LPX
rs1443502MRC1X
rs1457523KCNMA1X
rs1459990FAM13C1X
rs1459996FAM13C1X
rs1468063TNFRSF6XXX
rs1471384CTNNA3X
rs1474hCG1655317X
rs1475435EPC1X
rs1477069ADAMTS14XXX
rs1477070ADAMTS14X
rs1477071ADAMTS14X
rs1477536hCG1644026X
rs1484247SORCS3X
rs1516510KCNMA1X
rs1536444SORBS1X
rs1538204CNNM2X
rs1538311ADKhCG1644605X
rs1538599LGI1X
rs1539163DDX21X
rs1541009FRMD4X
rs1541046GBF1PITX3X
rs1544210NAX
rs1551067MYST4X
rs1551687hCG1773755X
rs1555319NRP1X
rs1556612hCG23658X
rs1556641ARMC4X
rs1556864hCG1647210X
rs1561087KCNMA1X
rs1563824FAM13C1X
rs156697GSTO2X
rs157076GSTO2X
rs1571013TNFRSF6X
rs1571781NRP1X
rs1572798ADAMTS14X
rs1572934TNKS2X
rs15772RPP38X
rs1609746hCG2042429X
rs161229TCF8X
rs161254TCF8X
rs161255TCF8X
rs1638421hCG2023700X
rs1639134KIF5BX
rs1650146hCG2040947X
rs1668154ASCC1X
rs166924FAM13C1X
rs1671308RSU1X
rs16924989HERC4X
rs16925584CXXC6X
rs17010003hCG32744X
rs17091403hCG1781474hCG2040349X
rs17091424TDRD1X
rs17098707GRK5X
rs17101193hCG1641930X
rs17108179hCG2040337X
rs17108991RBP4XXX
rs17109671PLCE1X
rs17110999NAXXX
rs17113613PEO1X
rs17116350COL17A1XXX
rs17133693AKR1CL2X
rs17152897MCM10X
rs17173698PAPSS2X
rs1720293hCG1815358X
rs1721804FER1L3X
rs17229970hCG1802476X
rs1735641hCG25651X
rs17366712hCG1774090X
rs1739HPS1X
rs17391197SMBPX
rs17445028IDEX
rs17445328IDEX
rs17468739IFIT2X
rs17473271PRG1X
rs1749849RAI17X
rs1749851RAI17X
rs17506606hCG2042945X
rs17508082PLCE1X
rs17511CTNNA3X
rs1751658hCG23635X
rs17516758PLCE1X
rs17517578C10orf117X
rs17526356SIRT1X
rs1753586PARD3X
rs1761987hCG2041939X
rs1767174SGPL1X
rs17673844hCG1811160X
rs1769692LIPFX
rs17730369CWF19L1XXX
rs17731COPEBX
rs1775230APBB1IPX
rs17756919SVILX
rs1775715KIF5BX
rs17768650ANUBL1X
rs1777329SVILX
rs1781935hCG20065X
rs1782644RAI17X
rs1782645RAI17X
rs178598TCF8X
rs1786909CTNNA3X
rs17879914CYP2C19hCG2044079X
rs17881479SFTPA1SFTPA2X
rs17883804CHUKX
rs17884026CHUKX
rs17885900SFTPDX
rs1797077RSU1X
rs1799939RETX
rs1800373SNCGX
rs1800451MBL2X
rs1800898PAX2X
rs1801222CUBNX
rs1801230CUBNX
rs1803997MXI1X
rs1804689HPS1X
rs1804934PYCSX
rs180643NAX
rs1830951NAX
rs1832196IDEX
rs1833477NAX
rs1837949hCG1788856X
rs1837950hCG1788856X
rs1856564IMPKX
rs1856591hCG37897X
rs1856679DKFZP566K0524X
rs1858610PLCE1X
rs1864590NET-7X
rs1865638hCG2040457hCG2042457X
rs1866435DLG5X
rs1867998CDH23X
rs1868627MYST4X
rs1868751FAM13C1X
rs1871063KCNMA1X
rs1871065KCNMA1X
rs1871084ADKX
rs1871446CDC2X
rs1874147AP3M1X
rs1874150VCLX
rs1874151VCLX
rs1874664ATE1X
rs1877993KCNMA1X
rs1880055C10orf27X
rs1880057SGPL1X
rs1880389hCG1818441X
rs1880676CHATX
rs1885434NRAPX
rs1885517NAX
rs188571LIPFX
rs1886996MPHOSPH1X
rs1886997MPHOSPH1X
rs1887027hCG1642404XXX
rs1887922IDEX
rs1888685NRP1X
rs1888686NRP1X
rs1889568DUSP5X
rs1890739hCG1647787X
rs1891110FAM24BX
rs1891269hCG1641716X
rs1891386hCG1818441X
rs1891565FER1L3X
rs1892110hCG1787893X
rs1897367RHOBTB1X
rs1897516hCG1658018X
rs1898082C10orf11X
rs1900005hCG1817383X
rs1903870CTNNA3X
rs1903894hCG2040450KCNMA1X
rs1903908hCG2039140XXX
rs1904416CDC2X
rs1904589NODALX
rs1904634CTNNA3X
rs1905542KIAA1598X
rs1907724KCNMA1X
rs1907732KCNMA1X
rs1907733KCNMA1X
rs1907737KCNMA1X
rs1907740KCNMA1X
rs1912277hCG1818441X
rs1914345BTAF1X
rs1915440TMEM26X
rs1916389CTNNA3hCG2038400LRRTM3X
rs1917138NAX
rs1917155hCG1818441X
rs1923260ATAD1X
rs1923694TLL2X
rs1923696TLL2X
rs1923934GLUD1X
rs1924504hCG23635X
rs1925576CTNNA3hCG2038400LRRTM3X
rs1925591CTNNA3hCG1810898LRRTM3X
rs1925604CTNNA3hCG1810898X
rs1925607CTNNA3hCG2038400LRRTM3X
rs1925621CTNNA3hCG2038400LRRTM3X
rs1925627CTNNA3hCG1810898LRRTM3X
rs1926564ACSL5X
rs1926736MRC1X
rs1928494hCG2040451X
rs1931757hCG1811021X
rs1932574C10orf57X
rs1934952CYP2C8X
rs1934963CYP2C9X
rs1935JMJD1CX
rs1935347HTR7X
rs1935349HTR7XXX
rs1935350HTR7X
rs1935351HTR7X
rs1937348STAMX
rs1953758ATRNL1X
rs1962336hCG1653562X
rs1969724C10orf6X
rs1969815hCG2038406HELLSX
rs1970473hCG2040007XXX
rs1973972XPNPEP1XXX
rs1977584hCG2006597X
rs1979363CTNNA3X
rs1979487hCG2040312X
rs1983864LOXL4X
rs1983894C10orf45X
rs1986558hCG1818441X
rs1991808KCNMA1X
rs1993986C10orf64X
rs1998709PLCE1X
rs1998756HPSE2X
rs1998864DOCK1X
rs1999240MYO3AX
rs1999764IDEX
rs2001245MYST4X
rs2001740hCG1980421X
rs2001813NAX
rs2002773PARD3X
rs2004558FER1L3X
rs200910hCG25654X
rs2018728hCG2036689XXX
rs2020172hCG20065X
rs2024179ATRNL1X
rs2025453TLL2X
rs2025459PARD3X
rs2026015ACBD5X
rs2027108NAX
rs2030057CXXC6X
rs2031612TNFRSF6X
rs2040009ITGB1X
rs2043618ASAH2X
rs2057227hCG1815019X
rs2062258PPIFX
rs2062988DHTKD1X
rs2065364NRP1X
rs2066271DNAJC1X
rs2066323NT5C2X
rs2070845IFIT2X
rs2071496MKI67X
rs2095890hCG2023943X
rs2096181FER1L3X
rs211070hCG1643662X
rs211291KIF5BX
rs211299KIF5BX
rs211424hCG1807268X
rs2120902hCG32855X
rs2126750CTNNA3X
rs2133696CTNNA3X
rs2147289hCG23635X
rs2148493hCG1811160X
rs2152143MKI67X
rs2153779HTR7X
rs2162540FGFR2X
rs2163188C10orf74X
rs2170132C10orf64X
rs2172659LOC220929X
rs2182162CTNNA3hCG1810898LRRTM3X
rs220049TCF8X
rs220059TCF8X
rs2210497hCG2036689X
rs2227310CASP7X
rs2227564PLAUX
rs2228059IL15RAX
rs2228149IL2RAX
rs2228527PGBD3X
rs2228529PGBD3X
rs2228638NRP1X
rs2230660ZNF239X
rs2230661ZNF239X
rs2232659FAM26BX
rs2234962BAG3X
rs2234965ANXA7X
rs2236319SIRT1X
rs2236379PRKCQX
rs2240MKI67X
rs2240711hCG2023700X
rs2241666hCG2024246ZWINTX
rs2243897hCG1652542X
rs2244380OPTNX
rs2244647SFXN2X
rs2250266NAX
rs2251101IDEX
rs2253545KCNMA1X
rs2254067hCG2042943X
rs2254174C10orf27X
rs2254266CAMK2GX
rs2254419C10orf92X
rs2255607KIAA1279X
rs2262274C10orf35X
rs2270962CWF19L1XXX
rs2271362PRDX3XXX
rs2271690hCG2041592SARA1X
rs2271904HSGT1X
rs2271908MRPS16X
rs2273697ABCC2X
rs2273740XPNPEP1X
rs2273747C10orf119INPP5FX
rs2273749INPP5FX
rs2274109MCM10X
rs2274223PLCE1XXX
rs2274224PLCE1XXX
rs2274741hCG25239X
rs2275047AVPI1X
rs2275060hCG23658X
rs2275069ITIH5X
rs2275111SFXN4X
rs2275272PYCSX
rs2275382BA108L7.2X
rs2275383BA108L7.2X
rs2275580KIAA0690X
rs2275586MMS19LX
rs2275716SLC25A16X
rs2275720ADAM8X
rs2275799NRAPX
rs2277212CUGBP2X
rs2277257SLC29A3X
rs2281699hCG32858X
rs2281797C10orf49X
rs2281854hCG1817644X
rs2281878C10orf95X
rs2281891CYP2C18X
rs2284665PRSS11X
rs2286735NRAPX
rs2286748TRIM8X
rs2290167hCG1655308X
rs2292307KIAA0913X
rs2292584C10orf64X
rs2292948hCG2024499X
rs2293277C10orf3X
rs2295715hCG2041216X
rs2295716SEMA4GX
rs2295772SEC31L2X
rs2295774SEC31L2X
rs2295778HIF1ANX
rs2295874TACC2X
rs2295876TACC2X
rs2295879TACC2X
rs2296136hCG24072X
rs2296436HPS1X
rs2296441C10orf33X
rs2296467MSRBX
rs2296545C10orf59X
rs2296690PYCSX
rs2297145hCG25239XXX
rs2297151YME1L1XXX
rs2297452ZMYND17X
rs2297492C10orf25X
rs2297882C10orf97X
rs2297991GPAMhCG2041212X
rs2298075SEC31L2X
rs2298122DRD1IPX
rs2304804ANKRD22X
rs2305204PNLIPRP1X
rs2305386PKD2L1X
rs2306264JMJD1CX
rs2308327MGMTX
rs2339402TMEM23X
rs2339507TMEM23X
rs236212NAX
rs2368184ABI1X
rs2370771hCG2041958X
rs237596NAX
rs2388486GATA3hCG2041865X
rs2393989C10orf74X
rs2394341CTNNA3hCG1810898X
rs2394522VPS26X
rs2394641hCG2041592X
rs2394800CDH23X
rs2394848CHST3X
rs2395335C10orf11hCG2040332X
rs2395373C10orf11XXX
rs2395576C10orf56X
rs2420367HTR7X
rs2421013C10orf87X
rs2421131hCG2040007X
rs2422324PDE6CX
rs2429485hCG1642042X
rs2435381GALNACT-2X
rs2437257MRC1X
rs2441743CTNNA3X
rs2452505PHYHIPLX
rs2456664CTNNA3X
rs2456751CTNNA3X
rs2462712hCG23635X
rs2474329hCG1729712X
rs2474519C10orf9X
rs2474571hCG25655X
rs2475298SEC23IPX
rs2478568SLC39A12X
rs2478577MRC1X
rs2484180hCG1642042X
rs2487068SLC29A3X
rs2487999OBFC1X
rs2488142NAX
rs2492651NAX
rs2501578ADD3X
rs2503084hCG1730556PBEF1X
rs2505323hCG1642042XXX
rs2505327hCG1642042X
rs2515641CYP2E1X
rs2531670NAX
rs2531685hCG2036773KIAA1598X
rs2616652hCG2040450X
rs2620918CTNNA3X
rs2645227hCG2041853X
rs266089CXCL12X
rs2663056NAX
rs2675694LDB3OPN4X
rs2675705hCG1643076X
rs2694791GFRA1X
rs2704482COL13A1X
rs2719995KCNMA1X
rs2735343PTENX
rs2738222hCG25651X
rs2758988C10orf11X
rs2761286FER1L3X
rs276222KIAA1754X
rs276229KIAA1754X
rs2764343PLCE1X
rs2764345PLCE1X
rs2766628hCG2040450X
rs2778979PLXDC2X
rs2787140hCG1659888X
rs2794981PFKFB3X
rs2797567hCG39531X
rs2798000PLCE1X
rs2804535VDAC2X
rs2805910PRG1X
rs2805915PRG1X
rs2808096ARHGAP12X
rs2812968hCG1729643X
rs2817698SLIT1X
rs2839668GAD2MYO3AX
rs284596FAM13C1X
rs284624FAM13C1X
rs284856C10orf26X
rs2855025PRG1X
rs2862507hCG1642531X
rs2894016CTNNA3X
rs2894087NET-7X
rs2894103hCG1796715X
rs2894280COL13A1X
rs2894347NAX
rs2901127HTR7X
rs290481TCF7L2X
rs2915772PNLIPX
rs2927501ADAM12X
rs2946994CTBP2X
rs2950354hCG41428X
rs2986401PYCSX
rs2996224Rab11-FIP2XXX
rs2997211MPP7X
rs2999278ZNF239X
rs3006365hCG2044073X
rs3006739C10orf68X
rs3007GDF10X
rs3010503PNLIPX
rs3013236DMBT1X
rs3014185FAM26AX
rs3026782RETX
rs303169LOC387700X
rs303218IFIT1X
rs303426MAP3K8X
rs303438MAP3K8X
rs303450MAP3K8X
rs303465LIPFX
rs303523hCG1640331X
rs303533NAX
rs303537NAX
rs305375hCG1805714X
rs3071SCDX
rs3088142DUSP13X
rs3101793hCG1785360XXX
rs3189030NRAPX
rs35773KCNMA1X
rs35791KCNMA1X
rs363282TRIKX
rs363294PDZK8X
rs366107LIPFX
rs369421GATA3hCG2041865X
rs371210NAX
rs3730463POLLX
rs373304FAM13C1X
rs3737015PDLIM1X
rs3737294CSPG6X
rs3739989TMEM23X
rs3739998hCG1643737X
rs3740015DHTKD1X
rs3740094C10orf10X
rs3740097RASSF4X
rs3740199ADAM12X
rs3740211SEPHS1X
rs3740215hCG2041844X
rs3740329ZNF11BX
rs3740423MKI67X
rs3740462UNC5BX
rs3740469SLKXXX
rs3750718CPN1X
rs3750805hCG1776259TCF7L2X
rs3750898DCLRE1AX
rs3758402RASSF4X
rs3758490ZNF365X
rs3763695SEC31L2X
rs3763735TYSND1X
rs3763747SLC16A9X
rs3763792CNNM1X
rs3764990MIRX
rs3765101PITRM1X
rs3765595RSU1X
rs3780971RSU1X
rs378308LIPFX
rs3793663hCG1789661USP54X
rs3793706SEC31L2X
rs3793771WNT8BX
rs3802557hCG1817623XXX
rs3802656LIPAX
rs3808909ARMC4X
rs3812619HSGT1X
rs3814165hCG24161X
rs3814568RASSF4X
rs3814596PITRM1X
rs3816HPS6X
rs3816699PFKPX
rs3818672hCG2042945X
rs3818909ZDHHC16X
rs3824700MYO3AX
rs3824754CYT19X
rs3829142hCG2041141X
rs3829909hCG1776259X
rs3850680SORCS1X
rs3852407PLEKHK1X
rs3858340BAG3X
rs3862018HABP2XXX
rs3862030SUFUX
rs3862501KCNMA1X
rs3862511RAI17X
rs388972FAM13C1X
rs3900887TFAMX
rs390414LIPFX
rs391260LIPFX
rs391683LIPFX
rs3939ANKRD1X
rs3952313SPAG6X
rs4025981NEBLX
rs402781LIPFX
rs405635LIPFX
rs4065PLAUX
rs4078488CH25HX
rs4096395COL13A1X
rs412927LIPFX
rs4144422RPP30X
rs4147179ARHGAP21X
rs415996LIPFX
rs416957LIPFX
rs418276LIPFX
rs4237438FRMD4X
rs4242746PITRM1X
rs4323796ADAMTS14X
rs436207FAM13C1X
rs4400684JMJD1CX
rs4412676ADAM12hCG1644692X
rs4417206PYCSXXX
rs444386LIPFX
rs4485000CACNB2X
rs4548513CTNNA3X
rs4581397hCG1791394X
rs4595427JMJD1CX
rs4630205IFIT4LIPAXXX
rs4646953NAX
rs4646957IDEX
rs4646958IDEX
rs4691NDST2X
rs4745805hCG2041396X
rs4746015COL13A1X
rs4746332C10orf11X
rs4746821SUPV3L1X
rs4746946H2AFY2X
rs4747194CDH23X
rs4747647hCG1774090X
rs4747796hCG1792626X
rs4750568hCG2039913hCG2041288X
rs4751651C10orf84X
rs4751995PNLIPRP2X
rs4751996PNLIPRP2X
rs4838592ARHGAP22X
rs4880241C10orf39X
rs4880801ADARB2X
rs4917723BLNKX
rs4917766NAX
rs4919058MLR2X
rs492943XPNPEP1X
rs4933617RPP30X
rs4933620RPP30XXX
rs493392PARD3X
rs4935502PCDH15X
rs4948550BICC1X
rs4948970hCG17919X
rs495998NAXXX
rs498055hCG1641328XXX
rs500470NAXXX
rs5030920TACR2X
rs5030949HK1X
rs523611KCNMA1X
rs526219PIK3AP1X
rs527458KCNMA1X
rs530872MRC1XXX
rs532678PTENX
rs533343NAXXX
rs533383NAXXX
rs533480SORBS1XXX
rs542007KCNMA1XXX
rs554765SORBS1X
rs558764hCG1796761X
rs559198IFIT5X
rs566484PIK3AP1X
rs569511PKD2L1X
rs577537CRTAC1XXX
rs5870ACTR1AX
rs590142hCG1648219X
rs591157C10orf129X
rs595652CX40.1X
rs597371AMACOX
rs600879SORCS1XXX
rs607437SORCS1X
rs6163CYP17A1X
rs618687hCG1640833X
rs621375KIAA1914X
rs622491hCG1640638X
rs623980XPNPEP1X
rs625039hCG1781727LBX1X
rs625859PIK3AP1X
rs626394PARD3X
rs626859PARD3X
rs636555C10orf79hCG23142X
rs646668KIAA1914X
rs646767PKD2L1X
rs647758PARD3XXX
rs6480404HK1X
rs6481530NAX
rs649785AMACOX
rs650212PARD3X
rs6537579NAX
rs657477PARD3XXX
rs6580FAM26BXXX
rs6585312TRUB1X
rs6597731ADAM12X
rs6602141RSU1X
rs6602160RSU1XXX
rs6646ABLIM1X
rs6686SEC61A2X
rs67179hCG1783557X
rs673009PARD3X
rs678188PARD3X
rs6816OGDHLX
rs682304PIK3AP1X
rs684395hCG2042948X
rs687528PIK3AP1X
rs6896ANXA7X
rs6901PITRM1X
rs690763MRC1X
rs691196MRC1X
rs691773MRC1X
rs691863MRC1X
rs692126MRC1XXX
rs693986ATRNL1X
rs7006DPCDX
rs7013C10orf10X
rs701834LZTS2X
rs701836LZTS2X
rs701846CPEB3X
rs701865PDE6CX
rs702366ALOX5X
rs703258VCLX
rs703460SORCS3X
rs703461SORCS3X
rs703973RAI17X
rs703981RAI17X
rs703982RAI17X
rs703990RAI17X
rs704010RAI17X
rs7070570CTNN3X
rs7072367CWF19L1XXX
rs7072645ADAMTS14X
rs7073610CWF19L1X
rs7074064BMPR1AX
rs7074242hCG1641715X
rs7075141IDI1X
rs7075260hCG1817623X
rs7075831BLNKX
rs7075888hCG40944X
rs7075964hCG2023790XPNPEP1X
rs7076888SORBS1X
rs7077596hCG2036689X
rs7079901RSU1X
rs7080160hCG1646572X
rs7080643hCG23635X
rs7081273ADAMTS14X
rs7081275JMJD1CX
rs7081960CCAR1X
rs7082044hCG25652X
rs7082342hCG1800341X
rs7082434FBXO18X
rs7082558HTR7X
rs7084090IDEX
rs7084874CDH23hCG1745900X
rs7085991NAX
rs7086446hCG2040215X
rs7089142PCDH21X
rs7089312FLJ22761hCG2038551X
rs7089349hCG39169X
rs7091896SIRT1X
rs7092539JMJD1CX
rs7093729RSU1X
rs7094973ANKRD2XXX
rs7097295hCG20065X
rs7099478GRK5X
rs7099565TRUB1X
rs7099777NAX
rs7100129NAX
rs7100340NAX
rs7100382hCG2042429X
rs7100623IDEX
rs7184MRPL43X
rs7199hCG23640X
rs719909PANK1X
rs725529hCG41574X
rs726817C10orf4X
rs727427PANK1X
rs727532ABLIM1X
rs728289PSAPX
rs7304COMTD1VDAC2X
rs731947hCG2040574X
rs732102SORBS1X
rs735104NAX
rs736189ADAMTS14X
rs736535MAWBPX
rs736597VTI1AX
rs7377PRG1X
rs740595hCG2023700X
rs746472hCG1811015X
rs748164ADAMTS14X
rs748165ADAMTS14X
rs748235HK1X
rs749049PYCSX
rs749304SORCS3X
rs749377ARHGAP22X
rs750431ADAMTS14X
rs751450CHST3X
rs752372KCNMA1X
rs752974LZTS2X
rs753270RAI17X
rs755381KCNIP2X
rs780157RAI17X
rs780631RSU1X
rs780668SLC29A3X
rs787037APBB1IPX
rs787041APBB1IPX
rs787634FER1L3X
rs788219MASTLX
rs788237MASTLX
rs7895441NAX
rs7896327MINPP1X
rs7897619IFIT4LIPAX
rs7897947NFKB2X
rs7899065SORBS1X
rs7899853RSU1X
rs7900095SORBS1X
rs7900392FER1L3X
rs7900830PHYHX
rs7900859hCG2006597hCG2041102X
rs7901045PCDH15X
rs7902355DC-TM4F2XXX
rs7903091CBARA1X
rs7903397SVILX
rs7903964CTNNA3X
rs7905087PI4KIIX
rs7905162hCG41189X
rs7905784MCM10X
rs7906450NAXXX
rs7906504GHITMX
rs7906894hCG20066X
rs7908112RSU1X
rs7908745MIRX
rs7909832hCG23996PTERX
rs7910154hCG1783494X
rs7911748RSU1X
rs7912249SORBS1X
rs7913176NHLRC2XXX
rs7914287CTNNA3X
rs7915504hCG2023773X
rs7916571hCG2040007XXX
rs7916821MYPNX
rs7918084hCG1641008X
rs7918118GTPBP4X
rs7923749NAX
rs792718NAX
rs805657SLKX
rs805721COL17A1X
rs807023hCG1647209X
rs807037KAZALD1X
rs807038KAZALD1X
rs807042NAX
rs8139NT5C2X
rs814624LIPFX
rs814626LIPFX
rs814628LIPFX
rs816827KCNMA1X
rs8181357FLJ44653X
rs8187694ABCC2X
rs821942SORCS1XXX
rs827241PCBDX
rs829237TMEM20X
rs8354ARL3X
rs838759hCG1652542X
rs8473MKI67X
rs860989KCNMA1X
rs866255HERC4X
rs867407NAX
rs867629NAX
rs8677ANK3X
rs868750CHATX
rs869156RASSF4X
rs869801DOCK1X
rs870957RASSF4XXX
rs874556FLJ22761X
rs874885KCNIP2X
rs877779CREMX
rs880348hCG1788074X
rs881343NAX
rs881406RAI17X
rs882052DOCK1X
rs882845C10orf10RASSF4X
rs882872hCG1818441X
rs883604MAPK8X
rs884144NKX2-3X
rs885822PRF1X
rs892691ALOX5X
rs894375CRTAC1X
rs902991NEURLX
rs906217SUPV3L1X
rs906219FLJ22761X
rs912485PIK3AP1X
rs914325CAMK1DX
rs915230hCG2042179X
rs915432CBARA1X
rs921742RSU1X
rs922239hCG2039963X
rs923799hCG1811015X
rs927099NRP1X
rs932512hCG1655317X
rs9325593SNCGX
rs9333269ITGA8X
rs934187ALOX5X
rs9414761hCG1820925hCG41574X
rs9416746BICC1X
rs9419048C10orf125SprnX
rs942077hCG2036763X
rs9420822BTRCX
rs9423590hCG20066X
rs942431PARD3X
rs942775STAMXXX
rs942789RAI17X
rs943265TECTBX
rs943542SORBS1X
rs945189NAX
rs947599C10orf3X
rs951308MYST4X
rs951647LIPAX
rs952919GFRA1X
rs954439IFIT2LIPAX
rs955157C10orf11hCG2041509X
rs959629PAPD1X
rs962524MPHOSPH1X
rs9664986SVILX
rs9665610NAX
rs977096C10orf35X
rs980994NAX
rs985273ABLIM1X
rs994174hCG1650570X
rs994811C10orf107X
rs9971293GDF2X
rs998799PAX2X
rs999995KCNMA1X

Note.— The public gene name or hCG identifier for predicted genes from the Celera database indicates which sample sets were genotyped, and a 60-bp sequence is provided for SNPs without a public “rs” identifier. NA=not applicable.

Web Resources

The URLs for data presented herein are as follows:

Online Mendelian Inheritance in Man (OMIM), http://www.ncbi.nlm.nih.gov/Omim/ (for AD, APP, PSEN1, PSEN2, LOAD, APOE, GAPD, RPS3A, PYCS, ALDH18A1, ENTPD1, CTNNA3, PLAU, IDE, BCL2, PARP1, SORBS1, and SORCS1)

References

Agresti A (1990) Categorical data analysis. John Wiley & Sons, New York
Balciuniene J, Emilsson L, Oreland L, Pettersson U, Jazin E (2002) Investigation of the functional effect of monoamine oxidase polymorphisms in human brain. Hum Genet 110:1–7 [PubMed] [Cross Ref]10.1007/s00439-001-0652-8
Berg L, McKeel DW Jr, Miller JP, Storandt M, Rubin EH, Morris JC, Baty J, Coats M, Norton J, Goate AM, Price JL, Gearing M, Mirra SS, Saunders AM (1998) Clinicopathologic studies in cognitively healthy aging and Alzheimer’s disease: relation of histologic markers to dementia severity, age, sex, and apolipoprotein E genotype. Arch Neurol 55:326–335 [PubMed] [Cross Ref]10.1001/archneur.55.3.326
Bertram L, Blacker D, Mullin K, Keeney D, Jones J, Basu S, Yhu S, McInnis MG, Go RC, Vekrellis K, Selkoe DJ, Saunders AJ, Tanzi RE (2000) Evidence for genetic linkage of Alzheimer’s disease to chromosome 10q. Science 290:2302–2303 [PubMed] [Cross Ref]10.1126/science.290.5500.2302
Blacker D, Bertram L, Saunders AJ, Moscarillo TJ, Albert MS, Wiener H, Perry RT, Collins JS, Harrell LE, Go RC, Mahoney A, Beaty T, Fallin MD, Avramopoulos D, Chase GA, Folstein MF, McInnis MG, Bassett SS, Doheny KJ, Pugh EW, Tanzi RE (2003) Results of a high-resolution genome screen of 437 Alzheimer’s disease families. Hum Mol Genet 12:23–32 [PubMed] [Cross Ref]10.1093/hmg/ddg007
Blalock EM, Geddes JW, Chen KC, Porter NM, Markesbery WR, Landfield PW (2004) Incipient Alzheimer’s disease: microarray correlation analyses reveal major transcriptional and tumor suppressor responses. Proc Natl Acad Sci USA 101:2173–2178 [PMC free article] [PubMed] [Cross Ref]10.1073/pnas.0308512100
Busby V, Goossens S, Nowotny P, Hamilton G, Smemo S, Harold D, Turic D, et al (2004) α-t-catenin is expressed in human brain and interacts with the Wnt signaling pathway but is not responsible for linkage to chromosome 10 in Alzheimer’s disease. Neuromolecular Med 5:133–146 [PubMed] [Cross Ref]10.1385/NMM:5:2:133
Clement M, Posada D, Crandall KA (2000) TCS: a computer program to estimate gene genealogies. Mol Ecol 9:1657–1659 [PubMed] [Cross Ref]10.1046/j.1365-294x.2000.01020.x
Corder EH, Saunders AM, Strittmatter WJ, Schmechel DE, Gaskell PC, Small GW, Roses AD, Haines JL, Pericak-Vance MA (1993) Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science 261:921–923 [PubMed]
Ertekin-Taner N, Graff-Radford N, Younkin LH, Eckman C, Baker M, Adamson J, Ronald J, Blangero J, Hutton M, Younkin SG (2000) Linkage of plasma Aβ42 to a quantitative locus on chromosome 10 in late-onset Alzheimer’s disease pedigrees. Science 290:2303–2304 [PubMed] [Cross Ref]10.1126/science.290.5500.2303
Farrer LA, Bowirrat A, Friedland RP, Waraska K, Korczyn AD, Baldwin CT (2003) Identification of multiple loci for Alzheimer disease in a consanguineous Israeli-Arab community. Hum Mol Genet 12:415–422 [PubMed] [Cross Ref]10.1093/hmg/ddg037
Germer S, Holland MJ, Higuchi R (2000) High-throughput SNP allele-frequency determination in pooled DNA samples by kinetic PCR. Genome Res 10:258–266 [PMC free article] [PubMed] [Cross Ref]10.1101/gr.10.2.258
Goate A, Chartier-Harlin M-C, Mullan M, Brown J, Crawford F, Fidani L, Giuffra L, Haynes A, Irving N, James L, Mant R, Newton P, Rooke K, Roques P, Talbot C, Pericak-Vance M, Roses A, Williamson R, Rossor M, Owen M, Hardy J (1991) Segregation of a missense mutation in the amyloid precursor protein gene with familial Alzheimer’s disease. Nature 349:704–706 [PubMed] [Cross Ref]10.1038/349704a0
Hermey G, Plath N, Hubner CA, Kuhl D, Schaller HC, Hermans-Borgmeyer I (2004) The three Sorcs genes are differentially expressed and regulated by synaptic activity. J Neurochem 88:1470–1476 [PubMed]
Hermey G, Riedel IB, Hampe W, Schaller HC, Hermans-Borgmeyer I (1999) Identification and characterization of SorCS, a third member of a novel receptor family. Biochem Biophys Res Commun 266:347–351 [PubMed] [Cross Ref]10.1006/bbrc.1999.1822
Hu ZB, Minden MD, McCulloch EA, Stahl J (2000) Regulation of drug sensitivity by ribosomal protein S3a. Blood 95:1047–1055 [PubMed]
Kehoe P, Wavrant-De Vrieze F, Crook R, Wu WS, Holmans P, Fenton I, Spurlock G, Norton N, Williams H, Williams N, Lovestone S, Perez-Tur J, Hutton M, Chartier-Harlin MC, Shears S, Roehl K, Booth J, Van Voorst W, Ramic D, Williams J, Goate A, Hardy J, Owen MJ (1999) A full genome scan for late onset Alzheimer’s disease. Hum Mol Genet 8:237–245 [PubMed] [Cross Ref]10.1093/hmg/8.2.237
Knoblauch H, Bauerfeind A, Krahenbuhl C, Daury A, Rohde K, Bejanin S, Essioux L, Schuster H, Luft FC, Reich JG (2002) Common haplotypes in five genes influence genetic variance of LDL and HDL cholesterol in the general population. Hum Mol Genet 11:1477–1485 [PubMed] [Cross Ref]10.1093/hmg/11.12.1477
Levy-Lahad E, Wasco W, Poorkaj P, Romano DM, Oshima J, Pettingell WH, Yu CE, Jondro PD, Schmidt SD, Wang K, Crowley A, Fu Y-H, Guenette S, Galas D, Nemens E, Wijsman E, Bird T, Schellenberg G, Tanzi R (1995) Candidate gene for the chromosome 1 familial Alzheimer’s disease locus. Science 269:973–977 [PubMed]
Li Y, Hollingworth P, Moore P, Foy C, Archer N, Powell J, Nowotny P, Holmans P, O’Donovan M, Tacey K, Doil L, van Luchene R, Garcia V, Rowland C, Lau K, Cantanese J, Sninsky J, Hardy J, Thal L, Morris JC, Goate A, Lovestone S, Owen M, Williams J, Grupe A (2005) Genetic association of the APP binding protein 2 gene (APBB2) with late onset Alzheimer disease. Hum Mutat 25:270–277 [PubMed] [Cross Ref]10.1002/humu.20138
Li Y, Nowotny P, Holmans P, Smemo S, Kauwe JS, Hinrichs AL, Tacey K, et al (2004) Association of late-onset Alzheimer’s disease with genetic variation in multiple members of the GAPD gene family. Proc Natl Acad Sci USA 101:15688–15693 [PMC free article] [PubMed] [Cross Ref]10.1073/pnas.0403535101
McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM (1984) Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 34:939–944 [PubMed]
Myers A, Holmans P, Marshall H, Kwon J, Meyer D, Ramic D, Shears S, Booth J, DeVrieze FW, Crook R, Hamshere M, Abraham R, Tunstall N, Rice F, Carty S, Lillystone S, Kehoe P, Rudrasingham V, Jones L, Lovestone S, Perez-Tur J, Williams J, Owen MJ, Hardy J, Goate AM (2000) Susceptibility locus for Alzheimer’s disease on chromosome 10. Science 290:2304–2305 [PubMed] [Cross Ref]10.1126/science.290.5500.2304
Myers A, Wavrant De-Vrieze F, Holmans P, Hamshere M, Crook R, Compton D, Marshall H, et al (2002) Full genome screen for Alzheimer disease: stage II analysis. Am J Med Genet 114:235–244 [PubMed] [Cross Ref]10.1002/ajmg.10183
Myers AJ, Marshall H, Holmans P, Compton D, Crook RJ, Mander AP, Nowotny P, Smemo S, Dunstan M, Jehu L, Wang JC, Hamshere M, Morris JC, Norton J, Chakraventy S, Tunstall N, Lovestone S, Petersen R, O’Donovan M, Jones L, Williams J, Owen MJ, Hardy J, Goate A (2004) Variation in the urokinase-plasminogen activator gene does not explain the chromosome 10 linkage signal for late onset AD. Am J Med Genet B Neuropsychiatr Genet 124:29–37 [PubMed] [Cross Ref]10.1002/ajmg.b.20036
Nowotny P, Hinrichs AL, Smemo S, Kauwe J, Maxwell T, Holmans P, Hamshere M, et al (2005) Association studies between risk for late-onset Alzheimer’s disease and variants in insulin degrading enzyme. Am J Med Genet B Neuropsychiatr Genet 136:62–68 [PubMed]
Pastor P, Goate AM (2004) Molecular genetics of Alzheimer’s disease. Curr Psychiatry Rep 6:125–133 [PubMed]
Pericak-Vance MA, Bass MP, Yamaoka LH, Gaskell PC, Scott WK, Terwedow HA, Menold MM, Conneally PM, Small GW, Vance JM, Saunders AM, Roses AD, Haines JL (1997) Complete genomic screen in late-onset familial Alzheimer disease: evidence for a new locus on chromosome 12. JAMA 278:1237–1241 [PubMed] [Cross Ref]10.1001/jama.278.15.1237
Pericak-Vance MA, Grubber J, Bailey LR, Hedges D, West S, Santoro L, Kemmerer B, Hall JL, Saunders AM, Roses AD, Small GW, Scott WK, Conneally PM, Vance JM, Haines JL (2000) Identification of novel genes in late-onset Alzheimer’s disease. Exp Gerontol 35:1343–1352 [PubMed] [Cross Ref]10.1016/S0531-5565(00)00196-0
Rogaeva E, Premkumar S, Song Y, Sorbi S, Brindle N, Paterson A, Duara R, Levesque G, Yu G, Nishimura M, Ikeda M, O’Toole C, Kawarai T, Jorge R, Vilarino D, Bruni AC, Farrer LA, St George-Hyslop PH (1998) Evidence for an Alzheimer disease susceptibility locus on chromosome 12 and for further locus heterogeneity. JAMA 280:614–618 [PubMed] [Cross Ref]10.1001/jama.280.7.614
Sherrington R, Rogaev EI, Liang Y, Rogaeva EA, Levesque G, Ikeda M, Chi H, et al (1995) Cloning of a gene bearing missense mutations in early-onset familial Alzheimer’s disease. Nature 375:754–760 [PubMed] [Cross Ref]10.1038/375754a0
Song D, Sakamoto S, Taniguchi T (2002) Inhibition of poly(ADP-ribose) polymerase activity by Bcl-2 in association with the ribosomal protein S3a. Biochemistry 41:929–934 [PubMed] [Cross Ref]10.1021/bi015669c
Stephens M, Donnelly P (2003) A comparison of Bayesian methods for haplotype reconstruction from population genotype data. Am J Hum Genet 73:1162–1169 [PMC free article] [PubMed]
Stephens M, Smith NJ, Donnelly P (2001) A new statistical method for haplotype reconstruction from population data. Am J Hum Genet 68:978–989 [PMC free article] [PubMed]
Templeton AR, Maxwell T, Posada D, Stengard JH, Boerwinkle E, Sing CF (2005) Tree scanning: a method for using haplotype trees in phenotype/genotype association studies. Genetics 169:441–453 [PMC free article] [PubMed] [Cross Ref]10.1534/genetics.104.030080
Templeton AR, Weiss KM, Nickerson DA, Boerwinkle E, Sing CF (2000) Cladistic structure within the human lipoprotein lipase gene and its implications for phenotypic association studies. Genetics 156:1259–1275 [PMC free article] [PubMed]
Van Eerdewegh P, Little RD, Dupuis J, Del Mastro RG, Falls K, Simon J, Torrey D, et al (2002) Association of the ADAM33 gene with asthma and bronchial hyperresponsiveness. Nature 418:426–430 [PubMed] [Cross Ref]10.1038/nature00878
Westfall P, Young S (1993) Resampling-based multiple testing. John Wiley & Sons, New York

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