Association analysis of dynamin-binding protein (DNMBP) on chromosome 10q with late onset Alzheimer's disease in a large caucasian UK sample.код для вставкиСкачать
RESEARCH ARTICLE Neuropsychiatric Genetics Association Analysis of Dynamin-Binding Protein (DNMBP) on Chromosome 10q With Late Onset Alzheimer’s Disease in a Large Caucasian UK Sample A.R. Morgan,1* P. Hollingworth,1 R. Abraham,1 S. Lovestone,2 C. Brayne,3 D.C. Rubinsztein,3 A. Lynch,4 B. Lawlor,4 M. Gill,4 M.C. O’Donovan,1 M.J. Owen,1 and J. Williams1 1 Department of Psychological Medicine, School of Medicine, Cardiff University, Cardiff, UK Department of Neuroscience, Institute of Psychiatry, Kings College, London, UK 2 3 Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK 4 Mercer’s Institute for Research on Aging, St. James Hospital and Trinity College, Dublin, Ireland Received 8 January 2008; Accepted 25 March 2008 A recent scan of single nucleotide polymorphisms (SNPs) in the region 40–107 Mb on chromosome 10q in a large Japanese case–control cohort identified six SNPs in or near the dynamin-binding protein gene (DNMBP) that were associated with late onset Alzheimer’s disease (LOAD) in individuals lacking the APOE e4 allele [Kuwano et al. (2006); Hum Mol Genet 15:2170–2182]. We genotyped these six SNPs in 1,212 unrelated Caucasian patients of UK origin with LOAD and 1,389 ethnically, gender and age matched control subjects. We did not observe a statistically significant association with the risk of LOAD for any of the six SNPs in the sample as a whole. When stratifying the sample by APOE one SNP (intergenic SNP rs11190302) was associated with LOAD in individuals lacking the e4 allele (genotypic P ¼ 0.027, allelic P ¼ 0.066). However this association was in the opposite direction to that detected in the Japanese population. It remains to be determined whether DNMBP is associated with LOAD. 2008 Wiley-Liss, Inc. Key words: late-onset Alzheimer’s disease; DNMBP; chromosome 10; association INTRODUCTION Several groups have observed linkage with risk of AD or related measures on chromosome 10 [Kehoe et al., 1999; Bertram et al., 2000; Ertekin-Taner et al., 2000; Myers et al., 2000, 2002; Blacker et al., 2003; Farrer et al., 2003], and many have reported association with different candidate genes on chromosome 10 (see the AlzGene Database. Available at: http://www.alzgene.org [Bertram et al., 2007]), but attempts to replicate these findings have rarely proved consistent and the identification of the LOAD gene on this chromosome remains elusive. Kuwano et al.  performed a large scale single nucleotide polymorphism (SNP) based association analysis in a large Japanese case–control cohort (1,526 LOAD samples and 1,666 controls). They looked at 1,206 SNPs in a region implicated by several linkage 2008 Wiley-Liss, Inc. How to Cite this Article: Morgan AR, Hollingworth P, Abraham R, Lovestone S, Brayne C, Rubinsztein DC, Lynch A, Lawlor B, Gill M, O’Donovan MC, Owen MJ, Williams J. 2009. Association Analysis of Dynamin-Binding Protein (DNMBP) on Chromosome 10q With Late Onset Alzheimer’s Disease in a Large Caucasian UK Sample. Am J Med Genet Part B 150B:61–64. studies, between 60 and 107 Mb on chromosome 10, and identified six SNPs associated with LOAD among individuals lacking the e4 allele. Three of the six SNPs, including the most statistically significant (rs3740058), are located in the dynamin-binding protein gene (DNMBP) on 10q24; the other three fall downstream of this gene. DNMBP (chr10:101,626,898–101,759,666) is a scaffold protein that brings the dynamin and actin regulatory proteins together and is concentrated at synapses in the brain. It is an excellent candidate gene for AD because of its role in the amyloid precursor protein (APP) recycling pathways. Additional Supporting Information may be found in the online version of this article. Grant sponsor: Medical Research Council, UK; Grant sponsor: Alzheimer’s Research Trust, UK. *Correspondence to: Dr. A.R. Morgan, Department of Psychological Medicine, Wales College of Medicine, Cardiff University, Heath Park, Cardiff CF14 4XN, UK. E-mail: firstname.lastname@example.org Published online 1 May 2008 in Wiley InterScience (www.interscience.wiley.com) DOI 10.1002/ajmg.b.30768 61 62 Here we attempted to validate the finding of Kuwano et al. in a well characterized case–control dataset which consists of 1,212 unrelated Caucasian patients of UK origin with LOAD and 1,389 ethnically, gender and age matched control subjects. Another effort to replicate the finding reported by Kuwano et al. has recently been published [Minster et al., 2007]. In this study the most significant SNP from the Japanese study (rs3740058) was examined in large Caucasian American case–control cohort (1,030 LOAD cases, 910 controls) and the other 5 in a subset of this cohort (298 cases, 311 controls). No associations were reported. METHODS Samples Clinical data and DNA samples were collected from 1,212 individuals (70% females) with late-onset Alzheimer’s disease and 1,389 control subjects (62.4% females). Age at onset ranged from 59 to 95 years (mean ¼ 75.6 years, SD ¼ 6.84). All cases were Caucasian, of UK origin (parents born in the UK) and diagnosed with probable AD in accordance with the National Institute of Neurological and Communication Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Associations (NINCDS–ADRDA) clinical diagnostic criteria for AD [McKhann et al., 1984]. Controls were matched for age (mean ¼ 76.26 years, SD ¼ 6.23), gender and ethnicity. The sample consisted of individuals ascertained from both community and hospital settings in the UK collected as part of the National Alzheimer’s Research Initiative, funded by the Medical Research Council. AD cases and controls described here were ascertained by four collaborating centers: Department of Psychological Medicine, Cardiff University, Cardiff (coordinating center); Institute of Psychiatry, London; Cambridge University, Cambridge; and Mercer’s Institute for Research on Aging, St. James Hospital and Trinity College, Dublin [see Morgan et al., 2007 for full descriptive data for whole sample]. Ethical permission was obtained from the Multi-centre Research Ethics Committee (MREC), relevant local Ethics Committees and NHS trusts. Genotyping The Sequenom (www.sequenom.de) genotyping platform, which uses the MALDI-TOF primer extension assay [Jurinke et al., 2002; Storm et al., 2003], was used to genotype the six SNPs. Quality control measures, for all genotyping results, included independent double genotyping, genotyping of duplicate samples on our sample plates and genotyping of CEPH samples and subsequent comparison with genotypes in the hapmap where available. We also ensured that all results were in HWE. Statistical Analysis SNPs were tested for deviation from the Hardy–Weinberg equilibrium (HWE) in both cases and controls. Genotype and allele frequencies for each SNP were analyzed by 2 3 and 2 2 Chi-square respectively, to determine if there were significant differences between cases and controls. Differences in allele and genotype frequencies between cases and controls stratified by apoe e4 carrier status were also tested using AMERICAN JOURNAL OF MEDICAL GENETICS PART B Chi-square analysis (e4 negative controls vs. e4 negative cases and e4 positive controls vs. e4 positive cases). Calculations of statistical power were completed using PS 2.1.31 [Dupont and Plummer, 1998]. RESULTS All six SNPs were in HWE in both cases and controls. See Table I for genotype and allele counts and frequencies for each of the six SNPs in our dataset. There were no significant differences between cases and controls for any of the six SNPs. When the sample was stratified by apoe e4 carrier status there were no significant differences in allele or genotype frequencies between e4 positive cases and e4 positive controls for any of the six SNPs (Supplementary Table SI). When comparing e4 negative cases and e4 negative controls five SNPs did not demonstrate evidence of association. However, one SNP—rs11190302 was associated with LOAD (genotypic P ¼ 0.027, allelic P ¼ 0.066; see Table II for results for rs11190302 and Supplementary Table SII for results of all six SNPs). We also investigated other sub-phenotypes of AD for association (family history, gender, age of onset, diabetes, depression) but found no other associations for any of the six SNPs (results available upon request). DISCUSSION With our sample we had 94.2% power to detect the reported odds ratio of 1.22 in the total sample and 95.3% power to detect the reported odds ratio of 1.38 in individuals lacking the e4 allele. We did not observe a statistically significant association between the associated SNPs from Kuwano et al., with the risk of AD in the whole sample set and only one SNP was marginally statistically significant when studying individuals lacking the e4 allele. And this was in the opposite direction (in our sample the C allele was overrepresented in the cases, whereas Kuwano et al. found the T allele to be associated). This SNP (rs11190302) is intergenic and lies approximately 4 kb from DNMBP. The difference may be due to the different ethnic backgrounds of the two populations (our allele frequencies differ from those reported in the Japanese population by Kuwano et al. but are more similar to those reported in the Caucasian American sample reported by Minster et al.). The different populations are likely to have differences in their genetic background which includes LD and this could account for the different associations. Another possibility is that there is a multilocus effect at this chromosomal region and there may be differences between the two populations in this SNPs correlation with other, possibly causal, variants. Or it is possible that we may be seeing a false positive result in our sample for rs11190302. Our result is only marginally statistically significant, and will not survive multiple testing. However, it is not uncommon for different studies to report disease-marker association but with opposite alleles associated. For example, in LOAD two independent studies have reported opposite alleles of the same SNP in the gene GSTO1 as being associated with age at onset in LOAD [Li et al., MORGAN ET AL. 63 TABLE I. Genotype and Allele Counts (Frequencies) for the Six SNPs in the Whole Sample (Unstratified by APOE e4 Status) Number of subjects (frequency) Number of alleles (frequency) SNP ID rs911541 Genotype GG GA AA LOAD 11 (0.01) 236 (0.23) 765 (0.76) Control 15 (0.01) 260 (0.22) 890 (0.76) P ¼ 0.79 Allele G A LOAD 258 (0.13) 1,766 (0.87) Control 290 (0.12) 2,040 (0.88) P ¼ 0.77 OR ¼ 1.03 (0.86–1.23) rs3740066 TT TC CC 120 (0.14) 411 (0.47) 342 (0.39) 149 (0.15) 462 (0.48) 360 (0.37) P ¼ 0.51 T C 651 (0.37) 1,095 (0.63) 769 (0.39) 1,182 (0.61) P ¼ 0.25 OR ¼ 0.91 (0.80–1.04) rs11190302 TT TC CC 197 (0.19) 489 (0.48) 332 (0.33) 240 (0.21) 587 (0.50) 342 (0.29) P ¼ 0.24 T C 883 (0.43) 1,153 (0.57) 1,067 (0.46) 1,271 (0.54) P ¼ 0.13 OR ¼ 0.91 (0.81–1.03) rs11190305 GG GT TT 150 (0.15) 481 (0.48) 380 (0.38) 178 (0.15) 583 (0.50) 401 (0.35) P ¼ 0.32 G T 781 (0.39) 1,241 (0.61) 939 (0.40) 1,385 (0.60) P ¼ 0.23 OR ¼ 0.93 (0.82–1.05) rs35715207 CC CG GG 154 (0.15) 490 (0.48) 380 (0.37) 180 (0.15) 591 (0.50) 414 (0.35) P ¼ 0.55 C G 798 (0.39) 1,250 (0.61) 951 (0.40) 1,419 (0.60) P ¼ 0.43 OR ¼ 0.95 (0.84–1.08) rs3740058 AA AG GG 159 (0.16) 471 (0.47) 369 (0.37) 190 (0.16) 561 (0.48) 414 (0.36) P ¼ 0.80 A G 789 (0.39) 1,209 (0.61) 941 (0.40) 1,389 (0.60) P ¼ 0.55 OR ¼ 0.96 (0.85–1.09) 2003; Kolsch et al., 2004]. For further discussion concerning association of opposite alleles at the same SNP with the same disease see Lin et al. . Although DNMBP is an excellent candidate gene because of its role in the APP recycling pathways and being located within a chromosome 10 linkage region, we are unable to confirm that DNMBP is associated with LOAD and recommend that further replication studies are undertaken to determine if this is a true association. Minster et al.  also failed to replicate the findings by Kuwano et al. . rs3740058 [the most significant SNP from Kuwano et al., 2006] was genotyped in 1,030 Caucasian Americans with LOAD and 910 healthy Caucasian Americans. The other 5 SNPs were genotyped in a smaller sample set of 298 LOAD cases and 311 controls. For all six SNPs differences between cases and controls in genotype and allele frequencies were not statistically significant, and allele frequencies in cases and controls stratified by APOE e4 carrier status were also not statistically significant. In our sample none of the six SNPs were associated with APOE e4 positive LOAD. This was also true for Kuwano et al. We also did not find evidence for an association for any SNP with any other phenotype (e.g., AAO, family history, gender). It is not clear whether Kuwano et al.  or Minster et al.  investigated other phenotypes as these are not reported in their publications. Further replication in other large sample sets, and particularly replication in another Japanese sample, will be required to assess the true effects of DNMBP variants in LOAD. TABLE II. Genotype and Allele Counts (Frequencies) for rs11190302 in Individuals Lacking the e4 Allele Number of subjects (frequency) SNP ID rs11190302 Genotype TT TC CC LOAD 75 (0.20) 167 (0.44) 140 (0.37) Control 154 (0.20) 387 (0.51) 222 (0.29) P ¼ 0.027 Number of alleles (frequency) Allele T C LOAD 317 (0.42) 447 (0.58) Control 695 (0.46) 831 (0.54) P ¼ 0.066 OR ¼ 0.85 (0.71–1.01) 64 ACKNOWLEDGMENTS We would like to thank the many patients with AD and their families who participated in this study. AMERICAN JOURNAL OF MEDICAL GENETICS PART B Kolsch H, Linnebank M, Lutjohann D, et al. 2004. Polymorphisms in glutathione S-transferase omega-1 and AD, vascular dementia, and stroke. Neurology 63:2255–2260. REFERENCES Kuwano R, Miyashita A, Arai H, et al. 2006. Dynamin-binding protein gene on chromosome 10q is associated with late-onset Alzheimer’s Disease. Hum Mol Genet 15(13):2170–2182. Bertram L, Blacker D, Mullin K, et al. 2000. 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