Human Molecular Genetics

Human Molecular Genetics Advance Access originally published online on July 6, 2005
Human Molecular Genetics 2005 14(16):2399-2404; doi:10.1093/hmg/ddi241

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The H1c haplotype at the MAPT locus is associated with Alzheimer's disease

A.J. Myers¹, M. Kaleem¹, L. Marlowe¹, A.M. Pittman^2,3, A.J. Lees^2,4, H.C. Fung^1,2,5, J. Duckworth¹, D. Leung¹, A. Gibson⁶, C.M. Morris⁶, R. de Silva^2,3 and J. Hardy^1,2,3,*

¹Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, 35 Convent Drive, Bethesda, MD 20892-3707, USA, ²Reta Lila Weston Institute of Neurological Studies, University College London, Windeyer Building, 46 Cleveland Street, London W1T 4JF, UK, ³Department of Molecular Neuroscience, Institute of Neurology, Queen Square, London WC1N 3BG, UK, ⁴Sara Koe PSP Research Centre, Institute of Neurology, 1 Wakefield Street, London WC1N 1PJ, UK, ⁵Second Department of Neurology, Chang Gung Memorial Hospital and College of Medicine, Chang Gung University, 199 Tung Hwa North Road, Taipei 10591, Taiwan and ⁶Institute for Ageing and Health, MRC Building, Newcastle General Hospital, Westgate Road, Newcastle-upon-Tyne NE4 6BE, UK

^* To whom correspondence should be addressed at: Laboratory of Neurogenetics, National Institute on Aging, Porter Neuroscience Building, 35 Convent Drive, Bethesda, MD 20892-3707, USA. Tel: +1 3014516081; Fax: +1 3014800335; Email: hardyj{at}mail.nih.gov

Received April 7, 2005; Revised May 31, 2005; Accepted June 29, 2005

	ABSTRACT

TOP ABSTRACT INTRODUCTION RESULTS DISCUSSION MATERIALS AND METHODS REFERENCES

 
Although it is clear that microtubule associated protein tau (MAPT) is involved in Alzheimer's disease (AD) pathology, it has not been clear whether it is involved genetically. We have recently examined the MAPT locus in progressive supranuclear palsy and found that a haplotype (H1c) on the background of the well-described H1 clade is associated with PSP. Here we report that the same haplotype is associated with the risk of AD in two autopsy confirmed series of cases with ages at death >65 years.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION RESULTS DISCUSSION MATERIALS AND METHODS REFERENCES

 
Along with senile plaques, neurofibrillary tangles comprising paired helical filaments of phosphorylated tau protein are the pathognomic features of Alzheimer's disease AD (1). Recent studies have shown that genetic variability at the MAPT locus is associated with increased risk for the sporadic tauopathies, PSP (2) and corticobasal degeneration (3). These associations, which have been replicated many times, divided the MAPT locus between two divergent clades, H1 and H2. Recently, our group and others have shown that the H2 clade is essentially a single un-recombining haplotype covering several genes and 1.8 Mb on chromosome 17q21. In contrast, the more common H1 clade shows considerable diversity and has a normal pattern of linkage disequilibrium except with H2 (4–7). We have further shown that a variant of this clade MAPT H1c is largely responsible for the association between the H1 clade and the sporadic tauopathies (6,8).

Several studies on variability within MAPT and the occurrence of AD have been published, with inconclusive, though largely negative results (9–14). These reports have compared alleles that discriminated between the H1 and H2 clades, but did not assess whether variability on the H1 background showed association with disease. Following our observation that specific variants of the H1 clade at MAPT (8) were responsible for the association with the tauopathies, we examined the association of the PSP-associated haplotype, H1c, with autopsy confirmed, late onset AD (LOAD).

	RESULTS

TOP ABSTRACT INTRODUCTION RESULTS DISCUSSION MATERIALS AND METHODS REFERENCES

 
Single locus analysis
We genotyped six polymorphisms which we have shown previously tag the haplotype diversity in MAPT in Caucasians in two series of autopsy-confirmed controls and autopsy-confirmed LOAD cases obtained from brain banks in the US and UK. (see Fig. 1 for information on the usefulness of these SNPs to tag diversity in these populations and Table 1 for descriptive statistics of cases and controls). The single locus associations with AD are shown in Table 2. Tests of association of the intron 9 insertion–deletion (del-In9) polymorphism, which has been used to define the H1/H2 clades, were negative as we and others have previously reported (9–14). Two of the tagging variants (rs242557 and rs2471738) had significant P-values in both the US series and when both the US and UK series were collapsed (Table 3). One of these tag variants (rs242557) also showed a trend towards association (allelic P-value=0.094, genotypic P-value=0.061) within the UK population.

View larger version (13K): [in this window] [in a new window]   Figure 1. MAPT tagging markers capture the diversity of MAPT. Solid line: Performance plot of the six MAPT SNP tag markers using the data available from CEPH in the hapmap project (http://www.hapmap.org. The plot is a row of vector performance values (as measured by haplotype r2 using criterion 5 from TagIT) for each of our tag SNPs against each of the SNP loci typed in the CEPH trios. High r2 values indicate good performance, because r2 is a measure of linkage disequilibrium. If there is perfect linkage disequilibrium between two markers, r2 will approach 1, indicating that the two markers are segregating together and thus are genetically equivalent. On average, our set of tagging SNPs captures 95% (average r2=0.95) of the diversity of the known SNPs as a whole and predominantly scores >90% against individual SNP loci. Broken line: In contrast, examining just the del-In9 variant's performance demonstrates that it performs well for some loci (r2>80%), whereas it performs poorly (r2<50%) for several loci. This is because there are many variants of the H1 clade. As the del-In9 variant only distinguishes H1 and H2, it is a reasonable marker to tag the variants that occur on the H1 and H2 backgrounds; however, it will perform poorly if used to tag loci that define sub-haplotypes of the H1 clade. This is important for the current study, as all previous studies examining AD risk and MAPT genotypes only looked at variants that defined the H1 or H2 clades and variants of the H1 clade.

 

View this table: [in this window] [in a new window]   Table 1. Sample statistics

 

View this table: [in this window] [in a new window]   Table 2. Single locus associations

 

View this table: [in this window] [in a new window]   Table 3. Single locus associations within APOE-4 positive and negative subsets of the combined US and UK sample

 
Single locus analysis: APOE sub-analysis
We noted that when the single locus P-values were adjusted for age, sex and APOE status, many of the single locus P-values became more significant (see Table 2 for both series collapsed rs242557 P-value prior to age, sex, APOE adjustment=0.007, after adjustment=2.49E-07). We examined whether this effect was mainly due to age differences, gender differences or differences due to APOE background and found that the most robust interaction for each marker was with APOE status (data not shown, see Materials and Methods for description of analysis). To further examine this interaction, we divided the entire sample including both US and UK samples into two sub-series on the basis of APOE 4 genotype; cases and controls that possessed at least one 4 allele were analysed separately from cases and controls that had no 4 alleles. We found significant single locus P-values only in the sub-series where neither cases nor controls had any APOE 4 alleles, suggesting that the single tag variant association is driven by those individuals who do not possess APOE 4 alleles.

Haplotype analysis
The location of all tag SNPs with respect to MAPT exon structure as well as major haplotype frequencies and description of the alleles at each tag SNP for the major MAPT haplotypes is shown in Figure 2. Haplotype frequencies were obtained from the program SNPHAP (Clayton, D: http://www-gene.cimr.cam.ac.uk/clayton/software/snphap). As expected, we found no difference in the frequency of haplotype A (H2a) between cases and controls in the UK or US series or when both samples are combined (UK LOAD frequency=24.41%, control frequency=25.44%, US LOAD frequency=22.10%, US control frequency=22.52%, combined series LOAD frequency=23.39%, control frequency=23.48%). This is in contrast to the clear negative association of this haplotype with PSP (8). Thus, these results are consistent with our single locus analysis and with previous reports (8,12,14) that the del-In9 polymorphism of MAPT is not associated with LOAD.

View larger version (7K): [in this window] [in a new window]   Figure 2. MAPT haplotypes. The locations of all tag SNPs used in this study with respect to the exon structure of MAPT are shown. In addition, the five major (frequency >5%) MAPT haplotypes are listed along with their frequency in controls, LOAD and PSP. Under the location of each tag SNP, the allele for that particular SNP is shown for each haplotype (e.g. for Haplotype H2a: rs1467967=A, rs242557=G, rs3785883=G, rs2471738=C, del-In9=del and rs7521=G). The del-In9 polymorphism tags all H1 haplotypes, separating them from H2. The ‘del-In9’ allele is a 238 bp deletion first reported by Baker et al. (2). Figure adapted from Pittman et al. (8).

 
As we had previously shown that the H1c variant of the MAPT locus was involved in risk for PSP (8), we decided to perform an analysis on this haplotype alone, thus minimizing multiple testing confounds. Using the constrain flag in the program Whap (http://www.genome.wi.mit.edu/~shaun/whap), we found a significant result testing the H1c variant against all other haplotypes in the UK series (empirical P-value=0.045, 500 permutations of likelihood ratio test to obtain P-value), which replicated in the US series (empirical P-value=0.018, 500 permutations of likelihood ratio test to obtain P-value). When both series were combined, likelihood ratio tests of haplotype H1c gave a P-value of 0.004. Examining the frequencies as predicted by SNPHAP, it appeared that the association was due to an over-representation of the H1c haplotype in LOAD (UK LOAD frequency=15.11%, control frequency=9.29%, US LOAD frequency=13.17%, US control frequency=8.05%, combined series LOAD frequency=13.91%, control frequency=8.51%). This association is in the same direction as, although smaller, that seen in our analysis of PSP where the H1c frequency is 24% (8).

Haplotype analysis: APOE sub-analysis
In the light of the putative interaction with APOE genotype that we found examining single locus associations, we decided to examine whether APOE status had any influence on our H1c haplotype association. We first tested whether there was an APOE interaction with MAPT using the full dataset and the ‘–gxe’ and ‘–alt-gxe’ flags in Whap. These two flags test whether there is a significant haplotype effect while adjusting for epistatic effects of another locus (–gxe) and whether there is a significant interaction between the genotypes of one locus and the haplotypes of the other (–alt-gxe). When haplotype H1c was tested for association controlling for the effect of the APOE locus, the P-value increased moderately from 0.004 to 0.005 (500 permutations of LRT to obtain P-value). When APOE was included in the model, using the ‘–alt-gxe’ flag, the P-value decreased considerably (P-value with APOE=5.16E-22, 500 permutations to obtain P-value), indicating a significant interaction between APOE genotype and MAPT haplotype. We then stratified our sample as in our single locus analysis by splitting the combined series into the subset of cases and controls that possessed APOE 4 alleles and into the cases and controls that had no APOE 4 alleles. As in the single locus analysis, the association between haplotype H1c and disease risk was only seen in those individuals who had no APOE 4 alleles (H1c P-value in subset of entire series where individuals had at least one 4 allele=0.238 and H1c P-value in subset of entire series where individuals had no 4 allele=0.008, 500 permutations to obtain P-values for both tests).

	DISCUSSION

TOP ABSTRACT INTRODUCTION RESULTS DISCUSSION MATERIALS AND METHODS REFERENCES

 
The dominant hypothesis for the aetiology and pathogenesis of AD has been the amyloid hypothesis (14). This hypothesis is based on the observation that all the autosomal dominant mutations in either the APP or presenilin genes that cause AD, do so through their effect on APP/Aß metabolism. However, experiments in which mice with APP mutations have been crossed with those with MAPT mutations have shown that the major route by which Aß kills neurons involves tau biology and tangle formation (15–17). Furthermore, tau expression appears to be needed for Aß toxicity in ex vivo experiments (18). We believe our data are most consistent with the view that, in the presence of an amyloid load, those individuals with MAPT loci which are either highly expressing or prone to express a more pathogenic species of tau through alternate splicing (19), are more prone to disease. Our single locus results would indicate that, as we found with PSP, the most likely region for a pathogenic variant(s) to occur is between just upstream of exon 1 and just within intron 9, as only rs242557 (5' of exon 1) and rs2471738 (within intron 9) give significant single locus results. The SNP rs242557 falls into a 181 bp region that is conserved in human, chimp, mouse, dog and rat (ch17: 41375547–41375728, UCSC genome browser build 35, May 2004), which is 19 kb upstream of the first coding exon of MAPT. The SNP rs2471738 does not lie within a conserved region of intron 9 and does not appear to interrupt the donor or acceptor splice sites, as it is 2 kb away from the closest intron–exon junction. This suggests that perhaps this variant is not functional, but is associated with risk because it is in linkage disequilibrium with another variant. In our analysis, it appears as though there might be a stronger association between the H1c variant of MAPT and risk in individuals who do not possess APOE 4 alleles. However, it should be noted that our APOE sub-analyses are underpowered because control individuals possessing APOE 4 alleles are fairly rare. Analysis in larger populations will need to be performed to confirm these initially interesting results. Irrespective of APOE status, we obtained significant associations in both of our pathological series with the H1c haplotype: the same haplotype which shows robust association with PSP. This suggests that modulation of tau expression is a worthwhile approach to consider for the treatment of AD (20).

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION RESULTS DISCUSSION MATERIALS AND METHODS REFERENCES

 
Samples
All samples were of Caucasian origin obtained from either the Newcastle Brain Bank, Newcastle-upon-Tyne, UK (UK series) or various brain banks throughout the United States (US series, see Acknowledgements for specific sites). All samples were pathologically confirmed, with 40% of controls and 30% of cases having Braak and Braak staging. Controls were free of neuropathology at autopsy.

Markers
We previously analysed the haplotype structure of MAPT using markers from the CEPH database (http://www.hapmap.org). Using the program Tagit (http://popgen.biol.ucl.ac.uk/software), we found that a minimum of five SNPs are needed to capture the haplotype diversity at the MAPT locus. We tested the performance of our five tagging SNPs and the del-In9 against each individual SNP typed within the CEPH-trios, using criterion 5 (haplotype r²) in the program Tagit. On average, our set of tag SNPs captures 95% of the diversity of the known CEPH variants and scores >90% for most individual loci. Performance plots of the tagging variants as well as the del-In9 polymorphism on its own are shown in Figure 1.

Genotyping
SNP genotyping was performed by pyrosequencing (see http://www.pyrosequencing.com/ for a description of this method). Primers are available on request. The genotyping of del-In9 was performed as previously described (2).

Statistical analysis
Linkage disequilibrium between the tag SNPs was determined and visualized using the program haploview (http://www.broad.mit.edu/mpg/haploview/). D' plots for each sub-series are shown in Figure 3. All single locus analyses were performed using SPSS software version 11. Age, gender and APOE-adjusted P-values for the single locus analysis were obtained by performing a logistic regression analysis, fixing age, gender and APOE in the model and then fitting a model in which either genotypes or alleles of the locus in question were included. Single locus interaction effects were determined by creating regression models in which two out of three factors (gender, age or APOE status) were fixed and then assessing the interaction between the other factor and the genotypes or alleles at the tag variant in question. For the APOE sub-analyses, only the combined sample was used because of the inherent low power of this type of analysis. Heterogeneity tests for all loci between the UK and US series were negative, allowing them to be combined into a more powerful series. All haplotype analyses were performed using the program Whap (http://www.broad.mit.edu/personal/shaun/whap/). The constrain flag was used to assess the significance of the H1c haplotype, and the –gxe and –alt-gxe flags were used to assess the contribution of APOE status to the putative haplotype effects. As with the single locus analysis, only the combined sample was used for the APOE sub-analysis because of power constraints.

View larger version (29K): [in this window] [in a new window]   Figure 3. Linkage disequilibrium in each series. Plots of the relative D' levels between each of the markers used in this analysis using the program haploview (http://www.broad.mit.edu/mpg/haploview/) are shown. At the top of the figure, the coding exons of MAPT are shown, as well as the relative positions of the tagging SNPs. The second half of the figure shows the D' values for each pair of tagging markers in both the UK and US series. Note that in both series, all of the tagging SNPs are in complete linkage disequilibrium with del-In9 (marker 5, D'>90%, darkly shaded areas on each graph), but are not in strong linkage with each other (D'<90%, more lightly shaded areas of each graph), indicating that these markers are H1 specific. Numbers in the figure indicate D' valuesx100. Quadrants, where there was perfect LD (D'=1.0), were left blank.

 

	ACKNOWLEDGEMENTS

 
None of this work would have been possible without the generous participation of the patients and controls and their families. This work was supported by the Reta Lila Weston Trust, the PSP (Europe) Association, the MRC, UK and the NIA/NIH Intramural Research Program, USA. Many data and biomaterials were collected from several NIA–NACC funded sites. Marcelle Morrison-Bogorad, PhD, Tony Phelps, PhD and Walter Kukull PhD are thanked for helping to co-ordinate this collection. The directors, pathologists and technicians involved include: National Institute on Aging: Ruth Seemann; John Hopkins Alzheimer's Disease Research Center (NIA grant no. AG 05146): Juan C. Troncoso, MD, Dr Olga Pletnikova; University of California, Los Angeles (NIA grant no. P50 AG16570): Harry Vinters, MD, Justine Pomakian; The Kathleen Price Bryan Brain Bank, Duke University Medical Center (NIA grant no. AG05128, NINDS grant no. NS39764, NIMH MH60451 also funded by Glaxo Smith Kline): Christine Hulette, MD; Stanford University: Dikran Horoupian, MD, Ahmad Salehi, MD, PhD; New York Brain Bank, Taub Institute, Columbia University (NYBB): Jean Paul Vonsattel, MD; Massachusetts General Hospital: E. Tessa Hedley-Whyte, MD, Karlotta Fitch; University of Michigan (NIH grant P50-AG08671): Dr Roger Albin, Lisa Bain, Eszter Gombosi; University of Kentucky: William Markesbery, MD, Sonya Anderson; Mayo Clinic Jacksonville: Dennis W. Dickson, MD, Natalie Thomas; University Southern California: Carol A. Miller, MD, Jenny Tang, MS, Dimitri Diaz; Washington University, St Louis Alzheimer's Disease Research Center: Dan McKeel, MD, John C. Morris, MD, Eugene Johnson, Jr, PhD, Virginia Buckles, PhD, Deborah Carter; University of Washington, Seattle: Thomas Montine, MD, PhD, Aimee Schantz, MEd. A.J.M. is a resident research associate of the National Academy of Sciences (USA). A.J.M. and J.H. would like to thank the Verum Foundation and the EU DIADEM Project.

Conflict of Interest statement. None declared.

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