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Human Molecular Genetics, 2003, Vol. 12, No. 8 859-867
DOI: 10.1093/hmg/ddg094
© 2003 Oxford University Press

Haplotypes extending across ACE are associated with Alzheimer's disease

Patrick G. Kehoe1, Hagit Katzov2, Lars Feuk2, Anna M. Bennet3, Boo Johansson4, Björn Wiman5, Ulf de Faire3,6, Nigel J. Cairns7, Gordon K. Wilcock1, Anthony J. Brookes2, Kaj Blennow8 and Jonathan A. Prince2,*

1Department of Care of the Elderly, University of Bristol, The John James Building, Frenchay Hospital, Bristol, UK, 2Center for Genomics and Bioinformatics, Karolinska Institute, Stockholm, Sweden, 3Division of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden, 4Department of Psychology, University of Göteborg, Göteborg, Sweden, 5Department of Clinical Chemistry, Karolinska Hospital, Stockholm, Sweden, 6Department of Cardiology, Karolinska Hospital, Stockholm, Sweden, 7Department of Neuropathology, Institute of Psychiatry, King's College, London, UK and 8Department of Clinical Neuroscience and Transfusion Medicine, University of Göteborg, Sahlgren's University Hospital, Sweden

Received December 12, 2002; Accepted February 7, 2003


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Numerous genes have been implicated in Alzheimer's disease (AD), but, with the exception of a demonstrated association with the {varepsilon}4 allele of APOE, findings have not been consistently replicated across populations. One of the most widely studied is the gene for angiotensin I converting enzyme (ACE ). A meta-analysis of published data on a common Alu indel polymorphism in ACE was performed which indicated highly significant association of the insertion allele with AD (OR 1.30; 95% CI 1.19 – 1.41; P=4x10-8). To further explore the influence of ACE on AD, several single-nucleotide polymorphisms (SNPs) were genotyped in five independent populations represented by over 3100 individuals. Analyses based upon single markers and haplotypes revealed strong evidence of association in case – control models and also in a model examining the influence of variation in ACE upon cerebrospinal fluid levels of amyloid ß42 peptide (Aß42). The most significant evidence for association with AD was found for an SNP, A-262T, located in the ACE promoter (OR 1.64; 95% CI 1.33 –1.94; P=2x10-5). Estimates of population attributable risk for the common allele of this SNP suggest that it, or an allele in tight linkage disequilibrium (LD) with it, may contribute to as much as 35% of AD in the general population. Results support a model whereby decreased ACE activity may influence AD susceptibility by a mechanism involving ß-amyloid metabolism.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Alzheimer's disease (AD; MIM 104300) is a neurodegenerative disorder characterized by progressive memory loss and is the most common cause of dementia in the elderly. Efforts to identify the genetic causes of certain rare familial forms of AD, representing a small fraction of all known AD cases, have been largely successful. By the use of linkage mapping methods, mutations in the genes for amyloid precursor protein (APP), presenilin-1 (PSEN1) and presenilin-2 (PSEN2) have been found to underlie the majority of familial cases (1–3). However, for the more common form of AD, which probably results from a complex interplay between multiple genes and environmental factors, inheritance of the {varepsilon}4 allele of the APOE gene is the only genetic risk factor for which there is broad consensus (4).

Over the last decade, genetic association studies have been used to suggest numerous genes as risk factors for AD (5), but most findings have never been replicated in independent materials. As a result of these difficulties in AD and in other phenotypes, the credibility of association methods for the identification of the genetic components of complex human traits has fallen under considerable scrutiny. Several papers have been written which illustrate the general difficulties to be expected using association methods (6–8). Cited problems include inadequate statistical power, lack of correction for multiple testing, reliance upon markers which may be in weak linkage disequilibrium (LD) with functional risk variants, genetic heterogeneity, publication bias and potential gene–gene and/or gene–environment interaction. For a handful of studies, the awareness of these and other issues has led to the conclusive identification of genetic risk factors in complex disorders such as type 2 diabetes (9), breast cancer (10) and Crohn's disease (11).

With respect to AD, the greater proportion of studies into putative risk genes has succumbed to many of these problems. Notably, most findings have not been replicated, few studies have employed high-powered population samples and, in the majority of cases, only single variants with unknown functional relevance have been assessed. In particular, studies focussing on single variants have ignored the potential for alternative polymorphisms to mediate susceptibility for disease where such effects may be better captured using haplotype-based methods (12,13). Here, we provide evidence that variation in the gene for angiotensin I converting enzyme (ACE) contributes substantially to AD. Findings have been facilitated by meta-analysis of previously published studies on variants of ACE and AD, and by additional genotyping and haplotype analyses in several independent case–control populations.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
We were interested in whether meta-analysis of published association findings could provide significant evidence for the involvement of a candidate gene in AD that could then be confirmed by additional genotyping in multiple independent case–control materials. In reviewing the literature, the most widely studied genes in AD with three or more confirming findings, apart from APOE, were found to be A2M, ACE, BCHE, HLA-A2, LRP, PSEN1, SERPINA3 and VLDLR. For a subset of these (BCHE, ACE and LRP), meta-analyses have been previously performed, in each case concluding that the studied genes do play a significant role in AD (14–16). We conducted a meta-analysis on published data (identified by exhaustive review of MEDLINE up to June, 2002) for a common Alu indel polymorphism in ACE which included 21 populations examined in 18 studies [extending upon the 12 studied populations in Narain et al. (15); Table 1]. We chose to focus on ACE for several reasons. First, genetic variation in ACE has a highly reproduced effect on variation in circulating ACE protein levels (17), supporting a potential role for the gene in phenotypes which may be influenced by ACE activity. Second, variation in ACE is well documented, thus facilitating haplotype-based analyses (18,19). Third, a recent publication demonstrated the involvement of ACE in the degradation of amyloid ß-peptide (Aß), providing a putative biological link to AD (20). The results of the current meta-analysis corroborated earlier findings (15), indicating that the Alu insertion allele in ACE confers a modest overall increased risk for AD (OR 1.30; 95% CI 1.19–1.41; Table 1).


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  		Table 1. Published data for the Alu indel polymorphism in AD
 
To better characterize the nature of the observed association between ACE and AD, we conducted a haplotype analysis in several AD and control samples. We began by genotyping seven SNPs (Table 2) in ACE in sample sets A and B (Table 3). Assays were created for five additional non-synonymous SNPs previously identified in African populations (18), but these were all found to be monomorphic after testing 95 Swedish control individuals. With the seven confirmed SNPs, 10 haplotypes with frequencies above 1% were identified using HAPLOTYPER (21) (Table 4). In order to incorporate haplotypes into statistical analyses and for genotyping in additional populations, three SNPs were identified which could delineate or ‘tag’ (22) haplotypes with frequencies above 5% (Table 4). LD, estimated using the r2 metric (23), was high between all of the studied SNPs (Table 5). Initial analyses on haplotypes generated from the three tag-SNPs did not reveal significant differences in distributions between cases and controls in sets A and B when studied independently, but significant enrichment of haplotype H1 in AD was observed by combining odds ratios (Peto's method) (24) from the 2 sets [OR 1.27; 95% CI 1.05–1.49 (Table 6, panels 1 and 2)]. Based upon positive haplotype findings in sets A and B, the three tag-SNPs were then genotyped in sets C and D (Table 6, panels 3 and 4). Significant enrichment of H1 in sets C and D was again observed (combined OR 1.27; 95% CI 1.07–1.47). Combining results from all four groups further supported a significant excess of H1 in AD (OR 1.27; 95% CI 1.12–1.42) and a deficit of H2 in AD (OR 0.82; 95% CI 0.66–0.97). Given that H1 contains the Alu insertion allele, these findings are in complete agreement with meta-analysis data, both suggesting that an equivalent common allele contributes to AD susceptibility. Two final models examining summed haplotype counts from all sample sets were also generated (Table 6, panels 5–6). In these we noted, in addition to significant distortions of H1 and H2 between cases and controls, a significant deficit of H5 in AD, which suggests that there may be more than one pathogenic allele in the gene.


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  		Table 2. Details of SNPs, PCR and DASH conditions
 

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  		Table 3. Clinical materials
 

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  		Table 4. Discerned haplotypes in ACE
 

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  		Table 5. Pairwise LD for ACE markers
 

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  		Table 6. Haplotype associations
 
Based upon its putative involvement in ß-amyloid degradation (20), we explored the possible influence of ACE variants on CSF levels of Aß42. CSF Aß42 levels were measured as previously described (25) in a total of 237 cases and 49 controls from sets A and C. Significantly lower levels of Aß42 were observed in the AD group compared with controls, consistent with what has been shown in numerous previous studies (Student's t-test, P<0.0001) (26). To perform an analysis of ACE haplotypes and Aß42 levels, a clade strategy was employed similar to that used by Soubrier et al. (27). Previous studies on haplotype diversity in ACE have suggested a cladistic structure involving three major clades (A, B and C), where clade A has been shown to be associated with low plasma ACE activity, and clades B and C with higher activity (18,19,27). We noted from the work of Soubrier et al. (27) and Farrall et al. (19) that haplotypes defined by as few as two SNPs (one on either side of a putative ancestral recombination or gene conversion event) could be efficiently assigned to one of the three major clades. Using two of the three tag SNPs to predict haplotypes (ACE3 and ACE6; Table 4), and modeling effects by ANOVA, significant differences in CSF-Aß42 levels between ACE clades were observed (Fig. 1). These differences, while subtle, were consistent with the presence of a detrimental allele(s) in clade A (which contains H1) and/or a protective role for an allele(s) within clade B (containing H2). However, we also noted significant differences in individuals bearing the combination of haplotypes belonging to clades B and C compared with other groups (Fig. 1).



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  		Figure 1. Mean values (±SEM) of Aß42 levels for AD patients with different phased multilocus genotypes as estimated using the HAPLOTYPER program and binned by clade affiliation. The number of individuals in each group is shown in parentheses. Significance was determined both with ANOVA (shown at top left) and by the Kruskal–Wallis non-parametric test (P=0.02). There was no evidence of confounding effects of age, duration, or gender. Approximately 7% of variation in CSF Aß42 levels is explained in this model.

 
With substantial evidence of ACE haplotypes influencing AD, we investigated whether any of the single markers that had been typed in all 4 case-control populations would also exhibit significant association. Tests of genotype distributions between cases and controls revealed all of the three tag-SNPs to be significantly associated with AD (Table 7). The strongest effect was found for the ACE6 marker, which is located in the ACE promoter (OR 1.64; 95% CI 1.33–1.94). In agreement with haplotype findings, the allele of this site that was enriched in AD is present on the H1 haplotype (Table 6). To quantify the impact of this SNP on AD, we calculated population attributable risk (28), which suggested under a dominant model that the detrimental allele at this site (or an allele in strong LD with it) may contribute to as much as 35% of AD in the general population.


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  		Table 7. Single marker associations
 
Since essentially all existing data on variation in ACE in relation to AD are based upon the Alu indel polymorphism, it was considered necessary to obtain genotypes for this marker in at least one of the studied sample sets. This was done for set D materials, in addition to the three tag-SNPs. Standard chi-square tests did not reveal any significant differences for alleles or genotypes between cases and controls for the Alu indel marker (P=0.6 and 0.9, respectively; data not shown). Estimates of LD between the Alu indel polymorphism and other studied markers in set D ranged from r2=0.46 to r2=0.91 (Table 5).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
MATERIALS AND METHODS
 REFERENCES
 
We have employed multiple independent clinical materials to provide reproducible evidence that variants of ACE have a considerable impact upon AD. Results are consistent with a modest, but highly significant detrimental effect of a common allele of ACE that because of its high frequency may underlie a large proportion of AD cases in the general population. The validity of findings is further independently substantiated by a meta-analysis of published studies on variation in ACE and AD. While the majority of prior studies have been of limited scope, employing small populations and focussing exclusively upon a single Alu indel polymorphism in ACE, their utility in meta-analysis is clearly underscored here, highlighting the critical importance of the data from negative association studies being published and/or made readily available to the general public.

The shortcomings of previous studies on the Alu indel illustrates the importance of typing multiple SNPs (or other types of variation), of using haplotype based approaches, and of having some understanding of LD structure in regions of interest when undertaking association studies. In this context, it is noteworthy that a recent study has indicated that the Alu indel polymorphism can be excluded as the site which influences ACE levels (29). Within our own data set, the ACE6 marker, which showed the strongest effect on AD, was in the weakest LD with the Alu indel (r2=0.46). In contrast, the ACE3 marker, which showed the weakest effect on AD, was in the strongest LD with the Alu indel (r2=0.91). Based upon these premises, we consider it plausible that reliance upon the Alu indel may have contributed to many of the negative findings previously reported. Assuming that ACE6 is in tight LD with a ‘true’ pathogenic variant(s), based upon the odds ratio we report (1.64), sample sizes on the order of 300 cases and 300 controls are required to achieve 80% power at a 0.05 significance level (surpassing sample sizes for most previous studies; Table 1). Diminishing LD requires a proportional increase in sample size to maintain power, the relationship being ~1/r2 (30). Thus, use of the Alu indel would dictate that sample size needs to be more than doubled to have reasonable (80%) power to detect the effect.

A series of experiments have been previously undertaken aimed at refining the location of variants in ACE which influence circulating ACE levels (29). Findings have suggested the presence of one or more variants that contribute to the ACE trait, but as yet none have been tested in isolation for their functional role. Specifically, both intragenic and promoter variants were observed to act independently to influence ACE levels (29). While all of our studied SNPs are shown to be associated with AD, the strength of the finding for the common ACE6 promoter variant alludes to perturbed expression of ACE as potentially underlying its effects upon AD. However, there is no way to exclude one or more alternative sites, as the high level of LD between all studied SNPs is prohibitive in terms of providing further resolution, at least in European populations. A number of sequencing efforts have exhaustively screened the transcribed region of ACE and while sequence variants outside the studied region may be relevant, none of the yet identified polymorphisms are represented by ‘obvious’ pathogenic alleles.

Our observations suggest an equivalence between the alleles that are associated with AD and those that are associated with reduced circulating ACE levels (17). The implied relationship is thus that reduced activity of ACE, either by modification of the protein or reduced expression levels, underlies an increase in susceptibility to AD. Further, recent work has indicated that ACE contributes to the metabolism of Aß, whereby increased Aß degradation may prevent its aggregation, thus reducing susceptibility to AD (20). In principle, this would be consistent with our findings in terms of association with AD. However, in addition to effects upon AD, we also investigated the potential influence of ACE variants on CSF-Aß42. While findings were significant, they were not amendable to simple interpretation. The primary haplotype groups (belonging to A and B clades) differed in terms of levels of CSF-Aß42, with lower levels in clade A compared to clade B, but the lowest CSF-Aß42 levels were observed in the group in which clade B and clade C haplotypes are found in combination. While this implies possible allelic interaction, we note that a confirmation of such an effect might come appropriately from a study of existing data on plasma ACE levels (e.g. from Soubrier et al., 27). An effect of this nature, if real, would most likely also contribute to inconsistencies in case–control studies. We regard our findings on CSF-Aß42 as preliminary, clearly in need of further study, but nonetheless worthy of mention here.

To date, the only well-replicated risk factor for AD is the {varepsilon}4 allele of APOE (4). It is worth noting, however, that variants of both APOE and ACE have been found to influence a number of phenotypes, including cardiovascular disease and various measures of lipid metabolism (31). In addition, the {varepsilon}4 allele of APOE has been shown to be associated with reduced CSF-Aß42 (32), an effect which may be shared by variants of ACE. In view of all of these findings, common biological pathways linking the effects of APOE, ACE, lipid and Aß metabolism seem to be implied in AD aetiology.

In summary, results indicate that genetic variation in ACE substantially contributes to AD susceptibility. This represents the strongest evidence to date of a second gene, in addition to APOE, that influences the sporadic form of AD. However, while the data are consistent with one common susceptibility allele of ACE, we cannot exclude the possibility that multiple pathogenic alleles exist across the gene as has previously been hypothesized to be the case (29). The identification of functional variants of ACE thus represents one of the last hurdles to overcome before the mechanism of its involvement in AD can be defined.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
REFERENCES
 
Clinical materials
Details of all clinical materials are provided in Table 3. Swedish LOAD sets A and C consisted of a total of 390 patients. Set A was recruited from a prospective longitudinal study at Göteborg University of patients with dementia. Set C was recruited as part of a longitudinal geriatric population study in Piteå, Sweden. In the AD group, 297 had a clinical and 93 a neuropathological diagnosis. All clinically diagnosed AD patients underwent a thorough investigation, which included a medical history, physical, neurological and psychiatric examination, screening laboratory tests, ECG, X-ray of the chest, EEG and computerized tomography (CT) of the brain. Clinical AD diagnoses were made according to the NINCDS-ADRDA criteria (33). All neuropathologically diagnosed AD patients also fulfilled the clinical NINCDS-criteria for probable AD and met the neuropathological CERAD criteria for definitive AD (34).

Swedish controls for set A consisted of 77 healthy volunteers and 108 autopsy individuals. The healthy volunteers were individuals without history, symptoms or signs of psychiatric or neurological disease, malignant disease, or systemic disorders. Cognitive status was examined using MMSE (35), and individuals with scores below 28 were not included as controls. The autopsy control group consisted of patients who had died from cardiac disease or malignant disease. Their medical records revealed no history of dementia or other psychiatric or neurological diseases. Post-mortem examination revealed no macroscopic infarcts, and all brains scored four or lower on the histopathological scoring system (see above). All autopsy cases (AD and control) were matched by age-at-death and all clinically diagnosed AD cases and healthy volunteers were matched by age-at-onset/age-at-exam, respectively.

Swedish controls for set C consisted of 326 individuals from the Swedish Twin Registry. All 80-year-old and older twin pairs in Sweden, where both co-twins were still alive were recruited to participate in the OCTO-Twin study. All participants underwent a thorough health examination, structured interviews/tests of functional capacity, cognitive abilities and memory. The preliminary diagnosis was made on the basis of performance on a battery of tests for dementia and cognitive impairment, including MMSE. Further tests were selected to sample across diverse specific cognitive abilities, including verbal, spatial, speed of processing and memory abilities. A dementia work-up was performed in all cases suspected for dementia and in those demonstrating significant cognitive decline. Control subjects chosen showed no symptoms of cognitive decline. One sibling, randomly chosen from each twin pair, was included in this control sample.

The Scottish EOAD sample (set B) consisted of 121 consecutively ascertained presenile (<65 years) dementia patients from the Lothian Psychiatric Case Register assessed by the NINCDS criteria as possible or probable AD. Scottish controls for set B consisted of 152 local church congregation volunteers from the Lothian region who met the MMSE exclusion criteria for dementia. The EOAD materials were selected from non-familial cases, and the most common presenilin-I mutations have been screened for. The few positives found were discarded from the test set.

The English case–control group (set D) consisted of 335 autopsy confirmed cases of sporadic AD where 273 had a single diagnosis of AD and the remainder were cases with a primary diagnoses of AD with either concurrent vascular dementia pathology (n=35) or dementia of the Lewy body type (n=26). A total of 110 age-matched elderly controls were also used which had no previous clinical evidence of memory impairment and were confirmed at autopsy for the absence of any memory impairment-related pathology. The DNA used in this set was extracted from donated brain tissue from both the South West Brain Bank in Bristol (252 AD; 58 controls) and the MRC Brain bank in London (83 AD; 52 controls) and the work was carried out with Local Research Ethics Committee knowledge and approval. All neuropathological confirmations were assessed by an experienced neuropathologist and diagnosed according to the CERAD criteria. A total of 40 individuals diagnosed with AD were included in this set that had previously been reported on for the Alu indel polymorphism (36).

Set E consisted of 1526 healthy controls. This material constitutes the control group of participants in the Stockholm Heart Epidemiology Program (SHEEP), a population-based case–control study aimed to investigate the effects of different risk factors for myocardial infarction in men and women. In this sub-set of SHEEP, only controls originally matched to surviving cases were included. More detailed demographic characteristics of these control subjects (i.e. who had not suffered a myocardial infraction) were reported elsewhere (37). The subjects were aged 45–70 and were selected from the Stockholm County population registry.

CSF Aß42 measurement
Cerebrospinal fluid levels of Aß42 were estimated in a subset of individuals from sets A and C. For this, lumbar puncture was performed at the L3/L4 or L4/L5 interface. The first 12 ml of CSF was collected in polypropylene tubes and gently mixed to avoid gradient effects. All CSF samples with erythrocyte counts of more than 500/µl were excluded. CSF samples were centrifuged at 2000g for 10 min. Aliquots were stored at -80°C until biochemical analyses were performed. Aß42 was determined using a sandwich ELISA specific for Aß42, as previously described (25).

SNP selection and verification
All reported SNPs may be found in the dbSNP database (www.ncbi.nlm.nih.gov/SNP/) under their respective IDs (Table 2). Surrounding 50 bp sequences in each direction were examined for repeats and duplicated sequences using Repeatmasker (http://repeatmasker.genome.washington.edu/cgi-bin/RepeatMasker/) and Blast (www.ncbi.nlm.nih.gov/blast). To verify that SNPs were polymorphic in our study populations, each was tested in a set of 16 Swedish control samples. Assays in which all 16 samples were monomorphic were excluded from further analysis. For the rare previously identified non-synonymous SNPs, 95 controls were used. All SNPs that were polymorphic in the Swedish population were also found to be polymorphic in the Scottish population.

Genotyping
Genotyping of SNPs was performed using dynamic allele specific hybridization (DASH) (38). Optimal PCR temperatures as well as sequences for PCR primers and iFRET probes are shown in Table 2. All PCR reactions were run in 20 µl volumes with 1.5 mM MgCl2 and using 5–20 ng genomic DNA.

Statistical analysis
Deviation from Hardy–Weinberg equilibrium for alleles at individual loci as well as differences in genotype and haplotype distributions between groups were assessed by the chi-square statistic. Tests for association between haplotypes and CSF Aß42 levels were performed using analysis of variance (ANOVA), and significant findings were further assessed using Kruskal–Wallis analysis of ranks. Confounding effects of duration, age-at-assessment or sex were evaluated by including each term as a covariate in ANOVA models. All of the above statistical analyses were performed using StatView version 5.0 (Abacus Concepts). Meta-analyses were performed using Peto's method (24). Haplotype frequencies were estimated using the HAPLOTYPER program (21). LD between marker pairs within ACE was estimated using the r2 metric (23). Population attributable risk was calculated under a dominant model for the ACE6 marker (28).


   ACKNOWLEDGEMENTS
 
Generous financial support was provided by: Pharmacia Corporation, Loo and Hans Ostermans Foundation, The Knut and Alice Wallenberg Foundation, The National Institute on Aging (AG:08861), The Swedish Old Servants Foundation (Gamla Tjänarinnor), Åke Wibergs Foundation, Torsten and Ragnar Söderbergs Foundation, Fredrik and Ingrid Thurings Foundation, King Gustav the Vth and Queen Victoria's Foundation, The Swedish Heart and Lung Foundation, Petrus and Augusta Hedlunds Foundation, and The Swedish Alzheimer Foundation (Alzheimerfonden).


   FOOTNOTES
 
* To whom correspondence should be addressed at: Center for Genomics and Bioinformatics, Karolinska Institute, Berzeliusväg 35, 171 77 Stockholm, Sweden. Tel: +46 87286274; Fax: +46 8324826; Email: Jonathan.Prince{at}cgb.ki.se Back


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 

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