East Asian Arch Psychiatry 2011;21:79-84

ORIGINAL ARTICLE

Dr Kangguang Lin, MMed, Department of Geriatric Psychiatry, Guangzhou Psychiatric Hospital, Affiliated Hospital of Guangzhou Medical College, Guangzhou 510370, PR China.
Dr Muni Tang, MD, Department of Geriatric Psychiatry, Guangzhou Psychiatric Hospital, Affiliated Hospital of Guangzhou Medical College, Guangzhou 510370, PR China.
Dr Yangbo Guo, MD, Department of Geriatric Psychiatry, Guangzhou Psychiatric Hospital, Affiliated Hospital of Guangzhou Medical College, Guangzhou 510370, PR China.
Dr Haiying Han, Department of Geriatric Psychiatry, Guangzhou Psychiatric Hospital, Affiliated Hospital of Guangzhou Medical College, Guangzhou 510370, PR China.
Ms Yuhua Lin, Department of Molecular Genetics Laboratory, Guangzhou Psychiatric Hospital, Affiliated Hospital of Guangzhou Medical College, Guangzhou 510370, PR China.

Address for correspondence: Dr Kangguang Lin, Guangzhou Psychiatric Hospital, Affiliated Hospital of Guangzhou Medical College, 36 Mingxin Road, Fangchun District, Guangzhou, Guangdong Province 510370, PR China.
Tel: (86-20) 8189 1425; Fax: (86-20) 8189 1391; Email: linkangguang@163.com

Submitted: 23 November 2010; Accepted: 15 February 2011

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Introduction

Late-onset Alzheimer’s disease (LOAD) is a genetically complex and heterogeneous disorder. A hereditary basis for Alzheimer’s disease (AD) was estimated to about 60% to 80%.¹ Nearly all subsequent studies confirmed that ε4 allele of apolipoprotein E (ApoE) as a genetic susceptibility factor for LOAD, since it was first found by means of genetic linkage analysis in 1991.² The ApoE ε4 allele has been estimated to account for only 20% of the genetic risk in LOAD, and recent studies including both the candidate gene and genome-wide approaches have found several risk genes for LOAD³ (http://www.alzgene.org). Although highly estimated, all the candidate genes reported might not explain over 50% of all LOAD inheritance, which is in contrast to what is known about the genetics of other complex diseases such as age-related macular degeneration.⁴ In other words, there is a substantial proportion of unaccounted genetic risk for LOAD, even after genome-wide association studies.⁵

The human regulator of calcineurin 1 gene (RCAN1, also called DSCR1, Adapt78, MCIPI, or calcipressin 1) is located on chromosome 21q22.12.⁶ RCAN1 is a regulator on the activity of calcineurin and observed to be overexpressed both in the brains of Down’s syndrome patients and AD patients.^7,8 Overexpression of RCAN1 contributed to hyperphosphorylated tau,^9,10 reduced synaptic vesicles,¹¹ and abnormal synaptic morphology.¹² However, lack of RCAN1 displayed severe learning deficits in drosophila,¹³ memory defects, and impaired late-phase long-term potentiation in mice.¹⁴ Furthermore, Porta et al¹⁵ found that RCAN1 modulated neuronal cell survival and death pathways depending on the RCAN1 dosage.

The RCAN1 gene consists of 7 exons, which can be alternatively spliced to produce different mRNA isoforms, of which RCAN1-1 and RCAN1-4 are the 2 major observed forms.¹⁶ Yang et al¹⁷ found that the upstream of exon 4 contained a cluster of nuclear factor of activated T-cells (NFAT)–binding motifs that contributed to the alternative promoter usage. The promoter of RCAN1-4 is activated by calcineurin that RCAN1 can inhibit in return, which formed a negative feedback circuit. Different CCAAT / enhancer-binding protein β (C/EBP β) isoforms and NFAT isoforms can activate transcription of RCAN1-4 through binding to conserved C/EBP β– binding sites located on the promoter region.^18,19 There are several polymorphisms, including (1) rs78899361 (g.21561755C>T); (2) rs8135540 (g.21561747A>C); (3) rs10550296 (g.21561498_21561501del4); (4) rs3831376 (g.21561495_21561498del4); and (5) rs71324311 (g.21561494_21561497del4)] located in the suggested promoter region. Exonic splicing enhancer (ESE) finder (Cold Spring Harbor Laboratory, New York, US) was used to test whether these polymorphisms had the ability to affect or act as an ESE and found polymorphisms around several ESE motifs in the region (range contig position from 21561001 to 21561901). Although highly estimated, some of these polymorphisms might have the potential to interfere with the splicing of RCAN1 and expression of RCAN1-4. In addition, rs8135540 is a tag single-nucleotide polymorphism (SNP) and the use of common tag SNPs in association studies assumes the common disease–common variant hypotheses.²⁰

Despite RCAN1 being a candidate gene on both functional and positional grounds, there are no studies so far considering the genetic association of RCAN1 and AD. Our aim was to study the possible genetic association between the polymorphisms located in the RCAN1 (the probable promoter for RCAN1-4) and AD.

Methods

Subjects

As shown in Table 1, the study group consisted of 142 clinically diagnosed AD patients and 99 non-demented elderly controls (NECs). Patients and NECs were selected from old folks’ homes and urban and rural communities in the survey area of dementia epidemiology in Guangzhou from 2001 to 2002. Among the patients, 67 were chosen from the Guangzhou Psychiatric Hospital. The diagnosis of AD was based on criteria given in the Diagnostic and Statistical Manual of Mental Disorders, 4th edition,²¹ as well as the National Institute of Neurological and Communicative Diseases and Stroke / Alzheimer’s Disease and Related Disorders Association.²² All patients examined had late onset of AD (defined as onset at age ≥ 65 years). In addition, they had no family history of dementia, psychotic disorder, or medical history of neurological disease. All AD patients and NECs were unrelated Chinese Han. Informed consent was obtained from each subject directly or from his / her guardian. The protocol for this study was approved by the respective Institutional Ethical Committees.

Marker Selection and Genotyping

Information about SNP was obtained from 2 open databases: National Center for Biotechnology Information dbSNP (Build 135 http://www.ncbi.nlm.nih.gov/snp/]) and International HapMap Project (Rel 28 PhasesⅡ+Ⅲ, on [NCBI B36 assembly, dbSNP b126 [http://hapmap.ncbi.nlm.nih.gov/]).

Genomic DNA was extracted from whole blood according to standard procedures. Genotyping analysis of ApoE was performed as previously described.²³ The ≈540-bp genomic segment for the promoter position of RCAN1-4 (-870 to -330 bp) including polymorphisms (rs78899361, rs8135540, rs10550296, rs3831376, rs71324311) was produced using the following primers: 5’-gctactcagacaacacgctcct-3’ and 5’-cctctggcataaatgggtt-3’. The product was sequenced with an ABI 3700 sequencer and a BigDye^TM Terminator V3.0 cycle Sequencing (Applied Biosystems, US) and the polymorphisms were detected by Mutation Surveyor (Applied Biosystems Genetic Analyzers, US), and ambiguities resolved by visual observation of peak heights (Figure).

Data Analyses

Genotypic and allelic frequencies were calculated, and the Hardy-Weinberg equilibrium was tested with a dedicated software program (utility programs for analysis of genetic linkage by The Rockefeller University, USA [http:// linkage.rockefeller.edu/]). The χ² test was applied to compare genotypic and allelic frequencies in cases and controls. Logistic regression analysis was used to explore the main effect, confounding, effect modification, and interactions between age, gender, and ApoE and RCAN1 genotypes. Linkage disequilibrium (LD) was estimated by SHEsis software.²⁴ The ESE finder was used for the ESE test (http://rulai.cshl.edu/tools/ESE/). For all of the tests, the criterion for statistical significance was set at p ≤ 0.05.

Results

This study identified a novel variation (CTCA/-, NT_01151211: g21561493-21561496del4), all of which were heterozygous deletions (het_del). The 3 bp (thymine- cytimidine-adenine) overlap of this novel variation with rs71324311 suggested their complete joint occurrence, which was considered the same polymorphism as rs71324311. The distributions of rs71324311, rs10550296 and rs8135540 were in Hardy-Weinberg equilibrium (p > 0.05). Table 2 shows both genotypic and allelic associations in the cases and controls. There were 4 subjects carrying the rs71324311 het_del genotype in NEC, but none in the AD cases. The frequency of the het_del genotype (4%) and the del allele (2%) in controls were significantly higher than that (0%, 0% respectively) in AD cases (Fisher’s exact test, p = 0.03; crude odds ratio [OR] = 0.96, 95% confidence interval [CI] = 0.92-0.99 vs. p = 0.03; crude OR = 0.98, 95% CI = 0.96-1.00).

No significant difference was found in the distributions of alleles or genotypes of rs10550296 and rs8135540 between AD cases and NECs (Table 2). However, we did find a trend towards a significant difference in the distributions of genotypes of rs10550296 between 2 groups (χ² = 1.93; p = 0.17; crude OR = 1.44, 95% CI = 0.85-2.41). Then, the logistic regression analysis was used to explore the main effect, confounding, effect modification, or interactions between age, gender, and ApoE and rs10550296 or rs8135540 genotypes. rs10550296 (by del allele), rs8135540 (by genotypes), ApoE (by ε4 allele) genotypes and gender were categorical variables, while age was included as a continuous variable (1-year intervals). The analysis revealed that the het_del carriers of rs10550296 had an adjusted OR of 2.11 (95% CI = 1.05-4.20; χ² = 4.42; p = 0.04) to have AD compared to homozygotes of the major allele. We further tested whether there were statistical interactions between rs10550296 genotype and age (categorised age ≤ 72 years and > 72 years), gender, and ApoE genotype, but no significant interaction was found (data not shown). The analysis also suggested rs8135540 had neither influence on the risk of developing AD (χ² = 0.59; p = 0.44; adjusted OR = 1.17, 95% CI = 0.78-1.75) nor the interaction between rs8135540 genotype and age, gender and ApoE genotypes (data not shown).

There was no variation on rs3831376 and rs78899361 among the 142 AD cases and 99 NECs. Because of these distributions, the case-control analysis was not pursued on these 2 polymorphisms.

The two markers (rs10550296 and rs8135540) were found not to be in LD with each other (D’ = 0.06, r² < 0.001, Fisher’s exact test, p = 0.86) in the control group (rs71324311 was not included because of low allelic frequency).

Discussion

RCAN1 was originally discovered as an oxidant stress- inducible gene and played a critical role in oxidative stress.^25,26 In fact, many studies indicated that oxidative stress in AD patient brains was a very early event and served as an initiator. In AD, this also included lipid peroxidation preceded amyloid plaque formation, increased antioxidative enzyme activities, and tau protein phosphorylation.^27-31 In addition, the importance of RCAN1 protein in locomotor activity and working memory was recognised by some studies.^32,33 In our studies, we found preliminary evidence of 2 RCAN1 polymorphisms associated with AD, of which rs71324311 het_del genotype suggested a protective factor with a slight OR of 0.96. The rs10550296 het_del genotype conferred a moderate AD risk with an OR of 2.11. Both of these 2 variants were located in the promoter region of RCAN1-4 and the putative regulatory region,^17,19 which might have a potential influence on the transcription of RCAN1-4. Ermak et al³⁴ reported that RCAN1 mRNA levels in AD postmortem brain samples was 2-fold higher than that in age-matched controls. We speculated that these polymorphisms played their roles in the risk of developing AD through influencing transcription or the splicing of RCAN1. However, another study⁸ found that RCAN1-1 (but not RCAN1-4) was overexpressed in AD postmortem brains. The possibilities are that the level of RCAN1-4 in the early stage of AD could not be detected in the postmortem brain samples, which might play a vital role in the oxidative stress in early AD, or the amount of RCAN1-4 in different cellular localisation could not be evaluated by means of western blotting. In addition, genetic linkage studies have provided evidence for both LOAD and familial AD susceptibility locus on this 21q region.^35,36 Thus, it is possible that the 2 tested polymorphisms are LD with a ‘real risk locus’ either in RCAN1 itself or in another gene nearby. However, the functional significance of these 2 polymorphisms remains unknown. Moreover, unravelling the mechanisms by which the het_del genotype of these 2 polymorphisms are associated with lower or higher risks for AD will depend on future functional studies. Interestingly, the frequency of rs71324311 het_del genotype (4%) was low (only 4 out of 99 NECs were heterozygous), and none of the AD cases carried the genotype. Further larger sample studies are needed to test whether this could be a marker for non-AD status. In addition, the Chi-square test only showed a trend towards a difference, while the logistic regression analysis found an adjusted OR of 2.11 for AD risk in rs10550296 het_del carriers. This implied that confounding factors such as age, gender and ApoEε4 allele should be considered while studying the role of rs10550296 in the risk of AD.

We found no statistically significant association between rs8135540 and AD, even though we adjusted for age, gender and the ApoEε4 allele. The rs8135540 is a tag SNP (A to C substitution). If a tag SNP was not associated with functional polymorphism or a ‘real risk locus’, it would not be easy to reveal the association. In our samples, the rs8135540 was not in significant LD with rs10550296. Our studies suggested that rs8135540 might not play a major role in AD, since the 38% frequency of the variant alleles in the AD cases were unexpectedly similar to the 37% frequency in NECs. In addition, we observed a higher frequency of rs8135540 C allele in our study than the 20% found in the HapMap project. This implied regional differences in Chinese populations, since our samples represented the southern Chinese Han population, while the HapMap Project recruited 45 unrelated subjects from Beijing.

A limitation to this study was that we used single direction sequence traces. For instance, it was hard to genotype rs8135540 if a deletion mutation happened upstream. Although the Mutation Surveyor reported an accuracy of 95% when conducting single direction analysis, rs8135540 could not be genotyped in 5 subjects and in a few subjects there were ambiguities due to confusing signals. The chance of a genotyping error for rs8135540 was much higher than that for other tested polymorphisms. Another limitation is related to the modest sample size. Although our sample size had the ability to detect statistically significant differences between rs71324311 and rs10550296 and AD, the low frequency of the minor alleles might have increased the risk for a false-positive result. Therefore a larger study sample is required to confirm these findings.

In conclusion, the present study is the first attempt for an association analysis of RCAN1 polymorphism with AD. Moreover, we found associations with 2 polymorphisms in our samples. Indeed, RCAN1 was considered to be pathophysiologically related to AD. Further studies evaluating these polymorphisms and other RCAN1 variants in large samples of AD patients in different ethnic population would be of interests and are needed to clarify the role of RCAN1 polymorphism in AD.

Acknowledgement

This work was supported by Guangzhou Medical Science and Technology Projects (Project No: 2008-YB-101).

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