Pharmacopsychiatry 2015; 48(03): 111-117
DOI: 10.1055/s-0035-1545300
Original Paper
© Georg Thieme Verlag KG Stuttgart · New York

Association of the Choline Acetyltransferase Gene with Responsiveness to Acetylcholinesterase Inhibitors in Alzheimer’s Disease

H. Yoon*
1   Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
,
W. Myung*
1   Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
,
S.-W. Lim
2   Center for Clinical Research, Samsung Biomedical Research Institute, Seoul, Korea
3   SAIHST, Sungkyunkwan University School of Medicine, Seoul, Korea
,
H. S. Kang
2   Center for Clinical Research, Samsung Biomedical Research Institute, Seoul, Korea
,
S. Kim
4   Biostatistics Team, Samsung Biomedical Research Institute, Seoul, Korea
,
H.-H. Won
2   Center for Clinical Research, Samsung Biomedical Research Institute, Seoul, Korea
,
B. J. Carroll
5   Pacific Behavioral Research Foundation, Carmel, CA, USA
,
D. K. Kim
1   Department of Psychiatry, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
› Author Affiliations
Further Information

Correspondence

D. K. Kim, MD, PhD
Department of Psychiatry
Samsung Medical Center
Sungkyunkwan University School of Medicine
81 Irwon-ro
Gangnam-gu
Seoul 135-710   
Korea   

Publication History

received 14 July 2014
revised 23 December 2014

accepted 19 January 2015

Publication Date:
02 March 2015 (online)

 

Abstract

Introduction: The response to acetylcholinesterase inhibitors (AChEIs) of Alzheimer’s disease (AD) patients varies depending on the genetic characteristics of the patient. We have examined the association of response to AChEIs and genetic polymorphisms in AD patients.

Methods: 158 patients with AD underwent treatment with AChEIs, and the therapeutic effect was assessed with the Korean version of the Mini Mental State Examination (K-MMSE). The association of 25 SNPs located in 3 genes (CHAT, CHT and ACHE) with changes in the K-MMSE score was analyzed.

Results: The response to AChEIs in AD patients was significantly associated with 2 SNPs on the intronic region of CHAT rs2177370 (uncorrected P=0.0025, FDR controlled P=0.026) and rs3793790 (uncorrected P=0.0024, FDR controlled P=0.026).

Conclusion: The results of our study confirmed again that genetic polymorphism of CHAT has an influence on drug response in AD.


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Introduction

Dementia is a progressive neurodegenerative disease with a rising prevalence and societal burden [1] [2]. Alzheimer’s disease (AD) is the most common form in dementia and it accounts for 60–70% of all cases [3].

AD is associated with widespread degeneration of cholinergic neurons, and acetylcholinesterase inhibitor (AChEI) drugs are approved for symptomatic treatment, with the aim of restoring the cholinergic deficit [4]. However, therapeutic response rates vary from 40–70% [5]. If the response to the drug initially selected is insufficient, a change of drugs can be considered. However, the recognition of non-response requires prolonged observation. Thus, an ability to predict response early in the course of AD is an important therapeutic objective.

One promising approach is pharmacogenomics [6]. Several preliminary pharmacogenomic studies [7] [8] have reported that the clinical response to donepezil is highest in carriers of the APOE epsilon4 allele, although a recent large study obtained a negative result [9].

The pathology of the brain cholinergic system is prominent in AD and AChEI drugs are widely used. Thus, the cholinergic system is a logical target for pharmacogenomic studies. There have been several studies on possible associations between genetic polymorphisms of cholinergic-related genes and the therapeutic effect of AChEIs [10] [11]. However, there are limitations as follows in those previous studies. First, the results are inconsistent. Second, the selection of SNPs was limited, so the entire candidate gene region was not covered. Moreover, ethnic heterogeneity was not explored in these studies. In the present study we have examined the polymorphic variations of the genes encoding 3 enzymes involved in the synthesis, transport, and metabolism of acetylcholine in the cholinergic system ([Fig. 1]) [11] [12]. Choline acetyltransferase (ChAT) encoded by the gene CHAT synthesizes acetylcholine, using choline and acetyl-CoA as substrates [11]. The choline transporter (ChT) catalyzes the uptake of choline from the extracellular space to the neuronal cytoplasm, and is encoded by SLC5A7 [12]. Acetylcholine esterase (AChE) is encoded by ACHE and acts to hydrolyze acetylcholine, thereby inactivating the neurotransmitter [11]. This study extends previous reports by the simultaneous coverage of 3 genes important for function of the brain cholinergic system. We also aimed to assess in our Asian (Korean) population the replicability of previous reports in Caucasians [10] [11]. The hypothesis of this exploratory study is that SNPs of genes involved in the synthesis and movement of acetylcholine may affect the response of AChEIs in AD.

Zoom Image
Fig. 1 The function of ChAT, AChE and ChT involved in synthesis and movement of acetylcholine in the cholinergic system. (from the KEGG database, http://www.genome.jp/kegg/). (Color figure available online only).

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Patients and Methods

Subjects

Subjects were 158 patients diagnosed with AD from the Clinical Trial Program in the Geropsychiatry Clinic at the Samsung Medical Center. All were of unrelated Korean ancestry. Patients were registered between November 2001 and January 2012. Subjects were eligible for this clinical trial only if they satisfied all following criteria: All patients were diagnosed as AD or probable AD according to the standards of the NINCDS-ADRDA (National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer’s Disease and Related Disorders Association) [13]; They had a score of 26 or less in the Korean version of the Mini-Mental State Examination (K-MMSE) [14]; They had a history of cognitive decline which was gradual in onset and progressive for more than 6 months; they had a reliable caregiver who helped them to take their medication, participate in the assessment, and provide ongoing information about them [13]. Patients were excluded if any of the following conditions was present: other neurodegenerative diseases except AD (i. e., Parkinson’s disease or Huntington’s disease), psychiatric disorder or severe behavioral disturbances requiring psychotropic medications, cerebral injuries induced by trauma, hypoxia, and/or ischemia, clinically active cerebrovascular disease, medical history of seizure disorder, and other physical conditions requiring acute treatments.

All subjects underwent brain magnetic resonance imaging (MRI), neurological evaluation, and routine laboratory tests prior to this clinical trial in order to screen for other possible causes of dementia. The Institutional Review Board (IRB) at Samsung Medical Center approved the protocol. Written informed consent was obtained from both caregiver and patient. The study is registered (NCT01198093) in ClinicalTrials.gov.


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Procedures

Subjects were assigned to receive monotherapy for 26 weeks with an acetylcholinesterase inhibitor (donepezil, galantamine or rivastigmine) as determined by a clinician. In this semi-naturalistic clinical trial, the choice of drug was based on the anticipated side effects in at-risk individuals and on current clinical practice guidelines. Donepezil was administered to 84 patients, galantamine to 52 patients and rivastigmine to 22 patients.

Doses were titrated into the usual range based on tolerability and side effects. All subjects were assessed in clinic visits after 1 week and 4 weeks on drug to adjust the dosage and evaluate adverse events. Psychotropic medications except acetylcholinesterase inhibitors were not allowed with one exception. Benzodiazepines could be used only as a short-term adjunctive for insomnia. If the subjects did not show any significant changes or serious adverse events, the interval for clinic visits was increased to 13 weeks. Experienced geriatric psychiatrists performed the assessment at each visit for clinical review of cognitive status, to examine physical and neurological status, and to review adverse events. Vital sign checks, physical examinations, laboratory tests including complete blood counts, blood chemistry profiles, vitamin B12/folate levels, syphilis serology, thyroid function tests, and ECG at baseline were carried out in all subjects.


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Selection of SNP markers and genotyping

These SNPs were genotyped using the MassARRAY system (Sequenom, Inc., San Diego, Calif). 25 SNPs were discovered and selected as candidate genes with the computer program Tagger [15] with criteria of r 2>0.65 and minor allele frequency>0.05 in combined Asian population (JPT/HCB). 21 for CHAT, 3 for SLC5A7 and one for ACHE were genotyped. The total missing genotype counts were 50 (total call rate: 98.7%), these genotyping data were not included in the SNP association analyses. All investigators and raters were blinded to the results of genotyping throughout the study. The laboratory worker who performed the genotyping was blind to clinical data of the subjects. The organization and selected SNP locations of CHAT gene are shown in [Fig. 2]. There were no significant differences in genotype distribution of the 25 SNPs according to drug choice.

Zoom Image
Fig. 2 CHAT organization and single-nucleotide polymorphism (SNP) locations (from National Center for Biotechnology Information Gene Database, http://www.ncbi.nlm.nih.gov/gene/). The horizontal line represents the genomic sequence and vertical bars represent exons. Plus signs and minus signs denote SNPs with significant association and SNPs with negative results, respectively.

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Measures

The response rate was assessed and compared at 26 weeks of treatment. Response was defined as no change (i. e., no deterioration) or improvement on the score of the Korean version of the Mini-Mental State Examination (K-MMSE) [16] [17]. Global severity of disease was assessed according to the Clinical Dementia Rating (CDR) [18]. These research assessments of cognitive outcome were performed by a single, trained rater.


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Data analysis

Continuous variables were presented as mean±standard deviation (SD) or as median and interquartile range. Categorical variables were summarized as frequencies and proportions. Wilcoxon rank-sum test or Student’s t test was performed to compare continuous variables between 2 groups according to the normality of the distribution. The association of categorical variables was determined based on the chi-squared test in all subjects.

We assessed the associations between each SNP and responsiveness by using the exact Cochran-Armitage test for trend (a genotypic trend model) [19]. Chi-squared testing was used to examine deviation from Hardy-Weinberg equilibrium [20]. The four-gamete rule by Haploview was used to check linkage disequilibrium (LD) structure [21]. Phasing haplotypes were conducted using PHASE 2.1.1 for each of the haplotype blocks individually [22]. The exact Cochran-Armitage test for a trend was used to examine the associations between a haplotype allele and response. For the significance of association of a SNP or haplotype allele, the false discovery rate (FDR) control was used to correct each P-value [23].

The associated SNPs and haplotype alleles were entered into a multiple logistic regression model to evaluate the impact of each genetic variable on response, adjusting for other variables. In this model, the genetic variable represented the minor allele count for a subject (0, 1 or 2) and the dependent variable represented the treatment outcome (1=response and 0=non-response). Results were considered as significant with a threshold of P<0.05. All statistical tests were performed using SAS 9.1 (SAS Institute, Inc., Cary, North Carolina).


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Results

Subject characteristics

Clinical and demographic characteristics are shown in [Table 1]. Mean age of the subjects was 72.66 (SD=8.31) years and most were in the early stage of Alzheimer’s disease. The rate of response to acetylcholinesterase inhibitors was 102 of 158 (64.6%). There was no significant difference between responders and non-responders with respect to gender, age, education level and baseline global severity (CDR). The rate of response was not affected by choice of drug (donepezil, galantamine and rivastigmine). However, there was a marginally significant difference between responders and non-responders in baseline K-MMSE score (P=0.04).

Table 1 Clinical and demographic characteristics (n=158).

Total

Responder (n=102)

Non-Responder (n=56)

Statistics

P

Gender, male (%)

64 (40.5%)

39 (38.2%)

25 (44.6%)

Χ2 1=0.62

0.43a.

Age (year, mean±SD)

72.66±8.31

73.47±8.18

71.18±8.41

t156=−1.67

0.10b.

Education (year, median and interquartile)

8 (6, 12)

6 (6, 12)

9 (6, 12)

Z=1.19

0.23c.

Drug (%)

 Donepezil

84 (53.2%)

57 (55.9%)

27 (48.2%)

Χ2 2=1.39

0.50a.

 Galantamine

52 (32.9%)

33 (32.4%)

19 (33.9%)

 Rivastigmine

22 (13.9%)

12 (11.8%)

10 (17.9%)

Baseline Dementia Severity

K-MMSE score (mean±SD)

19.11±4.73

18.55±4.70

20.13±4.64

t156=2.02

0.04 b.

CDR (%)

 0.5

54 (34.2%)

32 (31.4%)

22 (39.3%)

Χ2 2=1.30

0.52a.

 1

74 (46.8%)

51 (50.0%)

23 (41.1%)

 2

30 (19.0%)

19 (18.6%)

11 (19.6%)

SD, standard deviation; K-MMSE score, Korean Mini Mental State Examination score; CDR, Clinical Dementia Rating

a. Chi-squared test was used

b. Student’s t test was used

c. Wilcoxon rank-sum test was used


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SNP association analysis with responder of acetylcholinesterase inhibitors

The results of SNP association analysis are shown in [Table 2]. The observed genotype frequencies in each case fitted the ones expected according to the Hardy-Weinberg equilibrium, except one SNP, rs12246528 (P=2.80×10−24). However, we did not exclude this SNP, because this pharmacogenetic study was conducted in AD patients and did not have a normal control group [19] [24]. Moreover, 2 adjacent SNPs (rs2177370 and rs3793790) were significantly associated with response.

Table 2 SNP association analysis with responsiveness.

SNP by Group

Genotype Count

Location a.

Statistics for HWE b.

P c.

FDR Corrected P

CHAT (chromosome 10)

rs3810950

GG

GA

AA

 Responder

75

24

1

50824619

Χ 2 1=0.34

0.73

1

 Non-Responder

40

14

1

P=0.56

rs4838391

CC

TC

TT

 Responder

58

39

4

50832109

Χ 2 1=0.09

0.14

1

 Non-Responder

27

23

6

P=0.77

rs4838392

AA

GA

GG

 Responder

34

49

15

50834978

Χ 2 1=0.46

0.61

1

 Non-Responder

19

26

6

P=0.50

rs12246528

GA

GG

AA

 Responder

12

89

0

50835264

Χ 2 1=103.35

0.42

1

 Non-Responder

4

51

0

P=2.80×10-24

rs11101187

CC

CT

TT

 Responder

93

9

0

50837034

Χ 2 1=2.18

0.79

1

 Non-Responder

53

2

1

P=0.14

rs2177370

CC

TC

TT

 Responder

48

47

6

50838874

Χ 2 1=0.29

0.003

0.03

 Non-Responder

44

7

4

P=0.59

rs3793790

AA

GA

GG

 Responder

46

52

4

50840736

Χ 2 1=0.91

0.002

0.03

 Non-Responder

42

10

3

P=0.34

rs3793791

CC

TC

CC

 Responder

49

45

8

50841704

Χ 2 1=0.25

0.90

1

 Non-Responder

31

18

7

P=0.61

rs12266458

CC

TC

TT

 Responder

36

47

19

50847997

Χ 2 1=0.81

0.21

1

 Non-Responder

15

25

15

P=0.37

rs1917818

AA

CA

CC

 Responder

62

30

10

50849342

Χ 2 1=6.36

0.20

1

 Non-Responder

39

13

3

P=0.01

rs11101192

GG

GA

AA

 Responder

60

32

8

50854767

Χ 2 1=4.66

1

1

 Non-Responder

34

15

6

P=0.03

rs7094248

CC

GC

GG

 Responder

52

36

12

50855368

Χ 2 1=4.34

0.55

1

 Non-Responder

33

17

6

P=0.04

rs11101193

GG

GT

TT

 Responder

71

24

7

50856138

Χ 2 1=7.56

0.68

1

 Non-Responder

41

12

3

P=0.01

rs3793797

TT

CT

CC

 Responder

64

27

11

50857849

Χ 2 1=3.15

1

1

 Non-Responder

31

22

2

P=0.08

rs10776586

TT

TC

CC

 Responder

53

36

8

50858346

Χ 2 1=0.08

0.89

1

 Non-Responder

27

20

3

P=0.78

rs12264845

CC

CA

AA

 Responder

37

54

11

50863083

Χ 2 1=0.69

0.90

1

 Non-Responder

23

24

8

P=0.41

rs7076926

TT

CT

CC

 Responder

55

43

4

50863565

Χ 2 1=1.42

0.49

1

 Non-Responder

28

24

4

P=0.23

rs7094421

AA

GA

GG

 Responder

76

23

1

50863623

Χ 2 1=0.49

0.25

1

 Non-Responder

47

9

0

P=0.48

rs3793798

TT

AT

AA

 Responder

51

39

10

50871466

Χ 2 1=0.21

0.53

1

 Non-Responder

25

25

6

P=0.64

rs3793800

AA

AG

GG

 Responder

80

21

1

50871716

Χ 2 1=0.29

0.43

1

 Non-Responder

47

9

0

P=0.59

rs3793801

CC

TC

TT

 Responder

44

47

10

50872912

Χ 2 1=0.67

0.61

1

 Non-Responder

26

26

4

P=0.41

SLC5A7 (chromosome 2)

rs6542746

CC

TC

TT

 Responder

50

41

10

13279665

Χ 2 1=0.02

0.37

1

 Non-Responder

31

22

3

P=0.88

rs6720783

GG

GT

TT

 Responder

48

46

6

13297151

Χ 2 1=2.64

1

1

 Non-Responder

25

26

3

P=0.11

rs11685873

GG

AG

AA

 Responder

73

27

1

13285348

Χ 2 1=0.86

0.75

1

 Non-Responder

42

10

4

P=0.35

ACHE (chromosome 7)

rs6942609

GG

AG

AA

 Responder

40

50

11

38928323

Χ 2 1=1.06

0.70

1

 Non-Responder

24

27

5

P=0.30

SNP, single-nucleotide polymorphism; HWE, Hardy-Weinberg equilibrium; FDR, false discovery rate

a. Genomic position (NCBI Build 37)

b. Chi-squared test was used

c. Exact Cochran-Armitage test for trend was used

The rs2177370 in the intronic region of CHAT gene was significantly associated with response (uncorrected P=0.0025, FDR controlled P=0.026). The rs3793790 located in the same intron of the rs2177370 showed a significant association with responsiveness (uncorrected P=0.0024, FDR controlled P=0.026). These associations were preserved after controlling for gender, age, education year, drug and baseline K-MMSE score (for rs2177370, P=0.0065, odds ratio=2.45, 95% confidence interval=1.28–4.68; for rs3793790, P=0.0039, odds ratio=2.73, 95% confidence interval=1.38–5.38).


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Haplotype association analysis with responder of acetylcholinesterase inhibitors

We discovered 4 haplotype blocks in the CHAT gene ([Fig. 3]). Among the 13 haplotype allele, 2 alleles in block 2 that included rs2177370 had significant associations with response (for haplotype CC, uncorrected P=0.004, FDR controlled P=0.023; for haplotype CT, uncorrected P=0.003, FDR controlled P=0.023). These haplotypes were also associated with response after controlling for gender, age, education year, drug and baseline K-MMSE score (for haplotype CC, P=0.006, odds ratio=0.44, 95% confidence interval=0.24–0.79; for haplotype CT, P=0.006, odds ratio=2.47, 95% confidence interval=1.29–4.72). However, no haplotype blocks were found to be significantly associated with response in the SLC5A7 gene or the ACHE gene ([Table 3]).

Zoom Image
Fig. 3 Linkage disequilibrium (LD) and haplotype structure of CHAT. Pairwise SNP |D′| values (×100) of linkage (|D′|=1 not shown) are shown together with haplotype blocks. Black squares represent less than 4 distinct 2-marker haplotypes and white squares represent 4 distinct 2-marker haplotypes by the 4 gamete rule. Triangles surrounding the markers represent haplotype blocks identified using the default 4-gamete rule algorithm of Haploview 4.2.

Table 3 Haplotype association analysis with responsiveness in CHAT gene.

Haplotype by Group

Allele count

P a.

FDR Corrected P

0

1

2

Block 1 (rs4838391-rs4838392-rs12246528)

CGG

  Responder

44

46

12

0.70

0.83

  Non-Responder

23

30

3

CAG

  Responder

41

48

13

0.61

0.83

  Non-Responder

23

29

4

TAG

  Responder

58

40

4

0.14

0.45

  Non-Responder

27

23

6

Block 2 (rs11101187-rs2177370)

CC

  Responder

10

48

44

0.004

0.023

  Non-Responder

5

9

42

CT

  Responder

49

47

6

0.003

0.023

  Non-Responder

45

7

4

Block 3 (rs1917818-rs11101192-rs7094248-rs11101193-rs3793797)

CGCTT

  Responder

72

23

7

0.78

0.85

  Non-Responder

41

12

3

AGCGC

  Responder

64

28

10

1

1

  Non-Responder

31

23

2

AAGGT

  Responder

61

32

9

0.62

0.83

  Non-Responder

34

16

6

AGCGT

  Responder

60

38

4

0.07

0.32

  Non-Responder

25

26

5

Block 4 (rs12264845-rs7076926-rs7094421-rs3793798-rs3793800-rs3793801)

ATGTGC

  Responder

80

21

1

0.43

0.83

  Non-Responder

47

9

0

ACATAC

  Responder

55

43

4

0.49

0.83

  Non-Responder

28

24

4

CTAAAC

  Responder

51

41

10

0.62

0.83

  Non-Responder

25

25

6

CTATAT

  Responder

45

47

10

0.70

0.83

  Non-Responder

26

26

4

FDR, False discovery rate

a. Exact Cochran-Armitage test for trend was used


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Discussion

In this study we assessed 25 SNPs of 3 cholinergic system genes (CHAT, SLC5A7 and ACHE) for association with response to AChEI drugs in AD. We found that 2 SNPs in the intronic region of CHAT, rs2177370 and rs3793790 had a significant association with drug response. Haplotype association analysis which was additionally performed showed that block 2 including rs2177370 among 4 haplotype blocks of the CHAT gene had a significant association with drug response. However, the ACHE and SLC5A7 genes did not contain SNPs or haplotypes that were significantly associated with response. From this we conclude that the brain’s ability to synthesize ACh in AD is a critical factor for response to AChEIs, whereas transport and inactivation of the transmitter are less important factors.

The association of CHAT gene polymorphisms with response is consistent with a previous study [10], but the association with CHAT rs2177370 has not been previously described. In one previous study CHAT rs733722 had a significant association with AChEI drug response in AD patients [10]. In a second study, no association of CHAT rs2177369 with response was reported [11]. The CHAT gene has also been studied for association with AD onset [11], AD risk factor [25], and depression in AD [25] ([Fig. 2]). Although the significantly associated SNPs in our study differ from those in previous studies, these other results suggest convergent evidence for the importance of the CHAT gene as a significant gene marker that affects the response of AChEIs. Our results call attention to the role of ChAT in the synthesis of acetylcholine and to the mechanism of action of AChEIs in patients with AD.

Acetylcholinesterase inhibitors are drugs that inhibit the acetylcholinesterase enzyme from breaking down acetylcholine, thereby increasing both the level and duration of action of the neurotransmitter acetylcholine [26]. However, AChEI drugs depend for their efficacy on an adequate synthesis of ACh. When ACh synthesis already is impaired by degeneration of cholinergic neurons in AD, then a genetically determined relatively high synthesis capacity in the remaining neurons would be expected to favor response to AChEI drugs, and vice versa. We might infer that haplotype CC, with an odds ratio for response of 0.44, is associated with a relatively reduced rate of ACh synthesis, whereas haplotype CT, with an OR of 2.47, is associated with a relatively high rate of ACh synthesis. Additional studies are needed to establish the functional direction of influence that rs2177370 and rs3793790 exert on the activity of CHAT.

We did not confirm the report of Scacchi et al. that the ACHE rs2571598 had a significant association with drug response in AD patients treated with rivastigmine [11]. We found no association between the ACHE gene and response to AChEI drugs. The discrepancies between our study and Scacchi’s may due to differences of SNP selection, ethnicity and the genetic models adopted. In a previous study examining the CHAT gene, rs3810950 had a significant association with both depression [25] and disease progression [27] in AD. However, there was no association with drug response in this study. Because both comorbid depression and disease stage can influence cognitive function in AD, these factors will need to be considered in future pharmacogenetic studies.

We conducted this study in Korean patients. In our previous pharmacogenetic study of the serotonin transporter in patients with depression, conflicting results were reported according to ethnicity (Caucasian, Asian) [28]. Most of the existing genetic studies for drug response in AD patients have been limited to Caucasian populations. Thus, replication studies in different ethnic populations will be required. Our study is the first haplotype association study of response of AChEIs and found that haplotype blocks located on CHAT may affect response in both favorable and unfavorable directions. A possible limitation or a potential advantage in this study was the use of 3 members of the AChEI drug class. On the one hand we lack statistical power to examine SNP associations with response to individual drugs. On the other hand, by using all the common members of the AChEI class our results may be generalizable to the clinical setting.


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Author Contributions

The individual authors contributed as follows: Doh Kwan Kim, Woojae Myung, Shin-Won Lim and Hyeyeon Yoon were involved in study planning and the writing of the manuscript; Doh Kwan Kim conducted the clinical parts of the study. Hyo Shin Kang was involved in data acquisition, Seonwoo Kim, Woojae Myung, Hong-Hee Won and Hyeyeon Yoon performed the statistical analyses; Bernard J. Carroll edited the manuscript and assisted with interpretation of the data.


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Conflict of Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Acknowledgements

This study was supported by grants of the Korea Health 21 R&D Project, Ministry of Health, Welfare and Family Affairs, Korea (A050079 and A060618) and Eisai Korea.

* These individuals contributed equally to this article as co-first authors


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  • 5 Jann MW, Shirley KL, Small GW. Clinical pharmacokinetics and pharmacodynamics of cholinesterase inhibitors. Clin Pharmacokinet 2002; 41: 719-739
  • 6 Scott SA. Personalizing medicine with clinical pharmacogenetics. Genet Med 2011; 13: 987-995
  • 7 Bizzarro A, Marra C, Acciarri A et al Apolipoprotein E epsilon4 allele differentiates the clinical response to donepezil in Alzheimer’s disease. Dement Geriatr Cogn Disord 2005; 20: 254-261
  • 8 Choi SH, Kim SY, Na HR et al Effect of ApoE genotype on response to donepezil in patients with Alzheimer’s disease. Dement Geriatr Cogn Disord 2008; 25: 445-450
  • 9 Rigaud AS, Traykov L, Latour F et al Presence or absence of at least one epsilon 4 allele and gender are not predictive for the response to donepezil treatment in Alzheimer’s disease. Pharmacogenetics 2002; 12: 415-420
  • 10 Harold D, Macgregor S, Patterson CE et al A single nucleotide polymorphism in CHAT influences response to acetylcholinesterase inhibitors in Alzheimer’s disease. Pharmacogenet Genomics 2006; 16: 75-77
  • 11 Scacchi R, Gambina G, Moretto G et al Variability of AChE, BChE, and ChAT genes in the late-onset form of Alzheimer’s disease and relationships with response to treatment with Donepezil and Rivastigmine. Am J Med Genet B Neuropsychiatr Genet 2009; 150B: 502-507
  • 12 Brandon EP, Mellott T, Pizzo DP et al Choline transporter 1 maintains cholinergic function in choline acetyltransferase haploinsufficiency. J Neurosci 2004; 24: 5459-5466
  • 13 McKhann G, Drachman D, Folstein M et al 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 1984; 34: 939-944
  • 14 Han C, Jo SA, Jo I et al An adaptation of the Korean mini-mental state examination (K-MMSE) in elderly Koreans: demographic influence and population-based norms (the AGE study). Arch Gerontol Geriatr 2008; 47: 302-310
  • 15 de Bakker PI, Yelensky R, Pe’er I et al Efficiency and power in genetic association studies. Nat Genet 2005; 37: 1217-1223
  • 16 Kang YW, Na DL, Hahn S. A validity study on the Korean Mini-Mental State Examination in dementia patients. J Korean Neurol Assoc 1997; 15: 300-308
  • 17 Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975; 12: 189-198
  • 18 Morris JC. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology 1993; 43: 2412-2414
  • 19 Balding DJ. A tutorial on statistical methods for population association studies. Nat Rev Genet 2006; 7: 781-791
  • 20 Schaid DJ, Jacobsen SJ. Biased tests of association: comparisons of allele frequencies when departing from Hardy-Weinberg proportions. Am J Epidemiol 1999; 149: 706-711
  • 21 Barrett JC, Fry B, Maller J et al Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 2005; 21: 263-265
  • 22 Stephens M, Donnelly P. A comparison of bayesian methods for haplotype reconstruction from population genotype data. Am J Hum Genet 2003; 73: 1162-1169
  • 23 Storey JD, Tibshirani R. Statistical significance for genomewide studies. Proc Natl Acad Sci USA 2003; 100: 9440-9445
  • 24 Rodriguez S, Gaunt TR, Day IN. Hardy-Weinberg equilibrium testing of biological ascertainment for Mendelian randomization studies. Am J Epidemiol 2009; 169: 505-514
  • 25 Grunblatt E, Reif A, Jungwirth S et al Genetic variation in the choline O-acetyltransferase gene in depression and Alzheimer’s disease: the VITA and Milano studies. J Psychiatr Res 2011; 45: 1250-1256
  • 26 Anand P, Singh B. A review on cholinesterase inhibitors for Alzheimer’s disease. Arch Pharm Res 2013; 36: 375-399
  • 27 Lee JJ, Jo SA, Park JH et al Choline acetyltransferase 2384 G>a polymorphism and the risk of Alzheimer’s disease. Alzheimer Dis Assoc Disord 2012; 26: 81-87
  • 28 Myung W, Lim SW, Kim S et al Serotonin transporter genotype and function in relation to antidepressant response in Koreans. Psychopharmacology (Berl) 2013; 225: 283-290

Correspondence

D. K. Kim, MD, PhD
Department of Psychiatry
Samsung Medical Center
Sungkyunkwan University School of Medicine
81 Irwon-ro
Gangnam-gu
Seoul 135-710   
Korea   

  • References

  • 1 Kawas CH, Brookmeyer R. Aging and the public health effects of dementia. N Engl J Med 2001; 344: 1160-1161
  • 2 Ballard C, Gauthier S, Corbett A et al Alzheimer’s disease. Lancet 2011; 377: 1019-1031
  • 3 Hendrie HC. Epidemiology of dementia and Alzheimer’s disease. Am J Geriatr Psychiatry 1998; 6: S3-S18
  • 4 Ellis JM. Cholinesterase inhibitors in the treatment of dementia. J Am Osteopath Assoc 2005; 105: 145-158
  • 5 Jann MW, Shirley KL, Small GW. Clinical pharmacokinetics and pharmacodynamics of cholinesterase inhibitors. Clin Pharmacokinet 2002; 41: 719-739
  • 6 Scott SA. Personalizing medicine with clinical pharmacogenetics. Genet Med 2011; 13: 987-995
  • 7 Bizzarro A, Marra C, Acciarri A et al Apolipoprotein E epsilon4 allele differentiates the clinical response to donepezil in Alzheimer’s disease. Dement Geriatr Cogn Disord 2005; 20: 254-261
  • 8 Choi SH, Kim SY, Na HR et al Effect of ApoE genotype on response to donepezil in patients with Alzheimer’s disease. Dement Geriatr Cogn Disord 2008; 25: 445-450
  • 9 Rigaud AS, Traykov L, Latour F et al Presence or absence of at least one epsilon 4 allele and gender are not predictive for the response to donepezil treatment in Alzheimer’s disease. Pharmacogenetics 2002; 12: 415-420
  • 10 Harold D, Macgregor S, Patterson CE et al A single nucleotide polymorphism in CHAT influences response to acetylcholinesterase inhibitors in Alzheimer’s disease. Pharmacogenet Genomics 2006; 16: 75-77
  • 11 Scacchi R, Gambina G, Moretto G et al Variability of AChE, BChE, and ChAT genes in the late-onset form of Alzheimer’s disease and relationships with response to treatment with Donepezil and Rivastigmine. Am J Med Genet B Neuropsychiatr Genet 2009; 150B: 502-507
  • 12 Brandon EP, Mellott T, Pizzo DP et al Choline transporter 1 maintains cholinergic function in choline acetyltransferase haploinsufficiency. J Neurosci 2004; 24: 5459-5466
  • 13 McKhann G, Drachman D, Folstein M et al 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 1984; 34: 939-944
  • 14 Han C, Jo SA, Jo I et al An adaptation of the Korean mini-mental state examination (K-MMSE) in elderly Koreans: demographic influence and population-based norms (the AGE study). Arch Gerontol Geriatr 2008; 47: 302-310
  • 15 de Bakker PI, Yelensky R, Pe’er I et al Efficiency and power in genetic association studies. Nat Genet 2005; 37: 1217-1223
  • 16 Kang YW, Na DL, Hahn S. A validity study on the Korean Mini-Mental State Examination in dementia patients. J Korean Neurol Assoc 1997; 15: 300-308
  • 17 Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975; 12: 189-198
  • 18 Morris JC. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology 1993; 43: 2412-2414
  • 19 Balding DJ. A tutorial on statistical methods for population association studies. Nat Rev Genet 2006; 7: 781-791
  • 20 Schaid DJ, Jacobsen SJ. Biased tests of association: comparisons of allele frequencies when departing from Hardy-Weinberg proportions. Am J Epidemiol 1999; 149: 706-711
  • 21 Barrett JC, Fry B, Maller J et al Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 2005; 21: 263-265
  • 22 Stephens M, Donnelly P. A comparison of bayesian methods for haplotype reconstruction from population genotype data. Am J Hum Genet 2003; 73: 1162-1169
  • 23 Storey JD, Tibshirani R. Statistical significance for genomewide studies. Proc Natl Acad Sci USA 2003; 100: 9440-9445
  • 24 Rodriguez S, Gaunt TR, Day IN. Hardy-Weinberg equilibrium testing of biological ascertainment for Mendelian randomization studies. Am J Epidemiol 2009; 169: 505-514
  • 25 Grunblatt E, Reif A, Jungwirth S et al Genetic variation in the choline O-acetyltransferase gene in depression and Alzheimer’s disease: the VITA and Milano studies. J Psychiatr Res 2011; 45: 1250-1256
  • 26 Anand P, Singh B. A review on cholinesterase inhibitors for Alzheimer’s disease. Arch Pharm Res 2013; 36: 375-399
  • 27 Lee JJ, Jo SA, Park JH et al Choline acetyltransferase 2384 G>a polymorphism and the risk of Alzheimer’s disease. Alzheimer Dis Assoc Disord 2012; 26: 81-87
  • 28 Myung W, Lim SW, Kim S et al Serotonin transporter genotype and function in relation to antidepressant response in Koreans. Psychopharmacology (Berl) 2013; 225: 283-290

Zoom Image
Fig. 1 The function of ChAT, AChE and ChT involved in synthesis and movement of acetylcholine in the cholinergic system. (from the KEGG database, http://www.genome.jp/kegg/). (Color figure available online only).
Zoom Image
Fig. 2 CHAT organization and single-nucleotide polymorphism (SNP) locations (from National Center for Biotechnology Information Gene Database, http://www.ncbi.nlm.nih.gov/gene/). The horizontal line represents the genomic sequence and vertical bars represent exons. Plus signs and minus signs denote SNPs with significant association and SNPs with negative results, respectively.
Zoom Image
Fig. 3 Linkage disequilibrium (LD) and haplotype structure of CHAT. Pairwise SNP |D′| values (×100) of linkage (|D′|=1 not shown) are shown together with haplotype blocks. Black squares represent less than 4 distinct 2-marker haplotypes and white squares represent 4 distinct 2-marker haplotypes by the 4 gamete rule. Triangles surrounding the markers represent haplotype blocks identified using the default 4-gamete rule algorithm of Haploview 4.2.