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CR1, ABCA7, and APOE genes affect the features of cognitive impairment in Alzheimer's disease
Journal of the Neurological Sciences 339 (2014) 91–96
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CR1, ABCA7, and APOE genes affect the features of cognitive impairment in Alzheimer's disease Sun Ju Chung a,⁎, Mi-Jung Kim b, Young Jin Kim a, Juyeon Kim a, Sooyeoun You c, Eun Hye Jang a, Seong Yoon Kim d, Jae-Hong Lee a a
Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea Department of Neurology, Bobath Memorial Hospital, Seongnam, Republic of Korea Department of Neurology, Dongsan Medical Center, Keimyung University, Daegu, Republic of Korea d Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea b c
a r t i c l e
i n f o
Article history: Received 27 September 2013 Received in revised form 18 January 2014 Accepted 22 January 2014 Available online 31 January 2014 Keywords: Alzheimer's disease ABCA7 APOE CR1 Single nucleotide polymorphism Phenotype
a b s t r a c t Background: The genetic factors that determine the heterogeneity of cognitive impairment in Alzheimer's disease (AD) patients have been rarely reported. We aimed to investigate the association between top hits of genomewide association studies (GWAS) and specific cognitive domains in AD patients. Methods: We investigated 86 single nucleotide polymorphisms (SNPs) selected from 12 genes (ABCA7, APOE, BIN1, CD2AP, CD33, CLU, CR1, EPHA1, LRAT, MS4A6A, PCDH11X, and PICALM) based on results of the recent GWAS and genotyped in 211 AD cases. We also analyzed results of comprehensive neuropsychological evaluations in all cases. We performed multiple regression analyses. Results: There were four significant associations between genotypes and phenotypes of AD patients: CR1 SNP rs11803956 correlated with Mini-Mental State Examination (MMSE) score (β = 1.718, Pcorrected = 0.002); ABCA7 SNP rs3752232 correlated with Rey Complex Figure Test (RCFT) copy score (β = −6.861, Pcorrected = 0.013); APOE SNP rs2075650 correlated with the percentile of RCFT copy score (β = 14.005, Pcorrected = 0.021) and the percentile of total score in phonemic fluency (β = 11.052, Pcorrected = 0.035). Conclusion: Our results suggest that CR1, ABCA7, and APOE correlate with specific aspects of cognitive impairments in AD patients. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Alzheimer's disease (AD) is the most common neurodegenerative disorder, causing slowly progressive loss of cognitive functions, ultimately leading to dementia and death. AD is characterized by the presence of plaques of amyloid β (Aβ) peptides in the form of extracellular senile plaques and hyperphosphorylated tau protein in the form of intracellular neurofibrillary tangles [1]. Despite the core clinical features of progressive memory impairment, visuospatial decline, aphasia, and loss of executive function in AD, there is substantial clinical heterogeneity among patients with AD [2]. There are variations in cognitive, behavioral, and psychological symptoms [3]. The neurobiological basis for this clinical heterogeneity is uncertain but it may be related to the regional distribution of the pathogenic changes in AD. In turn, these variations in pathogenic changes in AD patients may be associated with genotype patterns in the AD-susceptibility loci.
Recently, several genome-wide association studies (GWAS) have identified the handful of genetic loci that are significantly associated with AD susceptibility [4–8]. The ε4 allele of APOE was the strongest genetic risk factor for late-onset AD in recent GWAS and additional novel susceptibility genes showed a significant association with the risk of AD [4,5]. However, the majority of published GWAS have been conducted to identify genetic variations responsible for AD susceptibility using case–control study design comparing individuals with disease to those without. This dichotomous clinical outcome obscures reality that AD cases present with a variety of cognitive and behavioral features. In the present study, we aimed to investigate the association of AD GWAS top hits with the specific domains of cognitive impairment in AD cases. 2. Methods 2.1. Study subjects
⁎ Corresponding author at: Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul 138-736, Republic of Korea. Tel.: +82 2 3010 3440; fax: +82 2 474 4691. E-mail addresses: [email protected], [email protected] (S.J. Chung). 0022-510X/$ – see front matter © 2014 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jns.2014.01.029
We included 211 AD cases from the previous replication study of GWAS top hits associated with AD [9]. All cases with AD (age at onset ≥60 years old) enrolled prospectively from the clinical practice
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Table 1 Demographic and clinical characteristics of Alzheimer's disease (AD) cases. Characteristics
AD cases (n = 211)
Total samples (n) Men (n) Age at study (years, mean ± SD) Disease duration (years, mean ± SD) Education (years, mean ± SD) APOE ε4 carrier (n) Neuropsychologic testa (maximal attainable score) MMSE (30) K-IADL (33) CDR (5) Geriatric Depression Scale (30) Forward digit span (9) Backward digit span (8) Boston Naming Test (60) Rey Complex Figure Test Copy score (36) Immediate recall (36) Delayed recall (36) Seoul Verbal Learning Test Immediate recall (36) Delayed recall (12) Controlled Oral Word Association Test Animal Supermarket Phonemic total
211 71 (33.6%) 71.6 ± 8.4 2.3 ± 4.0 8.6 ± 5.4 101 (47.9%)
Normative data of neuropsychologic testb
20.4 ± 4.7 19.7 ± 1.2 0.8 ± 0.4 14.0 ± 7.7 4.9 ± 1.2 3.0 ± 1.0 31.5 ± 11.9
27.7 ± 1.6
5.4 ± 1.5 3.8 ± 1.0 41.4 ± 7.5
25.2 ± 10.8 3.6 ± 3.7 2.7 ± 3.6
31.6 ± 2.4 14.2 ± 5.8 13.4 ± 4.9
11.0 ± 3.9 0.7 ± 1.3
17.0 ± 4.0 4.9 ± 2.5
9.3 ± 3.7 9.2 ± 4.3 14.8 ± 8.5
16.7 ± 3.6 17.2 ± 4.9 22.1 ± 7.1
Key: SD, standard deviation; MMSE, Mini-Mental State Examination; K-IADL, Korean Instrumental Activities of Daily Living; CDR, Clinical Dementia Rating. a The results of neuropsychological test are described as mean scores ± SD. b These normative data of neuropsychological tests were obtained from 14 cognitive normal individuals (ages, 70–74 years old) with 7–9 years of education duration.
of the Department of Neurology and Psychiatry of Asan Medical Center, Seoul, Korea, from March 1, 2010. The diagnosis of AD was made by an experienced neurologist (J.H.L.) and psychiatrist (S.Y.K.) using the National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer's Disease and Related Disorders Association criteria for probable AD [10]. All cases resided within South Korea and are all ethnic Koreans. All subjects provided demographics, family history, social history, history of environmental exposures, and medical history. All subjects were given physical and neurological examinations. For all subjects, genomic DNA was collected, extracted, and stored. The Institutional Review Board (IRB) of Asan Medical Center approved this study, and all subjects were required to provide informed consent as compatible with the IRB regulation. 2.2. Neuropsychological assessments All subjects underwent comprehensive neuropsychological tests using a standardized battery called the Seoul Neuropsychological Screening Battery (SNSB) [11]. This battery assesses five cognitive domains: attention, memory, language, visuospatial function, and frontal/executive function. The SNSB also includes the Mini-Mental State Examination (MMSE), Korean Instrumental Activities of Daily Living (K-IADL), and Clinical Dementia Rating (CDR). The functional decline was assessed by informant interview using the K-IADL scale. The additional information was based on the report of family members or caregivers when a patient visited our memory disorder clinic. Our analyses specifically focused on nine cognitive tests in the SNSB [11], including MMSE, K-IADL, CDR, digit span, Boston Naming Test, SVLT, RCFT, Controlled Oral Word Association Test (COWAT), and Geriatric Depression Scale (GDS). We also analyzed our data according to the five cognitive domains of SNSB (attention, memory, language, visuospatial function, and frontal/executive function) (Supplementary Table 1). Attention was assessed by digit span forward and digit span backward. Memory was assessed by orientation, Seoul Verbal Learning Test (SVLT) free/delayed recalls, SVLT recognition, Rey Complex Figure Test (RCFT) immediate/delayed recalls, and RCFT recognition.
Language and related functions were assessed by Boston Naming Test and calculation tests. Visuospatial function was assessed by RCFT copy. Frontal/executive function was assessed by motor impersistence, contrasting program, go–no-go test, fist-edge-palm task, Luria loop task, category word generation (animal), phonemic word generation, and Stroop test. We used raw scores of all neuropsychological tests and also interpreted data using percentile scores in the following neuropsychological tests: MMSE, digit span forward/backward, Boston Naming Test, RCFT, SVLT, and Stroop test. 2.3. Genotyping The genotyping methods were previously reported [9]. We selected 88 single nucleotide polymorphisms (SNPs) in the 12 genes: ABCA7, APOE, BIN1, CD2AP, CD33, CLU, CR1, EPHA1, LRAT, MS4A6A, PCDH11X, and PICALM genes. These 12 genes were selected based on results of the recent GWAS that reported AD-susceptibility loci [4–8,12–14], and the selected genes included AlzGene top 10 results (ABCA7, APOE, BIN1, CD2AP, CD33, CLU, CR1, MS4A6A, and PICALM genes) (http:// www.alzgene.org). We included a SNP that showed a significant association with AD in previous GWAS [4–8,12–14] and also had a minor allele frequency ≥0.05 on the basis of the HapMap JPT and CHB samples [15]. Additional tag SNPs (minor allele frequency ≥ 0.05) were selected for 12 selected genes using the HapMap JPT and CHB samples [15]. The LDSelect program was used to identify tag SNPs using a linkage disequilibrium (LD) r2 threshold of 0.8 and with minor allele frequencies ≥0.05. Two tag SNPs were selected for each LD bin when the number of SNPs in the bin was 10 or more. We genotyped 86 SNPs: 65 SNPs using SNPtype assay (Fluidigm, San Francisco, CA, USA), 15 SNPs using TaqMan assay (ABI, Foster City, CA, USA), and 6 SNPs using SNaPshot assay (ABI, Foster City, CA, USA). The selected 2 SNPs of PCDH11X gene (X chromosome) were not genotyped due to the design failure of PCR primer because approximately 200 bp sequences upstream of the 5′ end and downstream of the 3′ end of the selected two SNPs in the X chromosome showed more than 98% homology compared with sequences of the same regions in the Y chromosome. APOE genotypes (rs429358 and rs7412) were determined
Key: GWAS, genome-wide association studies; SE, standard error; MMSE, Mini-Mental State Examination; RCFT, Rey Complex Figure Test; COWAT, Controlled Oral Word Association Test; SNP, single nucleotide polymorphism. a The pairwise association between neuropsychological assessments and SNPs is listed in order of decreasing statistical significance as indicated by the Pcorrected values after adjustment for age, sex, education, and disease duration. These four pairing of neuropsychological assessments and SNPs remain significant after the correction for multiple comparisons. b NCBI build of 37.3 of the human genome. c β, regression coefficients. d Corrected P values after the correction for multiple comparisons.
0.002 0.013 0.021 0.035 0.391 1.772 3.740 3.052 T/C A/G A/G A/G CR1 ABCA7 APOE APOE rs11803956 rs3752232 rs2075650 rs2075650 MMSE score RCFT copy score Percentile of RCFT copy score Percentile of COWAT phonemic total score
207803021 1043748 45395619 45395619
1 19 19 19
Intron Nonsynonymous Intron Intron
0.48 0.08 0.23 0.23
1.718 −6.861 14.005 11.052
Pcorrected valued Allele (major/minor) Region Chromosome Gene Positionb SNP Neuropsychological assessments
Table 2 Association of common variants of GWAS top hits with the cognitive impairment of Alzheimer's disease cases (N = 211) in the order of statistical significance.a
Minor allele frequency
βc
SE
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by allele discrimination on a TaqMan 7900 Real Time PCR system. Analyses of genotyping data were carried out using Fluidigm SNP Genotyping Analysis software (version 3.1.1; Fluidigm) for SNPtype assay, SDS software package (version 2.4; Applied Biosystems) for TaqMan assay, and GeneMapper software (version 4.0; Applied Biosystems) for SNaPshot assay. Only variants with minor allele frequencies N0.01 and in Hardy–Weinberg equilibrium (P N 0.001) were included. 2.4. Statistical analysis We studied the association of each genetic variant with the SNSB scores of specific cognitive domains in the AD sample overall, using multiple regression analyses and a log additive genetic coding scheme [16]. We also performed similar analyses using dominant or recessive coding schemes. We further examined the association of the APOE alleles' status (ε2, ε3, and ε4) with the cognitive dysfunction in the AD samples overall. All analyses were adjusted for age at study, sex, education, and disease duration. For each genetic variant, we calculated a regression coefficient β and a two-tailed P value. We also performed similar analyses only using AD cases with age of onset ≥ 65 years old (N = 159) to investigate more homogenous clinical samples, eliminating any possible confounder. We estimated our statistical power to detect the association of common genetic variants with AD susceptibility and age at onset using Quanto version 1.2.4. We assumed a log additive allele effect and applied a multiple testing correction for 86 independent tests (α = 0.00058). For minor allele frequency of 0.4, our study had 80% power to detect OR as small as 1.56. For minor allele frequency of 0.05, our study had 80% power to detect OR as small as 2.23. We had similar power to detect small HRs for survival free of AD (data not shown). The statistical package SAS (version 9.1.3; SAS Institute Inc., Cary, NC, USA) was used for all analyses. In addition to the uncorrected P values, we also divided the uncorrected P values by the number of 86 genotyped SNPs to perform the multiple-comparison correction. 3. Results 3.1. Sample The demographic and clinical characteristics of 211 AD cases are described in Table 1. The mean disease duration of AD cases at the time of neuropsychological test was 2.3 ± 4.0 years. 3.2. Main effects of genetic variants on the cognitive impairment in AD There were four significant associations between genetic variants and scores of specific cognitive tests, and these associations remained significant after the correction for multiple comparisons (Table 2) (Fig. 1). The CR1 SNP rs11803956 was significantly associated with MMSE score (β = 1.72, Pcorrected = 0.002). The ABCA7 SNP rs3752232 showed a significant association with the copy score of RCFT (β = −6.86, Pcorrected = 0.013). The APOE SNP rs2075650 showed a significant association with the percentile of RCFT copy score (β = 14.01, Pcorrected = 0.021) and percentile of COWAT phonemic total score (β = 11.05, Pcorrected = 0.035). In analysis using only AD cases with age of onset ≥65 years old (N = 159), CR1 SNP rs11803956 was also significantly associated with MMSE scores (Supplementary Table 2). 3.3. Main effects of genetic variants on five cognitive domains in AD There were two significant associations between genetic variants and five types of cognitive domains (attention, memory, language, visuospatial function, and frontal/executive function). The CR1 SNP
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Fig. 1. Box plots for four significant associations between genetic variants and neuropsychological assessments in Alzheimer's disease cases (N = 211). (A) The CR1 SNP rs11803956 was significantly associated with Mini-Mental State Examination (MMSE) score (β = 1.72, Pcorrected = 0.002). (B) The ABCA7 SNP rs3752232 showed a significant association with the copy score of Rey Complex Figure Test (RCFT) (β = −6.86, Pcorrected = 0.013). (C and D) The APOE SNP rs2075650 showed a significant association with the percentile of RCFT copy score (β = 14.01, Pcorrected = 0.021) and percentile of Controlled Oral Word Association Test (COWAT) phonemic total score (β = 11.05, Pcorrected = 0.035). The horizontal lines in the box of each genotype denote the median value of scores. The top and bottom of the box indicate the interquartile range and the I bars indicate the minimum and maximum of scores.
Table 3 Association of APOE ε4 carrier status (one or two copies of ε4 allele) with the cognitive impairment of Alzheimer's disease cases (N = 211) in the order of statistical significance.a Neuropsychological assessments
βb
SE
Pcorrected valuec
Percentile of COWAT phonemic total score RCFT copy score COWAT phonemic total score Percentile of RCFT copy score Percentile of forward digit span Backward digit span
14.35 3.86 3.53 13.43 8.49 0.28
3.93 1.26 1.21 4.77 3.88 0.13
0.031 0.212 0.359 0.466 N0.99 N0.99
Key: SE, standard error; COWAT, Controlled Oral Word Association Test; RCFT, Rey Complex Figure Test. a The pairwise associations between APOE ε4 carrier status (one or two copies of ε4 allele) and neuropsychological assessments are listed in order of decreasing statistical significance as indicated by the Pcorrected values after adjustment for age, sex, education, and disease duration. The APOE ε4 carrier status and percentile of COWAT phonemic total score remain significant after the correction for multiple comparisons. Multiple regression analysis was used. b β, regression coefficients. c Corrected P values after the correction for multiple comparisons.
rs11803956 was significantly associated with attention (β = 0.69, Pcorrected = 0.015). The ABCA7 SNP rs3752232 was significantly associated with visuospatial function (β = −6.86, Pcorrected = 0.013). In analysis using only AD samples with age of onset ≥65 years old, only PICALM SNP rs10792821 showed a significant association with memory domain (β = 4.89, Pcorrected = 0.029). 3.4. Main effects of the APOE on the cognitive impairment in AD The APOE ε4 carriers (one or two copies of ε4 allele) showed a significant association with percentile of COWAT phonemic total score, which remained significant after the correction for multiple comparisons (β = 14.35, Pcorrected = 0.032) (Table 3). The APOE ε4 carriers showed nominally significant associations with other five cognitive tests, including RCFT copy score, COWAT phonemic total score, percentile of RCFT copy score, percentile of forward digit span, and backward digit span, but these associations did not remain significant after the correction for multiple comparisons (Table 3). The APOE
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ε4/ε4 homozygote carriers showed nominally significant association with the percentile of RCFT copy score, but did not remain significant after the correction for multiple comparisons. The APOE ε2 carriers (one or two copies of ε2 allele) were not associated with the specific cognitive tests in AD. 4. Discussion This study indicated that the CR1 SNP rs11803956, ABCA7 SNP rs3752232, and APOE SNP rs2075650 were significantly associated with the specific cognitive impairment of AD patients. The CR1 SNP rs11803956 showed the most significant association with MMSE scores in AD patients, including overall samples and those with age of onset ≥ 65 years old. These results suggest that individual genes or genetic variants may exert effects on specific cognitive domains in AD. The CR1 was highlighted as a major susceptibility locus for AD susceptibility in recent GWAS [4,8,17]. CR1 encodes for the main receptor of the complement C3b protein that is involved in Aβ clearance [18]. Complement activation leads to the formation of C3 convertases on the surface of the pathogen or protein undergoing complement attack. The cleavage of C3 by C3 convertases results in the formation of C3a and C3b fragments. C3b binds covalently to acceptor molecules and can mediate phagocytosis through CR1, which was proposed to participate in Aβ clearance [19–21]. In the present study, there was a significant association of the genotype in the CR1 SNP rs11803956 with the MMSE score, which is consistent with the findings of Chibnik et al., which showed that the risk allele within the CR1 locus (rs6656401) has a broad impact on cognition in an aging population and a greater burden of AD-related neuropathology [22]. More specifically, the previous study suggested that the CR1 locus (rs6656401) has an effect on global cognitive dysfunction by an enhanced burden of AD-related neuropathology, particularly amyloid plaques [22]. In the present study, CR1 SNP rs11803956 also showed association with the scores for attention domain. Although the enhanced accumulation of amyloid plaques by the risk allele within the CR1 locus may explain the genotype–phenotype association, the precise pathogenic mechanisms of these cognitive endophenotypes in AD affected by the CR1 need to be further investigated. The ABCA7 gene has been identified by recent GWAS as a susceptibility locus in AD [8,23]. ABCA7 encodes an ATP-binding cassette (ABC) transporter, which is highly expressed in the brain, particularly in the hippocampal CA1 neurons and microglia [24]. ABCA7 mediates the biogenesis of high-density lipoprotein with cellular lipid and helical apolipoprotein [25]. ABCA7 also regulates amyloid precursor protein processing and inhibits Aβ secretion in cultured cells overexpressing APP [26]. In the present study, ABCA7 SNP rs3752232 showed the association with the RCFT copy scores. RCFT measures non-amnestic cognitive functions including visual–perceptual abilities, planning, and working memory (executive functions), and it also measures visual memory [27]. There has been no previous report on the association of the ABCA7 and specific domains of cognitive impairment in AD. Further functional studies of the ABCA7 are needed to confirm the association between ABCA7 genotype patterns and these cognitive endophenotypes of AD. APOE is the major genetic risk factor for late-onset AD [28], and associated with increased Aβ plaque load in cognitively normal APOE ε4 carriers. However, once patients progress to clinically manifest AD, the effects of APOE ε4 are less clear [29]. In previous studies, the presence of APOE ε4 allele predisposes for the amnestic-predominantly hippocampal-driven variant of AD [30], whereas non-memory deficits such as visuospatial disabilities, language problems, and executive dysfunction have been prominent in APOE ε4 non-carriers [31,32]. In the present study, APOE SNP rs2075650 showed the association with the percentile of RCFT copy score and COWAT phonemic total score (Table 2), but showed no association with scores of cognitive tests reflecting the memory deficit in AD. Interestingly, it seems rather paradoxical that the APOE ε4 carriers showed positive associations with the better score of non-memory cognitive tests, such as percentile
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of COWAT phonemic total score (Table 3). Our results are consistent with the previous findings of reversed APOE ε4 dose effect for amyloid deposition in the frontal lobe [29]. Other previous studies reported that the absence of APOE ε4 in patients with early-onset AD is associated with accelerated shrinkage of the brain and faster cognitive decline [33,34]. Together with the present study findings, the APOE ε4 may not be the major genetic risk determinant for non-amnestic cognitive dysfunction in clinically manifesting AD. The growing recognition in recent years of AD variability reflects the increasing understanding of the heterogeneity of the distribution of AD pathology among individuals. Understanding of the molecular mechanisms behind AD variability merits further investigation that is needed to facilitate functional experimental studies for candidate genes and eventually allow for clinical trials targeting AD patients with specific cognitive impairment. In the present study, despite studying the recently identified GWAS top hits and comprehensive neuropsychological tests in AD cases, we found the significant associations between three genes (CR1, ABCA7, and APOE) and specific cognitive impairment, which suggests an evidence for the notion that AD phenotypic variations may be partly caused by genetic variations. This study has some potential limitations. First, the small sample size might limit the power of this study. Replication of our suggestive findings with independent samples may yield more robust evidence of genetic–phenotypic associations. Second, we did not stratify AD subjects according to clinically distinct profiles of AD, such as temporal (pure amnestic) variant, left (language) variant, right (visuoperceptive) variant, and frontal (executive) variant. We included prototypic AD cases with a late-onset AD dementia according to the clinical diagnostic criteria of AD. Future large-scale studies may investigate the genetic determinants for each distinct AD subtype. Third, biomarkers were not used for the diagnosis of AD in this study. Future studies need to use established biomarkers to provide considerable diagnostic benefit. Fourth, we applied a multiple-comparison correction only for the number of genetic variants, without consideration of the number of neuropsychological tests. Future studies need a larger sample size to counteract the problem of these multiple comparisons. Finally, cognitive impairment in AD is a complex multifactorial process, and therefore other risk factors, such as epigenetics and environmental factors, should also be considered in future studies. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.jns.2014.01.029. Conflict of interest All authors have no actual or potential conflicts of interest. Acknowledgments This study was supported by a grant of the Korea Healthcare Technology R & D Project, Ministry of Health & Welfare, Republic of Korea (A092042). References [1] Braak H, Braak E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol 1991;82:239–59. [2] Cummings JL. Cognitive and behavioral heterogeneity in Alzheimer's disease: seeking the neurobiological basis. Neurobiol Aging 2000;21:845–61. [3] Lam B, Masellis M, Freedman M, Stuss DT, Black SE. Clinical, imaging, and pathological heterogeneity of the Alzheimer's disease syndrome. Alzheimers Res Ther 2013;5:1. [4] Lambert JC, Heath S, Even G, Campion D, Sleegers K, Hiltunen M, et al. Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer's disease. Nat Genet 2009;41:1094–9. [5] Harold D, Abraham R, Hollingworth P, Sims R, Gerrish A, Hamshere ML, et al. Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease. Nat Genet 2009;41:1088–93. [6] Seshadri S, Fitzpatrick AL, Ikram MA, DeStefano AL, Gudnason V, Boada M, et al. Genome-wide analysis of genetic loci associated with Alzheimer disease. JAMA 2010;303:1832–40.
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Contents lists available at ScienceDirect
Journal of the Neurological Sciences journal homepage: www.elsevier.com/locate/jns
CR1, ABCA7, and APOE genes affect the features of cognitive impairment in Alzheimer's disease Sun Ju Chung a,⁎, Mi-Jung Kim b, Young Jin Kim a, Juyeon Kim a, Sooyeoun You c, Eun Hye Jang a, Seong Yoon Kim d, Jae-Hong Lee a a
Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea Department of Neurology, Bobath Memorial Hospital, Seongnam, Republic of Korea Department of Neurology, Dongsan Medical Center, Keimyung University, Daegu, Republic of Korea d Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea b c
a r t i c l e
i n f o
Article history: Received 27 September 2013 Received in revised form 18 January 2014 Accepted 22 January 2014 Available online 31 January 2014 Keywords: Alzheimer's disease ABCA7 APOE CR1 Single nucleotide polymorphism Phenotype
a b s t r a c t Background: The genetic factors that determine the heterogeneity of cognitive impairment in Alzheimer's disease (AD) patients have been rarely reported. We aimed to investigate the association between top hits of genomewide association studies (GWAS) and specific cognitive domains in AD patients. Methods: We investigated 86 single nucleotide polymorphisms (SNPs) selected from 12 genes (ABCA7, APOE, BIN1, CD2AP, CD33, CLU, CR1, EPHA1, LRAT, MS4A6A, PCDH11X, and PICALM) based on results of the recent GWAS and genotyped in 211 AD cases. We also analyzed results of comprehensive neuropsychological evaluations in all cases. We performed multiple regression analyses. Results: There were four significant associations between genotypes and phenotypes of AD patients: CR1 SNP rs11803956 correlated with Mini-Mental State Examination (MMSE) score (β = 1.718, Pcorrected = 0.002); ABCA7 SNP rs3752232 correlated with Rey Complex Figure Test (RCFT) copy score (β = −6.861, Pcorrected = 0.013); APOE SNP rs2075650 correlated with the percentile of RCFT copy score (β = 14.005, Pcorrected = 0.021) and the percentile of total score in phonemic fluency (β = 11.052, Pcorrected = 0.035). Conclusion: Our results suggest that CR1, ABCA7, and APOE correlate with specific aspects of cognitive impairments in AD patients. © 2014 Elsevier B.V. All rights reserved.
1. Introduction Alzheimer's disease (AD) is the most common neurodegenerative disorder, causing slowly progressive loss of cognitive functions, ultimately leading to dementia and death. AD is characterized by the presence of plaques of amyloid β (Aβ) peptides in the form of extracellular senile plaques and hyperphosphorylated tau protein in the form of intracellular neurofibrillary tangles [1]. Despite the core clinical features of progressive memory impairment, visuospatial decline, aphasia, and loss of executive function in AD, there is substantial clinical heterogeneity among patients with AD [2]. There are variations in cognitive, behavioral, and psychological symptoms [3]. The neurobiological basis for this clinical heterogeneity is uncertain but it may be related to the regional distribution of the pathogenic changes in AD. In turn, these variations in pathogenic changes in AD patients may be associated with genotype patterns in the AD-susceptibility loci.
Recently, several genome-wide association studies (GWAS) have identified the handful of genetic loci that are significantly associated with AD susceptibility [4–8]. The ε4 allele of APOE was the strongest genetic risk factor for late-onset AD in recent GWAS and additional novel susceptibility genes showed a significant association with the risk of AD [4,5]. However, the majority of published GWAS have been conducted to identify genetic variations responsible for AD susceptibility using case–control study design comparing individuals with disease to those without. This dichotomous clinical outcome obscures reality that AD cases present with a variety of cognitive and behavioral features. In the present study, we aimed to investigate the association of AD GWAS top hits with the specific domains of cognitive impairment in AD cases. 2. Methods 2.1. Study subjects
⁎ Corresponding author at: Department of Neurology, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul 138-736, Republic of Korea. Tel.: +82 2 3010 3440; fax: +82 2 474 4691. E-mail addresses: [email protected], [email protected] (S.J. Chung). 0022-510X/$ – see front matter © 2014 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jns.2014.01.029
We included 211 AD cases from the previous replication study of GWAS top hits associated with AD [9]. All cases with AD (age at onset ≥60 years old) enrolled prospectively from the clinical practice
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Table 1 Demographic and clinical characteristics of Alzheimer's disease (AD) cases. Characteristics
AD cases (n = 211)
Total samples (n) Men (n) Age at study (years, mean ± SD) Disease duration (years, mean ± SD) Education (years, mean ± SD) APOE ε4 carrier (n) Neuropsychologic testa (maximal attainable score) MMSE (30) K-IADL (33) CDR (5) Geriatric Depression Scale (30) Forward digit span (9) Backward digit span (8) Boston Naming Test (60) Rey Complex Figure Test Copy score (36) Immediate recall (36) Delayed recall (36) Seoul Verbal Learning Test Immediate recall (36) Delayed recall (12) Controlled Oral Word Association Test Animal Supermarket Phonemic total
211 71 (33.6%) 71.6 ± 8.4 2.3 ± 4.0 8.6 ± 5.4 101 (47.9%)
Normative data of neuropsychologic testb
20.4 ± 4.7 19.7 ± 1.2 0.8 ± 0.4 14.0 ± 7.7 4.9 ± 1.2 3.0 ± 1.0 31.5 ± 11.9
27.7 ± 1.6
5.4 ± 1.5 3.8 ± 1.0 41.4 ± 7.5
25.2 ± 10.8 3.6 ± 3.7 2.7 ± 3.6
31.6 ± 2.4 14.2 ± 5.8 13.4 ± 4.9
11.0 ± 3.9 0.7 ± 1.3
17.0 ± 4.0 4.9 ± 2.5
9.3 ± 3.7 9.2 ± 4.3 14.8 ± 8.5
16.7 ± 3.6 17.2 ± 4.9 22.1 ± 7.1
Key: SD, standard deviation; MMSE, Mini-Mental State Examination; K-IADL, Korean Instrumental Activities of Daily Living; CDR, Clinical Dementia Rating. a The results of neuropsychological test are described as mean scores ± SD. b These normative data of neuropsychological tests were obtained from 14 cognitive normal individuals (ages, 70–74 years old) with 7–9 years of education duration.
of the Department of Neurology and Psychiatry of Asan Medical Center, Seoul, Korea, from March 1, 2010. The diagnosis of AD was made by an experienced neurologist (J.H.L.) and psychiatrist (S.Y.K.) using the National Institute of Neurological and Communicative Disorders and Stroke–Alzheimer's Disease and Related Disorders Association criteria for probable AD [10]. All cases resided within South Korea and are all ethnic Koreans. All subjects provided demographics, family history, social history, history of environmental exposures, and medical history. All subjects were given physical and neurological examinations. For all subjects, genomic DNA was collected, extracted, and stored. The Institutional Review Board (IRB) of Asan Medical Center approved this study, and all subjects were required to provide informed consent as compatible with the IRB regulation. 2.2. Neuropsychological assessments All subjects underwent comprehensive neuropsychological tests using a standardized battery called the Seoul Neuropsychological Screening Battery (SNSB) [11]. This battery assesses five cognitive domains: attention, memory, language, visuospatial function, and frontal/executive function. The SNSB also includes the Mini-Mental State Examination (MMSE), Korean Instrumental Activities of Daily Living (K-IADL), and Clinical Dementia Rating (CDR). The functional decline was assessed by informant interview using the K-IADL scale. The additional information was based on the report of family members or caregivers when a patient visited our memory disorder clinic. Our analyses specifically focused on nine cognitive tests in the SNSB [11], including MMSE, K-IADL, CDR, digit span, Boston Naming Test, SVLT, RCFT, Controlled Oral Word Association Test (COWAT), and Geriatric Depression Scale (GDS). We also analyzed our data according to the five cognitive domains of SNSB (attention, memory, language, visuospatial function, and frontal/executive function) (Supplementary Table 1). Attention was assessed by digit span forward and digit span backward. Memory was assessed by orientation, Seoul Verbal Learning Test (SVLT) free/delayed recalls, SVLT recognition, Rey Complex Figure Test (RCFT) immediate/delayed recalls, and RCFT recognition.
Language and related functions were assessed by Boston Naming Test and calculation tests. Visuospatial function was assessed by RCFT copy. Frontal/executive function was assessed by motor impersistence, contrasting program, go–no-go test, fist-edge-palm task, Luria loop task, category word generation (animal), phonemic word generation, and Stroop test. We used raw scores of all neuropsychological tests and also interpreted data using percentile scores in the following neuropsychological tests: MMSE, digit span forward/backward, Boston Naming Test, RCFT, SVLT, and Stroop test. 2.3. Genotyping The genotyping methods were previously reported [9]. We selected 88 single nucleotide polymorphisms (SNPs) in the 12 genes: ABCA7, APOE, BIN1, CD2AP, CD33, CLU, CR1, EPHA1, LRAT, MS4A6A, PCDH11X, and PICALM genes. These 12 genes were selected based on results of the recent GWAS that reported AD-susceptibility loci [4–8,12–14], and the selected genes included AlzGene top 10 results (ABCA7, APOE, BIN1, CD2AP, CD33, CLU, CR1, MS4A6A, and PICALM genes) (http:// www.alzgene.org). We included a SNP that showed a significant association with AD in previous GWAS [4–8,12–14] and also had a minor allele frequency ≥0.05 on the basis of the HapMap JPT and CHB samples [15]. Additional tag SNPs (minor allele frequency ≥ 0.05) were selected for 12 selected genes using the HapMap JPT and CHB samples [15]. The LDSelect program was used to identify tag SNPs using a linkage disequilibrium (LD) r2 threshold of 0.8 and with minor allele frequencies ≥0.05. Two tag SNPs were selected for each LD bin when the number of SNPs in the bin was 10 or more. We genotyped 86 SNPs: 65 SNPs using SNPtype assay (Fluidigm, San Francisco, CA, USA), 15 SNPs using TaqMan assay (ABI, Foster City, CA, USA), and 6 SNPs using SNaPshot assay (ABI, Foster City, CA, USA). The selected 2 SNPs of PCDH11X gene (X chromosome) were not genotyped due to the design failure of PCR primer because approximately 200 bp sequences upstream of the 5′ end and downstream of the 3′ end of the selected two SNPs in the X chromosome showed more than 98% homology compared with sequences of the same regions in the Y chromosome. APOE genotypes (rs429358 and rs7412) were determined
Key: GWAS, genome-wide association studies; SE, standard error; MMSE, Mini-Mental State Examination; RCFT, Rey Complex Figure Test; COWAT, Controlled Oral Word Association Test; SNP, single nucleotide polymorphism. a The pairwise association between neuropsychological assessments and SNPs is listed in order of decreasing statistical significance as indicated by the Pcorrected values after adjustment for age, sex, education, and disease duration. These four pairing of neuropsychological assessments and SNPs remain significant after the correction for multiple comparisons. b NCBI build of 37.3 of the human genome. c β, regression coefficients. d Corrected P values after the correction for multiple comparisons.
0.002 0.013 0.021 0.035 0.391 1.772 3.740 3.052 T/C A/G A/G A/G CR1 ABCA7 APOE APOE rs11803956 rs3752232 rs2075650 rs2075650 MMSE score RCFT copy score Percentile of RCFT copy score Percentile of COWAT phonemic total score
207803021 1043748 45395619 45395619
1 19 19 19
Intron Nonsynonymous Intron Intron
0.48 0.08 0.23 0.23
1.718 −6.861 14.005 11.052
Pcorrected valued Allele (major/minor) Region Chromosome Gene Positionb SNP Neuropsychological assessments
Table 2 Association of common variants of GWAS top hits with the cognitive impairment of Alzheimer's disease cases (N = 211) in the order of statistical significance.a
Minor allele frequency
βc
SE
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by allele discrimination on a TaqMan 7900 Real Time PCR system. Analyses of genotyping data were carried out using Fluidigm SNP Genotyping Analysis software (version 3.1.1; Fluidigm) for SNPtype assay, SDS software package (version 2.4; Applied Biosystems) for TaqMan assay, and GeneMapper software (version 4.0; Applied Biosystems) for SNaPshot assay. Only variants with minor allele frequencies N0.01 and in Hardy–Weinberg equilibrium (P N 0.001) were included. 2.4. Statistical analysis We studied the association of each genetic variant with the SNSB scores of specific cognitive domains in the AD sample overall, using multiple regression analyses and a log additive genetic coding scheme [16]. We also performed similar analyses using dominant or recessive coding schemes. We further examined the association of the APOE alleles' status (ε2, ε3, and ε4) with the cognitive dysfunction in the AD samples overall. All analyses were adjusted for age at study, sex, education, and disease duration. For each genetic variant, we calculated a regression coefficient β and a two-tailed P value. We also performed similar analyses only using AD cases with age of onset ≥ 65 years old (N = 159) to investigate more homogenous clinical samples, eliminating any possible confounder. We estimated our statistical power to detect the association of common genetic variants with AD susceptibility and age at onset using Quanto version 1.2.4. We assumed a log additive allele effect and applied a multiple testing correction for 86 independent tests (α = 0.00058). For minor allele frequency of 0.4, our study had 80% power to detect OR as small as 1.56. For minor allele frequency of 0.05, our study had 80% power to detect OR as small as 2.23. We had similar power to detect small HRs for survival free of AD (data not shown). The statistical package SAS (version 9.1.3; SAS Institute Inc., Cary, NC, USA) was used for all analyses. In addition to the uncorrected P values, we also divided the uncorrected P values by the number of 86 genotyped SNPs to perform the multiple-comparison correction. 3. Results 3.1. Sample The demographic and clinical characteristics of 211 AD cases are described in Table 1. The mean disease duration of AD cases at the time of neuropsychological test was 2.3 ± 4.0 years. 3.2. Main effects of genetic variants on the cognitive impairment in AD There were four significant associations between genetic variants and scores of specific cognitive tests, and these associations remained significant after the correction for multiple comparisons (Table 2) (Fig. 1). The CR1 SNP rs11803956 was significantly associated with MMSE score (β = 1.72, Pcorrected = 0.002). The ABCA7 SNP rs3752232 showed a significant association with the copy score of RCFT (β = −6.86, Pcorrected = 0.013). The APOE SNP rs2075650 showed a significant association with the percentile of RCFT copy score (β = 14.01, Pcorrected = 0.021) and percentile of COWAT phonemic total score (β = 11.05, Pcorrected = 0.035). In analysis using only AD cases with age of onset ≥65 years old (N = 159), CR1 SNP rs11803956 was also significantly associated with MMSE scores (Supplementary Table 2). 3.3. Main effects of genetic variants on five cognitive domains in AD There were two significant associations between genetic variants and five types of cognitive domains (attention, memory, language, visuospatial function, and frontal/executive function). The CR1 SNP
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Fig. 1. Box plots for four significant associations between genetic variants and neuropsychological assessments in Alzheimer's disease cases (N = 211). (A) The CR1 SNP rs11803956 was significantly associated with Mini-Mental State Examination (MMSE) score (β = 1.72, Pcorrected = 0.002). (B) The ABCA7 SNP rs3752232 showed a significant association with the copy score of Rey Complex Figure Test (RCFT) (β = −6.86, Pcorrected = 0.013). (C and D) The APOE SNP rs2075650 showed a significant association with the percentile of RCFT copy score (β = 14.01, Pcorrected = 0.021) and percentile of Controlled Oral Word Association Test (COWAT) phonemic total score (β = 11.05, Pcorrected = 0.035). The horizontal lines in the box of each genotype denote the median value of scores. The top and bottom of the box indicate the interquartile range and the I bars indicate the minimum and maximum of scores.
Table 3 Association of APOE ε4 carrier status (one or two copies of ε4 allele) with the cognitive impairment of Alzheimer's disease cases (N = 211) in the order of statistical significance.a Neuropsychological assessments
βb
SE
Pcorrected valuec
Percentile of COWAT phonemic total score RCFT copy score COWAT phonemic total score Percentile of RCFT copy score Percentile of forward digit span Backward digit span
14.35 3.86 3.53 13.43 8.49 0.28
3.93 1.26 1.21 4.77 3.88 0.13
0.031 0.212 0.359 0.466 N0.99 N0.99
Key: SE, standard error; COWAT, Controlled Oral Word Association Test; RCFT, Rey Complex Figure Test. a The pairwise associations between APOE ε4 carrier status (one or two copies of ε4 allele) and neuropsychological assessments are listed in order of decreasing statistical significance as indicated by the Pcorrected values after adjustment for age, sex, education, and disease duration. The APOE ε4 carrier status and percentile of COWAT phonemic total score remain significant after the correction for multiple comparisons. Multiple regression analysis was used. b β, regression coefficients. c Corrected P values after the correction for multiple comparisons.
rs11803956 was significantly associated with attention (β = 0.69, Pcorrected = 0.015). The ABCA7 SNP rs3752232 was significantly associated with visuospatial function (β = −6.86, Pcorrected = 0.013). In analysis using only AD samples with age of onset ≥65 years old, only PICALM SNP rs10792821 showed a significant association with memory domain (β = 4.89, Pcorrected = 0.029). 3.4. Main effects of the APOE on the cognitive impairment in AD The APOE ε4 carriers (one or two copies of ε4 allele) showed a significant association with percentile of COWAT phonemic total score, which remained significant after the correction for multiple comparisons (β = 14.35, Pcorrected = 0.032) (Table 3). The APOE ε4 carriers showed nominally significant associations with other five cognitive tests, including RCFT copy score, COWAT phonemic total score, percentile of RCFT copy score, percentile of forward digit span, and backward digit span, but these associations did not remain significant after the correction for multiple comparisons (Table 3). The APOE
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ε4/ε4 homozygote carriers showed nominally significant association with the percentile of RCFT copy score, but did not remain significant after the correction for multiple comparisons. The APOE ε2 carriers (one or two copies of ε2 allele) were not associated with the specific cognitive tests in AD. 4. Discussion This study indicated that the CR1 SNP rs11803956, ABCA7 SNP rs3752232, and APOE SNP rs2075650 were significantly associated with the specific cognitive impairment of AD patients. The CR1 SNP rs11803956 showed the most significant association with MMSE scores in AD patients, including overall samples and those with age of onset ≥ 65 years old. These results suggest that individual genes or genetic variants may exert effects on specific cognitive domains in AD. The CR1 was highlighted as a major susceptibility locus for AD susceptibility in recent GWAS [4,8,17]. CR1 encodes for the main receptor of the complement C3b protein that is involved in Aβ clearance [18]. Complement activation leads to the formation of C3 convertases on the surface of the pathogen or protein undergoing complement attack. The cleavage of C3 by C3 convertases results in the formation of C3a and C3b fragments. C3b binds covalently to acceptor molecules and can mediate phagocytosis through CR1, which was proposed to participate in Aβ clearance [19–21]. In the present study, there was a significant association of the genotype in the CR1 SNP rs11803956 with the MMSE score, which is consistent with the findings of Chibnik et al., which showed that the risk allele within the CR1 locus (rs6656401) has a broad impact on cognition in an aging population and a greater burden of AD-related neuropathology [22]. More specifically, the previous study suggested that the CR1 locus (rs6656401) has an effect on global cognitive dysfunction by an enhanced burden of AD-related neuropathology, particularly amyloid plaques [22]. In the present study, CR1 SNP rs11803956 also showed association with the scores for attention domain. Although the enhanced accumulation of amyloid plaques by the risk allele within the CR1 locus may explain the genotype–phenotype association, the precise pathogenic mechanisms of these cognitive endophenotypes in AD affected by the CR1 need to be further investigated. The ABCA7 gene has been identified by recent GWAS as a susceptibility locus in AD [8,23]. ABCA7 encodes an ATP-binding cassette (ABC) transporter, which is highly expressed in the brain, particularly in the hippocampal CA1 neurons and microglia [24]. ABCA7 mediates the biogenesis of high-density lipoprotein with cellular lipid and helical apolipoprotein [25]. ABCA7 also regulates amyloid precursor protein processing and inhibits Aβ secretion in cultured cells overexpressing APP [26]. In the present study, ABCA7 SNP rs3752232 showed the association with the RCFT copy scores. RCFT measures non-amnestic cognitive functions including visual–perceptual abilities, planning, and working memory (executive functions), and it also measures visual memory [27]. There has been no previous report on the association of the ABCA7 and specific domains of cognitive impairment in AD. Further functional studies of the ABCA7 are needed to confirm the association between ABCA7 genotype patterns and these cognitive endophenotypes of AD. APOE is the major genetic risk factor for late-onset AD [28], and associated with increased Aβ plaque load in cognitively normal APOE ε4 carriers. However, once patients progress to clinically manifest AD, the effects of APOE ε4 are less clear [29]. In previous studies, the presence of APOE ε4 allele predisposes for the amnestic-predominantly hippocampal-driven variant of AD [30], whereas non-memory deficits such as visuospatial disabilities, language problems, and executive dysfunction have been prominent in APOE ε4 non-carriers [31,32]. In the present study, APOE SNP rs2075650 showed the association with the percentile of RCFT copy score and COWAT phonemic total score (Table 2), but showed no association with scores of cognitive tests reflecting the memory deficit in AD. Interestingly, it seems rather paradoxical that the APOE ε4 carriers showed positive associations with the better score of non-memory cognitive tests, such as percentile
95
of COWAT phonemic total score (Table 3). Our results are consistent with the previous findings of reversed APOE ε4 dose effect for amyloid deposition in the frontal lobe [29]. Other previous studies reported that the absence of APOE ε4 in patients with early-onset AD is associated with accelerated shrinkage of the brain and faster cognitive decline [33,34]. Together with the present study findings, the APOE ε4 may not be the major genetic risk determinant for non-amnestic cognitive dysfunction in clinically manifesting AD. The growing recognition in recent years of AD variability reflects the increasing understanding of the heterogeneity of the distribution of AD pathology among individuals. Understanding of the molecular mechanisms behind AD variability merits further investigation that is needed to facilitate functional experimental studies for candidate genes and eventually allow for clinical trials targeting AD patients with specific cognitive impairment. In the present study, despite studying the recently identified GWAS top hits and comprehensive neuropsychological tests in AD cases, we found the significant associations between three genes (CR1, ABCA7, and APOE) and specific cognitive impairment, which suggests an evidence for the notion that AD phenotypic variations may be partly caused by genetic variations. This study has some potential limitations. First, the small sample size might limit the power of this study. Replication of our suggestive findings with independent samples may yield more robust evidence of genetic–phenotypic associations. Second, we did not stratify AD subjects according to clinically distinct profiles of AD, such as temporal (pure amnestic) variant, left (language) variant, right (visuoperceptive) variant, and frontal (executive) variant. We included prototypic AD cases with a late-onset AD dementia according to the clinical diagnostic criteria of AD. Future large-scale studies may investigate the genetic determinants for each distinct AD subtype. Third, biomarkers were not used for the diagnosis of AD in this study. Future studies need to use established biomarkers to provide considerable diagnostic benefit. Fourth, we applied a multiple-comparison correction only for the number of genetic variants, without consideration of the number of neuropsychological tests. Future studies need a larger sample size to counteract the problem of these multiple comparisons. Finally, cognitive impairment in AD is a complex multifactorial process, and therefore other risk factors, such as epigenetics and environmental factors, should also be considered in future studies. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.jns.2014.01.029. Conflict of interest All authors have no actual or potential conflicts of interest. Acknowledgments This study was supported by a grant of the Korea Healthcare Technology R & D Project, Ministry of Health & Welfare, Republic of Korea (A092042). References [1] Braak H, Braak E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol 1991;82:239–59. [2] Cummings JL. Cognitive and behavioral heterogeneity in Alzheimer's disease: seeking the neurobiological basis. Neurobiol Aging 2000;21:845–61. [3] Lam B, Masellis M, Freedman M, Stuss DT, Black SE. Clinical, imaging, and pathological heterogeneity of the Alzheimer's disease syndrome. Alzheimers Res Ther 2013;5:1. [4] Lambert JC, Heath S, Even G, Campion D, Sleegers K, Hiltunen M, et al. Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer's disease. Nat Genet 2009;41:1094–9. [5] Harold D, Abraham R, Hollingworth P, Sims R, Gerrish A, Hamshere ML, et al. Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease. Nat Genet 2009;41:1088–93. [6] Seshadri S, Fitzpatrick AL, Ikram MA, DeStefano AL, Gudnason V, Boada M, et al. Genome-wide analysis of genetic loci associated with Alzheimer disease. JAMA 2010;303:1832–40.
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