Abstract
The molecular pathways underlying age-related memory changes remain unclear. There is a substantial genetic contribution to memory performance though life span. A recent study has implicated RbAp48, which mediates its effect on age-related memory decline by interacting with CBP (CREB1 Binding Protein) and influencing this histone acetylation pathway. To validate these findings, we tested whether genetic variants in RbAp48, CREB1 and CREBBP are associated with memory performance in three independent datasets consisting of 2674 cognitively healthy elderly. Genetic variant rs2526690 in the CREBBP gene was significantly associated with episodic memory performance (Pmeta = 3.7 × 10-4) in a multivariate model adjusted for age, sex and APOE status. Identifying genetic variants that modulate mechanisms of cognitive aging will allow identifying valid targets for therapeutic intervention.
Keywords: histone metabolism, meta-analysis, episodic memory performance
Introduction
Although there is substantial evidence that decline in cognitive performance occurs with normal ageing, the neurobiological basis of these age-related cognitive changes remains unclear. Cross-sectional and longitudinal studies showed that across cognitive domains, memory performance undergoes significant decline with increasing age (Small, et al., 1999). Heritability estimates from twin and family studies indicate that genetic variants strongly influence cognitive ability differences throughout the lifespan, including in old age (Harris and Deary, 2011). To date, however, most associations in or surrounding common variants are largely unreplicated, with the exception of the Apolipoprotein E (APOE) gene,(Wisdom, et al., 2011) and have little biological support.
In our increasingly ageing society, the population aged over 60 years is set to rise threefold to 2 billion by 2050 (Publications, 2001), consequently the burden of age-related cognitive impairment will increase. Characterizing genetic factors accounting for the age-related memory deficits will identify valid targets for therapeutic intervention to ameliorate cognitive impairment in the elderly.
Recently, gene expression analysis of human postmortem tissue harvested from the hippocampal formation identified a substantial age-related decline in the expression of the histone-binding protein RbAp48 gene (Pavlopoulos, et al., 2013). Inhibition of RbAp48 in young genetically engineered mice caused memory deficits similar to those associated with ageing, while increasing RbAp48 expression in old mice reversed age-related memory impairment.
Rbap48 gene is known to facilitate the action of the CREB1 gene's binding protein CREBBP, which is acetylates histones and affects age-related memory loss. In the present study, we investigated whether genetic variants in these histone acetylation pathway genes (RbAp48, CREBBP and CREB1) influence memory performance in cognitive healthy elderly.
Material and Methods
Study Cohorts
The National Institute of Aging Late Onset Alzheimer Disease (NIA-LOAD)
The NIA-LOAD Family Study was described elsewhere (Wijsman, et al., 2011). From the total cohort, 494 non-demented and unrelated healthy individuals were included in the present study. Episodic memory scores at the last cognitive assessment were computed as the average of the two standardized measures of Logical Memory IA and IIA (Wechsler, 1987). Genome-wide genotyping was performed using Illumina Human610Quadv1_B BeadChips (Illumina, San Diego, CA, USA) (Naj, et al., 2011).
The Alzheimer's Disease Genetic Consortium (ADGC)
A total of 1744 cognitively normal elderly from ADGC cohort consisting of 5 different independent NIA-funded Alzheimer's Disease Centers (Naj, et al., 2011) were used to test the association of histone acetylation pathway genes and episodic memory performance. Episodic memory scores at the last cognitive assessment were computed as the average of the two standardized measures of Logical Memory IA and IIA (Wechsler, 1987). Genome-wide genotyping was performed using various genotyping arrays (Saykin, et al., 2010). In order to test the possible association of the histone pathway genes and Alzheimer's Disease, we additionally used a sample of 11,840 demented subjects from 15 different independent ADGC sub-cohorts.
The Washington Heights Aging Project (WHICAP)
WHICAP is a population-based study of elderly individuals residing in New York (Mayeux, et al., 2001). The memory domain included the total and delayed recall of the Selective Reminding Test (Buschke and Fuld, 1974) and the recognition component of the Benton Visual Retention Test (Benton, 1955). The composite measure of memory was computed as the average of the standardized individual memory tests from the last cognitive assessment (Siedlecki, et al., 2008). Our analysis was restricted to the White subsample consisting of 436 cognitively healthy elderly. Genome-wide genotyping was done using the Omni Express platform by Illumina.
Statistical methods
Imputed genotype data
In order to significantly improve the SNP coverage of the genes analyzed based on the different GWAS platforms, we used the imputed genotype data available for each of the study cohorts.
Genome-wide imputation of allele dosages within each of the study cohorts was performed using the worldwide reference panel (v3, released March 2012) from 1000 Genomes for imputation of genotypes (build 37, http://www.1000genomes.org/announcements/updated-integrated-phase-1-release-calls-2012-03-16) and the IMPUTE2 (http://mathgen.stats.ox.ac.uk/impute/impute_v2.html) software applying strict pre-phasing, pre-imputation filtering, and variant position and strand alignment control. Only imputed SNP dosages with an imputation quality estimate of R2 ≥ 0.30 were included in the final SNP set for analysis.
Tagging SNPs
Using the tagger program implemented in Haploview 4.0 (Barrett, et al., 2005), tag-SNPs across the three genes were selected on the basis of linkage disequilibrium patterns observed in the Caucasian samples from the International HapMap Project (http://hapmap.ncbi.nlm.nih.gov/). The tag-SNPs were selected within a 50-Kb region flanking either side of the gene to capture all alleles with a correlation coefficient r2 ≥ 0.8.
Single-marker tests of association
Regression models adjusted for sex, age and education were conducted in the three different cohorts using PLINK (Purcell, et al., 2007). In each of the cohorts, interaction analysis between SNP markers significant in single-marker association tests and the APOE locus (coded as 0/1 based on the absence/presence of e4 allele) was performed using linear regression analyses which modeled the main effect of both loci, an interaction term of the SNP × APOE, and covariates (sex, age and education).
Statistical significance
Multiple testing adjustment of the obtained p-values was carried out using The Genetic Type I error calculator tool (Li, et al., 2012) to compute gene-specific thresholds of significance based on the number of SNPs used to tag (tagSNPs) each of the analyzed genes: 37 tagSNPs in CREB1 (p ≤ 0.001), 98 tagSNPs in CREBBP (p ≤ 5 ×10-4) and 40 tagSNPs in RBBP4 (p ≤ 0.001).
Meta-analysis
SNP association with episodic memory performance was obtained from the three independent cohorts and combined by meta-analysis using METAL (Willer, et al., 2010). Results obtained from SNP-APOE interaction models within each cohort were also meta-analyzed. Because of the known APOE-e4 association with impaired cognitive performance (Mayeux, et al., 2001) and the suggestive interaction between the most significant SNP and APOE locus (Pmeta=0.07), we stratified our analysis by APOE classifying the cohort's participants as carriers of one, two or no copies of APOE-e4 allele.
Results
The strongest genetic association with episodic memory performance was observed for intronic SNP rs2526690 in CREBBP, reaching statistical significance after adjusting for multiple testing (Pmeta = 3.7 × 10-4). When comparing the estimates of the beta coefficient of the SNP based on the APOE-E4 status, the SNP effect size appeared to be driven by the non-carriers of APOE-E4 allele (all subjects: β= 0.20, SE=0.07 ; APOE-E4 non-carriers β= 0.13, SE=0.08).
Although not reaching statistically significant thresholds, three additional SNPs in CREBBP (rsrs36099109, rs112455953 and rs112193373) showed nominal associations that were directionally consistent across cohorts among individuals lacking the APOE-E4 allele (Pmeta= 0.006, Pmeta=0.001 and Pmeta=-0.002 respectively).
Within CREB1 gene proximity (39-Kb upstream the gene), SNP rs72954151 was found nominally associated with episodic memory (Pmeta= 0.008) in the non-carriers of the APOE-E4 allele. SNP marker rs9660296 located 8-Kb upstream of RBBP4 gene appeared nominally associated with episodic memory performance (Pmeta= 0.040) among non-carriers of APOE-E4.
(Table 1 summarizes all SNP associations with nominal p-values under any of the three APOE status models considered for analysis).
Table 1. Meta-analysis of SNP associations with episodic memory performance in three independent cohorts of cognitively healthy elderly.
| Gene | SNP | bp | A1 | All subjects | E4 carriers | non-E4 carriers | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Effect | Pmeta | Dir. | Effect | Pmeta | Dir. | Effect | Pmeta | Dir. | ||||
| CREB1 | rs80140096 | 208353957 | G | 0.05 | 0.034 | -+----- | -0.02 | 0.770 | +++++-+ | 0.08 | 0.009 | -+----- |
| rs72954151 | 208355330 | G | 0.04 | 0.066 | ++-+--- | -0.04 | 0.439 | ++-++-- | 0.07 | 0.008 | -+----- | |
| rs2042484 | 208363062 | T | 0.00 | 0.829 | +-++--+ | 0.08 | 0.046 | +-+++-+ | -0.02 | 0.286 | -+----- | |
| rs74844716 | 208392215 | T | 0.04 | 0.188 | +-++-++ | -0.03 | 0.756 | +----++ | 0.09 | 0.040 | +-++-++ | |
| rs55834243 | 208443586 | C | 0.05 | 0.302 | -+-++-- | -0.10 | 0.256 | -++++-+ | 0.11 | 0.046 | -+--+-- | |
| CREBBP | rs79848897 | 3737375 | C | 0.04 | 0.151 | -----+- | -0.08 | 0.103 | +++-+++ | 0.08 | 0.011 | -----+- |
| rs2108430 | 3738078 | T | 0.02 | 0.751 | -++-+-- | -0.10 | 0.028 | -+-+--- | 0.06 | 0.063 | +++-+-+ | |
| rs72778151 | 3738286 | T | 0.04 | 0.157 | +++++++ | -0.10 | 0.114 | --+---- | 0.08 | 0.019 | +++++++ | |
| rs36099109 | 3742348 | T | 0.04 | 0.149 | +++++-- | -0.12 | 0.043 | ------- | 0.09 | 0.006 | +++++++ | |
| rs79213162 | 3744912 | C | 0.07 | 0.038 | +-++-++ | 0.06 | 0.303 | +-+++++ | 0.06 | 0.124 | +-++-++ | |
| rs75712687 | 3745273 | A | 0.04 | 0.212 | ++++++- | -0.10 | 0.106 | ------- | 0.09 | 0.021 | +++++++ | |
| rs75987714 | 3745883 | G | 0.07 | 0.113 | ---+-++ | -0.02 | 0.734 | +--++++ | 0.10 | 0.042 | ---+-++ | |
| rs6500550 | 3746241 | T | 0.01 | 0.931 | -+--+-- | -0.11 | 0.018 | ---++-- | 0.05 | 0.121 | +++-+-+ | |
| rs1639150 | 3747204 | C | 0.05 | 0.044 | ---++-- | 0.00 | 0.876 | -+++--- | 0.06 | 0.046 | ---++-- | |
| rs112455953 | 3748679 | T | 0.06 | 0.059 | +++++-+ | -0.12 | 0.063 | ------- | 0.11 | 0.001 | +++++++ | |
| rs112193373 | 3748761 | A | 0.05 | 0.107 | +++++-- | -0.13 | 0.044 | ------- | 0.11 | 0.002 | +++++++ | |
| rs39733 | 3773164 | T | 0.03 | 0.160 | ++++-++ | 0.12 | 0.015 | ++-++++ | 0.00 | 0.848 | -+++-+- | |
| rs7199513 | 3773490 | G | 0.06 | 0.019 | ------- | 0.01 | 0.020 | --+---- | 0.04 | 0.223 | ----+-+ | |
| rs130024 | 3834316 | T | 0.00 | 0.815 | --+-+-+ | 0.15 | 0.038 | +-+-+++ | -0.04 | 0.463 | --+---+ | |
| rs7198381 | 3864502 | A | 0.19 | 0.001 | +++++++ | 0.00 | 0.072 | +--++++ | 0.14 | 0.030 | +++++++ | |
| rs62039107 | 3890293 | G | 0.03 | 0.244 | -+--+-- | 0.12 | 0.019 | +------ | 0.00 | 0.950 | -+--+-- | |
| rs2526690 | 3917531 | G | 0.20 | 3.7 × 10-4 | ------- | 0.00 | 0.018 | -++---+ | 0.13 | 0.033 | ------- | |
| rs2386817 | 3938602 | A | 0.13 | 0.010 | +-+++++ | 0.00 | 0.046 | +--+++- | 0.07 | 0.173 | +-+-+++ | |
| rs58670576 | 3939457 | C | 0.15 | 0.018 | -----+- | 0.08 | 0.428 | -+---++ | 0.15 | 0.028 | ----++- | |
| rs72760840 | 3951740 | A | 0.04 | 0.119 | ++-++++ | 0.15 | 0.006 | +++++++ | 0.01 | 1.000 | -+-+-+- | |
| rs2080248 | 3956074 | G | 0.13 | 0.022 | -+-+--- | 0.00 | 0.553 | -+---++ | 0.00 | 0.032 | -+-+--- | |
| rs73503973 | 3959437 | C | 0.17 | 0.015 | -+-+--- | 0.00 | 0.451 | -+----- | 0.00 | 0.018 | -+----- | |
| rs117150760 | 3971681 | C | 0.09 | 0.121 | -+---+- | -0.08 | 0.618 | -+++-++ | 0.14 | 0.033 | -+----- | |
| RBBP4 | rs180743675 | 33080061 | A | 0.98 | 0.328 | +++++-+ | 0.44 | 0.016 | +++-+++ | -0.09 | 0.472 | +-+++-- |
| rs9660296 | 33108400 | T | 1.70 | 0.089 | +-++-++ | 0.05 | 0.779 | -+++--+ | 0.15 | 0.040 | +-+-+++ | |
| rs659867 | 33143896 | C | 1.94 | 0.053 | -+--+-- | 0.00 | 0.202 | +++-+-- | 0.17 | 0.088 | -+----- | |
A1 corresponds to the allele as reported as associated; highlighted in bold are meta-analysis p-values reaching significance after multiple testing adjustment; highlighted in cursive are nominally significant p-values.
Analysis of the episodic memory associated SNPs in a cohort of 11,840 demented subjects from the ADGC did not identify any significant association (Table 2), reinforcing the hypothesis that the association is not related to Alzheimer's disease, but age-related memory impairment.
Table 2.
Meta-analysis of the SNP associations with episodic memory performance in a sample of 11,840 demented individuals from the ADGC cohort.
| Gene | SNP | bp | A1 | Effect | Pmeta | Dir. |
|---|---|---|---|---|---|---|
| CREB1 | rs80140096 | 208353957 | G | 0.00 | 0.904 | -++--++--+-+?+- |
| rs72954151 | 208355330 | G | 0.01 | 0.671 | -++--+---++-++- | |
| rs2042484 | 208363062 | T | 0.00 | 0.856 | -++-+?---+++?+- | |
| rs74844716 | 208392215 | T | 0.06 | 0.106 | +--++?++-++??++ | |
| rs55834243 | 208443586 | C | 0.09 | 0.155 | -??-??--?-????? | |
| CREBBP | rs79848897 | 3737375 | C | 0.00 | 0.966 | +---+?---+-+++- |
| rs2108430 | 3738078 | T | 0.01 | 0.595 | -+++-?+-+-+---+ | |
| rs72778151 | 3738286 | T | 0.02 | 0.506 | --++-?+++-+-?-- | |
| rs36099109 | 3742348 | T | 0.02 | 0.409 | --++-?+++-++?-- | |
| rs79213162 | 3744912 | C | -0.07 | 0.149 | --++-?-+--+-?-- | |
| rs75712687 | 3745273 | A | 0.02 | 0.520 | --++-?+++-+-?-- | |
| rs75987714 | 3745883 | G | 0.03 | 0.585 | ++-?+?-???????? | |
| rs6500550 | 3746241 | T | 0.04 | 0.068 | -+++-?+-+-+-?++ | |
| rs1639150 | 3747204 | C | 0.01 | 0.729 | +---+?++-+???-- | |
| rs112455953 | 3748679 | T | 0.02 | 0.493 | --++-?+++-+-?-- | |
| rs112193373 | 3748761 | A | 0.02 | 0.493 | --++-?+++-+-?-- | |
| rs39733 | 3773164 | T | 0.11 | 0.081 | ??????????+??+? | |
| rs7199513 | 3773490 | G | 0.03 | 0.369 | --??+?-???????? | |
| rs130024 | 3834316 | T | 0.14 | 0.141 | ???+?????????+? | |
| rs62039107 | 3890293 | G | 0.01 | 0.782 | +-+++?-++--+?-- | |
| rs2526690 | 3917531 | G | -0.09 | 0.732 | ?????????????-? |
A1 corresponds to the allele as reported as associated; SNPs no imputed or with poor imputation quality were not considered in the meta-analysis.
Discussion
We examined whether genetic variants in members of the cell signaling pathway, RbAp48, CREB1 and CREBBP, are associated with episodic memory performance in cognitively healthy elderly subjects. We identified a SNP in CREBBP significantly associated with episodic memory in meta-analyses of three independent cohorts (Pmeta= 3.7 × 10-4). Cognitively healthy elderly carrying the G allele at SNP rs2526690 showed significantly better average episodic memory scores when compared with carriers of the A allele(β= 0.20, SE=0.07 versus β=-0.20, SE=0.07). The effect size of the identified SNP is relatively small, in agreement with previous findings supporting the hypothesis that genetic contributions to cognitive phenotypes most likely involve multiple quantitative trait loci and environmental factors. Several other genetic variants in RBBP4 and CREB1 also showed nominal associations (Pmeta≤ 0.05) with episodic memory performance. Consistent with the idea that this signaling pathway is defective in age-related memory loss, our results show that genetic variation in these genes might be associated with memory performance in cognitively healthy elderly subjects.
Acknowledgments
NIA-LOAD (U24-AG026395, R01-AG041797); ADGC (U01-AG032984, U01-AG016976, U24-AG21886); WHICAP (P01-AG007232, R01-AG037212).
The authors would like to thank the ADGC for access to the data.
References
- Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21(2):263–5. doi: 10.1093/bioinformatics/bth457. [DOI] [PubMed] [Google Scholar]
- Benton A. The Visual Retention Test. New York: Psychological Corporation; 1955. [Google Scholar]
- Buschke H, Fuld PA. Evaluating storage, retention, and retrieval in disordered memory and learning. Neurology. 1974;24(11):1019–25. doi: 10.1212/wnl.24.11.1019. [DOI] [PubMed] [Google Scholar]
- Harris SE, Deary IJ. The genetics of cognitive ability and cognitive ageing in healthy older people. Trends Cogn Sci. 2011;15(9):388–94. doi: 10.1016/j.tics.2011.07.004. [DOI] [PubMed] [Google Scholar]
- Li MX, Yeung JM, Cherny SS, Sham PC. Evaluating the effective numbers of independent tests and significant p-value thresholds in commercial genotyping arrays and public imputation reference datasets. Hum Genet. 2012;131(5):747–56. doi: 10.1007/s00439-011-1118-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mayeux R, Small SA, Tang M, Tycko B, Stern Y. Memory performance in healthy elderly without Alzheimer's disease: effects of time and apolipoprotein-E. Neurobiol Aging. 2001;22(4):683–9. doi: 10.1016/s0197-4580(01)00223-8. [DOI] [PubMed] [Google Scholar]
- Naj AC, Jun G, Beecham GW, Wang LS, Vardarajan BN, Buros J, Gallins PJ, Buxbaum JD, Jarvik GP, Crane PK, Larson EB, Bird TD, Boeve BF, Graff-Radford NR, De Jager PL, Evans D, Schneider JA, Carrasquillo MM, Ertekin-Taner N, Younkin SG, Cruchaga C, Kauwe JS, Nowotny P, Kramer P, Hardy J, Huentelman MJ, Myers AJ, Barmada MM, Demirci FY, Baldwin CT, Green RC, Rogaeva E, St George-Hyslop P, Arnold SE, Barber R, Beach T, Bigio EH, Bowen JD, Boxer A, Burke JR, Cairns NJ, Carlson CS, Carney RM, Carroll SL, Chui HC, Clark DG, Corneveaux J, Cotman CW, Cummings JL, DeCarli C, DeKosky ST, Diaz-Arrastia R, Dick M, Dickson DW, Ellis WG, Faber KM, Fallon KB, Farlow MR, Ferris S, Frosch MP, Galasko DR, Ganguli M, Gearing M, Geschwind DH, Ghetti B, Gilbert JR, Gilman S, Giordani B, Glass JD, Growdon JH, Hamilton RL, Harrell LE, Head E, Honig LS, Hulette CM, Hyman BT, Jicha GA, Jin LW, Johnson N, Karlawish J, Karydas A, Kaye JA, Kim R, Koo EH, Kowall NW, Lah JJ, Levey AI, Lieberman AP, Lopez OL, Mack WJ, Marson DC, Martiniuk F, Mash DC, Masliah E, McCormick WC, McCurry SM, McDavid AN, McKee AC, Mesulam M, Miller BL, Miller CA, Miller JW, Parisi JE, Perl DP, Peskind E, Petersen RC, Poon WW, Quinn JF, Rajbhandary RA, Raskind M, Reisberg B, Ringman JM, Roberson ED, Rosenberg RN, Sano M, Schneider LS, Seeley W, Shelanski ML, Slifer MA, Smith CD, Sonnen JA, Spina S, Stern RA, Tanzi RE, Trojanowski JQ, Troncoso JC, Van Deerlin VM, Vinters HV, Vonsattel JP, Weintraub S, Welsh-Bohmer KA, Williamson J, Woltjer RL, Cantwell LB, Dombroski BA, Beekly D, Lunetta KL, Martin ER, Kamboh MI, Saykin AJ, Reiman EM, Bennett DA, Morris JC, Montine TJ, Goate AM, Blacker D, Tsuang DW, Hakonarson H, Kukull WA, Foroud TM, Haines JL, Mayeux R, Pericak-Vance MA, Farrer LA, Schellenberg GD. Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer's disease. Nat Genet. 2011;43(5):436–41. doi: 10.1038/ng.801. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Pavlopoulos E, Jones S, Kosmidis S, Close M, Kim C, Kovalerchik O, Small SA, Kandel ER. Molecular mechanism for age-related memory loss: the histone-binding protein RbAp48. Sci Transl Med. 2013;5(200):200ra115. doi: 10.1126/scitranslmed.3006373. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Publications, U. World Population Prospects 2001 [Google Scholar]
- Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81(3):559–75. doi: 10.1086/519795. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Saykin AJ, Shen L, Foroud TM, Potkin SG, Swaminathan S, Kim S, Risacher SL, Nho K, Huentelman MJ, Craig DW, Thompson PM, Stein JL, Moore JH, Farrer LA, Green RC, Bertram L, Jack CR, Jr, Weiner MW. Alzheimer's Disease Neuroimaging Initiative biomarkers as quantitative phenotypes: Genetics core aims, progress, and plans. Alzheimers Dement. 2010;6(3):265–73. doi: 10.1016/j.jalz.2010.03.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Siedlecki KL, Honig LS, Stern Y. Exploring the structure of a neuropsychological battery across healthy elders and those with questionable dementia and Alzheimer's disease. Neuropsychology. 2008;22(3):400–11. doi: 10.1037/0894-4105.22.3.400. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Small SA, Stern Y, Tang M, Mayeux R. Selective decline in memory function among healthy elderly. Neurology. 1999;52(7):1392–6. doi: 10.1212/wnl.52.7.1392. [DOI] [PubMed] [Google Scholar]
- Wechsler D. The Wechsler Memory Scale-Revised. The Psychological Corporation; San Antonio, TX: 1987. [Google Scholar]
- Wijsman EM, Pankratz ND, Choi Y, Rothstein JH, Faber KM, Cheng R, Lee JH, Bird TD, Bennett DA, Diaz-Arrastia R, Goate AM, Farlow M, Ghetti B, Sweet RA, Foroud TM, Mayeux R. Genome-wide association of familial late-onset Alzheimer's disease replicates BIN1 and CLU and nominates CUGBP2 in interaction with APOE. PLoS Genet. 2011;7(2):e1001308. doi: 10.1371/journal.pgen.1001308. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics. 2010;26(17):2190–1. doi: 10.1093/bioinformatics/btq340. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wisdom NM, Callahan JL, Hawkins KA. The effects of apolipoprotein E on non-impaired cognitive functioning: a meta-analysis. Neurobiol Aging. 2011;32(1):63–74. doi: 10.1016/j.neurobiolaging.2009.02.003. [DOI] [PubMed] [Google Scholar]