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Association study in Alzheimer's disease of single nucleotide polymorphisms implicated with coffee consumption.


More than 90% of new therapeutics developed for Alzheimer's disease (AD) have been unsuccessful (1). The lack of an effective treatment contributed to increase the attention to life style and dietary interventions that could modify the etiology of the disease (2). Epidemiological studies have indicated a negative association between coffee consumption and AD, suggesting that caffeine may have neuroprotective effects against cognitive decline (2-5). This xanthine-derived substance, highly concentrated in coffee, is a stimulant to the central nervous system that may be beneficial against certain deficits associated with AD (3,6,7). Putative mechanisms for caffeine neuroprotection in AD include the facilitation of beta-amyloid clearance (7,8), and the upregulation of cholinergic neurotransmission (9) and/or signalling pathways related to neuronal plasticity and survival (10-12). Most of those effects are probably mediated the stimulation of adenosine receptors (13). However, evidence of beneficial effects of caffeine in human cognition is largely derived from epidemiological associations, with scarce direct evidence for the protective effects of coffee/caffeine in patients with AD14. Coffee consumption is determined by both environmental and genetic factors. Environmental factors related to coffee consumption include mainly age and sex, but it is also influenced by geographical location, religious preferences and socioeconomic conditions. Great effort has been made to identify genetic factors involved in coffee intake. Meta-analyses of genome-wide association indicated some common genetic variants that influence coffee consumption, localized in CYP1A1/CYP1A2, NRCAM and AHR genes15-17. AD is a multifactorial neurodegenerative disorder resulting from the interaction between multiple genetic and environmental factors18-20. Since there are genetic factors associated with both AD and coffee consumption, one cannot rule out the possibility that the negative association observed in epidemiological studies are due to a common genetic background, or even interactions among related gene products. In the present study, our aim was to evaluate genetic associations of single nucleotide polymorphisms (SNP) related to coffee consumption in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, comprising patients with AD or mild cognitive impairment (MCI) and healthy age-matched controls. Also to investigate possible interactions among the products of genes associated with AD and those located near the coffee consumption SNP.



Data used in the preparation of this article were obtained from the ADNI database ( The ADNI was launched in 2003 by the National Institute on Aging (NIA), the National Institute of Biomedical Imaging and Bioengineering (NIBIB), the Food and Drug Administration (FDA), private pharmaceutical companies and non-profit organizations, as a $60 million, 5-year public-private partnership. The primary goal of ADNI has been to test whether serial magnetic resonance imaging (MRI), positron emission tomography (PET), other biological markers, and clinical and neuropsychological assessment can be combined to measure the progression of MCI and early AD. Determination of sensitive and specific markers of very early AD progression is intended to aid researchers and clinicians to develop new treatments and monitor their effectiveness, as well as lessen the time and cost of clinical trials.

The Principal Investigator of this initiative is Michael W Weiner, MD, VA Medical Center and University of California--San Francisco. ADNI is the result of efforts of many co-investigators from a broad range of academic institutions and private corporations, and subjects have been recruited from over 50 sites across the U.S. and Canada. The initial goal of ADNI was to recruit 800 subjects but ADNI has been followed by ADNI-GO and ADNI-2. To date these three protocols have recruited over 1,500 adults, ages 55 to 90, to participate in the research, consisting of cognitively normal older individuals, people with early or late MCI, and people with early AD. The follow up duration of each group is specified in the protocols for ADNI-1, ADNI-2 and ADNI-GO. Subjects originally recruited for ADNI-1 and ADNI-GO had the option to be followed in ADNI-2. For up-to-date information, see

A total of 757 individuals were genotyped using the Illumina Human Genome 610 Quad BeadChips in the ADNI database downloaded in November 2011. We excluded individuals with less than 65 years of age, since they might correspond to the early onset forms of AD. The most recent clinical data of those subjects, at the time, revealed 198 healthy controls (CT), 193 classified as MCI and 318 diagnosed with AD. All those individuals had less than 10% missing genotypes. There was no information regarding coffee consumption in the ADNI database at the time of download.

Genotype data of SNPs that had been strongly associated with coffee consumption15-17 was retrieved from the ADNI database. From the chosen SNPs (rs12148488, rs2470893, rs2472297, rs2472304, rs382140, rs4410790, rs5751876, rs6495122, rs762551), only rs5751876 was not present in the ADNI database. The remaining SNPs passed our quality control with a call rate above 90% and minor allele frequency greater than 2%. rs16868941 was in Hardy Weinberg disequilibrium (p < 0.10; table 1) and was excluded from further analysis. Quality control analysis was performed with PLINK v1.07 and R software.

Firstly, we compared the genome location of the coffee consumption and AD SNPs from the top 10 associated SNPs in the repository of meta-analyses AlzGene (last updated 18th April 2011 - http:// (21).

We used the Search Tool for the Retrieval of Interacting Genes/ Proteins (STRING; (22) to investigate known protein interactions and pathway enrichment among the coffee consumption genes (up to 50 kb of distance, if the SNP is not inside a gene) and the top 10 AD associated genes from Alzgene (21). Significance for this analysis was set as p < 0.05 after FDR correction.

APOE alleles frequencies were retrieved from AlzGene metaanalysis and ADNI database. We used a chi-square test in LibreOffice Calc 3.5 (significance, p < 0.05) to compare the frequencies in control and AD individuals in those sets.

Association of each caffeine SNP among controls, MCI or AD was tested with Wald test for multinomial logistic regression controlled by age, gender, years of education and presence of the e4 allele of APOE. We also tested the model considering a dominant (MAF allele carrier vs non-carrier) or recessive (homozygous for the MAF allele vs other genotypes) pattern of inheritance for each MAF allele of each SNP. Significance was set as p < 0.0018, to correct for multiple comparisons with the conservative Bonferroni method. We also tested for association of controls, MCI or AD with caffeine SNP, age, gender, years of education and APOE genotype with a classification and regression tree (CART). These analyses were conducted with the aid of the R software version 2.15.2.


Demographic data is summarized in table 2. The MCI group had significantly fewer females than control (p = 0.010) or AD (p = 0.049) groups. AD subjects on average had fewer years of education than controls (p = 0.019). There was no difference in APOE alleles frequencies between ADNI and AlzGene (table 1, p > 0.90). We observed a strong association of the e4 allele of APOE and AD tested with a general linear model controlled by age, gender and education compared to healthy controls (p = 2.079 x [10.sup.-17]). Also, presence of APOE e4 in MCI was significantly different from both healthy controls (p = 0.0005) and AD patients (p = 4.908 x [10.sup.-7]). No association was observed between the coffee consumption SNPs and AD, for the three different scenarios tested (general, dominant MAF allele and recessive MAF allele models; table 3). CART analysis showed no association of coffee consumption SNPs and the three groups after cross validation. However, if we exclude MCI from the analysis, rs6495122 appears as a relevant factor to classify between controls and AD (Figure 1). Our analysis of protein interactions with STRING revealed no known interactions among coffee consumption associated proteins and the AD proteins. As can be seen in figure 2 the genes for AD and for coffee consumption had no significant interaction (with a confidence greater than 0.5 in STRING algorithm). Also, enrichment analysis of KEGG pathways showed only a significant (p = 0.038 after FDR correction) group of AD associated genes (PSEN1, PSEN2, APP and APOE).




Our results suggest that it is unlikely that the negative association between coffee consumption and AD prevalence is due to a common genetic background, at least between the regions compared here. We found no association between coffee consumption SNPs and AD, also there was no correlation between genetic regions and gene products for those two characteristics.

Firstly, none of the evaluated coffee consumption SNPs (15-17) is genetically near any of the most associated SNPs for AD21. This rule out the possibility of linkage disequilibrium between them. Also, there was no significant association between coffee consumption SNPs and AD in general, dominant MAF allele and recessive MAF allele models in the ADNI cohort. Also, rs6495122 appears as a relevant factor for classification in CART only after APOE genotype and age, two already known risk factors for AD19. Lastly, we found no known interaction between the gene products considered for coffee consumption and AD, which might have suggested an indirect association. Cornelis et al. mentioned in his meta-analysis that the coffee consumption SNPs did not showed before in large AD GWAS studies (17). This is the first attempt to investigate if there is a genetic correlation behind the evidence for a protective effect of coffee in AD. Larger cohorts with genetic and coffee consumption information might be required to further elucidate this question.

Experimental data suggests that caffeine derivates have neurobiological benefits on cognition and AD pathology. It probably results from the effects of these substances on signalling pathways related to AD pathophysiology and/or neuronal resilience.

Animal models suggested that caffeine administration was associated with reduction of both soluble and deposited amyloid-[beta] (A[beta]) in brain (7). The hydrophobic nature of caffeine allows its rapid absorption through all biological membranes, rendering it is rapidly absorbed into the bloodstream and through the blood-brain barrier (23). In vitro studies, showed that caffeine increases basal synaptic transmission, but does not affect LTP, at the same synapses (24). However, the concentrations of caffeine required to exert these effects, are several orders of magnitude higher than the plasmatic concentration attained by ingestion of moderate amounts of coffee (17-25-26). The only pharmacological mechanism known for caffeine in the low micromolar range is the antagonism of adenosine receptors, namely adenosine A1 and A2A receptors and maybe adenosine A3 receptors (13-16-27-28), leading to many downstream changes, including alterations in gene expression. The blockade of adenosine receptors confers neuroprotection against Ap6, but the underlying mechanisms by which caffeine reduces the relative risk for AD are not well elucidated. Adenosine A1 receptors in the cerebral cortex and hippocampus are primarily located on pre-synaptic terminals. Caffeine can block those receptors in cholinergic terminals which increases extracellular levels of acetylcholine, an important neurotransmitter for cognitive processing, dramatically decreased in the AD brain (9). Another plausible hypothesis which could explain the decreasing level of Ap is based on enhanced clearance of A[beta] from the brain due to upregulation of P-glycoprotein (P-gp) induced by caffeine8. P-gp is an adenosine triphosphate (ATP) dependent transporter protein, which acts as an efflux pump. This transporter is located mainly in luminal membrane of brain capillary endothelium comprising the blood-brain-barrier, and is responsible for extrusion of drugs and toxins from the brain, including A[beta] (29). An increasing number of studies further suggest that alterations in expression and functional activity of P-gp contribute to the accumulation of A[beta] in the brain, and lead to increased risk for developing AD (30). A third possible mechanism by which caffeine could ameliorate AD prognosis is by acting in neuronal plasticity and survival. Caffeine induced both elongation of existing dendritic spines and new spine formation in primary cultured hippocampal neurons (11). Also, long-term caffeine treatment in AD transgenic mice decreased pro-inflammatory cytokines such as TNF[alpha] and IFN[gamma] in the brain (10). Taken together with its beneficial effects on signal transduction (12), these results suggest an important role for caffeine in neuronal plasticity and survival. There are also other hypotheses about the mechanisms involved in neuroprotection by caffeine (31), however the exactly mechanisms are not completely understood (8).

There is no specific information of coffee consumption in the ADNI database. This is a limitation of the present analysis, since the evaluated SNPs might not correspond directly to coffee consumption in this sample. Also, we cannot rule out that the lack of significance might be due to a lack of power, because of the sample size. On the other hand, the ADNI sample had frequencies of APOE allele similar to the general population and we also replicated the strong association between APOE e4 allele and AD. These results indicate there were no sampling errors.

If we consider a less conservative threshold of p < 0.05, there are some observable differences in the MCI group compared to AD and/or healthy controls, rs4410790 (general and dominant models), rs6495122 (general and recessive models) and rs2472304 (recessive model). As mentioned, rs6495122 also appears as a relevant factor for the CART. Interestingly, the daily dose associated with cognitive protection is 3 to 5 cups of coffee. Depending on preparation and coffee type this dose corresponds to 210-1,100 mg of caffeine per day5. In comparison, the coffee consumption SNPs are associated with a change of less than 1 mg/day in a general model, but a maximum 44 mg per day difference between genotypes17. Given the effects magnitude, these coffee consumption genetic variants may not be a determinant factor in the estimated protective coffee dose. However, they might act as outcome modifiers as a result of the direct and indirect interaction with other genetic and environmental factors. Thus, it might be a good approach to introduce those SNPs as covariables in future studies of coffee and caffeine consumption, cognitive deficit and AD.


Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (National Institutes of Health Grant U01 AG024904). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Alzheimer's Association; Alzheimer's Drug Discovery Foundation; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; GE Healthcare; Innogenetics, N.V; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are Rev November 7, 2012 facilitated by the Foundation for the National Institutes of Health ( The grantee organization is the Northern California Institute for Research and Education, and the study is co ordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of California, Los Angeles. This research was also supported by NIH grants P30 AG010129 and K01 AG030514.

The Laboratory of Neuroscience (LIM-27) receives financial support from FAPESP, Fundacao de Amparo a Pesquisa do Estado de Sao Paulo, and ABADHS, Associacao Beneficente Alzira Denise Hertzog da Silva.

DOI: 10.1590/0101-60830000000050

Received; 4/16/2015--Accepted; 4/27/2015


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[1] Laboratory of Neuroscience (LIM-27), Department and institute of Psychiatry, Faculty of Medicine, University of Sao Paulo (ipq-PMUSFj, Sao Paulo, Brazil.

[2] Center for Interdisciplinary Research on Applied Neurosciences (NAPNAj, USP Sao Paulo, Brazil.

[3] Research Assistance Service, School of Nursing, USP Sao Paulo, Brazil.
Table 1. Coffee consumption SNPs--List of SNPs associated
with coffee consumption, nearby genes (up to 50 kb, if the
SNP is not inside a gene) and chromosome they are located--
Minor allele freguency (MAF) and p value for Hardy-Weinberg
eguilibrium (HWE; In bold p < 0,10) for each SNP in the
Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort is
also presentee

SNP           Genes    Chr   MAF (%)    HWE

rs12148488    ppcdc    15    G (49)    0,275
rs16868941    ncald     8    A (19)    0.063
rs2470893    CYP1A1,   15    A (28)    0,179
rs2472297    CYP1A1,   15    T (21)    0,286
rs2472304    CYP1A2    15    G (37)    0,140
rs382140     LAMB4,     7    A (17)    0,379
rs4410790      AHR      7    T (41)    0,940
rs5751876    AD0RA2A   22      --       --
rs6495122    CPLX3,    15    A (45)    0,825
rs762551     CYP1A2    15    C (27)    0,855

SNP            HWE      HWE     HWE
             Control    MCI     AD

rs12148488    1,000    0,885   0.033
rs16868941     --      1,000   0,848
rs2470893     0,706    0,469   0,144
rs2472297     0,622    0,684   0,877
rs2472304     0,140    0,522   0,286
rs382140      0,507    0,464   0,535
rs4410790     0,659    0.042   0,347
rs6495122     0,774    0.020   0.056
rs762551      0,733    0,698   1,000

Table 2. Summarized demographic data of the ADNI individuals
selected for this paper and AP0E*e4 freguencies for ADNI and
AlzGene cohort # p < 0,05 in Fisher exact test when compared
to either Healthy control or Alzheimer's Disease groups, * p
< 0,05 in AN0VA, with post TUKEY-HSD when compared to
Healthy control group, & p < 0,05 in Fisher exact test when
compared to Healthy control)

                Healthy control     Mild cognitive

Gender               45,9               33,2 #
(% female)

Age (mean      79,2 [+ or -] 5,5   78,9 [+ or -] 6,6
[+ or -] SD)

Age at
[+ or -] SD)

Years of       16,0 [+ or -] 2,8   15,6 [+ or -] 3,2
[+ or -] SD)

Handedness           91,9                94,3
(% right

Ethnic               91,4                90,0

AP0E*e4 (%)           15                 25 #

AlzGene               14                  --


Gender                42,1
(% female)

Age (mean       79,3 [+ or -] 5,8
[+ or -] SD)

Age at          75,0 [+ or -] 5,9
[+ or -] SD)

Years of       15,2 [+ or -] 3,1 *
[+ or -] SD)

Handedness            93,7
(% right

Ethnic                91,8

AP0E*e4 (%)            42&

AlzGene                38&

Table 3. Association of AD and Coffee consumption SNPs in
the AON! cohort--Association of AD and Coffee consumption
SNPs in the AON! cohort was evaluated with a multinomial
logistic regression model controlled by age, gender, years
of education and presence of the e4 allele of APOE followed
by Wald test--Dominant and Recessive columns, correspond to
p value of the model, when testing for dominant (MAF allele
carrier vs non-carrier) and recessive homozygous for the MAF
allele vs other genotypes) pattern of association. General
is the p value with no pattern of inheritance considered.
Significance was set as p < G.0G18, to correct for multiple
comparisons with the conservative Bonferroni method

SNP                                          General

rs12148488   C:     GG(23); GT(50); TT(27)    G.431
             MCI:   GG(26); GT(51); TT(23)
             AD:    GG(27); GT(44); TT(29)
rs247G893    C:     CC(57); CT(36); TT(7)     G.392
             MCI:   CC(51); CT(43); TT(6)
             AD:    CC(5G); CT(39); TT(11)
rs2472297    C:     CC(69); CT(28); TT(3)     G.315
             MCI:   CC(6G); CT(34); TT(6)
             AD:    CC(58); CT(36); TT(6)
rs24723G4    C:     CC(19); CT(43); TT(38)    G.2G9
             MCI:   CC(11); CT(47); TT(42)
             AD:    CC(17); CT(44); TT(39)
rs38214G     C:     CC(65); CT(3G); TT(5)     G.741
             MCI:   CC(68); CT(28); TT(4)
             AD:    CC(71); CT(26); TT(3)
rs441G79G    C:     AA(17); AG(47); GG(36)    G.G49
             MCI:   AA(17); AG(57); GG(26)
             AD:    AA(17); AG(45); GG(38)
rs6495122    C:     GG(31); GT(48); TT(21)    G.G24
             MCI:   GG(28); GT(58); TT(14)
             AD:    GG(32); GT(44); TT(24)
rs762551     C:     AA(49); AC(43); CC(8)     G.29G
             MCI:   AA(57); AC(38); CC(5)
             AD:    AA(49); AC(42); CC(9)

SNP                                          Dominant

                                               Vs       AD vs
                                             Control     MCI

rs12148488   C:     GG(23); GT(50); TT(27)     --
             MCI:   GG(26); GT(51); TT(23)    G.324      --
             AD:    GG(27); GT(44); TT(29)    G.849     G.2GG
rs247G893    C:     CC(57); CT(36); TT(7)      --
             MCI:   CC(51); CT(43); TT(6)     G.247      --
             AD:    CC(5G); CT(39); TT(11)    G.249     G.934
rs2472297    C:     CC(69); CT(28); TT(3)      --
             MCI:   CC(6G); CT(34); TT(6)     G.G85      --
             AD:    CC(58); CT(36); TT(6)     G.446     G.847
rs24723G4    C:     CC(19); CT(43); TT(38)     --
             MCI:   CC(11); CT(47); TT(42)    G.324      --
             AD:    CC(17); CT(44); TT(39)    G.482     G.722
rs38214G     C:     CC(65); CT(3G); TT(5)      --
             MCI:   CC(68); CT(28); TT(4)     G.559      --
             AD:    CC(71); CT(26); TT(3)     G.174     G.444
rs441G79G    C:     AA(17); AG(47); GG(36)     --
             MCI:   AA(17); AG(57); GG(26)    G.G11      --
             AD:    AA(17); AG(45); GG(38)    G.782     G.G12
rs6495122    C:     GG(31); GT(48); TT(21)     --
             MCI:   GG(28); GT(58); TT(14)    G.629      --
             AD:    GG(32); GT(44); TT(24)    G.594     G.28G
rs762551     C:     AA(49); AC(43); CC(8)      --
             MCI:   AA(57); AC(38); CC(5)     G.11G      --
             AD:    AA(49); AC(42); CC(9)     G.618     G.211

SNP                                          Recessive

                                               Vs       AD vs
                                             Control     MCI

rs12148488   C:     GG(23); GT(50); TT(27)     --
             MCI:   GG(26); GT(51); TT(23)    G.364      --
             AD:    GG(27); GT(44); TT(29)    G.218     G.779
rs247G893    C:     CC(57); CT(36); TT(7)      --
             MCI:   CC(51); CT(43); TT(6)     G.738      --
             AD:    CC(5G); CT(39); TT(11)    G.33G     G.166
rs2472297    C:     CC(69); CT(28); TT(3)      --
             MCI:   CC(6G); CT(34); TT(6)     G.459      --
             AD:    CC(58); CT(36); TT(6)     G.624     G.733
rs24723G4    C:     CC(19); CT(43); TT(38)     --
             MCI:   CC(11); CT(47); TT(42)    G.G35      --
             AD:    CC(17); CT(44); TT(39)    G.752     G.G52
rs38214G     C:     CC(65); CT(3G); TT(5)      --
             MCI:   CC(68); CT(28); TT(4)     G.953      --
             AD:    CC(71); CT(26); TT(3)     G.698     G.652
rs441G79G    C:     AA(17); AG(47); GG(36)     --
             MCI:   AA(17); AG(57); GG(26)    G.859      --
             AD:    AA(17); AG(45); GG(38)    G.758     G.9G1
rs6495122    C:     GG(31); GT(48); TT(21)     --
             MCI:   GG(28); GT(58); TT(14)    G.142      --
             AD:    GG(32); GT(44); TT(24)    G.3G6     G.G1G
rs762551     C:     AA(49); AC(43); CC(8)      --
             MCI:   AA(57); AC(38); CC(5)     G.386      --
             AD:    AA(49); AC(42); CC(9)     G.433     G.G99
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Title Annotation:texto en ingles
Author:Yamamoto, Victor Junji; De Paula, Vanessa De Jesus Rodrigues; Forlenza, Orestes Vicente; dos Santos,
Publication:Archives of Clinical Psychiatry
Date:May 1, 2015
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