Gene Expression and Methylation Analysis of ABCA7 in Patients with Alzheimer’s Disease

Abstract

Background/Objective: The aim of this study was to examine the blood gene expression and methylation of ATP-binding cassette sub-family A member 7 gene (ABCA7) as a biological marker of AD.

Methods: AD subjects (n = 50; 11 males, 77.7±6.05 years old) and age- and sex-matched healthy controls (n = 50) were recruited. A single nucleotide polymorphism in ABCA7 (rs3764650), methylation rates of CpG sites in the ABCA7 promoter region, and ABCA7 mRNA expression levels in peripheral blood were examined.

Results: The distribution of the rs3764650 polymorphism in AD subjects was not different from that of controls. Although the methylation rates of AD subjects were not significantly different from those of controls, the ABCA7 mRNA expression level in AD subjects was significantly higher than that in controls. Additionally, the ABCA7 mRNA expression level in AD subjects was significantly correlated with Mini-Mental State Examination recall, the Alzheimer’s Disease Assessment Scale total score, and the Clinical Dementia Rating score. We also found a significant correlation between the ABCA7 mRNA expression level and duration of illness.

Conclusion: The ABCA7 mRNA expression level in peripheral blood may be a marker for early stages of AD and disease progression regardless of rs3764650 and the methylation rate of its promoter.

Keywords

Alzheimer’s disease ATP-binding cassette sub-family A member 7 gene epigenetics mRNA single nucleotide polymorphism

INTRODUCTION

Alzheimer’s disease (AD) is a chronic neurodegenerative disease and is characterized by cognitive impairment including short-term memory loss and psychological symptoms such as depression, apathy, delusion, and other symptoms that are due to aggregation of amyloid-β (Aβ) plaques and neurofibrillary tangles. Because of reduced levels of acetylcholine in the brain of AD patients, acetylcholinesterase inhibitors (AChEIs) have been used as a first-line treatment for AD [1, 2]. However, the progression of AD cannot be stopped even if treatment with AChEIs continues. Therefore, a new, fundamental therapeutic strategy based on the original causes of AD is needed.

Several studies identified certain genotypes of apolipoprotein E (APOE) as a genetic risk factor for AD [3]. Large-scale genome-wide association studies with European AD subjects also identified various candidate genes for AD, including CR1, CLU, PICALM, BIN1, CD2AP, CD33, EPHA1, MS4A6A/MS4E4, and ABCA7 (ATP-binding cassette subfamily A member 7 gene) [4 –8]. ABCA7 encodes a member of the superfamily of ATP-binding cassette transporters expressed on both microglia and neurons in human brain. ABCA7 is implicated in transport of phospholipids and enhances phagocytosis by macrophages [9 –13]. Deletion of ABCA7 in amyloidogenic mice increases insoluble Aβ levels and thioflavine-S-positive plaques in the brain regardless of changes in amyloid-β protein precursor processing [12]. ABCA7 deficiency facilitates the processing of amyloid-β protein precursor and Aβ production by increasing the levels of β-secretase 1 in primary neurons and mouse brain [14]. Moreover, phagocytic clearance of Aβ oligomers in the hippocampus is reduced in ABCA7 deletion mice [15]. These results indicate that dysfunction of ABCA7 may cause accumulation of Aβ through impaired phagocytic function and increase the susceptibility to AD.

A single nucleotide polymorphism (SNP) in ABCA7, rs3764650, is associated with development of AD, and meta-analyses of all data in European studies conclude that ABCA7 rs3764650 is a susceptibility loci for AD (OR = 1.22) [4]. Although association studies investigating a link between rs3764650 and AD in Chinese (n = 633 and n = 1,224), Japanese (n = 1,735), Korean (n = 844), African American (n = 5,896), and Canadian (n = 1,104) individuals reported a weak or negligible association [16], a meta-analysis of these studies identified a significant association [17]. Moreover, ABCA7 expression is increased in AD brain, although the rs3764650 major allele T that decreases AD risk is associated with increased ABCA7 expression [18]. Additionally, methylation rates of three CpG sites in AD brain are associated with greater odds for AD diagnosis [19]. However, these sites are far (more than thousands of nucleotides) from the ABCA7 transcription start site (TSS), and the correlation between methylation rates of these CpG sites and ABCA7 expression is weak(r range, –0.2 to 0.2).

Although these results from mouse and human brain suggest that ABCA7 is related to AD pathogenesis, whether the gene polymorphism, expression, and methylation of ABCA7 are related to the development and psychological symptoms of AD has not been well investigated. In transgenic AD model mice, neutrophil deletion or inhibition of neutrophil trafficking via lymphocyte function-associated antigen-1 block reduces AD-like neuropathology and alleviates cognitive impairment [20]. This result demonstrates that neutrophils contribute to AD pathogenesis and cognitive impairment. Therefore, investigation of peripheral blood from AD patients may increase our understanding of AD pathogenesis and identify convenient clinical biomarkers [21 –24].

The aim of this study was to examine the blood gene expression and methylation of ATP-binding cassette sub-family A member 7 gene (ABCA7) as a biological marker of AD.

METHODS

Subjects

Demographic data for each group of participants are shown in Table 1. We enrolled 50 AD subjects [11 males and 39 females, mean age±standard deviation (SD) = 77.7±6.05 years] who visited Ehime University Hospital, Zaidan Niihama Hospital, or Kuroda Hospital, Ehime, Japan from August 2013 to January 2016. AD subjects were diagnosed with and classified as having probable AD dementia according to criteria by the National Institute on Aging and the Alzheimer’s Association [25]. Of the 50 participants, 25 AD subjects took donepezil, and the other 25 did not take AChEIs at the time of blood sampling. AD subjects were evaluated with the Mini-Mental State Examination (MMSE) to assess their cognitive function [26], Clinical Dementia Rating (CDR) as measured by family caregivers [27], and Neuropsychiatric Inventory (NPI) to assess their psychological symptoms [28]. Control participants were 50 elderly individuals (11 males and 39 females, mean age±SD = 76.3±6.02 years) without cognitive impairment, psychiatric signs, or a past history of mental disorders as determined by at least two certified psychiatrists based on clinical interviews. All participants were unrelated, of Japanese origin, and provided written informed consent forms that were approved by the institutional ethics committees of Ehime University Hospital, Zaidan Niihama Hospital, and Kuroda Hospital.

Blood sample collection, extraction of genomic DNA (gDNA), and synthesis of complementary DNA (cDNA)

gDNA was obtained from whole peripheral blood samples collected in potassium EDTA tubes and extracted using the QIAamp DNA Blood Mini Kit (Qiagen, Tokyo, Japan) according to the standard protocol. Total RNA was isolated from whole peripheral blood samples using PaxGene Blood RNA Systems tubes (BD, Tokyo, Japan) according to the standard protocol. The RNA concentration and purity were measured with a NanoDrop–1000 (Thermo Fisher Scientific, Yokohama, Japan), and the 260/280 ratio was between 1.8 and 2.0. RNA (1.0 μg) in a 40-μl total reaction volume per sample was used to synthesize cDNA by using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA, USA).

Genotyping analysis

SNP analysis of rs3764650 was performed with real-time quantitative PCR. A specific TaqMan probe for the SNP analysis was selected for NM_019112.3; assay ID: C__27478162_10 (TaqMan Assays, Applied Biosystems). The minor allele frequency of rs3764650 was based on the current International HapMap project database (http://hapmap.ncbi.nlm.nih.gov/index.html.en). The additional SNPs, rs429358 (NG_007084.2; assayID: C__3084793_20) and rs7412 (NG_007084.2; assay ID: C__904973_10, TaqMan Assays, Applied Biosystems), were used to determine the APOE isoform. PCR was performed with 1×TaqMan PCR Master Mix, 1×TaqMan SNP genotyping assay, 10 ng gDNA, and ultrapure water in a final reaction volume of 6 μl in each well of an optical plate. Allelic discrimination was determined using the StepOnePlus Real-Time PCR System and analyzed using StepOnePlussoftware.

Bisulfite conversion and pyrosequencing

The methylation status was analyzed in the region of ABCA7 that is considered the promotor region (Fig. 1). This region included five CpG sites that bind several transcription factors (TFs) investigated by JASPAR 2016 (http://jaspar.genereg.net). JASPAR is an open-access database storing curated, non-redundant TF binding profiles representing TF binding preferences as position frequency matrices for multiple species in six taxonomic groups [29, 30]. Therefore, we anticipated that methylation of these CpG sites will change the ABCA7 mRNA expression level. gDNA extracted from peripheral blood was treated with bisulfate using the EpiTect Plus DNA Bisulfite Kit (Qiagen, Hilden, Germany) and then amplified with PCR using the forward primer 5^′-GGGTTTTCCTCAAAATCAGGGTAGCCACTA-3^′ and the reverse primer 5^′-[Biotin]-GACTAAACTAGAGGGAGCCTGGCCAGC-3^′. PCR was performed in a 40-μl final volume per sample and included 2.5 μl gDNA, 0.2 μM each primer, AmpliTaq gold (Applied Biosystems), 10×PCR buffer with 15 mM MgCl₂, and 2 mM dNTPs. Cycling conditions were as follows: denaturation at 94°C for 10 min, followed by 45 cycles of 94°C for 30 s, 58°C for 30 s, and 72°C for 1 min, with a final extension of 10 min at 72°C. The PCR products were sequenced with PyroMark Q24 Advanced (Qiagen, Hilden, Germany) using the sequencing primer 5^′-CCTCCTGCCATCCTCTGCAGAAGC-3^′. Methylation rates at each CpG were quantified in duplicate using PyroMark Q24 Advanced Software (Qiagen, Tokyo, Japan).

Expression analysis

For mRNA expression analysis, quantitative reverse transcription-PCR was performed using the StepOnePlus Real-Time PCR System (Applied Biosystems). Specific TaqMan probes were Hs01105117_m1 for ABCA7 and Hs99999905_m1 for GAPDH. We used GAPDH as a housekeeping gene because previous studies including ours consistently identified GAPDH as a suitable housekeeping gene for peripheral blood gene expression analysis using the Paxgene blood RNA system [31 –34]. The final volume of the reactions was 10 μl and included the TaqMan Universal Master Mix (Applied Biosystems). The expression levels were determined in triplicate. The ΔΔCt method was used to determine relative expression levels using StepOne software (Applied Biosystems) [35]. To correct for observational errors, PCR was performed in all plates with gDNA from the same control subjects in this study.

Statistical analysis

Statistical analysis was performed using SPSS Statistics version 22.0 (IBM Corp., Tokyo, Japan) and EZR [36]. For analysis of the effects of SNPs, all participants were divided into two groups according to the presence or absence of the rs3764650G allele in ABCA7 as in a previous study [18] and the APOE risk variant ɛ4. Additionally, all participants were divided into three groups according to the presence of the G allele of rs3764650 in a “dose-dependent” manner; T/T (dose = 0), G/T (dose = 1), and G/G (dose = 2). Linear regression analysis was performed between the ABCA7 mRNA expression level and the age, sex, rs3764650 allele, methylation rate of each CpG site, and APOE allele for AD patients and controls. The age and duration of illness in AD patients were compared between treated and not treated with AChEIs by the Student’s t-test or Mann-Whitney U test after the Shapiro-Wilk test. The ABCA7 mRNA expression level, mean methylation rate of all CpG sites were compared between AD and control subjects or AD patients treated or not treated with AChEIs using the Mann-Whitney U test with the Shapiro-Wilk test after Bonferroni correction. Sex differences and the distributions of ABCA7 alleles were compared with the χ² test. The difference in mRNA expression levels between the two groups according to the rs3764650 allele was compared with the Mann-Whitney U test in AD and control subjects. Correlations among age, duration of illness, MMSE total score, NPI total score, rs3764650 allele, ABCA7 mRNA expression level, and methylation rate of each CpG site were analyzed with Spearman’s correlation test after Bonferroni correction. Relationships among CDR scores or MMSE recall, the ABCA7 mRNA expression level, and the methylation rate of each CpG site were analyzed with the Kruskal-Wallis test after the Steel-Dwass test.

RESULTS

Participant characteristics and genotyping

The demographic data of the participants are shown in Table 1. AD and control subjects did not differ in gender or age. Clinical characteristics and the results of psychological tests in AD subjects are also shown in Table 1. The distribution of the rs3764650 alleles is shown in Table 2. The ratio of each allele in AD was not significantly different from those in control subjects (number with the G allele, p = 0.548; presence or absence of the G allele, p = 0.603).

Methylation status

The sequence and the position of the five CpG sites are depicted in Fig. 1. Methylation rates at each CpG site are shown in Fig. 2. Methylation rates at all CpG sites were correlated with each other in AD subjects as well as control subjects (Fig. 1). Methylation rates at each CpG site were not associated with sex or age at blood sampling. The methylation rates at CpG3 were significantly correlated with the number of G alleles at rs3764650. We found no correlations between methylation rates at each CpG site and education, age of onset, or duration of illness, and no significant differences between methylation rates at each CpG site in AD subjects and those in control subjects (Table 3 and Fig. 2).

ABCA7 mRNA expression level

Linear regression analysis between the ABCA7 mRNA expression level and diagnosis, age, sex, rs3764650 allele, methylation rate of each CpG site, and APOE allele revealed that only diagnosis was significantly associated with the ABCA7 mRNA expression level (p = 0.003). The ABCA7 mRNA expression level was not associated with sex (AD subjects, p = 0.582; control subjects, p = 0.433) or age at blood sampling (AD, p = 0.349; control, p = 0.983). The ABCA7 mRNA expression level among the groups divided according to the rs3764650 allele was not different in AD or control subjects (AD, p = 0.727; control, p = 0.894). The ABCA7 mRNA expression level in AD subjects was significantly higher than that in controls (Fig. 3, p = 0.017). Moreover, we found a significant negative correlation between the duration of illness and the ABCA7 mRNA expression level (r = –0.433, p = 0.002, Table 4 and Fig. 4). Even excluding 5 AD patients used in the period beyond 10 years of illness, the ABCA7 mRNA expression level was negatively correlated with duration of illness (Spearman’s correlation coefficients, r = –0.391, p = 0.007). The ABCA7 mRNA expression level in AD subjects treated with AChEIs was significantly lower than in those not treated with AChEIs (Supplementary Figure 1, p = 0.013, ^*p≤0.025 after Bonferroni correction was considered significant), and the duration of illness in AD subjects treated with AChEIs was longer than in those not treated with AChEIs (p = 0.015).

Relationships among the ABCA7 mRNA expression level, methylation rate, rs3764650 allele, and scores on the MMSE, CDR, and NPI

Correlations between the ABCA7 mRNA expression level and each parameter including psychological tests in AD subjects are shown in Table 4. The ABCA7 mRNA expression level was significantly associated with the ADAS total score and CDR score (ADAS total score, p = 0.005; CDR score, Kruskal-Wallis test, p = 0.032, Steel-Dwass, score 0.5 : 2 points, p = 0.01, Table 4 and Fig. 5, Supplementary Figure 2). Although the ABCA7 mRNA expression level was not correlated with the MMSE or NPI score, the recall score in the MMSE subscale was significantly associated with the ABCA7 mRNA expression level (Kruskal-Wallis test, p = 0.0068, Steel-Dwass, score 0 : 2 points, p = 0.049, Table 4 and Supplementary Figure 3). Other than CpG3, methylation rates in AD subjects were not correlated with the ABCA7 mRNA expression level, rs3764650, MMSE total score, CDR score, or NPI total score (Table 3). We found no allele effects of rs3764650 on cognition assessed with MMSE, ADAS, or CDR (data not shown).

DISCUSSION

Our study revealed three major findings. First, the frequencies of the rs3764650 alleles in AD subjects were not different from those in control subjects in our study, although this SNP was significantly associated with AD in a genome-wide association study [4]. Another study using AD brains reported that the rs3764650 T allele is associated with increased ABCA7 expression and decreased AD risk [18]. Although a meta-analysis including Japanese individuals identified a significant association between AD and rs3764650 [17], a study with only Japanese patients reported a negligible association [16]. However, we performed power calculations with Fisher’s exact test using EZR, and the sample size was not sufficient to detect differences in the distribution of alleles with rs3764650 (n = 2184). Therefore, we cannot conclude that rs3764650 is not associated with AD. We found no allele effects on ABCA7 mRNA expression in peripheral blood or cognition assessed with MMSE, ADAS, or CDR. Our results are consistent with previous reports that showed no association between the MMSE score and rs3764650 [16, 37]. Differences in ethnicity, sample size, and experimental setting (peripheral blood vs. brain tissue) may influence the results.

Second, the ABCA7 mRNA expression level in peripheral blood from AD patients was significantly higher than that in control subjects. ABCA7 is expressed throughout the mouse brain with particularly high expression in CA1 hippocampal neurons [38], as well as in the human brain [39, 40]. Additional analysis in human brain cells showed that the ABCA7 mRNA expression level is the highest in microglia [10]. ABCA7 likely plays roles in transporting phospholipids and enhancing phagocytosis by macrophages [9 –13]. Peripheral lymphocyte infiltration was observed in capillaries of AD brain tissue [41]. Recent study showed that in a mouse model of AD, Aβ-specific lymphocyte occurred in the brain after a single Aβ immunization provided that small amounts of IFN-γ were expressed in the brain, and induced microglia activation and efficient clearance of Aβ [42]. These findings indicated that peripheral lymphocyte could be influenced on the change of brain in AD. In another study, the ABCA7 mRNA expression level in peripheral blood was negatively correlated with hippocampal atrophy as assessed with magnetic resonance imaging in 50 normal individuals and 98 with mild cognitive impairment [37]. Therefore, the ABCA7 mRNA expression level may be associated with cognitive impairment in AD. The ABCA7 mRNA level in AD subjects treated with AChEIs was significantly lower than in those not treated with AChEIs in this study, and the duration of illness in AD subjects treated with AChEIs was significantly longer than in those not treated with AChEIs. Because the ABCA7 mRNA expression level in AD subjects showed a significant negative correlation with the duration of illness, we conclude that the ABCA7 mRNA expression level was more influenced on longer duration of illness rather than on whether medicated with AChEIs or not. Another study reported that the ABCA7 expression level in the parietal lobes of European Americans with AD was positively associated with the CDR [43]. The difference between this finding and ours may be influenced by the timing of brain or blood sampling. In the future, we should analyze ABCA7 expression levels in human brain and peripheral blood during the same period. Additionally, many neurodegenerative diseases including AD share chronic immune activation as a common feature, although these diseases are probably triggered by many different initiating events in the early stages [44]. Higher ABCA7 expression levels in peripheral blood may reflect neuroprotective effects in early stages of AD and a decrease in ABCA7 mRNA may reflect disease progression and cognitive decline.

Third, a previous study reported that three CpG sites were significantly associated with pathological AD diagnosis. After adjusting for multiple testing, cg02308560 and cg04587220 (30 base pairs apart) were observed in a polycomb-repressed region in HMHA1 proximal to the 3’-untranslated region of ABCA7. However, this study used human brain, and these CpG sites were far (about 30,000 base pairs) from the TSS of ABCA7. We set the target CpG sites within 500 base pairs of the TSS of ABCA7. Although this region has five CpG sites and is predicted to bind several major TFs [29, 30], we found no association between methylation rates of ABCA7 and AD or the ABCA7 expression level. Although the methylation rate at only CpG3 was significantly correlated with the number of G alleles at rs3764650, we found no correlations between the methylation rate at each CpG site and any other clinical parameters in AD or control subjects. Because this is the first study showing a relationship between AD and the methylation rates of ABCA7 in peripheral blood, further studies with other tissues, such as cerebral cortices, are warranted to confirm the finding.

Our study has several limitations. The first limitation is the small sample size. Second, this study was cross-sectional. We recruited AD patients in various stages and found an inverse correlation between ABCA7 mRNA expression and duration of illness. We should examine ABCA7 mRNA prospectively from the time of mild cognitive impairment through late stages of AD to confirm the stage-dependent expression changes. Third, we selected target CpG sites that may theoretically bind major TFs, and a verification study in vitro such as a luciferase assay is needed to confirm that these target CpG sites are actually bound by TFs and regulate gene expression. Finally, although there was no evidence of cognitive decline from a previous level or mental retardation in healthy controls, no education data for healthy controls is the limitation.

In summary, our results suggest that a higher ABCA7 mRNA expression level in peripheral blood may be a marker for neuroprotective effects against AD pathology, and a decrease in ABCA7 mRNA may reflect disease progression and cognitive decline regardless of rs3764650 and the methylation rates.

Footnotes

ACKNOWLEDGMENTS

We thank Zaidan Niihama Hospital and Kuroda Hospital for collecting blood samples and Ms. Chiemi Onishi for her technical assistance. This work was partly supported by JSPS KAKENHI Grant Numbers 25861015 and 15K09808.

Authors’ disclosures available online ().

Appendix

References

Jorm

(1986) Effects of cholinergic enhancement therapies on memory function in Alzheimer’s disease: A meta-analysis of the literature. Aust N Z J Psychiatry 20, 237–240.

Wilkinson

, Francis

, Schwam

, Payne-Parrish

(2004) Cholinesterase inhibitors used in the treatment of Alzheimer’s disease: The relationship between pharmacological effects and clinical efficacy. Drugs Aging 21, 453–478.

Slooter

, Cruts

, Kalmijn

, Hofman

, Breteler

, Van Broeckhoven

, van Duijn

(1998) Risk estimates of dementia by apolipoprotein E genotypes from a population-based incidence study: The Rotterdam Study. Arch Neurol 55, 964–968.

Hollingworth

, Harold

, Sims

, Gerrish

, Lambert

, Carrasquillo

, Abraham

, Hamshere

, Pahwa

, Moskvina

, Dowzell

, Jones

, Stretton

, Thomas

, Richards

, Ivanov

, Widdowson

, Chapman

, Lovestone

, Powell

, Proitsi

, Lupton

, Brayne

, Rubinsztein

, Gill

, Lawlor

, Lynch

, Brown

, Passmore

, Craig

, McGuinness

, Todd

, Holmes

, Mann

, Smith

, Beaumont

, Warden

, Wilcock

, Love

, Kehoe

, Hooper

, Vardy

, Hardy

, Mead

, Fox

, Rossor

, Collinge

, Maier

, Jessen

, Rüther

, Schürmann

, Heun

, Kölsch

, van den Bussche

, Heuser

, Kornhuber

, Wiltfang

, Dichgans

, Frölich

, Hampel

, Gallacher

, Hüll

, Rujescu

, Giegling

, Goate

, Kauwe

, Cruchaga

, Nowotny

, Morris

, Mayo

, Sleegers

, Bettens

, Engelborghs

, De Deyn

, Van Broeckhoven

, Livingston

, Bass

, Gurling

, McQuillin

, Gwilliam

, Deloukas

, Al-Chalabi

, Shaw

, Tsolaki

, Singleton

, Guerreiro

, Mühleisen

, Nöthen

, Moebus

, Jöckel

, Klopp

, Wichmann

, Pankratz

, Sando

, Aasly

, Barcikowska

, Wszolek

, Dickson

, Graff-Radford

, Petersen

, Alzheimer’s Disease Neuroimaging Initiative, van Duijn

, Breteler

, Ikram

, DeStefano

, Fitzpatrick

, Lopez

, Launer

, Seshadri

, consortium CHARGE, Berr

, Campion

, Epelbaum

, Dartigues

, Tzourio

, Alpérovitch

, Lathrop

, EADI1 consortium, Feulner

, Friedrich

, Riehle

, Krawczak

, Schreiber

, Mayhaus

, Nicolhaus

, Wagenpfeil

, Steinberg

, Stefansson

, Snaedal

, Björnsson

, Jonsson

, Chouraki

, Genier-Boley

, Hiltunen

, Soininen

, Combarros

, Zelenika

, Delepine

, Bullido

, Pasquier

, Mateo

, Frank-Garcia

, Porcellini

, Hanon

, Coto

, Alvarez

, Bosco

, Siciliano

, Mancuso

, Panza

, Solfrizzi

, Nacmias

, Sorbi

, Bossú

, Piccardi

, Arosio

, Annoni

, Seripa

, Pilotto

, Scarpini

, Galimberti

, Brice

, Hannequin

, Licastro

, Jones

, Holmans

, Jonsson

, Riemenschneider

, Morgan

, Younkin

, Owen

, O’Donovan

, Amouyel

, Williams

(2011) Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer’s disease. Nat Genet 43, 429–435.

Lambert

, Heath

, Even

, Campion

, Sleegers

, Hiltunen

, Combarros

, Zelenika

, Bullido

, Tavernier

, Letenneur

, Bettens

, Berr

, Pasquier

, Fiévet

, Barberger-Gateau

, Engelborghs

, De Deyn

, Mateo

, Franck

, Helisalmi

, Porcellini

, Hanon

, European Alzheimer’s Disease Initiative Investigators, de Pancorbo

, Lendon

, Dufouil

, Jaillard

, Leveillard

, Alvarez

, Bosco

, Mancuso

, Panza

, Nacmias

, Bossú

, Piccardi

, Annoni

, Seripa

, Galimberti

, Hannequin

, Licastro

, Soininen

, Ritchie

, Blanché

, Dartigues

, Tzourio

, Gut

, Van Broeckhoven

, Alpérovitch

, Lathrop

, Amouyel

(2009) Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer’s disease. Nat Genet 41, 1094–1099.

Naj

, Jun

, Beecham

, Wang

, Vardarajan

, Buros

, Gallins

, Buxbaum

, Jarvik

, Crane

, Larson

, Bird

, Boeve

, Graff-Radford

, De Jager

, Evans

, Schneider

, Carrasquillo

, Ertekin-Taner

, Younkin

, Cruchaga

, Kauwe

, Nowotny

, Kramer

, Hardy

, Huentelman

, Myers

, Barmada

, Demirci

, Baldwin

, Green

, Rogaeva

, St George-Hyslop

, Arnold

, Barber

, Beach

, Bigio

, Bowen

, Boxer

, Burke

, Cairns

, Carlson

, Carney

, Carroll

, Chui

, Clark

, Corneveaux

, Cotman

, Cummings

, DeCarli

, DeKosky

, Diaz-Arrastia

, Dick

, Dickson

, Ellis

, Faber

, Fallon

, Farlow

, Ferris

, Frosch

, Galasko

, Ganguli

, Gearing

, Geschwind

, Ghetti

, Gilbert

, Gilman

, Giordani

, Glass

, Growdon

, Hamilton

, Harrell

, Head

, Honig

, Hulette

, Hyman

, Jicha

, Jin

, Johnson

, Karlawish

, Karydas

, Kaye

, Kim

, Koo

, Kowall

, Lah

, Levey

, Lieberman

, Lopez

, Mack

, Marson

, Martiniuk

, Mash

, Masliah

, McCormick

, McCurry

, McDavid

, McKee

, Mesulam

, Miller

, Parisi

, Perl

, Peskind

, Petersen

, Poon

, Quinn

, Rajbhandary

, Raskind

, Reisberg

, Ringman

, Roberson

, Rosenberg

, Sano

, Schneider

, Seeley

, Shelanski

, Slifer

, Smith

, Sonnen

, Spina

, Stern

, Tanzi

, Trojanowski

, Troncoso

, Van Deerlin

, Vinters

, Vonsattel

, Weintraub

, Welsh-Bohmer

, Williamson

, Woltjer

, Cantwell

, Dombroski

, Beekly

, Lunetta

, Martin

, Kamboh

, Saykin

, Reiman

, Bennett

, Morris

, Montine

, Goate

, Blacker

, Tsuang

, Hakonarson

, Kukull

, Foroud

, Haines

, Mayeux

, Pericak-Vance

, Farrer

, Schellenberg

(2011) Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer’s disease. Nat Genet 43, 436–441.

Seshadri

, Fitzpatrick

, Ikram

, DeStefano

, Gudnason

, Boada

, Bis

, Smith

, Carassquillo

, Lambert

, Harold

, Schrijvers

, Ramirez-Lorca

, Debette

, Longstreth

Jr , Janssens

, Pankratz

, Dartigues

, Hollingworth

, Aspelund

, Hernandez

, Beiser

, Kuller

, Koudstaal

, Dickson

, Tzourio

, Abraham

, Antunez

, Du

, Rotter

, Aulchenko

, Harris

, Petersen

, Berr

, Owen

, Lopez-Arrieta

, Varadarajan

, Becker

, Rivadeneira

, Nalls

, Graff-Radford

, Campion

, Auerbach

, Rice

, Hofman

, Jonsson

, Schmidt

, Lathrop

, Mosley

, Au

, Psaty

, Uitterlinden

, Farrer

, Lumley

, Ruiz

, Williams

, Amouyel

, Younkin

, Wolf

, Launer

, Lopez

, van Duijn

, Breteler

, Consortium CHARGE, GERAD1 Consortium, EADI1 Consortium (2010) Genome-wide analysis of genetic loci associated with Alzheimer disease. JAMA 303, 1832–1840.

Harold

, Abraham

, Hollingworth

, Sims

, Gerrish

, Hamshere

, Pahwa

, Moskvina

, Dowzell

, Williams

, Jones

, Thomas

, Stretton

, Morgan

, Lovestone

, Powell

, Proitsi

, Lupton

, Brayne

, Rubinsztein

, Gill

, Lawlor

, Lynch

, Morgan

, Brown

, Passmore

, Craig

, McGuinness

, Todd

, Holmes

, Mann

, Smith

, Love

, Kehoe

, Hardy

, Mead

, Fox

, Rossor

, Collinge

, Maier

, Jessen

, Schürmann

, Heun

, van den Bussche

, Heuser

, Kornhuber

, Wiltfang

, Dichgans

, Frölich

, Hampel

, Hüll

, Rujescu

, Goate

, Kauwe

, Cruchaga

, Nowotny

, Morris

, Mayo

, Sleegers

, Bettens

, Engelborghs

, De Deyn

, Van Broeckhoven

, Livingston

, Bass

, Gurling

, McQuillin

, Gwilliam

, Deloukas

, Al-Chalabi

, Shaw

, Tsolaki

, Singleton

, Guerreiro

, Mühleisen

, Nöthen

, Moebus

, Jöckel

, Klopp

, Wichmann

, Carrasquillo

, Pankratz

, Younkin

, Holmans

, O’Donovan

, Owen

, Williams

(2009) Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer’s disease. Nat Genet 41, 1088–1093.

Jehle

, Gardai

, Li

, Linsel-Nitschke

, Morimoto

, Janssen

, Vandivier

, Wang

, Greenberg

, Dale

, Qin

, Henson

, Tall

(2006) ATP-binding cassette transporter A7 enhances phagocytosis of apoptotic cells and associated ERK signaling in macrophages. J Cell Biol 174, 547–556.

10.

Kim

, Guillemin

, Glaros

, Lim

, Garner

(2006) Quantitation of ATP-binding cassette subfamily-A transporter gene expression in primary human brain cells. Neuroreport 17, 891–896.

11.

Kim

, Weickert

, Garner

(2008) Role of ATP-binding cassette transporters in brain lipid transport and neurological disease. J Neurochem 104, 1145–1166.

12.

Kim

, Li

, Ruberu

, Chan

, Elliott

, Low

, Cheng

, Karl

, Garner

(2013) Deletion of Abca7 increases cerebral amyloid-beta accumulation in the J20 mouse model of Alzheimer’s disease. J Neurosci 33, 4387–4394.

13.

Wang

, Lan

, Gerbod-Giannone

, Linsel-Nitschke

, Jehle

, Chen

, Martinez

, Tall

(2003) ATP-binding cassette transporter A7 (ABCA7) binds apolipoprotein A-I and mediates cellular phospholipid but not cholesterol efflux. J Biol Chem 278, 42906–42912.

14.

Sakae

, Liu

, Shinohara

, Frisch-Daiello

, Ma

, Yamazaki

, Tachibana

, Younkin

, Kurti

, Carrasquillo

, Zou

, Sevlever

, Bisceglio

, Gan

, Fol

, Knight

, Wang

, Han

, Fryer

, Fitzgerald

, Ohyagi

, Younkin

, Bu

, Kanekiyo

(2016) ABCA7 deficiency accelerates amyloid-β generation and Alzheimer’s neuronal pathology. J Neurosci 36, 3848–3859.

15.

, Hsiao

, Paxinos

, Halliday

, Kim

(2016) ABCA7 mediates phagocytic clearance of amyloid-β in the brain. J Alzheimers Dis 54, 569–584.

16.

Liao

, Lee

, Hwang

, Wang

, Tsai

, Wang

, Fuh

(2014) ABCA7 gene and the risk of Alzheimer’s disease in Han Chinese in Taiwan. Neurobiol Aging 35, 2423.e7–2423.e13.

17.

Liu

, Li

, Zhang

, Jiang

, Ma

, Shang

, Liu

, Feng

, Zhang

, Liao

, Zhao

, Li

(2014) Analyzing large-scale samples confirms the association between the ABCA7 rs3764650 polymorphism and Alzheimer’s disease susceptibility. Mol Neurobiol 50, 757–764.

18.

Vasquez

, Fardo

, Estus

(2013) ABCA7 expression is associated with Alzheimer’s disease polymorphism and disease status. Neurosci Lett 556, 58–62.

19.

, Chibnik

, Srivastava

, Pochet

, Yang

, Xu

, Kozubek

, Obholzer

, Leurgans

, Schneider

, Meissner

, De Jager

, Bennett

(2015) Association of Brain DNA methylation in SORL1, ABCA7, HLA-DRB5, SLC24A4, and BIN1 with pathological diagnosis of Alzheimer disease. JAMA Neurol 72, 15–24.

20.

Zenaro

, Pietronigro

, Della Bianca

, Piacentino

, Marongiu

, Budui

, Turano

, Rossi

, Angiari

, Dusi

, Montresor

, Carlucci

, Naní

, Tosadori

, Calciano

, Catalucci

, Berton

, Bonetti

, Constantin

(2015) Neutrophils promote Alzheimer’s disease-like pathology and cognitive decline via LFA-1 integrin. Nat Med 21, 880–886.

21.

Mori

, Yoshino

, Ochi

, Yamazaki

, Kawabe

, Abe

, Kitano

, Ozaki

, Yoshida

, Numata

, Mori

, Iga

, Kuroda

, Ohmori

, Ueno

(2015) TREM2 mRNA expression in leukocytes is increased in Alzheimer’s disease and schizophrenia. PLoS One 10, e0136835.

22.

Yamazaki

, Yoshino

, Mori

, Okita

, Yoshida

, Mori

, Ozaki

, Sao

, Iga

, Ueno

(2016) Association study and meta-analysis of polymorphisms, methylation profiles, and peripheral mRNA expression of the serotonin transporter gene in patients with Alzheimer’s disease. Dement Geriatr Cogn Disord 41, 334–347.

23.

Yoshino

, Mori

, Yoshida

, Yamazaki

, Ozaki

, Sao

, Funahashi

, Iga

, Ueno

(2016) Elevated mRNA expression and low methylation of SNCA in Japanese Alzheimer’s disease subjects. J Alzheimers Dis 54, 1349–1357.

24.

Funahashi

, Yoshino

, Yamazaki

, Mori

, Ozaki

, Sao

, Ochi

, Iga

, Ueno

(2017) DNA methylation changes at SNCA intron 1 in patients with dementia with Lewy bodies. Psychiatry Clin Neurosci 71, 28–35.

25.

McKhann

, Knopman

, Chertkow

, Hyman

, Jack

Jr , Kawas

, Klunk

, Koroshetz

, Manly

, Mayeux

, Mohs

, Morris

, Rossor

, Scheltens

, Carrillo

, Thies

, Weintraub

, Phelps

(2011) The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7, 263–269.

26.

Folstein

, Folstein

, McHugh

(1975) “Mini-mental state”: A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12, 189–198.

27.

Morris

(1993) The Clinical Dementia Rating (CDR): Current version and scoring rules. Neurology 43, 2412–2414.

28.

Cummings

, Mega

, Gray

, Rosenberg-Thompson

, Carusi

, Gornbein

(1994) The Neuropsychiatric Inventory: Comprehensive assessment of psychopathology in dementia. Neurology 44, 2308–2314.

29.

Mathelier

, Fornes

, Arenillas

, Chen

, Denay

, Lee

, Shi

, Shyr

, Tan

, Worsley-Hunt

, Zhang

, Parcy

, Lenhard

, Sandelin

, Wasserman

(2016) JASPAR 2016: A major expansion and update of the open-access database of transcription factor binding profiles. Nucleic Acids Res 44, D110–D115.

30.

Sandelin

, Alkema

, Engström

, Wasserman

, Lenhard

(2004) JASPAR: An open-access database for eukaryotic transcription factor binding profiles. Nucleic Acids Res 32, D91–D94.

31.

Carrol

, Salway

, Pepper

, Saunders

, Mankhambo

, Ollier

, Hart

, Day

(2007) Successful downstream application of the Paxgene Blood RNA system from small blood samples in paediatric patients for quantitative PCR analysis. BMC Immunol 8, 20.

32.

, Tan

, Yu

, Sun

, Tan

, Wang

, Jiang

, Tan

(2014) Increased expression of TREM2 in peripheral blood of Alzheimer’s disease patients. J Alzheimers Dis 38, 497–501.

33.

Watanabe

, Iga

, Nishi

, Numata

, Kinoshita

, Kikuchi

, Nakataki

, Ohmori

(2014) Microarray analysis of global gene expression in leukocytes following lithium treatment. Hum Psychopharmacol Clin Exp 29, 190–198.

34.

Watanabe

, Iga

, Ishii

, Numata

, Shimodera

, Fujita

, Ohmori

(2015) Biological tests for major depressive disorder that involve leukocyte gene expression assays. J Psychiatr Res 66-67, 1–6.

35.

Livak

, Schmittgen

(2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods 25, 402–408.

36.

Kanda

(2013) Investigation of the freely available easy-to-use software ‘EZR’ for medical statistics. Bone Marrow Transplant 48, 452–458.

37.

Ramirez

, Goukasian

, Porat

, Hwang

, Eastman

, Hurtz

, Wang

, Vang

, Sears

, Klein

, Coppola

, Apostolova

(2016) Common variants in ABCA7 and MS4A6A are associated with cortical and hippocampal atrophy. Neurobiol Aging 39, 82–89.

38.

Kim

, Fitzgerald

, Kang

, Okuhira

, Bell

, Manning

, Koehn

, Lu

, Moore

, Freeman

(2005) Abca7 null mice retain normal macrophage phosphatidylcholine and cholesterol efflux activity despite alterations in adipose mass and serum cholesterol levels. J Biol Chem 280, 3989–3995.

39.

Ikeda

, Abe-Dohmae

, Munehira

, Aoki

, Kawamoto

, Furuya

, Shitara

, Amachi

, Kioka

, Matsuo

, Yokoyama

, Ueda

(2003) Posttranscriptional regulation of human ABCA7 and its function for the apoA-I-dependent lipid release. Biochem Biophys Res Commun 311, 313–318.

40.

Langmann

, Mauerer

, Zahn

, Moehle

, Probst

, Stremmel

, Schmitz

(2003) Real-time reverse transcription-PCR expression profiling of the complete human ATP-binding cassette transporter superfamily in various tissues. Clin Chem 49, 230–238.

41.

Itagaki

, McGeer

, Akiyama

(1988) Presence of T-cytotoxic suppressor and leucocyte common antigen positive cells in Alzheimer’s disease brain tissue. Neurosci Lett 91, 259–264.

42.

Fisher

, Nemirovsky

, Baron

, Monsonego

(2010) T cells specifically targeted to amyloid plaques enhance plaque clearance in a mouse model of Alzheimer’s disease. PLoS One 5, e10830.

43.

Karch

, Jeng

, Nowotny

, Cady

, Cruchaga

, Goate

(2012) Expression of novel Alzheimer’s disease risk genes in control and Alzheimer’s disease brains. PLoS One 7, e50976.

44.

Amor

, Puentes

, Baker

, Valk

(2010) Inflammation in neurodegenerative diseases. Immunology 129, 154–169.