TOMM40 and APOE Gene Expression and Cognitive Decline in Japanese Alzheimer’s Disease Subjects

Abstract

Background:

TOMM40 is located on chromosome 19, is in linkage disequilibrium with apolipoprotein E (APOE), andis reported in several genome-wide association studies to be associated with Alzheimer’s disease (AD).

Objective:

Assess APOE and TOM40 and mitochondrial genes as blood biomarkers for AD.

Methods:

We examined TOMM40, PTEN-induced putative kinase 1 (PINK1), Parkin RBR E3 ubiquitin protein ligase (PARK2), and APOE mRNA expression in relation to the methylation rates of CpG sites in the upstream region of TOMM40exon 1 in peripheral leukocytes and TOMM40523 polyT genotypes in 60 AD and age- and sex-matched control subjects.

Results:

TOMM40 mRNA expression was significantly lower in AD subjects (0.87±0.18 versus 1.0±0.23, p = 0.005), and PINK1 mRNA expression was higher in AD subjects (1.5±0.61 versus 1.0±0.52, p < 0.001). TOMM40 mRNA expression was significantly correlated with the Mini-Mental State Examination total score (r = 0.290, p = 0.027). There was no expressional change in peripheral APOE mRNA in either AD or control subjects (p = 0.32). Methylation rates in the upstream region of TOMM40exon 1 were not different between AD and control subjects (average rate: 1.37±0.99 versus 1.39±1.20, p = 0.885), and TOMM40523 polyT genotypes were also not different between AD and control subjects (p = 0.67).

Conclusion:

TOMM40 mRNA expression was lower in AD subjects and was correlated with cognitive decline. Significant changes in both TOMM40 and PINK1 mRNA may be related to mitochondrial dysfunction.

Keywords

Alzheimer’s disease apolipoprotein E (ApoE)methylation mitochondria mRNA expression Parkin RBR E3 ubiquitin protein ligase (PARK2)PTEN-induced putative kinase 1 (PINK1)translocase of outer mitochondrial membrane 40 (TOMM40)

INTRODUCTION

Over 46 million people live with dementia worldwide, and this number will triple by 2050 [1]. Alzheimer’s disease (AD) is the most common cause of dementia and causes memory impairment, executive dysfunction, visuospatial impairment, deficits in language, and behavioral symptoms. Pathologically, the presence of amyloid plaques that contain amyloid-β (Aβ), a peptide fragment of the amyloid-β protein precursor, is partially responsible for causing AD [2]. Other reports indicate that extracellular deposits of Aβ [3 –5] and neurofibrillary tangles, which occur following intracellular accumulation of hyperphosphorylated microtubule-associated protein tau [6, 7], play a key role in the pathogenesis of AD.

Several genome-wide association studies revealed the genetic risk of AD [8 –10]. The ɛ4 allele of apolipoprotein E (APOE) is reported to be the strongest genetic factor for risk of late-onset Alzheimer’s disease (LOAD) [11]. APOE has three alleles: APOE ɛ2, APOE ɛ3, and APOE ɛ4. People who have the ɛ4 allele of APOE are at greater risk of developing AD [12]. Translocase of outer mitochondrial membrane 40 (TOMM40) is a gene located close to and in linkage disequilibrium with APOE. TOMM40 is a channel-forming subunit that localizes to the outer membrane of mitochondria and forms a TOMM complex, which is involved in import and trafficking of protein into mitochondria [13]. Mitochondrial dysfunction is associated with the pathophysiology of AD [14 –16]. The rs59007384 polymorphism of TOMM40 was related to the accumulation of cortical Aβ in a genome-wide association study [10]. TOMM40 has a polyT repeat polymorphism (rs10524523), which affects the onset age of LOAD in an APOE-independent manner [17]. The TOMM40523 polyT genotypes also affect TOMM40 mRNA expression in the temporal and occipital cortex [18]. In one study, TOMM40 mRNA expression in peripheral blood was downregulated with the progression of AD and might be a useful diagnostic marker [19]. PTEN-induced putative kinase 1 (PINK1) and Parkin RBR E3 ubiquitin protein ligase (PARK2) are also related to mitochondrial functions. Both PINK1 and PARK2 have been studied not only in Parkinson’s disease [20, 21]but also in AD [22, 23]. TOMM40, PINK1, and PARK2 are present on the outer mitochondrial membrane and are involved in mitochondrial clearance [24]. In addition, PINK1 and PARK2 are linked to the mitochondrial maintenance and dynamicspathway [25].

DNA methylation, a key type of epigenetic process, plays a role in the regulation of neurodevelopment and is related to the pathogenesis of brain diseases [26, 27]. A general association between the methylation rate and gene expression has been reported [28, 29]. Our group previously reported that the methylation ratio of SNCA may be a useful biomarker for both AD [30] and diffuse Lewy bodydisease [31].

Here, we examined 1) TOMM40, PINK1, and PARK2 mRNA expression that is related to mitochondrial function, and APOE mRNA expression; 2) the methylation rates in the upstream region of TOMM40exon 1; and 3) 523 polyT genotypes of TOMM40 and genotypes of APOE in AD subjects.

METHODS

AD subjects and healthy controls

Demographic data for each group of participants are shown in Table 1. We enrolled 60 AD subjects [19 males and 41 females, mean age±standard deviation (SD); 76.9±5.0 y] who were outpatients at Ehime University Hospital, Zaidan Niihama Hospital, and Kuroda Hospital, Ehime, Japan. AD subjects were diagnosed as probable AD dementia by the Aging/Alzheimer’s Association criteria [32] and were living with at least one caregiver. All AD subjects had no cerebral vascular lesions as determined by head computed tomography or magnetic resonance imaging. AD subjects were evaluated with the Mini-Mental State Examination (MMSE) [33], Alzheimer’s Disease Assessment Scale (ADAS) [34], and Clinical Dementia Rating (CDR) [35] to assess their cognitive functions. We used the Montgomery-Åsberg Depression Rating Scale (MADRS) to assess their depression symptoms [36] and the Neuropsychiatric Inventory (NPI) to assess their psychological symptoms [37]. Control subjects were 60 elderly participants (19 males and 41 females, mean age±SD = 76.8±5.9 y) without cognitive impairment, psychiatric symptoms, or past mental disorders, and were diagnosed as mentally and cognitively normal by at least two certified psychiatrists based on clinical interviews. All participants were unrelated and of Japanese origin, and provided written informed consent forms approved by the institutional ethics committees of Ehime University Hospital, Zaidan Niihama Hospital, and Kuroda Hospital.

Table 1

Alzheimer’s disease and control subjects

	AD subjects	Control subjects	p value
	(n = 60)	(n = 60)
Sex (male: female)	19: 41	19: 41	1.0
Age (y)	76.9±5.0	76.8±5.9	0.66
ApoE ɛ4+/ɛ4–	28: 32	10: 48	<0.001
TOMM40523 polyT	6: 13: 41	6: 9: 45	0.67
S: V: VL

AD, Alzheimer’s disease; S, short; L, long; VL, very long.

Blood sample collection and processing of complementary DNA (cDNA) and genomic DNA (gDNA)

Total RNA samples were obtained from whole peripheral blood samples, which were collected in PaxGene Blood RNA Systems tubes (BD, Tokyo, Japan) according to the manufacturer’s protocol. RNA concentration and purity were measured with a NanoDrop-1000 system (Thermo Fisher Scientific, Yokohama, Japan), and acceptable 260/280 ratios were in the range of 1.8–2.0. For each 40-μl reaction, 1.0 μg RNA was used as a template to synthesize cDNAs with a High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA). gDNA samples were obtained from whole peripheral blood samples collected in potassium EDTA tubes, and gDNA was extracted using a QIAamp DNA Blood Mini Kit (Qiagen, Tokyo, Japan) according to the manufacturer’s protocol.

Real-time PCR procedure

mRNA expression was analyzed by real-time quantitative PCR using a StepOnePlus Real-Time PCR System (Applied Biosystems). The specific TaqMan probes were Hs01587378_mH for TOMM40, Hs00260868_m1 for PINK1, Hs01038322_m1 for PARK2, Hs00171168_mH for APOE, and Hs99999905_m1 for GAPDH (Applied Biosystems). GAPDH was suitable for normalization of quantitative RT-PCR and was used as the reference gene in this study [38 –40]. The final volume of each reaction was 10 μl, and each contained TaqMan Universal Master Mix (Applied Biosystems). Expression levels were examined in duplicate. The Δ ΔCt method and StepOne software (Applied Biosystems) were used to determine relative expressionlevels.

Bisulfite conversion and pyrosequencing

The upstream region of TOMM40exon 1 where the largest number of transcription factors was predicted to bind with a high score (predictive value >12) was subjected to methylation analysis and is depicted in Supplementary Figure 1. The gDNA extracted from leukocytes (1000 ng/sample) was converted with bisulfate using an EpiTect Plus DNA Bisulfite Kit (Qiagen, Valencia, CA). Converted gDNA was then used as a template for PCR amplification with 0.2 μM each of forward primer (5^′-GGTGGGAGGGTTTTAGGGTATAT-3^′) and reverse primer (5^′- ACTCAACCCCAACAAATC-3^′). The final volume of each PCR sample was 20.0 μl, and contained 2.4 μl gDNAs, 0.2 μM each of forward and reverse primers, 0.5 U AmpliTaq gold (Applied Biosystems), 10× PCR buffer with 15 mM MgCl₂, and 2 mM dNTP. Cycling conditions were as follows: denaturation for 10 min at 94°C; 45 cycles each of 94°C for 30 s, 53°C for 30 s, and 72°C for 1 min; and a final extension of 10 min at 72°C. The PCR products were sequenced with a PyroMark Q24 Advanced Sequencer (Qiagen) and the sequencing primer 5^′-GGGTTTTAGGGTATATTAAATT-3^′. We used non-converted DNA as an additional control for the specificity of PCR amplification of bisulfite-treated DNA. Methylation rates at each CpG site were quantified in duplicate using PyroMark Q24 Advanced Software (Qiagen). To measure the methylation rates accurately, the quality of all data was passed fully in PyroMark Q24 Advanced software.

Genotyping

We conducted repeated-primed PCR to measure TOMM40523 polyT genotypes using genotyping primers, as previously described [18]. Briefly, 50 ng of genomic DNA was used as a template in a final volume of 12.5 μl containing a final concentration of 0.2 mM 7-deaza dGTP (Sigma-Aldrich, St. Louis, MO), 1× Q-Solution, 5% dimethylsulfoxide, 1 mM MgCl₂, 1× PCR buffer (Qiagen), 0.4 μM reverse primer, and 0.4 μM 6FAM-fluorescently labeled forward primer. The thermal cycling conditions were an initial denaturation for 5 min and 35 subsequent cycles of denaturation at 95°C for 30 s, annealing at 58°C for 30 s, and elongation at 72°C for 1 min. PCR products were analyzed on an ABI3500 DNA Analyzer (Applied Biosystems) and visualized using GeneMapper software (Applied Biosystems). The typing success rate was 100%. We divided the 523 polyT genotypes according to Roses et al. [17]: Short (S), ≤19; Long (L), 20–29; Very Long(VL), ≥30.

Genotyping of single nucleotide polymorphisms (rs429358 and rs7412) in APOE was conducted using a TaqMan 5^′-exonuclease allelic discrimination assay (Assay ID: rs429538; C___3084793_20, rs7412; C__904973_10, Applied Biosystems) using a StepOnePlus real-time PCR system (Applied Biosystems). Genotyping call rates were 97.5% (rs429358) and 97.5% (rs7412). The APOE isotype-related genotypes are combinations of the APOE ɛ2, ɛ3, and ɛ4 alleles derived from the two genotypes of rs429358 (T334C) and rs7412 (C472T): ɛ2, 334T/472T; ɛ3, 334T/472C; and ɛ4, 334C/472C. The ɛ4 genotype is a risk factor for AD [41].

Statistical analysis

We performed statistical analyses using SPSS 22.0 software (IBM Japan, Tokyo, Japan) and tested normality using the Shapiro-Wilk test. Sex, TOMM40523 polyT genotypes, and APOE genotypes between AD and control subjects were analyzed with Fisher’s exact test. Comparisons of mRNA expression and each CpG methylation rate of TOMM40 between AD and control subjects were conducted with the Mann-Whitney U test. Comparisons of mRNA expression with sex and APOE genotypes, and acetylcholine esterase inhibitor medications, were also conducted with the Mann-Whitney U test. Correlations of mRNA expression with age, age of onset, duration of illness, MMSE, NPI, ADAS, MADRS, and methylation rates at each CpG site were conducted with the Spearman rank correlation. Correlations of TOMM40 mRNA expression with all MMSE subscales were conducted by linear regression. TOMM40 mRNA expression with CDR and recall in MMSE were compared by the Kruskal-Wallis test combined with the post hoc Steel-Dwass test (EZR version 1.26) [42]. Statistical significance was defined at the 95% level(p = 0.05).

RESULTS

Participant characteristics

Demographic data and the TOMM40523 and polyT APOE genotypes of participants are shown in Table 1. AD and control subjects did not differ in sex (p = 1.0), age (p = 0.66), or TOMM40523 polyT genotypes (p = 0.67). However, there was a significant difference in APOE genotype between the AD and control subjects (p < 0.001). The distribution of TOMM40523 polyT genotypes significantly differed between subjects with APOE ɛ4–and ɛ4+ in both AD (p < 0.001) and control subjects (p < 0.01). These data are shown in Table 2. Clinical characteristics and the results of psychological tests on AD subjects are shown in Table 3.

Table 2

Distribution of TOMM40523 polyT genotypes among APOE genotypes

APOE genotype	ɛ4–			ɛ4+
TOMM40523 polyT genotype	S	L	VL	S	L	VL	p
Total	6 (5.1)	4 (4.3)	65 (55.6)	5 (4.3)	17 (14.5)	19 (16.2)	<0.01
AD	3 (5.1)	0 (0)	25 (42.4)	3 (5.1)	13 (22.0)	15 (25.4)	<0.001
Ct	3 (5.2)	5 (8.6)	40 (69.0)	2 (3.4)	4 (6.9)	4 (6.9)	<0.01

Value are the actual numbers and parenthesized numbers are percentages (%). AD, Alzheimer’s disease subjects; Ct, control subjects; S, short; L, long; VL, very long.

Table 3

Demographic and clinical data for Alzheimer’s disease subjects

Characteristics	Alzheimer’s disease
	subjects
Sex, male	19
Age (y)	76.9±5.0
Age of onset (y)	74.71±7.0
Duration of illness (y)	73.3±6.5
Education (y)	10.9±2.7
Cholinesterase inhibitor medication (%)	40 (66.6)
MMSE total score	18.8±6.5
ADAS total score (n = 44)	17.7±9.0
NPI-10 total score	13.6±15.0
MADRS total score (n = 44)	5.2±6.5
CDR score (0:0.5:1:2:3)	11: 21: 18: 4

Values are the mean±standard deviation. MMSE, Mini-Mental State Examination; ADAS, Alzheimer’s Disease Assessment Scale; NPI, neuropsychiatric inventory; MADRS, Montgomery-Åsberg Depression Rating Scale; CDR, Clinical Dementia Rating.

mRNA expression levels

A significant difference between AD and control subjects was found in the TOMM40 mRNA expression level (AD: 0.87±0.18 versus control: 1.0±0.23, p = 0.005, Fig. 1) and PINK1 mRNA expression level (AD: 1.5±0.61 versus control: 1.0±0.52, p < 0.001, Fig. 2), but not in the PARK2 mRNA expression level (AD: 0.97±0.50 versus control: 1.0±0.44, p = 0.435, Fig. 3) or the APOE mRNA expression level (AD: 1.12±0.5 versus control: 1.0±0.4, p = 0.319, Fig. 4).

Fig.1

Comparison of TOMM40 mRNA expression between AD (n = 60) and control subjects (n = 60). Each symbol represents one individual. Comparisons between AD and control subjects were conducted with the Mann–Whitney U test. The horizontal bar represents the mean±standard error. AD, Alzheimer’s disease subjects; Ct, control subjects.

Fig.2

Comparison of PINK1 mRNA expression between AD (n = 60) and control subjects (n = 60). Each symbol represents one individual. Comparisons between AD and control subjects were conducted with the Mann–Whitney U test. The horizontal bar represents the mean±standard error. AD, Alzheimer’s disease subjects; Ct, control subjects.

Fig.3

Comparison of PARK2 mRNA expression between AD (n = 60) and control subjects (n = 60). Each symbol represents one individual. Comparisons between AD and control subjects were conducted with the Mann–Whitney U test. The horizontal bar represents the mean±standard error. AD, Alzheimer’s disease subjects; Ct, control subjects.

Fig.4

Comparison of APOE mRNA expression between AD (n = 60) and control subjects (n = 60). Each symbol represents one individual. Comparisons between AD and control subjects were conducted with the Mann–Whitney U test. The horizontal bar represents the mean±standard error. AD, Alzheimer’s disease subjects; Ct, control subjects.

TOMM40 mRNA expression levels were not correlated with sex (AD: p = 0.626; control: p = 0.869), TOMM40523 polyT genotypes (AD: p = 0.695; control: p = 0.158), APOE genotype (AD: p = 0.673; control: p = 0.629), age at onset (r = –0.154, p = 0.284), duration of illness in AD subjects (r = –0.20, p = 0.891), or acetylcholine esterase inhibitor medications (p = 0.220). TOMM40 mRNA expression levels of only the control subjects were correlatedwith age at blood sampling (AD: r = –0.231, p = 0.081; control: r = –0.309, p = 0.017, Supplementary Figure 2).

PINK1 mRNA expression levels were not correlated with sex (AD: p = 0.167; control: p = 0.715), APOE genotype (AD: p = 0.404; control: p = 0.681), TOMM40523 polyT genotypes (AD: p = 0.780; control: p = 0.077), age at blood sampling (AD: r = –0.128, p = 0.333; control: r = –0.011, p = 0.933), age at onset (r = –0.096, p = 0.501), duration of illness in AD subjects (r = –0.057, p = 0.691), or acetylcholine esterase inhibitor medications (p = 0.283).

PARK2 mRNA expression levels were not correlated with sex (AD: p = 0.553; control: p = 0.562), APOE genotype (AD: p = 0.704; control: p = 0.773), TOMM40523 polyT genotypes (AD: p = 0.847; control: p = 0.267), age at onset (r = –0.044, p = 0.757), duration of illness in AD subjects (r = 0.070, p = 0.620), or acetylcholine esterase inhibitor medications (p = 0.145). PARK2 mRNA expression levels were correlated with age at blood sampling in control subjects (AD: r = 0.008, p = 0.951; control: r = –0.326, p = 0.011).

APOE mRNA expression levels were not associated with APOE genotype (AD: p = 0.219; control: p = 0.551), TOMM40523 polyT genotypes (AD: p = 0.749; control: p = 0.143), age at blood sampling (AD: r = 0.017, p = 0.896, control: r = 0.053, p = 0.688), age at onset (r = 0.042, p = 0.766), orduration of illness in AD subjects (r = 0.089, p = 0.525), but were significantly associated with sex only in the AD group (AD: p = 0.035; control: p = 0.340) and the acetylcholine esterase inhibitor medication group (non-medicated: 1.0±0.33 versus medicated: 0.77±0.38, p = 0.003, Fig. 5).

Fig.5

Comparison of average APOE mRNA expression in AD subjects between drug-naive patients (n = 20) and those receiving cholinesterase inhibitor medications (n = 40) was conducted with the Mann–Whitney U test. The horizontal bar represents the mean±standard error. AchI, cholinesterase inhibitor.

mRNA expression and clinical parameters

TOMM40 mRNA expression levels were not correlated with ADAS (r = –2.07, p = 0.189), NPI (r = –0.084, p = 0.546), MADRS (r = 0.005, p = 0.975), or CDR (p = 0.214), but were significantly correlated with MMSE total score (r = 0.290, p = 0.027, Fig. 6). TOMM40 mRNA expression was significantly associated with the recall subcategory of MMSE when assessed with the multiple linear regression analysis stepwise method (R² = 0.165, p = 0.002; recall: p = 0.002, Supplementary Figure 4).

Fig.6

Correlation analysis between Mini-Mental State Examination (MMSE) score and TOMM40 mRNA expression in AD subjects (n = 60) was conducted with the Spearman’s rank correlation coefficient.

PINK1 mRNA expression levels were not correlated with MMSE (r = 0.044, p = 0.740), ADAS (r = 0.073, p = 0.642), NPI (r = 0.088, p = 0.524), MADRS (r = –0.095, p = 0.544), or CDR (p = 0.612).

PARK2 mRNA expression levels were not correlated with MMSE total score (r = 0.221, p = 0.093), ADAS (r = –0.123, p = 0.431), NPI (r = –0.084, p = 0.521), MADRS (r = 0.152, p = 0.331), or CDR (p = 0.725).

APOE mRNA expression levels were not correlated with MMSE (r = 0.031, p = 0.813), ADAS (r = –0.099, p = 0.524), NPI (r = –0.151, p = 0.267), or MADRS (r = –0.006, p = 0.968), but differed significantly across the CDR total score (p = 0.043, Supplementary Figure 3).

Methylation status of TOMM40

The sequences and positions of the 12 CpG sites in the upstream region of TOMM40exon 1 are shown in Supplementary Figure 1. Methylation rates in the AD group were not different from the control group. Methylation rates were CpG1 (AD versus control subjects: average±SD = 1.37±0.99 versus 1.39±1.20, p = 0.885), CpG2 (1.63±1.49 versus 1.70±1.54, p = 0.933), CpG3 (1.88±1.28 versus 1.85±1.30, p = 0.671), CpG4 (1.84±1.02 versus 1.81±1.06, p = 0.599), CpG5 (1.49±0.88 versus 1.40±0.90, p = 0.316), CpG6 (1.65±1.09 versus 1.55±1.08, p = 0.388), CpG7 (1.88±1.05 versus 1.88±1.11, p = 0.661), CpG8 (1.95±1.09 versus 2.08±1.18, p = 0.516), CpG9 (1.93±0.97 versus 1.96±1.12, p = 0.599), CpG10 (1.71±1.08 versus 1.68±1.10, p = 0.591), CpG11 (2.07±1.25 versus 2.09±1.30, p = 0.637), and CpG12 (2.64±1.63 versus 2.93±1.81, p = 0.591). Methylation rates at each CpG site were not correlated with TOMM40 mRNA expression.

DISCUSSION

There were three major findings from this study.

First, TOMM40 mRNA expression was lower in AD subjects than in control subjects (p = 0.005). This result is consistent with preceding studies showing significantly downregulated TOMM40 mRNA expression in blood samples with progression of AD [19 , 44]. We first revealed a significant negative correlation between TOMM40 mRNA expression and the MMSE total score. In addition, we found that TOMM40 mRNA expression was significantly correlated with the recall subcategory of MMSE when assessed with the multiple linear regression analysis method. Disruption of the episodic memory system is the earliest sign and a core feature of AD, and seems to be a strong predictor of progression from mild cognitive impairment to major cognitive disorders [45]. TOMM40 mRNA levels were significantly increased in the temporal cortex of Caucasian AD subjects compared to healthy control subjects [18]. TOMM40 mRNA expression was both upregulated and downregulated in the frontal cortex of AD postmortem brain compared with controls, regardless of the pathological stage [46]. On the other hand, TOMM40 protein expression in AD patients was decreased in Braak stages IV and V [43]. From these results, it is unclear if there is crosstalk between brain and blood samples used to determine TOMM40 mRNA expression, but decreased TOMM40 mRNA expression in peripheral blood may be a useful biomarker for the early stage of AD. We found a significant correlation between age and TOMM40 mRNA expression in the control subjects (p = 0.017, r = –0.309) and a tendency in the AD subjects (p = 0.081, r = –0.231). The same tendency was seen in a postmortem brain study [18]. PINK1 mRNA expression was higher in AD subjects than in control subjects (p < 0.001). From the preceding study [24], outer mitochondrial membrane capture including TOMM40 leads to accumulation of PINK1 at the outer mitochondrial membrane. Subsequently, PARK2 is also needed for the clearance of mitochondria. Mitochondrial dysfunction may be involved in AD pathogenesis [47]. Our results suggest that dysfunction of the outer mitochondrial membrane through the TOMM40 and PINK1 pathway may be involved in AD pathogenesis. Consistent with this hypothesis, PINK1-deficient mice show neurodegenerative changes [48]. Although PARK2 mRNA expression was not changed (p = 0.395), PARK2 mRNA expression levels were negatively correlated with age at blood sampling only in control subjects (r = –0.326, p = 0.011) and may reflect the decline in mitochondrial function with aging[49, 50].

Second, we could not find a correlation between TOMM40 mRNA expression and the 523 polyT genotype. Consistent with our result, the 523 polyT genotype did not affect TOMM40 mRNAexpression in blood samples from an Asian population, although the distribution of 523 polyT genotypes was not shown in this previous study [19]. The distribution of VL 523 polyT genotypes seemed to have a higher frequency of VL in Japanese AD subjects (68%) and healthy controls (75%) in our study. Subjects with APOE ɛ4–have significantly higher VL and lower L rates compared to those with APOE ɛ4+ [51]. Epidemiological data indicate that the frequency of the ɛ3 allele is higher in Japanese and Chinese individuals than in Caucasians [52 –56]. The high prevalence of the ɛ3 allele in this study affected the high prevalence of VL 523 polyT genotypes through linkage disequilibrium. Several reports have shown that 523 polyT genotypes contribute to the age of AD onset, and the L and VL alleles are associated with higher LOAD risk and earlier age at disease onset [57]. However, 523 polyT genotypes were not correlated with age at onset in our study. We believe this inconsistency is due to differences in the ethnicity of our study population and/or the high frequency of VLalleles.

Third, the APOE mRNA expression in AD subjects did not differ from that of control subjects, regardless of a significant difference in APOE genotype. Because the APOE genotype affects the protein structure and function [58], APOE mRNA expression levels may not be affected by the APOE genotype. We revealed that APOE mRNA expression in peripheral leukocytes was significantly decreased in AD subjects taking cholinesterase inhibitor medications compared to those without medication. One study suggested that APOE mRNA and protein expression in the hippocampus is negatively correlated with cognitive decline as measured by CDR [59]. Consistently, APOE mRNA expression levels in our study differed significantly across the CDR total score (p = 0.043, Supplementary Figure 3). We believe that the observed decreased APOE mRNA expression with cholinesterase inhibitor medication may be related to the prevention of cognitivedecline.

We found no significant change in the methylation ratio in the upstream region of TOMM40exon 1 in the blood of AD patients, and no correlation between the methylation ratio and TOMM40 mRNA expression. Generally, an inverse relationship is present between CpG methylation and transcriptional activity [60, 61]. In the promoter region, hypermethylation is usually related to transcriptional silencing [62, 63]. Although we selected target CpG sites that may theoretically bind major transcription factors in silico, an in vitro verification study such as a luciferase-reported assay is needed to confirm that these target CpG sites are bound by transcription factors and regulate gene expression.

Our study has several limitations. First, the sample size was relatively small, which may lead to a type II error. Second, this study was cross-sectional. We recruited AD patients in various stages of the disease and found an inverse correlation between TOMM40 mRNA expression and the duration of illness. We should examine TOMM40 mRNA prospectively from mild cognitive impairment through the late stages of AD to confirm the stage-dependent expression changes. Although altered expressions of both TOMM40 and PINK1 in this study may imply the mitochondrial dysfunction in AD blood cells, relative TOMM40 and PINK1 levels may remain unchanged if mitochondrial mass is reduced [64, 65]. Further research on mitochondrial mass in AD blood cells is needed to fully investigate this possibility. Lastly, we did not examine the relationship between mRNA expression in the brain and blood. In a future study, we should evaluate the correlation between brain and blood by postmortem brain and/or rodent modelstudies.

In conclusion, TOMM40 mRNA expression is lower in AD subjects and is correlated with cognitive decline. In addition, significant changes in both TOMM40 and PINK1 mRNA levels may be related to mitochondrial dysfunction in AD pathogenesis. APOE mRNA expression is not changed in AD subjects but may be associated with the progression and treatment of AD.

Footnotes

ACKNOWLEDGMENTS

The authors thank all the participants for understanding the aim of this study. We wish to thank Zaidan Niihama Hospital and Kuroda Hospital for collecting blood samples, and Ms. Chiemi Onishi for her technical assistance. This work was partially supported by a Health and Labour Science Research Grant from the Japanese Ministry of Health, Labour and Welfare, and a Grant-in-Aid for Scientific Research from the Japanese Ministry of Education, Culture, Sports, Science and Technology, JSPS KAKENHI Grant Numbers 15K09808 and16K21207.

Authors’ disclosures available online ().

The supplementary material is available in the electronic version of this article: .

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