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Population difference in the association of BDNF promoter methylation with mild cognitive impairment in the Xinjiang Uygur and Han populations
Author’s Accepted Manuscript Population difference in the association of BDNF promoter methylation with mild cognitive impairment in the Xinjiang Uygur and Han populations Wenjuan Ma, Xiaohui Zhou, Huihui Ji, Mei Luo, Guili Liu, Jinyun Li, Qinwen Wang, Shiwei Duan www.elsevier.com/locate/psychres
PII: DOI: Reference:
S0165-1781(15)00462-X http://dx.doi.org/10.1016/j.psychres.2015.07.017 PSY9069
To appear in: Psychiatry Research Received date: 5 March 2015 Revised date: 14 June 2015 Accepted date: 9 July 2015 Cite this article as: Wenjuan Ma, Xiaohui Zhou, Huihui Ji, Mei Luo, Guili Liu, Jinyun Li, Qinwen Wang and Shiwei Duan, Population difference in the association of BDNF promoter methylation with mild cognitive impairment in the Xinjiang Uygur and Han populations, Psychiatry Research, http://dx.doi.org/10.1016/j.psychres.2015.07.017 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Population difference in the association of BDNF promoter methylation with mild cognitive impairment in the Xinjiang Uygur and Han populations
Wenjuan MaA,#, Xiaohui ZhouA,*,#, Huihui JiB,#, Mei LuoA, Guili LiuB, Jinyun LiB, Qinwen WangB,*, Shiwei DuanB,*
A: Department of Internal Medicine for Cadres, the First Affiliated Hospital of Xinjiang Medical University, Urumchi 830000, China B:Ningbo Key Lab of Behavior Neuroscience, Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang315211, China
#: ML, XZ and HJ are co-first authors of this work *:Correspondenceshould be addressed to Drs. Xiaohui Zhou ([email protected]), Qinwen Wang ([email protected]), and ShiweiDuan ([email protected])
Abstract
Background: Mild cognitive impairment (MCI) is a clinical transitional stage between normal aging and Alzheimer disease, which leads to memory loss and a reduction in cognitive function. Brain derived neurotrophic factor (BDNF) plays an important role in neuronal development and plasticity. The aim of this study was to explore the association between BDNF promoter methylation and MCI in the Xinjiang Uygur and Han populations. Methods: A DNA methylation assay using bisulfite pyrosequencing technology was performed on 96 Uygur and 96 Han Chinese individuals from Xinjiang province, China. Results: We found a significantly higher BDNF methylation level in Han MCI cases than in Uygur MCI cases in males from Xinjiang province (p = 0.022). In addition, the methylation level was significantly higher in Xinjiang Han healthy Chinese individuals (Northwestern China) than in Ningbo Han healthy Chinese individuals (Southeastern China) (Female and Male: p = 1.17E-05; Female: p = 0.020; Male: p = 1.37E-04). But our results showed no significant association of BDNF methylation with MCI in either the Uygur or Han Chinese populations (p > 0.05). Further gender-based subgroup analyses did not find any significant results (p > 0.05). Conclusion: Our results indicate that different levels of BDNF methylation may be present in different populations and environments. This study also provides further information regarding the relationship between BDNF methylation levels and MCI in Xinjiang Uygur and Han ethnic groups.
Keywords: mild cognitive impairment, DNA methylation, BDNF, population difference
1. Introduction Mild cognitive impairment (MCI) is a clinical transitional stage between normal aging and Alzheimer disease, which leads to memory loss and cognitive function damage (Petersen et al., 1999). A longitudinal study showed that the conversion rates of MCI to AD are 10% to 30% in one year, 20% to 66% in 3 to 4 years, and 60.5% to 100% in 5 to 10 years (Luis et al., 2003). The prevalence of MCI in different regions in China varies from 5.4% to 25.0% (Cheng and Xiao, 2014), and it was 9.89% in Xinjiang Province in 2007 (Xiaohui Zhou, 2009). DNA methylation is involved in memory, cognitive performance, and dementia. MCI is a complex disease that is influenced by genetic and environmental factors (Forstl et al., 2009). DNA methylation is an important form of regulation of genes that function in the human nervous system (Fabi et al., 2013; Mitchelmore and Gede, 2014)and those related to cognitive function (Bian et al., 2005; Lubin, 2011). Environmental factors could affect epigenetic modifications and thus further influence phenotypes and gene expression (Feil and Fraga, 2011). DNA methylation is a promising biomarker for the diagnosis of psychiatric disorders (Ikegame et al., 2013b). Brain derived neurotrophic factor (BDNF) is a key mediator of activity-dependent processes in the brain and has a major impact on neuronal development and plasticity (Karpova, 2014). BDNF has been shown to have a protective effect on neurons (Numakawa et al., 2010). The serum BDNF level is significantly lower in MCI cases than in healthy individuals (Angelucci et al., 2010; Yu et al., 2008). A growing body of evidence has suggested that epigenetic modifications of BDNF are associated with the pathophysiology of psychiatric disorders (Ikegame et al., 2013a; Mitchelmore and Gede, 2014). BDNF promoter methylation increases significantly with aging (Keleshian et al., 2013). BDNF methylation may be involved in regulating the process of recognition memory, particularly in the hippocampus (Munoz et al., 2010). A significantly higher level of BDNF promoter methylation was observed in AD cases than in controls in a previous study (Chang et al., 2014). In view of the previous findings, we hypothesized that BDNF promoter methylation might contribute to the risk of MCI. The purpose of this study was to determine whether the level of BDNF promoter methylation was associated with MCI.
2. Materials and Methods 2.1. Sample collection A total of 96 Uygur and 96 Han Chinese individuals over 60 years old were enrolled from the Xinjiang Uygur autonomous region between 2010 and 2014. The cases and the controls were matched by age, gender and ethnicity. Personal information including demographics, lifestyle, disease investigation, height, weight, blood pressure, blood glucose, and blood lipid serological indexes were collected through a unified epidemiological survey. All candidates were evaluated by the scales of mini-mental stale examination (MMSE), montreal cognitive assessment (MOCA), activity of daily living (ADL), and Hachinski ischemic (HIS). MCI patients were diagnosed by psychologists and neurologists according to the DSM-IV criteria
(Cooper, 1995). Detailed patient characteristics are provided in Table 1. We excluded patients if they
suffered from mental illness, congenital mental retardation, depression, or nervous system disorders such as stroke, Parkinson's disease, or brain tumors, or if they had a history of head injury, special medication, severe infectious disease or toxic encephalopathy. Blood samples from all individuals were stored at -80°C in 3.2% citrate sodium-treated tubes. Written informed consent forms were received from all participants. The institutional ethics committee of the First Affiliated Hospital at Xinjiang Medical University approved this study.
2.2. Biochemical analyses TG, TC, high-density lipoprotein (HDL), and low density lipoprotein (LDL) levels in the plasma and blood glucose concentrations were measured using an enzymatic end point assay (Zhou et al., 2012).
2.3. DNA preparation and methylation assay. Human genomic DNA was isolated from peripheral blood samples using a nucleic acid extraction automatic analyzer (Lab-Aid 820, Xiamen, China). The DNA concentration was measured with a NanoDrop 2000 (NanoDrop 2000, Wilmington, USA). Bisulfite pyrosequencing
technology was used to determine the CpG methylation levels in a fragment of the BDNF promoter. The bisulfite pyrosequencing assay combined sodium bisulfite DNA conversion chemistry (EZ DNA Methylation-GoldTM Kit; ZYMO RESEARCH), polymerase chain reaction (PCR) amplification (Zymo TaqTM PreMix, ZYMO RESEARCH) and sequencing by synthesis assay (Pyromark Gold Q24 Reagents; Qiagen) of the target sequence. The PCR primers were designed using the PyroMark Assay Design software v2.0.1.15. The PCR and pyrosequencing primers
contained
forward
primer:
5’-TTAGTATTTAAGAGGAAAAGGGAAAGTTGT-3’,
reverse
primer:
5’-Biotin-CCCCCATCATAACTAAAAATCT-3’ and sequencing primer: 5’-GGGAAAGTTGTTGGG-3’.
2.4. Statistical analyses SPSS software (version 16.0; SPSS, Inc., Chicago, IL, USA) was used for all statistical tests, including the t-test for two independent samples, two-way analysis of variance (ANOVA) and Pearson's regression analysis. Two independent sample t-tests were used for comparisons of BDNF methylation and other phenotypes between MCI cases and controls. Using Pearson's correlation analysis, associations between BDNF methylation and the metabolic characteristics of MCI subjects were assessed. A value of p < 0.05 was considered a statistically significant difference. The population differentiation was measured using the fixation index (Fst) and the detail information was shown in the previous paper (Duan et al., 2008).
3. Results Elevated BDNF promoter methylation has been shown to be associated with the risk of AD (Chang et al., 2014). In light of previous findings, we aimed to test whether BDNF methylation contributed to the risk of MCI, an intermediate state in the development of AD. As shown in Figure 1, we selected a fragment containing 4 CpG sites in the BDNF promoter region as described previously (Chang et al., 2014). Our results showed that the methylation levels of the four CpG sites were closely related to each other (r > 0.821, p < 0.01); therefore, the mean values of the four CpGs were used to represent BDNF promoter methylation in the following analyses. In the present study, we examined MCI cases and controls from the Uygur and Han Chinese populations in the Xinjiang province of China. Our results showed no significant association of BDNF methylation with the risk of MCI in either the Uygur or Han Chinese populations (Table 1 and Figure 2, p > 0.05). Further gender-based subgroup analyses also did not find any significant results (Table 1 and Figure 2, p > 0.05), suggesting that BDNF methylation changes are likely to occur during the progression from MCI to AD. Interestingly, we found that BDNF methylation was significantly different between healthy Xinjiang Han Chinese individuals (Northwestern China) and healthy Ningbo Han Chinese individuals (Southeastern China) (Table 3 and Figure 3, p = 1.17E-05), suggesting that BDNF methylation is environment-dependent. This environmental difference was replicated in both male and female subgroup comparisons (Table 3 and Figure 3, female: p = 0.020; male: p = 1.37E-04). In addition, there was a trend toward a difference in BDNF methylation between Uygur and Han Chinese controls (p = 0.091, Table 2 and Figure 2). We also found significantly higher BDNF methylation in male Han MCI cases than in male Uygur MCI cases (p = 0.022, Table 2 and Figure 2). The above results imply that BDNF methylation is likely to be influenced by population and environmental differences. We also measured a total of 5 phenotypes among our subjects. As shown in Table 1, our results indicate a significant contribution of higher TC levels to the risk of MCI in the Uygur Chinese population (p = 0.030). We also found significantly lower HDL-C levels in Uygur MCI cases than in Uygur controls (p = 0.010). A further gender-based subgroup analysis indicated that lower HDL-C levels were associated with the risk of
MCI in the female Uygur Chinese population (p = 0.024), and higher TC and LDL-C levels were associated with MCI in the male Han Chinese population (TC: p = 0.045; LDL-C: p = 0.005). Among the tested phenotypes, we observed a significant age difference between the Xinjiang Uygur and Han populations (case: p = 6.78E-09; control: p = 3.22E-09, Table 2). After correcting for age, we found significantly higher TG levels in the Uygur controls than in the Han Controls (p = 0.043, Table 2), significantly lower levels of TC, HDL-C and LDL-C in the Uygur cases than in the Han cases (TC: p = 0.042; HDL-C: p = 0.011; LDL-C: p = 0.013 Table 2), and significantly lower levels of TC and LDL-C in the Uygur controls than in the Han controls (TC: p = 4.63E-04; LDL-C: p = 0.008, Table 2). Gender-based analyses showed significantly lower levels of HDL-C and LDL-C in the female Uygur cases than in the female Han cases (HDL-C: p = 0.023; LDL-C: p = 0.049, Table 2), significantly lower levels of TC and LDL-C in the female Uygur controls than in the female Han controls (TC: p = 0.011; LDL-C: p = 0.015, Table 2), significantly lower levels of TC and LDL-C in the male Uygur cases than in the male Han cases (TC: p = 0.023; LDL-C: p = 0.007, Table 2), and significantly lower TC levels in the male Uygur controls than in the male Han controls (p = 0.049, Table 2). As shown in Table 4 and Figure 4, there was a significant positive correlation between age and BDNF methylation in the Han MCI cases (r = 0.303, p = 0.036), especially in women (r = 0.553, p = 0.005). There was also a significant correlation between TG levels and BDNF methylation in the Uygur controls (r = 0.494, p = 3.54E-04, Table 5). Further gender-based subgroup analysis replicated the positive correlation between TG and BDNF methylation in both male and female Uygur controls (female: r = 0.451, p = 0.027; male: r = 0.642, p = 0.001, Table 5). In addition, there was a significant correlation between HDL-C levels and BDNF methylation in the Uygur controls (r = 0.474, p = 0.019, Table 5) and a significant correlation between LDL-C levels and BDNF methylation in the Uygur cases (r = 0.426, p = 0.038).
4. Discussion Our results showed no significant association between BDNF promoter methylation and the risk of MCI in either the Uygur or the Han Chinese populations. However, there was a population difference in BDNF promoter methylation among male MCI patients in Xinjiang province. A BDNF promoter methylation difference was found between Han Chinese in Xinjiang in Northwestern China and those in Ningbo in Southeastern China. BDNF plays a major role in brain development and plasticity (Dennis and Levitt, 2005). Epigenetic modifications in BDNF can be considered as a mechanism for modulation of the memory forming process that is used to read memory consolidation in subtypes of specific genes (Lubin et al., 2008). Increased methylation of the BDNF promoter is an independent risk factor for deterioration of cognitive function after stroke (Kim et al., 2012). Increased BDNF promoter methylation was found in the peripheral blood of AD patients (Chang et al., 2014). However, our results show that BDNF promoter methylation levels do not differ between cases and controls. We can speculate that abnormal changes in BDNF promoter methylation may occur in the transformation process from MCI to AD. The BDNF methylation differences across different populations might arise from interactions between genetic and environmental factors (Fraser et al., 2012). DNA methylation is affected by several factors such as diet and lifestyle (Lim and Song, 2012). Food and diet have shortand long-term impacts on the epigenome and participate in BDNF methylation (Dauncey, 2012, 2014). In one study, plasma BDNF was significantly elevated in subjects who were assigned to a MeDiet + nuts compared to a control group (Sanchez-Villegas et al., 2011). BDNF level has been linked to healthy lifestyle factors (Chan et al., 2008). In addition, serum BDNF levels and environmental pressure are also closely related (Chen et al., 2013; van Winkel et al., 2014). Our results showed that BDNF promoter methylation in the Xinjiang Han elderly is significantly higher than in the Ningbo Han elderly. Previous study has found a strong correlation between BDNF methylation and BDNF val66Met polymorphism, which was shown to be associated with a number of psychiatric disorders (Neves-Pereira et al., 2005; Tocchetto et al., 2011; Verhagen et al., 2010) including AD (Lim et
al., 2014). A further analysis showed there was significant ethnic difference in the frequency distribution of BDNF val66Met polymorphism among Asians, Caucasians and Africans (Fst > 0.15, Supplemental Table 1). However, the frequency distribution of BDNF val66Met polymorphism between Japanese (HapMap-JPT) and Han Chinese (HapMap-CHB) was not significantly difference (Fst < 0.05, Supplemental Table 1). In the current study, we found there was significant difference of BDNF methylation between Xinjiang Han Chinese and Xinjiang Uyghur Chinese. A further check of the frequency of BDNF val66Met polymorphism in the tested samples will be intrigue to explore the interaction of BDNF val66Met polymorphism with BDNF methylation. There are some limitations to our study. First, the DNA methylation level changes in different tissues (Pinsonneault and Sadee, 2003). We examined BDNF methylation only in peripheral blood as a surrogate for brain tissue. The BDNF methylation level in brain tissue needs to be further studied. Second, the sample size was limited. A larger sample size is needed to verify our results. Third, we selected only four CpG sites, which might not represent overall BDNF promoter methylation. Investigating other CpG sites might help to elucidate the contribution of BDNF methylation to the risk of MCI. Fourth, elderly subjects usually have more than one disease. Although we tried to control for confounding factors, unknown factors still exist that might provide spurious results. Finally, some p values in the current study might not meet the threshold for significance after correction for multiple testing. Independent studies are needed to confirm our findings. In conclusion, our study suggests that BDNF promoter methylation levels vary in different Xinjiang populations, although BDNF gene methylation was not a significant contributor to MCI pathogenesis according to our results.
Acknowledgements The research was supported by the grants from the National Natural Science Foundation of China (81471398, 81070873 and 81371469), the 973 program from the Ministry of Science and Technology of China (2013CB835100), the Disciplinary Project of Ningbo University (B01350104900), and the K. C. Wong Magna Fund in Ningbo University.
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► No association of BDNF methylation with MCI was found in either Uygur or Han Chinese populations. ► BDNF methylation levels of male Xinjiang Han MCI cases were higher than male Xinjiang Uygur MCI cases. ► BDNF methylation levels were significantly higher in Xinjiang Han Chinese in than Ningbo Han Chinese. ►The differences of populations and environments may affect levels of BDNF methylation.
Table 1: Characteristics of BDNF methylation and important parameters in the Xinjiang Uygur and Han Chinese populations Uygur
Han
Case(n=48)
Control(n=48)
p value
Case(n=48)
Control(n=48)
p value
70.83±4.54
71.02±4.42
0.838
77.41±5.52
77.70±5.53
0.797
23.59±3.76
23.12±4.14
0.570
24.49±2.78
24.49±3.33
0.986
Glu(mmol/L)
5.37±2.24
5.22±1.10
0.955a
0.76±0.09
0.74±0.10
0.519a
TG(mmol/L)
2.57±1.50
2.62±1.77
0.869a
0.23±0.21
0.17±0.23
0.184a
TC(mmol/L)
4.25±0.68
3.70±1.58
0.030
5.18±1.61
4.99±1.35
0.549
HDL-C(mmol/L)
0.03±0.10
0.13±.22
0.010a
1.34±.28
1.38±0.33
0.517a
Age(years) BMI
LDL-C(mmol/L)
2.49±0.50
2.44±0.58
0.652
3.16±1.04
2.95±0.93
0.292
meanBDNF methylation(%)
0.92±0.14
0.90±0.12
0.659a
0.97±0.13
0.99±0.17
0.628a
BMI
22.21±2.53
22.53±4.69
0.774
23.64±2.52
24.85±4.11
0.226
Age(years)
69.67±3.81
69.58±3.98
0.941
76.50±4.55
76.71±4.60
0.875
Glu(mmol/L)
0.67±0.08
0.69±0.09
0.456a
0.75±0.09
0.76±0.13
0.611a
TG(mmol/L)
0.35±0.26
0.33±0.33
0.802a
0.27±0.23
0.19±0.23
0.239a
TC(mmol/L)
4.34±0.71
3.60±1.65
0.052
4.93±1.67
5.42±1.27
0.255
HDL-C(mmol/L)
0.03±0.10
0.15±0.22
0.024a
0.13±0.08
0.15±0.10
0.417a
LDL-C(mmol/L)
2.49±0.54
2.48±0.56
0.983
3.05±0.95
3.26±0.95
0.452
meanBDNF methylation(%)
0.94±0.14
0.89±0.09
0.203a
0.95±0.16
0.98±0.19
0.594a
Age(years)
72.00±5.00
72.46±4.46
0.739
78.33±6.32
78.71±6.27
0.837
BMI
24.96±4.32
23.72±3.53
0.283
25.34±2.82
24.15±2.37
0.121
Glu(mmol/L)
0074±0.15
0.73±0.08
0.647a
0.77±0.11
0.73±0.06
0.094a
TG(mmol/L)
0.31±0.29
0.29±0.33
0.805a
0.19±0.20
0.15±0.24
0.496a
Female
Male
TC(mmol/L)
4.17±0.66
3.81±1.55
0.307
5.44±1.56
4.58±1.33
0.045
HDL-C(mmol/L)
0.04±0.11
0.11±0.23
0.183a
0.11±0.10
0.11±0.11
0.963a
LDL-C(mmol/L)
2.50±0.46
2.39±0.61
0.510
3.38±0.96
2.63±0.81
0.005
meanBDNF methylation(%)
0.89±0.14
0.91±0.15
0.640a
0.99±0.11
0.99±0.14
0.933a
* pvalues less than or equal to 0.05 are in bold. a: Log-transformation was used.
Table 2: Tests for population differences of BDNF methylation and important parameters in the Xinjiang population Case(n=96) Han(n=48) Uygur(n=48)
Control(n=96) p value
Age(years)
77.42±5.52
70.83±4.54
6.78E-09
BMI
24.49±2.78
23.58±3.76
0.186
Glu(mmol/L)
5.92±1.53
5.37±2.24
TG(mmol/L)
1.91±0.97
TC(mmol/L)
adjusted p value
Han(n=48) Uygur(n=48)
p value
adjusted p value
77.71±5.53
71.02±0.08
3.22E-09
0.182
24.49±3.34
23.12±4.14
0.077
0.040
0.163a
0.200a
0.74±0.10
0.71±0.08
0.520a
0.106a
2.57±1.50
0.012a
0.838a
0.16±0.23
0.30±0.32
0.017a
0.043a
5.18±1.61
4.25±.68
3.92E-04
0.042
4.99±1.35
3.70±1.58
4.21E-05
4.63E-04
HDL-C(mmol/L)
1.34±0.28
1.11±0.26
1.15E-04a
0.011a
0.13±0.11
0.13±0.22
0.993a
0.356a
LDL-C(mmol/L)
3.16±1.04
2.49±0.50
1.45E-04
0.013
2.95±0.93
2.44±0.58
0.002
0.008
0.97±0.13
0.92±0.14
0.043 a
0.274a
0.99±0.17
0.90±0.12
0.006 a
Age(years)
76.50±4.54
69.67±3.81
9.88E-07
76.71±4.60
69.58±3.98
7.11E-07
BMI
23.64±2.52
22.21±2.53
0.057
0.021
24.85±4.11
22.53±4.69
0.075
0.053
a
a
a
meanBDNF methylation(%)
0.091a
female
Glu(mmol/L)
0.75±0.09
0.67±0.08
0.05
0.162
0.76±0.13
0.69±0.09
0.031
0.125a
TG(mmol/L)
0.27±0.23
0.35±0.26
0.239a
0.404a
0.19±0.23
0.33±0.33
0.094a
0.349a
TC(mmol/L)
4.93±1.67
4.34±0.71
0.123
0.409
5.42±1.27
3.60±1.65
9.19E-05
0.011
HDL-C(mmol/L)
0.13±0.08
0.03±0.10
4.45E-04
0.023a
0.15±0.10
0.15±0.22
0.933a
0.591a
LDL-C(mmol/L)
2.94±1.08
2.49±0.54
0.076
0.049
3.26±0.95
2.49±0.56
0.001
0.96±0.16
0.94±0.14
0.709a
0.306a
0.99±0.20
0.90±0.09
0.550a
Age(years)
78.33±6.31
72.00±4.50
3.60E-04
78.71±6.27
72.46±4.46
2.44E-04
BMI
25.34±2.82
24.96±4.32
0.721
0.438
24±2.37
23.72±3.53
0.625
0.394
a
0.454
a
0.73±0.06
0.73±0.08
0.840
a
0.751a
Mean BDNFmethylation(%)
0.015 0.176a
male
Glu(mmol/L)
0.77±0.11
0.74±0.15
0.412
TG(mmol/L)
0.19±0.20
0.31±0.29
0.101a
0.327a
0.15±0.24
0.29±0.33
0.097a
0.062a
TC(mmol/L)
5.44±1.55
4.17±0.66
0.001
0.023
4.58±1.33
3.81±1.55
0.072
0.049
HDL-C(mmol/L)
0.11±0.10
0.04±0.11
0.032a
0.139a
0.11±0.11
0.11±0.23
0.927a
0.466a
LDL-C(mmol/L)
3.38±0.96
2.50±0.46
2.78E-04
0.007
2.63±0.81
2.39±0.61
0.25
0.325
0.99±0.11
0.89±0.15
0.009a
0.022a
1.00±0.15
0.91±0.15
0.058a
meanBDNF methylation(%)
* pvalues less than or equal to 0.05 are in bold. a: Log-transformation was used.
0.283a
Table 3: Tests for population differences in BDNF methylation between the Xinjiang and Ningbo populations Control Han
Xinjiang(n=48) Ningbo(n=62)
p value
Age
77.71±5.54
79.63±7.85
0.136
mean BDNF methylation (%)
0.99±0.17
0.84±0.16
1.17E-05a
Age
76.71±4.60
74.59±8.31
0.350
mean BDNF methylation (%)
0.99±0.20
0.83±0.21
0.020a
Age
78.71±6.27
81.53±6.84
0.098
mean BDNF methylation (%)
1.00±0.15
0.85±0.14
1.37E-04a
Female
Male
* pvalues less than or equal to 0.05 are in bold. a: Log-transformation was used.
Table 4: Correlation tests between age and BDNF methylation level. Uygur age
Han
control r
Case p
r
Control p
r
p
case r
p
total mean
0.087
0.554 -0.141 0.340
0.054
0.716 0.303 0.036
0.176
0.410 -0.038 0.862 -0.085 0.692 0.553 0.005
female mean male mean
-7.88E-04 0.997 -0.150 0.484
0.207
0.332 0.073 0.735
* pvalues less than or equal to 0.05 are in bold. a: Log-transformation was used.
Table 5: Correlation tests between BDNF methylation level and important parameters. Uygur
CpG methylation level
Han
control r
p
case
control
r
p
r
-0.11
0.438
5
a
0.062
0.060
-0.10
a
9
p
case r
p
-0.18
0.218
1
a
-0.20
0.156
8
a
Total Glu(mmol/L) 0.024
0.873a 3.54E-0
TG(mmol/L) 0.494
4a
0.274
0.677a
0.462a
-0.03 TC(mmol/L) 8
0.797
HDL-C(mmol/ L)
0.161
0.273a
0.168 0.255 0.071 -0.07
0.593
-0.13
9
a
5
LDL-C(mmol/ L)
0.634
0.275 0.058 0.112
0.359a
0.232
a
638.00 0.169
0.251
0.255 0.080 0.070
0
0.283 0.052
Female -0.19 Glu(mmol/L) 9
0.351a
-0.24
0.257
1
a
0.203
0.342a
-0.06
-0.02
0.899
7
a
-0.25
TG(mmol/L) 0.451
0.027
0.329 0.177
6
0.209
0.270 0.203 0.101
0.761
7
0.225
-0.26 TC(mmol/L) 6 HDL-C(mmol/ L)
0.532
0.007a
0.280
0.184
-0.14
0.468
-0.19
9
a
7
0.637
0.217 0.309 0.490
0.356a
0.148
a
0.706
0.249 0.240
LDL-C(mmol/ L)
0.426 0.038 0.081
Male Glu(mmol/L) 0.114
0.597a
0.015
0.946
-0.33
a
3
0.112a
-0.39
0.054
8
a
-0.19
-0.22
TG(mmol/L) TC(mmol/L)
0.642
0.001
0.229 0.282
0.069
0.748
0.024 0.911 0.018
HDL-C(mmol/ L)
7
0.998
-0.09
a
7
0.005
0.982a
0.001
0.143
0.504
0.075 0.729 0.034
0.357 0.932
6
0.288
0.350 0.093 0.074
0.654a
0.371
a
0.874
0.319 0.129
LDL-C(mmol/ L)
* pvalues less than or equal to 0.05 are in bold. a: Log-transformation was used.
Figure 1: The locations of the four BDNF promoter CpG sites and the correlations among them.
①CpG1; ②CpG2; ③CpG3; ④CpG4, F stands for Forward primer, R stands for Reverse primer, S stands for Sequencing primer.
Figure 2: Comparisons of BDNF methylation levels between MCI cases and controls.
Figure 3: Tests for population differences of BDNF methylation between the Xinjiang and Ningbo populations.
Figure 4: Correlation tests between age and BDNF methylation level in different samples. A) Han MCI cases; B) Han healthy controls; C) Uygur MCI cases; D) Uygur healthy controls.
HIGHLIGHTS
► No association of BDNF methylation with MCI was found in either Uygur or Han Chinese populations.
► BDNF methylation levels of male Xinjiang Han MCI cases were higher than male Xinjiang Uygur MCI cases.
► BDNF methylation levels were significantly higher in Xinjiang Han Chinese in than Ningbo Han Chinese.
►The differences of populations and environments may affect levels of BDNF methylation.
PII: DOI: Reference:
S0165-1781(15)00462-X http://dx.doi.org/10.1016/j.psychres.2015.07.017 PSY9069
To appear in: Psychiatry Research Received date: 5 March 2015 Revised date: 14 June 2015 Accepted date: 9 July 2015 Cite this article as: Wenjuan Ma, Xiaohui Zhou, Huihui Ji, Mei Luo, Guili Liu, Jinyun Li, Qinwen Wang and Shiwei Duan, Population difference in the association of BDNF promoter methylation with mild cognitive impairment in the Xinjiang Uygur and Han populations, Psychiatry Research, http://dx.doi.org/10.1016/j.psychres.2015.07.017 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Population difference in the association of BDNF promoter methylation with mild cognitive impairment in the Xinjiang Uygur and Han populations
Wenjuan MaA,#, Xiaohui ZhouA,*,#, Huihui JiB,#, Mei LuoA, Guili LiuB, Jinyun LiB, Qinwen WangB,*, Shiwei DuanB,*
A: Department of Internal Medicine for Cadres, the First Affiliated Hospital of Xinjiang Medical University, Urumchi 830000, China B:Ningbo Key Lab of Behavior Neuroscience, Zhejiang Provincial Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, Zhejiang315211, China
#: ML, XZ and HJ are co-first authors of this work *:Correspondenceshould be addressed to Drs. Xiaohui Zhou ([email protected]), Qinwen Wang ([email protected]), and ShiweiDuan ([email protected])
Abstract
Background: Mild cognitive impairment (MCI) is a clinical transitional stage between normal aging and Alzheimer disease, which leads to memory loss and a reduction in cognitive function. Brain derived neurotrophic factor (BDNF) plays an important role in neuronal development and plasticity. The aim of this study was to explore the association between BDNF promoter methylation and MCI in the Xinjiang Uygur and Han populations. Methods: A DNA methylation assay using bisulfite pyrosequencing technology was performed on 96 Uygur and 96 Han Chinese individuals from Xinjiang province, China. Results: We found a significantly higher BDNF methylation level in Han MCI cases than in Uygur MCI cases in males from Xinjiang province (p = 0.022). In addition, the methylation level was significantly higher in Xinjiang Han healthy Chinese individuals (Northwestern China) than in Ningbo Han healthy Chinese individuals (Southeastern China) (Female and Male: p = 1.17E-05; Female: p = 0.020; Male: p = 1.37E-04). But our results showed no significant association of BDNF methylation with MCI in either the Uygur or Han Chinese populations (p > 0.05). Further gender-based subgroup analyses did not find any significant results (p > 0.05). Conclusion: Our results indicate that different levels of BDNF methylation may be present in different populations and environments. This study also provides further information regarding the relationship between BDNF methylation levels and MCI in Xinjiang Uygur and Han ethnic groups.
Keywords: mild cognitive impairment, DNA methylation, BDNF, population difference
1. Introduction Mild cognitive impairment (MCI) is a clinical transitional stage between normal aging and Alzheimer disease, which leads to memory loss and cognitive function damage (Petersen et al., 1999). A longitudinal study showed that the conversion rates of MCI to AD are 10% to 30% in one year, 20% to 66% in 3 to 4 years, and 60.5% to 100% in 5 to 10 years (Luis et al., 2003). The prevalence of MCI in different regions in China varies from 5.4% to 25.0% (Cheng and Xiao, 2014), and it was 9.89% in Xinjiang Province in 2007 (Xiaohui Zhou, 2009). DNA methylation is involved in memory, cognitive performance, and dementia. MCI is a complex disease that is influenced by genetic and environmental factors (Forstl et al., 2009). DNA methylation is an important form of regulation of genes that function in the human nervous system (Fabi et al., 2013; Mitchelmore and Gede, 2014)and those related to cognitive function (Bian et al., 2005; Lubin, 2011). Environmental factors could affect epigenetic modifications and thus further influence phenotypes and gene expression (Feil and Fraga, 2011). DNA methylation is a promising biomarker for the diagnosis of psychiatric disorders (Ikegame et al., 2013b). Brain derived neurotrophic factor (BDNF) is a key mediator of activity-dependent processes in the brain and has a major impact on neuronal development and plasticity (Karpova, 2014). BDNF has been shown to have a protective effect on neurons (Numakawa et al., 2010). The serum BDNF level is significantly lower in MCI cases than in healthy individuals (Angelucci et al., 2010; Yu et al., 2008). A growing body of evidence has suggested that epigenetic modifications of BDNF are associated with the pathophysiology of psychiatric disorders (Ikegame et al., 2013a; Mitchelmore and Gede, 2014). BDNF promoter methylation increases significantly with aging (Keleshian et al., 2013). BDNF methylation may be involved in regulating the process of recognition memory, particularly in the hippocampus (Munoz et al., 2010). A significantly higher level of BDNF promoter methylation was observed in AD cases than in controls in a previous study (Chang et al., 2014). In view of the previous findings, we hypothesized that BDNF promoter methylation might contribute to the risk of MCI. The purpose of this study was to determine whether the level of BDNF promoter methylation was associated with MCI.
2. Materials and Methods 2.1. Sample collection A total of 96 Uygur and 96 Han Chinese individuals over 60 years old were enrolled from the Xinjiang Uygur autonomous region between 2010 and 2014. The cases and the controls were matched by age, gender and ethnicity. Personal information including demographics, lifestyle, disease investigation, height, weight, blood pressure, blood glucose, and blood lipid serological indexes were collected through a unified epidemiological survey. All candidates were evaluated by the scales of mini-mental stale examination (MMSE), montreal cognitive assessment (MOCA), activity of daily living (ADL), and Hachinski ischemic (HIS). MCI patients were diagnosed by psychologists and neurologists according to the DSM-IV criteria
(Cooper, 1995). Detailed patient characteristics are provided in Table 1. We excluded patients if they
suffered from mental illness, congenital mental retardation, depression, or nervous system disorders such as stroke, Parkinson's disease, or brain tumors, or if they had a history of head injury, special medication, severe infectious disease or toxic encephalopathy. Blood samples from all individuals were stored at -80°C in 3.2% citrate sodium-treated tubes. Written informed consent forms were received from all participants. The institutional ethics committee of the First Affiliated Hospital at Xinjiang Medical University approved this study.
2.2. Biochemical analyses TG, TC, high-density lipoprotein (HDL), and low density lipoprotein (LDL) levels in the plasma and blood glucose concentrations were measured using an enzymatic end point assay (Zhou et al., 2012).
2.3. DNA preparation and methylation assay. Human genomic DNA was isolated from peripheral blood samples using a nucleic acid extraction automatic analyzer (Lab-Aid 820, Xiamen, China). The DNA concentration was measured with a NanoDrop 2000 (NanoDrop 2000, Wilmington, USA). Bisulfite pyrosequencing
technology was used to determine the CpG methylation levels in a fragment of the BDNF promoter. The bisulfite pyrosequencing assay combined sodium bisulfite DNA conversion chemistry (EZ DNA Methylation-GoldTM Kit; ZYMO RESEARCH), polymerase chain reaction (PCR) amplification (Zymo TaqTM PreMix, ZYMO RESEARCH) and sequencing by synthesis assay (Pyromark Gold Q24 Reagents; Qiagen) of the target sequence. The PCR primers were designed using the PyroMark Assay Design software v2.0.1.15. The PCR and pyrosequencing primers
contained
forward
primer:
5’-TTAGTATTTAAGAGGAAAAGGGAAAGTTGT-3’,
reverse
primer:
5’-Biotin-CCCCCATCATAACTAAAAATCT-3’ and sequencing primer: 5’-GGGAAAGTTGTTGGG-3’.
2.4. Statistical analyses SPSS software (version 16.0; SPSS, Inc., Chicago, IL, USA) was used for all statistical tests, including the t-test for two independent samples, two-way analysis of variance (ANOVA) and Pearson's regression analysis. Two independent sample t-tests were used for comparisons of BDNF methylation and other phenotypes between MCI cases and controls. Using Pearson's correlation analysis, associations between BDNF methylation and the metabolic characteristics of MCI subjects were assessed. A value of p < 0.05 was considered a statistically significant difference. The population differentiation was measured using the fixation index (Fst) and the detail information was shown in the previous paper (Duan et al., 2008).
3. Results Elevated BDNF promoter methylation has been shown to be associated with the risk of AD (Chang et al., 2014). In light of previous findings, we aimed to test whether BDNF methylation contributed to the risk of MCI, an intermediate state in the development of AD. As shown in Figure 1, we selected a fragment containing 4 CpG sites in the BDNF promoter region as described previously (Chang et al., 2014). Our results showed that the methylation levels of the four CpG sites were closely related to each other (r > 0.821, p < 0.01); therefore, the mean values of the four CpGs were used to represent BDNF promoter methylation in the following analyses. In the present study, we examined MCI cases and controls from the Uygur and Han Chinese populations in the Xinjiang province of China. Our results showed no significant association of BDNF methylation with the risk of MCI in either the Uygur or Han Chinese populations (Table 1 and Figure 2, p > 0.05). Further gender-based subgroup analyses also did not find any significant results (Table 1 and Figure 2, p > 0.05), suggesting that BDNF methylation changes are likely to occur during the progression from MCI to AD. Interestingly, we found that BDNF methylation was significantly different between healthy Xinjiang Han Chinese individuals (Northwestern China) and healthy Ningbo Han Chinese individuals (Southeastern China) (Table 3 and Figure 3, p = 1.17E-05), suggesting that BDNF methylation is environment-dependent. This environmental difference was replicated in both male and female subgroup comparisons (Table 3 and Figure 3, female: p = 0.020; male: p = 1.37E-04). In addition, there was a trend toward a difference in BDNF methylation between Uygur and Han Chinese controls (p = 0.091, Table 2 and Figure 2). We also found significantly higher BDNF methylation in male Han MCI cases than in male Uygur MCI cases (p = 0.022, Table 2 and Figure 2). The above results imply that BDNF methylation is likely to be influenced by population and environmental differences. We also measured a total of 5 phenotypes among our subjects. As shown in Table 1, our results indicate a significant contribution of higher TC levels to the risk of MCI in the Uygur Chinese population (p = 0.030). We also found significantly lower HDL-C levels in Uygur MCI cases than in Uygur controls (p = 0.010). A further gender-based subgroup analysis indicated that lower HDL-C levels were associated with the risk of
MCI in the female Uygur Chinese population (p = 0.024), and higher TC and LDL-C levels were associated with MCI in the male Han Chinese population (TC: p = 0.045; LDL-C: p = 0.005). Among the tested phenotypes, we observed a significant age difference between the Xinjiang Uygur and Han populations (case: p = 6.78E-09; control: p = 3.22E-09, Table 2). After correcting for age, we found significantly higher TG levels in the Uygur controls than in the Han Controls (p = 0.043, Table 2), significantly lower levels of TC, HDL-C and LDL-C in the Uygur cases than in the Han cases (TC: p = 0.042; HDL-C: p = 0.011; LDL-C: p = 0.013 Table 2), and significantly lower levels of TC and LDL-C in the Uygur controls than in the Han controls (TC: p = 4.63E-04; LDL-C: p = 0.008, Table 2). Gender-based analyses showed significantly lower levels of HDL-C and LDL-C in the female Uygur cases than in the female Han cases (HDL-C: p = 0.023; LDL-C: p = 0.049, Table 2), significantly lower levels of TC and LDL-C in the female Uygur controls than in the female Han controls (TC: p = 0.011; LDL-C: p = 0.015, Table 2), significantly lower levels of TC and LDL-C in the male Uygur cases than in the male Han cases (TC: p = 0.023; LDL-C: p = 0.007, Table 2), and significantly lower TC levels in the male Uygur controls than in the male Han controls (p = 0.049, Table 2). As shown in Table 4 and Figure 4, there was a significant positive correlation between age and BDNF methylation in the Han MCI cases (r = 0.303, p = 0.036), especially in women (r = 0.553, p = 0.005). There was also a significant correlation between TG levels and BDNF methylation in the Uygur controls (r = 0.494, p = 3.54E-04, Table 5). Further gender-based subgroup analysis replicated the positive correlation between TG and BDNF methylation in both male and female Uygur controls (female: r = 0.451, p = 0.027; male: r = 0.642, p = 0.001, Table 5). In addition, there was a significant correlation between HDL-C levels and BDNF methylation in the Uygur controls (r = 0.474, p = 0.019, Table 5) and a significant correlation between LDL-C levels and BDNF methylation in the Uygur cases (r = 0.426, p = 0.038).
4. Discussion Our results showed no significant association between BDNF promoter methylation and the risk of MCI in either the Uygur or the Han Chinese populations. However, there was a population difference in BDNF promoter methylation among male MCI patients in Xinjiang province. A BDNF promoter methylation difference was found between Han Chinese in Xinjiang in Northwestern China and those in Ningbo in Southeastern China. BDNF plays a major role in brain development and plasticity (Dennis and Levitt, 2005). Epigenetic modifications in BDNF can be considered as a mechanism for modulation of the memory forming process that is used to read memory consolidation in subtypes of specific genes (Lubin et al., 2008). Increased methylation of the BDNF promoter is an independent risk factor for deterioration of cognitive function after stroke (Kim et al., 2012). Increased BDNF promoter methylation was found in the peripheral blood of AD patients (Chang et al., 2014). However, our results show that BDNF promoter methylation levels do not differ between cases and controls. We can speculate that abnormal changes in BDNF promoter methylation may occur in the transformation process from MCI to AD. The BDNF methylation differences across different populations might arise from interactions between genetic and environmental factors (Fraser et al., 2012). DNA methylation is affected by several factors such as diet and lifestyle (Lim and Song, 2012). Food and diet have shortand long-term impacts on the epigenome and participate in BDNF methylation (Dauncey, 2012, 2014). In one study, plasma BDNF was significantly elevated in subjects who were assigned to a MeDiet + nuts compared to a control group (Sanchez-Villegas et al., 2011). BDNF level has been linked to healthy lifestyle factors (Chan et al., 2008). In addition, serum BDNF levels and environmental pressure are also closely related (Chen et al., 2013; van Winkel et al., 2014). Our results showed that BDNF promoter methylation in the Xinjiang Han elderly is significantly higher than in the Ningbo Han elderly. Previous study has found a strong correlation between BDNF methylation and BDNF val66Met polymorphism, which was shown to be associated with a number of psychiatric disorders (Neves-Pereira et al., 2005; Tocchetto et al., 2011; Verhagen et al., 2010) including AD (Lim et
al., 2014). A further analysis showed there was significant ethnic difference in the frequency distribution of BDNF val66Met polymorphism among Asians, Caucasians and Africans (Fst > 0.15, Supplemental Table 1). However, the frequency distribution of BDNF val66Met polymorphism between Japanese (HapMap-JPT) and Han Chinese (HapMap-CHB) was not significantly difference (Fst < 0.05, Supplemental Table 1). In the current study, we found there was significant difference of BDNF methylation between Xinjiang Han Chinese and Xinjiang Uyghur Chinese. A further check of the frequency of BDNF val66Met polymorphism in the tested samples will be intrigue to explore the interaction of BDNF val66Met polymorphism with BDNF methylation. There are some limitations to our study. First, the DNA methylation level changes in different tissues (Pinsonneault and Sadee, 2003). We examined BDNF methylation only in peripheral blood as a surrogate for brain tissue. The BDNF methylation level in brain tissue needs to be further studied. Second, the sample size was limited. A larger sample size is needed to verify our results. Third, we selected only four CpG sites, which might not represent overall BDNF promoter methylation. Investigating other CpG sites might help to elucidate the contribution of BDNF methylation to the risk of MCI. Fourth, elderly subjects usually have more than one disease. Although we tried to control for confounding factors, unknown factors still exist that might provide spurious results. Finally, some p values in the current study might not meet the threshold for significance after correction for multiple testing. Independent studies are needed to confirm our findings. In conclusion, our study suggests that BDNF promoter methylation levels vary in different Xinjiang populations, although BDNF gene methylation was not a significant contributor to MCI pathogenesis according to our results.
Acknowledgements The research was supported by the grants from the National Natural Science Foundation of China (81471398, 81070873 and 81371469), the 973 program from the Ministry of Science and Technology of China (2013CB835100), the Disciplinary Project of Ningbo University (B01350104900), and the K. C. Wong Magna Fund in Ningbo University.
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► No association of BDNF methylation with MCI was found in either Uygur or Han Chinese populations. ► BDNF methylation levels of male Xinjiang Han MCI cases were higher than male Xinjiang Uygur MCI cases. ► BDNF methylation levels were significantly higher in Xinjiang Han Chinese in than Ningbo Han Chinese. ►The differences of populations and environments may affect levels of BDNF methylation.
Table 1: Characteristics of BDNF methylation and important parameters in the Xinjiang Uygur and Han Chinese populations Uygur
Han
Case(n=48)
Control(n=48)
p value
Case(n=48)
Control(n=48)
p value
70.83±4.54
71.02±4.42
0.838
77.41±5.52
77.70±5.53
0.797
23.59±3.76
23.12±4.14
0.570
24.49±2.78
24.49±3.33
0.986
Glu(mmol/L)
5.37±2.24
5.22±1.10
0.955a
0.76±0.09
0.74±0.10
0.519a
TG(mmol/L)
2.57±1.50
2.62±1.77
0.869a
0.23±0.21
0.17±0.23
0.184a
TC(mmol/L)
4.25±0.68
3.70±1.58
0.030
5.18±1.61
4.99±1.35
0.549
HDL-C(mmol/L)
0.03±0.10
0.13±.22
0.010a
1.34±.28
1.38±0.33
0.517a
Age(years) BMI
LDL-C(mmol/L)
2.49±0.50
2.44±0.58
0.652
3.16±1.04
2.95±0.93
0.292
meanBDNF methylation(%)
0.92±0.14
0.90±0.12
0.659a
0.97±0.13
0.99±0.17
0.628a
BMI
22.21±2.53
22.53±4.69
0.774
23.64±2.52
24.85±4.11
0.226
Age(years)
69.67±3.81
69.58±3.98
0.941
76.50±4.55
76.71±4.60
0.875
Glu(mmol/L)
0.67±0.08
0.69±0.09
0.456a
0.75±0.09
0.76±0.13
0.611a
TG(mmol/L)
0.35±0.26
0.33±0.33
0.802a
0.27±0.23
0.19±0.23
0.239a
TC(mmol/L)
4.34±0.71
3.60±1.65
0.052
4.93±1.67
5.42±1.27
0.255
HDL-C(mmol/L)
0.03±0.10
0.15±0.22
0.024a
0.13±0.08
0.15±0.10
0.417a
LDL-C(mmol/L)
2.49±0.54
2.48±0.56
0.983
3.05±0.95
3.26±0.95
0.452
meanBDNF methylation(%)
0.94±0.14
0.89±0.09
0.203a
0.95±0.16
0.98±0.19
0.594a
Age(years)
72.00±5.00
72.46±4.46
0.739
78.33±6.32
78.71±6.27
0.837
BMI
24.96±4.32
23.72±3.53
0.283
25.34±2.82
24.15±2.37
0.121
Glu(mmol/L)
0074±0.15
0.73±0.08
0.647a
0.77±0.11
0.73±0.06
0.094a
TG(mmol/L)
0.31±0.29
0.29±0.33
0.805a
0.19±0.20
0.15±0.24
0.496a
Female
Male
TC(mmol/L)
4.17±0.66
3.81±1.55
0.307
5.44±1.56
4.58±1.33
0.045
HDL-C(mmol/L)
0.04±0.11
0.11±0.23
0.183a
0.11±0.10
0.11±0.11
0.963a
LDL-C(mmol/L)
2.50±0.46
2.39±0.61
0.510
3.38±0.96
2.63±0.81
0.005
meanBDNF methylation(%)
0.89±0.14
0.91±0.15
0.640a
0.99±0.11
0.99±0.14
0.933a
* pvalues less than or equal to 0.05 are in bold. a: Log-transformation was used.
Table 2: Tests for population differences of BDNF methylation and important parameters in the Xinjiang population Case(n=96) Han(n=48) Uygur(n=48)
Control(n=96) p value
Age(years)
77.42±5.52
70.83±4.54
6.78E-09
BMI
24.49±2.78
23.58±3.76
0.186
Glu(mmol/L)
5.92±1.53
5.37±2.24
TG(mmol/L)
1.91±0.97
TC(mmol/L)
adjusted p value
Han(n=48) Uygur(n=48)
p value
adjusted p value
77.71±5.53
71.02±0.08
3.22E-09
0.182
24.49±3.34
23.12±4.14
0.077
0.040
0.163a
0.200a
0.74±0.10
0.71±0.08
0.520a
0.106a
2.57±1.50
0.012a
0.838a
0.16±0.23
0.30±0.32
0.017a
0.043a
5.18±1.61
4.25±.68
3.92E-04
0.042
4.99±1.35
3.70±1.58
4.21E-05
4.63E-04
HDL-C(mmol/L)
1.34±0.28
1.11±0.26
1.15E-04a
0.011a
0.13±0.11
0.13±0.22
0.993a
0.356a
LDL-C(mmol/L)
3.16±1.04
2.49±0.50
1.45E-04
0.013
2.95±0.93
2.44±0.58
0.002
0.008
0.97±0.13
0.92±0.14
0.043 a
0.274a
0.99±0.17
0.90±0.12
0.006 a
Age(years)
76.50±4.54
69.67±3.81
9.88E-07
76.71±4.60
69.58±3.98
7.11E-07
BMI
23.64±2.52
22.21±2.53
0.057
0.021
24.85±4.11
22.53±4.69
0.075
0.053
a
a
a
meanBDNF methylation(%)
0.091a
female
Glu(mmol/L)
0.75±0.09
0.67±0.08
0.05
0.162
0.76±0.13
0.69±0.09
0.031
0.125a
TG(mmol/L)
0.27±0.23
0.35±0.26
0.239a
0.404a
0.19±0.23
0.33±0.33
0.094a
0.349a
TC(mmol/L)
4.93±1.67
4.34±0.71
0.123
0.409
5.42±1.27
3.60±1.65
9.19E-05
0.011
HDL-C(mmol/L)
0.13±0.08
0.03±0.10
4.45E-04
0.023a
0.15±0.10
0.15±0.22
0.933a
0.591a
LDL-C(mmol/L)
2.94±1.08
2.49±0.54
0.076
0.049
3.26±0.95
2.49±0.56
0.001
0.96±0.16
0.94±0.14
0.709a
0.306a
0.99±0.20
0.90±0.09
0.550a
Age(years)
78.33±6.31
72.00±4.50
3.60E-04
78.71±6.27
72.46±4.46
2.44E-04
BMI
25.34±2.82
24.96±4.32
0.721
0.438
24±2.37
23.72±3.53
0.625
0.394
a
0.454
a
0.73±0.06
0.73±0.08
0.840
a
0.751a
Mean BDNFmethylation(%)
0.015 0.176a
male
Glu(mmol/L)
0.77±0.11
0.74±0.15
0.412
TG(mmol/L)
0.19±0.20
0.31±0.29
0.101a
0.327a
0.15±0.24
0.29±0.33
0.097a
0.062a
TC(mmol/L)
5.44±1.55
4.17±0.66
0.001
0.023
4.58±1.33
3.81±1.55
0.072
0.049
HDL-C(mmol/L)
0.11±0.10
0.04±0.11
0.032a
0.139a
0.11±0.11
0.11±0.23
0.927a
0.466a
LDL-C(mmol/L)
3.38±0.96
2.50±0.46
2.78E-04
0.007
2.63±0.81
2.39±0.61
0.25
0.325
0.99±0.11
0.89±0.15
0.009a
0.022a
1.00±0.15
0.91±0.15
0.058a
meanBDNF methylation(%)
* pvalues less than or equal to 0.05 are in bold. a: Log-transformation was used.
0.283a
Table 3: Tests for population differences in BDNF methylation between the Xinjiang and Ningbo populations Control Han
Xinjiang(n=48) Ningbo(n=62)
p value
Age
77.71±5.54
79.63±7.85
0.136
mean BDNF methylation (%)
0.99±0.17
0.84±0.16
1.17E-05a
Age
76.71±4.60
74.59±8.31
0.350
mean BDNF methylation (%)
0.99±0.20
0.83±0.21
0.020a
Age
78.71±6.27
81.53±6.84
0.098
mean BDNF methylation (%)
1.00±0.15
0.85±0.14
1.37E-04a
Female
Male
* pvalues less than or equal to 0.05 are in bold. a: Log-transformation was used.
Table 4: Correlation tests between age and BDNF methylation level. Uygur age
Han
control r
Case p
r
Control p
r
p
case r
p
total mean
0.087
0.554 -0.141 0.340
0.054
0.716 0.303 0.036
0.176
0.410 -0.038 0.862 -0.085 0.692 0.553 0.005
female mean male mean
-7.88E-04 0.997 -0.150 0.484
0.207
0.332 0.073 0.735
* pvalues less than or equal to 0.05 are in bold. a: Log-transformation was used.
Table 5: Correlation tests between BDNF methylation level and important parameters. Uygur
CpG methylation level
Han
control r
p
case
control
r
p
r
-0.11
0.438
5
a
0.062
0.060
-0.10
a
9
p
case r
p
-0.18
0.218
1
a
-0.20
0.156
8
a
Total Glu(mmol/L) 0.024
0.873a 3.54E-0
TG(mmol/L) 0.494
4a
0.274
0.677a
0.462a
-0.03 TC(mmol/L) 8
0.797
HDL-C(mmol/ L)
0.161
0.273a
0.168 0.255 0.071 -0.07
0.593
-0.13
9
a
5
LDL-C(mmol/ L)
0.634
0.275 0.058 0.112
0.359a
0.232
a
638.00 0.169
0.251
0.255 0.080 0.070
0
0.283 0.052
Female -0.19 Glu(mmol/L) 9
0.351a
-0.24
0.257
1
a
0.203
0.342a
-0.06
-0.02
0.899
7
a
-0.25
TG(mmol/L) 0.451
0.027
0.329 0.177
6
0.209
0.270 0.203 0.101
0.761
7
0.225
-0.26 TC(mmol/L) 6 HDL-C(mmol/ L)
0.532
0.007a
0.280
0.184
-0.14
0.468
-0.19
9
a
7
0.637
0.217 0.309 0.490
0.356a
0.148
a
0.706
0.249 0.240
LDL-C(mmol/ L)
0.426 0.038 0.081
Male Glu(mmol/L) 0.114
0.597a
0.015
0.946
-0.33
a
3
0.112a
-0.39
0.054
8
a
-0.19
-0.22
TG(mmol/L) TC(mmol/L)
0.642
0.001
0.229 0.282
0.069
0.748
0.024 0.911 0.018
HDL-C(mmol/ L)
7
0.998
-0.09
a
7
0.005
0.982a
0.001
0.143
0.504
0.075 0.729 0.034
0.357 0.932
6
0.288
0.350 0.093 0.074
0.654a
0.371
a
0.874
0.319 0.129
LDL-C(mmol/ L)
* pvalues less than or equal to 0.05 are in bold. a: Log-transformation was used.
Figure 1: The locations of the four BDNF promoter CpG sites and the correlations among them.
①CpG1; ②CpG2; ③CpG3; ④CpG4, F stands for Forward primer, R stands for Reverse primer, S stands for Sequencing primer.
Figure 2: Comparisons of BDNF methylation levels between MCI cases and controls.
Figure 3: Tests for population differences of BDNF methylation between the Xinjiang and Ningbo populations.
Figure 4: Correlation tests between age and BDNF methylation level in different samples. A) Han MCI cases; B) Han healthy controls; C) Uygur MCI cases; D) Uygur healthy controls.
HIGHLIGHTS
► No association of BDNF methylation with MCI was found in either Uygur or Han Chinese populations.
► BDNF methylation levels of male Xinjiang Han MCI cases were higher than male Xinjiang Uygur MCI cases.
► BDNF methylation levels were significantly higher in Xinjiang Han Chinese in than Ningbo Han Chinese.
►The differences of populations and environments may affect levels of BDNF methylation.