Dysregulation of BDNF in Prefrontal Cortex in Alzheimer’s Disease

Abstract

Background:

Brain-derived neurotrophic factor (BDNF) is essential for neurogenesis and has been implicated in Alzheimer’s disease (AD). However, few studies have investigated together the epigenetic, transcriptional, and translational regulation of this peptide in the brain in relation to AD.

Objective:

To investigate mechanisms underlying how BDNF is possibly dysregulated in the brain in relation to aging and AD neuropathology.

Methods:

Prefrontal cortex tissues were acquired from the Manchester Brain Bank (N = 67). BDNF exon I, and exon IV-containing transcripts and total long 3’ transcript gene expression were determined by quantitative PCR and bisulfite pyrosequencing was used to quantify DNA methylation within promoters I and IV. Protein concentrations were quantified via ELISA.

Results:

BDNF exon IV and total long 3’ isoform gene expression levels negatively associated with donor’s age at death (IV: r = –0.291, p = 0.020; total: r = –0.354, p = 0.004). Expression of BDNF exon I- containing isoform was significantly higher in Met-carriers of the rs6265 variant, compared to Val-homozygotes, when accounting for donor ages (F = 6.455, p = 0.014). BDNF total long 3’ transcript expression was significantly lower in those with early AD neuropathology, compared to those without any neuropathology (p = 0.021). There were no associations between BDNF promoter I and IV methylation or protein levels with ages, rs6265 genotype or AD neuropathology status.

Conclusion:

Prefrontal cortex BDNF gene expression is associated with aging, rs6265 carrier status, and AD neuropathology in a variant-specific manner that seems to be independent of DNA methylation influences.

Keywords

Alzheimer’s disease BDNF DNA methylation prefrontal cortex

INTRODUCTION

Brain-derived neurotrophic factor (BDNF) is a neurotrophin that promotes neurogenesis, synaptic plasticity, and long-term potentiation (LTP) in the CNS [1, 2]. BDNF has been implicated in the ‘age-by-disease hypothesis’, in which BDNF expression is reduced in the aging brain and a reduction in BDNF expression has been associated with multiple neurological disorders [3].

Reductions in BDNF have been widely investigated as a mediator of age-associated decline in synaptic density and cognitive function [4], with a significant association between BDNF and cognitive aging being observed [5 –7]. However, the underlying mechanisms behind age-associated BDNF declines are not completely understood.

The human BDNF gene has a complex structure involving 9 promoters and 11 exons of which only the exon IX at the 5’ end contains the coding sequence [8]. The untranslated 3’ exons, through alternative splicing, lead to different transcripts that still contain common coding region at the 3^′ end. Therefore, through the use of alternative promoters and splicing mechanisms, various different BDNF transcripts with alternative 5’ untranslated regions (UTRs) can be generated that all code for the same BDNF protein. Finally, two alternative polyadenylated transcription stop sites in exon IX can lead to transcripts with either short or long 3^′ UTRs. A study has shown that while the short 3^′ UTR BDNF mRNA variant is restricted to the cell body in hippocampal neurons, the long 3^′ UTR mRNAs are also observed in dendrites [9]. Together, in the human brain, all exons are expressed, but to different degrees in different brain structures (for review, see [10]). It is thought that these different promoters allow BDNF to respond to a greater variety of stimuli that further result in the generation of different transcripts that are stable in multiple intracellular environments [8]. As BDNF promoters mediate differential BDNF isoform expression in various parts of the brain, it is thought that changes to their activity could affect cellular and behavioral phenotypes [11]. Epigenetic mechanisms, predominantly promoter methylation that generally serves to silence gene expression, have been shown to regulate BDNF expression [12]. BDNF promoter IV is one of the most widely investigated promoters in the contest of DNA methylation changes associated with alterations in BDNF expression: For example McKinney et al. [3] found in the orbital frontal cortex that DNA methylation at promoters I, II, and IV were increased in older people and negatively correlated with BDNF expression. Keller et al. [13], for example, found significant increases in DNA methylation at BDNF promoter IV in the Wernicke area from suicide subjects, when compared to controls, that correlated with lower mRNA levels for BDNF exon IV containing transcript. In the periphery, increased methylation at BDNF promoters I and IV have been found in blood DNA from patients with mild cognitive impairment (MCI) compared to controls and increased methylation at CpGs in promoter IV predicted conversion from MCI to Alzheimer’s disease (AD) [14]. Further studies in blood DNA have shown increased BDNF methylation at promoter I in AD cases compared to controls [15, 16] and increased peripheral BDNF promoter I and IV in amnestic MCI compared to controls that further predicted the conversion from MCI to AD [14]. Interestingly, the conversion from amnestic MCI to AD depended upon an interaction of methylation with a non-synonymous single nucleotide polymorphism (SNP) in the BDNF gene, rs6265 [17]. However, there are some conflicting reports not finding increased BDNF methylation in peripheral DNA in AD compared to controls [15, 18]. Within the CNS, Rao and colleagues [19], studying groups of 10 AD and 10 control prefrontal cortex samples, found significant decrease in total BDNF mRNA in the AD brain compared to control brains together with increased promoter DNA methylation. A reduction in prefrontal cortex BDNF expression in AD has also been found in a study by Buchman et al. [19] on 535 older participants. Li et al. [29] found a reduction in temporal cortex and frontal cortex in AD, but specifically in females. They further found that rs6265 associated with transcriptional regulation only in the female brains. Garzon et al. investigating individual BDNF variants found transcript specific decreases of BDNF in AD brains. Few studies have investigated together the epigenetic, genetic, transcriptional, and translational regulation of this peptide in the brain in relation to AD.

The aim of this study was to investigate mechanisms underlying the dysregulation of BDNF within the AD brains studying human prefrontal cortex tissue for BDNF protein levels, promoter-specific expression, promoter DNA methylation specifically at promoters for exons I and IV and the rs6265 genotype.

METHODS

Study population

Fresh, frozen tissue was taken from superior frontal gyrus (Brodmann area 8). Samples were acquired from donors through the Manchester Brain Bank. Ethical approval was granted from the Manchester Brain Bank Committee. Donors were participants of a large prospective cognitive aging cohort known as The University of Manchester Age and Cognitive Performance Research Cohort [20, 21] and included all those with brain material and available neuropathological data. All participants are white British (Supplementary Table 1).

Stratification into AD neuropathology groups were based on the National Institute on Aging-Alzheimer’s Association guidelines [22]. Briefly, the amyloid-β (Aβ) plaque score (Thal), neurofibrillary tangle stage (Braak), and neuritic plaque score (CERAD) were used to create an “ABC” score. Four groups were determined: Not, Low, Intermediate, and High AD neuropathologic change. Those with high levels of Aβ and neuritic plaques with low neurofibrillary tangle score were excluded (“ABC” score: A2-3, B0-1, C0-3), due to potential contributions by other co-morbidities.

Gene expression analysis

Brain tissue (∼30 mg) was extracted for RNA using TRIsure™ (Bioline, UK), quantified using the Nanodrop 2000c (Thermo Scientific, Wilmington, USA) and qualifies using the Agilent Bioanalyser. RIN values are given in Supplementary Table 1. The Tetro cDNA synthesis kit (Bioline, UK) was used to reverse transcribe total RNA (2 μg), according to the manufacturer’s protocol using random hexamers. Relative gene expression was analyzed using qPCR with SensiFAST^TM SYBR® Lo-ROX kit (Bioline), in accordance with the manufacturer’s protocol using primers for BDNF exon I containing transcript (F: CAGCATCTGTTGGGGAGACGA; R: GCCACCTTGTCCTCGGATGT), BDNF exon IV containing transcript (F: TGGGAGTTTTGGGGCCGAAG; R: TGGTCATCACTCTTCTCACCTGG), BDNF total long 3’, (F: GGACCCTTCAGAGGTGGCTC; R: GTCGGCTTGAGTGTGGTCCT), ACTB (F: CATCCTCACCCTGAAGTACC; R: ATAGCAACGTACATGGCTGG) and GAPDH (F: CCGCATCTTCTTTTGCGTCG; R: TGGAATTTGCCATGGGTGGA). qPCR was performed on a Stratagene Mx3000P qPCR system (Agilent) in duplicate. Relative gene expression, accounting for primer efficiencies and normalized to GAPDH and ACTB, were determined using the geometric averaging method described by Vandesompele and colleagues [23]. Those samples with gene expression levels were not detected (Ct≥40) were excluded from analyses.

Genotyping

DNA samples were extracted from peripheral blood samples, as described previously [24]. Genotyping was performed using the Kompetitive Allele Specific PCR (KASP) assay (LGC Ltd) in reaction volumes of 10 μl together with 5 ng of DNA that was run on a Stratagene MX3000P qPCR machine (Agilent). Fluorescence values were read by the MXPro software to enable genotype calling.

Protein quantification

Brain tissue (∼100 mg) were lysed using RIPA buffer (Sigma) supplemented with 1x protease inhibitor cocktail and 0.1 M PMSF, as described previously [25]. Quantification of BDNF protein was performed using the Human/Mouse BDNF DuoSet ELISA (R&D Systems). Protein levels were normalized to total protein levels in the assay (pg/mg of total protein).

DNA methylation analysis

Genomic DNA was extracted using the Isolate II Genomic DNA kit (Bioline) and 500 ng bisulfite-converted using the EpiMark Bisulfite Conversion Kit (New England Biolabs). Primers were used to amplify regions of the BDNF promoter I (F: TGAGTGATGATTAAATGGGGATTG; R: BIO-ACTATTAACTCACATTTAAAAAACCATAAC; S: TGGGGATTGGGGGGA) and promoter IV (F: GATTTTGGTAATTCGTGTATTAGAGTGTT; R: BIO-AGATTAAATGGAGTTTTCGTTGAT; S: AATGGAGTTTTCGTTGATGGGGTGCA) using MyTaq HS mix PCR reagents (Bioline). The BDNF promoter I and promoter IV amplicons contained 5 and 9 CpG sites, respectively. Amplicons were processed on the Qiagen Q24 Workstation and sequenced on the Qiagen Q24 pyrosequencer. DNA methylation levels across each amplicon were averaged. See Supplemental Figure 1 for locations of the regions analyzed.

Statistical analysis

All analyses were performed using IBM SPSS Statistics (v.25). BDNF isoform expression, protein and DNA methylation levels were log10 transformed prior to statistical analysis. Correlations between gene expression, DNA methylation, and protein levels with donor age were performed using Pearson correlation tests. Correlations between gene expression, DNA methylation, and protein levels were performed using Partial correlation tests, with donor age as a covariate. Differences in gene expression, DNA methylation and protein levels between rs6265 variant groups were assessed using independent student t-tests. Further, differences between groups while controlling for donor age were assessed using a one-way ANCOVA. Differences in gene expression, DNA methylation and protein levels between AD neuropathological groups were assessed using one-way ANOVA, as well as a one-way ANCOVA to control for age. Results are presented as mean and standard deviation, unless otherwise stated. Statistical significance was accepted when p < 0.05.

RESULTS

Clinical and pathological characteristics of the study population can be found in Table 1.

Table 1

Clinicopathological characteristics for the donor samples

Characteristic	Mean (SD)
Age at death (y)	87.5 (6.1)
Sex (male/female)	21/46
Post-mortem delay (h)^a	76.1 (43.7)
Brain weight (g)^b	1207.4 (137.4)
BDNF rs6265 (N)
Val/Val	39 (58%)
Val/Met	25 (37%)
Met/Met	3 (5%)
Thal score (N)
0 (A0)	17 (25%)
1 (A1)	11 (16%)
2 (A2)	6 (9%)
3 (A2)	17 (25%)
4 (A3)	9 (13%)
5 (A3)	7 (10%)
Braak score (N)^c
0 (B0)	4 (6%)
I (B1)	11 (16%)
II (B1)	18 (27%)
III (B2)	13 (19%)
IV (B2)	12 (18%)
V (B3)	6 (9%)
VI (B3)	2 (3%)
CERAD score (N)
None (C0)	18 (27%)
Sparse (C1)	19 (28%)
Moderate (C2)	18 (27%)
Frequent (C3)	12 (18%)

^aN = 60; ^bN = 43; ^cN = 66.

Relationship between BDNF gene expression, DNA methylation, and protein levels with age

The association between BDNF exon I and IV and total long 3’ isoform expression with the age at death of donors was investigated (Fig. 1). There was a negative association between expression of exon IV containing (r = –0.291, p = 0.020; Fig. 1B) and total long 3’ (r = –0.354, p = 0.004; Fig. 1C) BDNF isoforms with age; however, no relationships were evident for BDNF exon I containing isoform (r = –0.201, p = 0.149; Fig. 1A).

Fig.1

Associations between donor age at death with (A) BDNF I variant, (B) BDNF IV variant, and (C) BDNF total mRNA expression.

There were no associations between BDNF protein levels (r = –0.143, p = 0.256) or DNA methylation levels (promoter I: r = –0.038, p = 0.761; promoter IV: r = 0.177, p = 0.156) with donor ages.

BDNF protein levels (pg/ml) did not differ between females (117.5±48.549) and males (127.022±36.528) = –0.783, p = 0.437. There were also no differences in expression of BDNF exon-4 containing transcripts (p = 0.597) and total long 3’UTR (p = 0.39) between genders; however, there was significantly increased BDNF exon-1 containing transcripts in males than females (p = 0.001). Regarding DNA methylation, there were no significant differences between genders in BDNF promoter 1 (p = 0.425) and promoter 4 (p = 0.606) methylation.

Correlations between BDNF gene expression, DNA methylation, and protein levels

The relationships between BDNF gene expression, DNA methylation and protein levels can be seen in Table 2. Since donor age significantly correlated with BDNF gene expression, correlations were controlled for donor ages throughout.

Table 2

Partial correlation matrix, controlling for donor ages, between BDNF gene expression, DNA methylation and protein levels

	Gene expression			DNA methylation
	BDNF I	BDNF IV	BDNF Total	Promoter I	Promoter IV	Protein
BDNF I
BDNF IV	0.586***
BDNF Total	0.327*	–0.233†
Promoter I	–0.282*	–0.181	–0.206
Promoter IV	–0.091	0.015	–0.007	0.383
Protein	0.251†	0.018	0.054	0.074	0.044

Results displayed are partial correlation coefficient values. ^†p < 0.10. *p < 0.05. ***p < 0.001.

Briefly, BDNF exon I isoform expression positively correlated with BDNF exon IV and total long 3’ isoform expression. BDNF exon IV expression did not correlate with total long 3’ variant expression. Promoter I DNA methylation negatively correlated with BDNF exon I isoform expression levels, however this correlation was lost (p = 0.08) when account for RIN values (Supplementary Table 2). However, there were no associations between promoter IV methylation and BDNF exon IV isoform expression levels. Protein levels were not associated with either BNDF exon I, exon IV, or total long 3’UTR RNA expression or DNA methylation levels.

Relationship between BDNF gene expression, DNA methylation, and protein levels with rs6265 variant

The rs6265 variant was in Hardy-Weinberg equilibrium in the study population (χ² = 0.162, p = 0.687).

To explore the differences in BDNF gene expression levels with the rs6265 variant, donors were stratified into Val-homozygotes and Met-allele carriers. There were no differences in BDNF exon I (t = –1.592, p = 0.118) and total long 3’ (t = 0.122, p = 0.904) variant gene expression levels between the two groups. However, the Met-allele carriers had significantly higher BDNF exon IV isoform expression compared to Val-homozygotes (t = –2.640, p = 0.010) (Fig. 2). This difference remained after controlling for donor age at death (F = 6.455, p = 0.014) and age AND RIN values (F = 7.229, p = 0.009).

Fig.2

Difference in BDNF gene expression between rs6265 Val-homozygotes and Met-carriers. BDNF I: Val-homozygotes N = 28, Met-carriers N = 25. BDNF IV: Val-homozygotes N = 37, Met-carriers N = 27. BDNF total long 3’UTR: Val-homozygotes N = 38, Met-carriers N = 28. *p < 0.05.

There were no differences in BDNF protein levels (t = 0.446, p = 0.657) or DNA methylation levels (promoter 1: – 0.435, p = 0.665; promoter 4: – 0.755, p = 0.453) between rs6265 variants.

Relationship between BDNF gene expression, DNA methylation, and protein levels with AD pathology

To investigate the difference in BDNF gene expression with AD pathology, donors were stratified based on the NIA-AA “ABC” score, which considers the amyloid plaque, neuritic plaque and neurofibrillary tangle scores. These groups were Not, Low, Intermediate, and High AD neuropathological change.

Overall, there were differences in BDNF total long 3’ isoform gene expression levels between AD pathological groups (F = 3.074, p = 0.035). Specifically, inter-group comparisons revealed a significant downregulation of BDNF total long 3’, isoform expression in the Low AD group, compared to the Not AD group (p = 0.021) (Fig. 3).

Fig.3

Difference in BDNF total long 3’variant gene expression between AD neuropathology groups. N = 16 (Not), 14 (Low), 26 (Intermediate), 5 (High). *p < 0.05.

This difference was also apparent when accounting for donor age at death (overall comparison: F = 3.323, p = 0.026; post-hoc comparison: p = 0.021), however when including age AND RIN values, there were no differences (F = 1.909, p = 0.139).

There were no differences in BDNF exon I (F = 2.766, p = 0.053) or IV (F = 0.405, p = 0.750) isoform expression levels between the AD neuropathological groups. Further, there were no differences in protein (F = 0.953, p = 0.421) or DNA methylation (promoter 1: F = 1.019, p = 0.391; promoter 4: F = 1.009, p = 0.396) levels between groups.

DISCUSSION

In the prefrontal cortex, BDNF gene expression was associated with donor age, rs6265 carrier status and early AD neuropathology in a variant-specific manner. These associations were independent of any influences of DNA methylation or protein levels. Thus, we provide further evidence to the complex mechanisms dysregulating central BDNF during aging and neurodegeneration.

The majority of research investigating age associations of BDNF levels in humans has focused on peripheral measures. Specifically, many reports suggest a gradual reduction in plasma and serum concentrations during aging [6 , 26–28]. There is, however, limited knowledge of BDNF regulation in human brain tissue across ages. We report significant reductions of BDNF exon IV and total long 3’, but not exon I, containing isoforms between the ages of 72 and 104 years old. This corroborates findings from that of Oh and colleagues, who also reported reductions in total and exon IV- containing RNAs in the prefrontal cortex, without any differences in the exon I-containing transcript, between ages 16 to 96 years [7]. Because only exon IX contains the coding region, all the different exon-containing RNA transcripts will be translated to a single species of BDNF polypeptide. It is hypothesized that this sophisticated gene serves to fine-tune a dynamic transcriptional regulation in different cell types by different neuronal activities. For example, it has been shown in rodent studies that fear conditioning increased both BDNF exon I and IV containing RNA in hippocampus, but only exon IV in the CA1 region [29, 30], while fear memory extinction elevated BDNF exon I and IV in prefrontal cortex [31]. Interestingly, a study on contextual fear conditioning caused a significant increase of BDNF exon I in WT hippocampus while the levels of exon IV remained unchanged [32]. This highlights that the different exons can be differently regulated. Mechanistically, within BDNF exon IV promoter three calcium responsive elements (i.e., CaRE1, 2 and 3) have been identified regulating calcium-mediated BDNF IV transcription, while in promoter I there is one CRE in promoter I that can be differently regulated by different Ca2+-stimulated protein kinases and other Ca2+-stimulated intracellular molecules [33]. The calcium hypothesis of aging [34, 35] hypothesizes a dysregulation of intracellular Ca2+ homeostasis is a primary factor contributing to aging-related learning and memory impairments in humans and other mammals that may further relate to AD. Perhaps this may reflect differential regulation of BDNF transcripts. Interestingly a NF-κB [36] site and an E-box [37] have been identified in exon IV promoter that again allow differential regulation and may again reflect age-related changes in these regulatory factors in the brain [38].

We report variant-specific associations with the rs6265 variant. Specifically, Met-carriers had an upregulation of BDNF transcripts containing exon IV, but not exon I or total long 3’UTR transcripts, compared to Val-homozygotes. The effect of the rs6265 polymorphism on BDNF gene expression is largely unknown [39]. A previous study involving over 500 prefrontal cortex donor samples revealed no differences of BDNF gene expression between rs6265 genotypes [40]. Despite the superior statistical power in this analysis, expression levels of different transcript variants were not reported, rather, only total expression. Given our preliminary insight suggesting the influence of the rs6265 variant may be transcript-specific in BDNF expression, it would be interesting to replicate our analysis in this population.

The reduction in BDNF expression with AD neuropathology is in agreement with other reports analyzing prefrontal [40], frontal [41], parietal [42], and temporal [41] cortical tissues, as well as the hippocampus [41]. Interestingly, our results further suggest the association between expressions and neuropathology magnitude may be stage specific. Specifically, those with early AD neuropathology having significant BDNF downregulation seem to be particularly affected. Increased neuroinflammation is suspected to have a major role in AD progression. The predominant hypothesis suggests levels of neuroinflammation peaks early on, possibly reflecting an initial anti-inflammatory response, followed by a second peak during conversion from MCI to AD, which may indicate a pro-inflammatory shift [43, 44]. This complex relationship may be related to the microglial reaction following the deposition and propagation of amyloid and hyperphosphorylated tau pathologies [45]. Numerous studies demonstrate that neuroinflammation in turn affects the expression of BDNF within the brain; therefore, reduction of BDNF expression and function may be a key mechanism underlying the negative impact of pro-inflammatory cytokines on neuroplasticity [46].

There are a number of limitations to this study. Variations in postmortem times and RIN values (Supplementary Table 1) impacted some of the results such as BDNF promoter I methylation and exon I-containing transcript expression, that when we adjusted for, significance was lost. Also, some RNA samples were unable to clearly measured for all transcripts from the total 67 subjects (i.e., exon I, n = 53; exon IV, n = 64; long 3’UTR, n = 66). A further confounding variable is that the prefrontal cortex samples also contain relatively heterogeneous cell populations that were not able to control for. Finally, we only investigated specific promoters and transcripts containing exon I, exon IV, and long 3’UTR, though it would be interesting to investigate further regions of the BDNF gene and more complete coverage of all the different transcripts.

Conclusion

In conclusion, we report prefrontal cortex BDNF gene expression is associated with aging, rs6265 carrier status, and AD neuropathology in a variant-specific manner. This dysregulation seems to be independent of DNA methylation influences at the I and IV promoters. These results add further evidence to the complex regulation of the BDNF gene within the cortex.

DISCLOSURE STATEMENT

Authors’ disclosures available online (https://www.j-alz.com/manuscript-disclosures/19-0049r2).

Footnotes

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

References

Kang

, Schuman

(1995) Long-lasting neurotrophin-induced enhancement of synaptic transmission in the adult hippocampus. Science 267, 1658–1662.

Figurov

, Pozzo-Miller

, Olafsson

, Wang

, Lu

(1996) Regulation of synaptic responses to high-frequency stimulation and LTP by neurotrophins in the hippocampus. Nature 381, 706–709.

McKinney

, Lin

C-W

, Oh

, Tseng

, Lewis

, Sibille

(2015) Hypermethylation of BDNF and SST genes in the orbital frontal cortex of older individuals: A putative mechanism for declining gene expression with age. Neuropsychopharmacology 40, 2604–2613.

, Nagappan

, Lu

(2014) BDNF and synaptic plasticity, cognitive function, and dysfunction. Handb Exp Pharmacol 220, 223–250.

Komulainen

, Pedersen

, Hänninen

, Bruunsgaard

, Lakka

, Kivipelto

, Hassinen

, Rauramaa

, Pedersen

, Rauramaa

(2008) BDNF is a novel marker of cognitive function in ageing women: The DR’s EXTRA Study. Neurobiol Learn Mem 90, 596–603.

Erickson

, Prakash

, Voss

, Chaddock

, Heo

, McLaren

, Pence

, Martin

, Vieira

, Woods

, McAuley

, Kramer

(2010) Brain-derived neurotrophic factor is associated with age-related decline in hippocampal volume. J Neurosci 30, 5368–5375.

, Lewis

, Sibille

(2016) The role of BDNF in age-dependent changes of excitatory and inhibitory synaptic markers in the human prefrontal cortex. Neuropsychopharmacology 41, 3080–3091.

Pruunsild

, Kazantseva

, Aid

, Palm

, Timmusk

(2007) Dissecting the human BDNF locus: Bidirectional transcription, complex splicing, and multiple promoters. Genomics 90, 397–406.

, Gharami

, Liao

G-Y

, Woo

, Lau

, Vanevski

, Torre

, Jones

, Feng

, Lu

, Xu

(2008) Distinct role of long 3’ UTR BDNF mRNA in spine morphology and synaptic plasticity in hippocampal neurons. Cell 134, 175–187.

10.

Cattaneo

, Cattane

, Begni

, Pariante

, Riva

(2016) The human BDNF gene: Peripheral gene expression and protein levels as biomarkers for psychiatric disorders. Transl Psychiatry 6, e958e958.

11.

Hing

, Sathyaputri

, Potash

(2018) A comprehensive review of genetic and epigenetic mechanisms that regulate BDNF expression and function with relevance to major depressive disorder. Am J Med Genet Part B Neuropsychiatr Genet 177, 143–167.

12.

Ikegame

, Bundo

, Murata

, Kasai

, Kato

, Iwamoto

(2013) DNA methylation of the BDNF gene and its relevance to psychiatric disorders. J Hum Genet 58, 434–438.

13.

Keller

, Sarchiapone

, Zarrilli

, Videtic

, Ferraro

, Carli

, Sacchetti

, Lembo

, Angiolillo

, Jovanovic

, Pisanti

, Tomaiuolo

, Monticelli

, Balazic

, Roy

, Marusic

, Cocozza

, Fusco

, Bruni

, Castaldo

, Chiariotti

(2010) Increased BDNF promoter methylation in the Wernicke area of suicide subjects. Arch Gen Psychiatry 67, 258–267.

14.

Xie

, Xu

, Liu

, Jiang

, Zhang

, Cui

, Zhang

, Xu

(2017) Elevation of peripheral BDNF promoter methylation predicts conversion from amnestic mild cognitive impairment to Alzheimer’s disease: A 5-year longitudinal study. J Alzheimers Dis 56, 391–401.

15.

Chang

, Wang

, Ji

, Dai

, Xu

, Jiang

, Hong

, Ye

, Zhang

, Zhou

, Liu

, Li

, Chen

, Li

, Zhou

, Zhuo

, Zhang

, Yin

, Mao

, Duan

, Wang

(2014) Elevation of peripheral BDNF Promoter methylation links to the risk of Alzheimer’s disease. PLoS One 9, e110773.

16.

Nagata

, Kobayashi

, Ishii

, Shinagawa

, Nakayama

, Shibata

, Kuerban

, Ohnuma

, Kondo

, Arai

, Yamada

, Nakayama

(2015) Association between DNA methylation of the BDNF promoter region and clinical presentation in Alzheimer’s disease. Dement Geriatr Cogn Dis Extra 5, 64–73.

17.

Xie

, Liu

, Jiang

, Zhang

, Cui

, Zhang

, Xu

(2017) DNA methylation and tag SNPs of the BDNF gene in conversion of amnestic mild cognitive impairment into Alzheimer’s disease: A cross-sectional cohort study. J Alzheimers Dis 58, 263–274.

18.

Carboni

, Lattanzio

, Candeletti

, Porcellini

, Raschi

, Licastro

, Romualdi

(2015) Peripheral leukocyte expression of the potential biomarker proteins Bdnf, Sirt1, and Psen1 is not regulated by promoter methylation in Alzheimer’s disease patients. Neurosci Lett 605, 44–48.

19.

Rao

, Keleshian

, Klein

, Rapoport

(2012) Epigenetic modifications in frontal cortex from Alzheimer’s disease and bipolar disorder patients. Transl Psychiatry 2, e132.

20.

Rabbitt

PMA

, McInnes

, Diggle

, Holland

, Bent

, Abson

, Pendleton

, Horan

(2004) The University of Manchester Longitudinal Study of Cognition in Normal Healthy Old Age, 1983 through 2003. Aging Neuropsychol Cogn 11, 245–279.

21.

Robinson

, Davidson

, Horan

, Pendleton

, Mann

DMA

(2018) Pathological correlates of cognitive impairment in The University of Manchester Longitudinal Study of Cognition in Normal Healthy Old Age. J Alzheimers Dis 64, 483–496.

22.

Hyman

, Phelps

, Beach

, Bigio

, Cairns

, Carrillo

, Dickson

, Duyckaerts

, Frosch

, Masliah

, Mirra

, Nelson

, Schneider

, Thal

, Thies

, Trojanowski

, Vinters H

, Montine

(2012) National Institute on Aging-Alzheimer’s Association guidelines for the neuropathologic assessment of Alzheimer’s disease. Alzheimers Dement 8, 1–13.

23.

Vandesompele

, De Preter

, Pattyn

, Poppe

, Van Roy

, De Paepe

, Speleman

(2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3, RESEARCH0034.

24.

Bradburn

, McPhee

, Bagley

, Carroll

, Slevin

, Al-Shanti

, Barnouin

, Hogrel

J-Y

, Pääsuke

, Gapeyeva

, Maier

, Sipilä

, Narici

, Robinson

, Mann

, Payton

, Pendleton

, Butler-Browne

, Murgatroyd

(2018) Dysregulation of C-X-C motif ligand 10 during aging and association with cognitive performance. Neurobiol Aging 63, 54–64.

25.

Bradburn

, McPhee

, Bagley

, Sipila

, Stenroth

, Narici

, Pääsuke

, Gapeyeva

, Osborne

, Sassano

, Meskers

CGM

, Maier

, Hogrel

J-Y

, Barnouin

, Butler-Browne

, Murgatroyd

(2016) Association between osteocalcin and cognitive performance in healthy older adults. Age Ageing 45, 844–849.

26.

Passaro

, Dalla Nora

, Morieri

, Soavi

, Sanz

, Zurlo

, Fellin

, Zuliani

(2015) Brain-derived neurotrophic factor plasma levels: Relationship with dementia and diabetes in the elderly population. J Gerontol A Biol Sci Med Sci 70, 294–302.

27.

Lommatzsch

, Zingler

, Schuhbaeck

, Schloetcke

, Zingler

, Schuff-Werner

, Virchow

(2005) The impact of age, weight and gender on BDNF levels in human platelets and plasma. Neurobiol Aging 26, 115–123.

28.

Golden

, Emiliano

, Maudsley

, Windham

, Carlson

, Egan

, Driscoll

, Ferrucci

, Martin

, Mattson

(2010) Circulating brain-derived neurotrophic factor and indices of metabolic and cardiovascular health: Data from the Baltimore Longitudinal Study of Aging. PLoS One 5, e10099.

29.

Lubin

, Roth

, Sweatt

(2008) Epigenetic regulation of bdnf gene transcription in the consolidation of fear memory. J Neurosci 28, 10576–10586.

30.

Fuchikami

, Yamamoto

, Morinobu

, Takei

, Yamawaki

(2010) Epigenetic regulation of BDNF gene in response to stress. Psychiatry Investig 7, 251.

31.

Rattiner

, Davis

, Ressler

(2004) Differential regulation of brain-derived neurotrophic factor transcripts during the consolidation of fear learning. Learn Mem 11, 727–731.

32.

L-C

, Gean

P-W

(2007) Transcriptional regulation of brain-derived neurotrophic factor in the amygdala during consolidation of fear memory. Mol Pharmacol 72, 350–358.

33.

Zheng

, Zhou

, Moon

, Wang

(2012) Regulation of brain-derived neurotrophic factor expression in neurons. Int J Physiol Pathophysiol Pharmacol 4, 188–200.

34.

Khachaturian

(1994) Calcium hypothesis of Alzheimer’s disease and brain aging. Ann N Y Acad Sci 747, 1–11.

35.

Khachaturian

(1987) Hypothesis on the regulation of cytosol calcium concentration and the aging brain. Neurobiol Aging 8, 345–346.

36.

Lipsky

, Xu

, Zhu

, Kelly

, Terhakopian

, Novelli

, Marini

(2001) Nuclear factor kappaB is a critical determinant in N-methyl-D-aspartate receptor-mediated neuroprotection. J Neurochem 78, 254–264.

37.

Jiang

, Tian

, Du

, Copeland

, Jenkins

, Tessarollo

, Wu

, Pan

, Hu

X-Z

, Xu

, Kenney

, Egan

, Turley

, Harris

, Marini

, Lipsky

(2008) BHLHB2 controls Bdnf promoter 4 activity and neuronal excitability. J Neurosci 28, 1118–1130.

38.

Zhang

, Li

, Purkayastha

, Tang

, Zhang

, Yin

, Li

, Liu

, Cai

(2013) Hypothalamic programming of systemic ageing involving IKK-β, NF-κB and GnRH. Nature 497, 211–216.

39.

Tsai

S-J

(2018) Critical issues in BDNF Val66Met genetic studies of neuropsychiatric disorders. Front Mol Neurosci 11, 156.

40.

Buchman

, Yu

, Boyle

, Schneider

, De Jager

, Bennett

(2016) Higher brain BDNF gene expression is associated with slower cognitive decline in older adults. Neurology 86, 735–741.

41.

G-D

, Bi

, Zhang

D-F

, Xu

, Luo

, Wang

, Fang

, Li

, Zhang

, Yao

Y-G

(2017) Female-specific effect of the BDNF gene on Alzheimer’s disease. Neurobiol Aging 53, 192.e11–192.e19.

42.

Garzon

, Yu

, Fahnestock

(2004) A new brain-derived neurotrophic factor transcript and decrease in brain-derived neurotrophic factor transcripts 1, 2 and 3 in Alzheimer’s disease parietal cortex. J Neurochem 82, 1058–1064.

43.

Calsolaro

, Edison

(2016) Neuroinflammation in Alzheimer’s disease: Current evidence and future directions. Alzheimers Dement 12, 719–732.

44.

Fan

, Aman

, Ahmed

, Chetelat

, Landeau

, Ray Chaudhuri

, Brooks

, Edison

(2015) Influence of microglial activation on neuronal function in Alzheimer’s and Parkinson’s disease dementia. Alzheimers Dement 11, 608–621.e7.

45.

Morales

, Jiménez

, Mancilla

, Maccioni

(2013) Tau oligomers and fibrils induce activation of microglial cells. J Alzheimers Dis 37, 849–856.

46.

Calabrese

, Rossetti

, Racagni

, Gass

, Riva

, Molteni

(2014) Brain-derived neurotrophic factor: A bridge between inflammation and neuroplasticity. Front Cell Neurosci 8, 430.