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Open Access

Peer-reviewed

Research Article

DNA methylation patterns of LINE-1 and Alu for pre-symptomatic dementia in type 2 diabetes

  • Chanachai Sae-Lee ,

    Roles Conceptualization, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft

    c.sae-lee2@ncl.ac.uk

    Affiliations Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom, Research division, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand

    ⨯
  • Julien De Biasi,

    Roles Writing – review & editing

    Affiliation Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, United Kingdom

    ⨯
  • Natassia Robinson,

    Roles Writing – review & editing

    Affiliation Institute of Health & Society, Newcastle University, Newcastle upon Tyne, United Kingdom

    ⨯
  • Timothy M. Barrow,

    Roles Supervision, Writing – review & editing

    Affiliation Faculty of Health Sciences and Wellbeing, University of Sunderland, Sunderland, United Kingdom

    ⨯
  • John C. Mathers,

    Roles Supervision, Writing – review & editing

    Affiliation Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom

    ⨯
  • Georgios Koutsidis,

    Roles Writing – review & editing

    Affiliation Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, United Kingdom

    ⨯
  • Hyang-Min Byun

    Roles Conceptualization, Supervision, Writing – review & editing

    Affiliation Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom

    ⨯

Abstract

The identification of early markers of dementia is important for higher-risk populations such as those with type 2 diabetes (T2D). Retrotransposons, including long interspersed nuclear element 1 (LINE-1) and Alu, comprise ~40% of the human genome. Although dysregulation of these retrotransposons can induce aberrant gene regulation and genomic instability, their role in the development of pre-symptomatic dementia (PSD) among T2D patients is unknown. Here, we examined locus-specific changes in LINE-1 and Alu methylation in PSD and the potential to offset these changes via supplementation with folate and vitamin B12. We interrogated DNA methylation patterns corresponding to 22,352 probes for LINE-1 and Alu elements using publicly-available Illumina Infinium 450K methylation datasets from i) an 18-month prospective study in 28 T2D patients (GSE62003) and ii) an intervention study in which 44 individuals were supplemented with folic acid (400 μg/day) and vitamin B12 (500 μg/day) over two years (GSE74548). We identified 714 differentially methylated positions (DMP) mapping to retrotransposons in T2D patients who developed PSD in comparison to those who did not (PFDR < 0.05), comprised of 2.4% (228 probes) of all LINE-1 probes and 3.8% (486 probes) of all Alu probes. These loci were enriched in genes with functions related to Alzheimer's disease and cognitive decline, including GNB5, GNG7 and PKN3 (p < 0.05). In older individuals supplemented with folate/vitamin B12, 85 (11.9%) PSD retrotransposon loci showed significant changes in methylation (p < 0.05): participants with the MTHFR CC genotype predominantly showed hypermethylation at these loci, while hypomethylation was observed more frequently in those with the TT genotype. In T2D patients, LINE-1 and Alu elements are differentially methylated in PSD in a locus-specific manner and may offer clinical utility in monitoring risk of dementia. Further work is required to examine the potential for dietary supplementation in lowering the risk of PSD.

Citation: Sae-Lee C, Biasi JD, Robinson N, Barrow TM, Mathers JC, Koutsidis G, et al. (2020) DNA methylation patterns of LINE-1 and Alu for pre-symptomatic dementia in type 2 diabetes. PLoS ONE 15(6): e0234578. https://doi.org/10.1371/journal.pone.0234578

Editor: Ruslan Kalendar, University of Helsinki, FINLAND

Received: January 24, 2020; Accepted: May 28, 2020; Published: June 11, 2020

Copyright: © 2020 Sae-Lee et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All data files are available in Gene Expression Omnibus with the identifiers 10.1016/j.neurobiolaging.2014.12.023 and 10.1186/s13148-015-0154-5 (GSE62300 and GSE74548).

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

List of abbreviations: T2D, Type 2 diabetes mellitus; LINE-1, Long Interspersed Nuclear Element 1; AD, Alzheimer’s disease; PSD, Pre-symptomatic dementia; SAM, S-adenosylmethionine; MTHFR, Methylenetetrahydrofolate reductase; IDCD, Israel Diabetes and Cognitive Decline; CDR, Clinical dementia rating; SD, Standard deviation; DMP, Differentially methylated position; GNB5, G Protein Subunit β 5; GNG7, G Protein Subunit γ 7; PKN3, Protein Kinase N3; SLC7A14, Solute Carrier Family 7 Member 14; TPD52, Tumor Protein D52; GNA12, G Protein Subunit Alpha 12

Introduction

Type 2 diabetes mellitus (T2D) is a metabolic disease affecting more than 200 million people worldwide in 2010, and global prevalence is predicted to increase to more than 400 million people by 2030 [1]. T2D is a recognised risk factor for dementia and for cognitive dysfunction in older people, affecting domains of processing speed, cognitive flexibility, learning and memory [2–7]. Alzheimer's disease (AD) is the most common cause of dementia and its development is associated with insulin resistance in the brain [8]. Up to 80% of AD patients have either impaired fasting blood glucose or T2D, and these conditions are associated with cell death in the brain and loss of β-cells in the pancreas [9].

To date, the characteristics of T2D patients who go on to develop dementia are unclear. Epigenetic changes occur during cognitive dysfunction and the development of dementia in T2D patients and, therefore, have potential as disease biomarkers. Retrotransposons, including long interspersed nuclear element 1 (LINE-1) and Alu, comprise approximately 40% of the human genome [10]. There are one-million copies of Alu and over 500,000 copies of LINE-1 in the human genome, which can replicate and integrate themselves into new locations throughout the genome [11–13]. The evolutionary age of these elements, that is the timing of their insertion into the human genome, can be estimated through sequence variants that facilitate their categorisation into subfamilies. Younger LINE-1 and Alu subfamilies have retained the ability to retrotranspose within the human genome [12, 14], and incorporation of these elements can interfere with the expression of adjacent genes, disrupting regulatory sequences of exon-intron interactions [15–17]. Aberrant activity of transposable elements has been implicated in neurological disorders, such as multiple sclerosis and AD, and can promote neuronal loss [18–20]. Furthermore, LINE-1 and Alu methylation has been widely measured as surrogate marker for global DNA methylation [15, 21–25]. Hypomethylation of these elements is associated with genomic instability [26] and occurs in multiple diseases including cancer [15, 22, 27] and AD [28]. Hypomethylation of retrotransposons is an essential factor promoting retrotransposition and becomes more common during ageing [15, 29, 30]. Blood methylation signatures of pre-symptomatic dementia (PSD) in older individuals with T2D have been identified, including differential methylation of loci mapping to genes linked to dementia [31]. Additionally, retrotransposons, including LINE-1 and Alu, are active in the human central nervous system throughout life [32, 33]. Therefore, we hypothesise that DNA methylation changes within LINE-1 or Alu elements are potential novel markers of early-stage dementia in T2D.

Folate and vitamin B12 are the source of coenzymes in one-carbon metabolism [34], and are involved in the maintenance of normal epigenetic patterns [35] by generating S-adenosylmethionine (SAM), the main methyl group donor for DNA methylation. Low serum concentrations of vitamin B12 and folate are observed frequently in AD patients [36] and can disrupt one-carbon metabolism and, therefore, SAM production [37]. Folate is essential for the development of the central nervous system, and folate insufficiency leads to high circulating concentrations of homocysteine [38], which are associated with cardiovascular disease [39, 40], venous thrombosis, cancer, psoriasis, T2D [39], renal and thyroid dysfunction [41], and with the development of dementia and AD [42, 43]. The well-characterised polymorphism within the methylenetetrahydrofolate reductase (MTHFR) gene at position 677 (C677T) results in a dose-dependent decrease in enzyme activity [44], leading to reduced SAM production, increased serum homocysteine and decreased serum folate concentration [45, 46]. However, the potential for intervention with nutrients involved in one-carbon metabolism to offset the epigenetic changes associated with PSD in T2D patients is unknown.

DNA methylation patterns are well known to display tissue-specific differences [47], but most loci show similar DNA methylation levels across a wide variety of tissue types. Equally, epigenetic changes in disease and in response to external stimuli may be unique to target tissues or may be more widespread throughout the body, and this is an important consideration when seeking to identify blood-based epigenetic biomarkers of disease. Changes in DNA methylation measured in the blood have been reported in response to a variety of environmental exposures [48, 49] and lifestyles [50], and also in the blood of patients with variety of pathologies [51, 52], but their role in disease aetiology can be complex. For example, differences in DNA methylation patterns observed in the blood of cancer patients may relate to changes in leukocyte composition of the blood as part of the body’s immune response to the tumour [53]. In the case of dementia, there is evidence that epigenetic marks in blood can serve as biomarkers of early disease, which may be related to brain-blood barrier leakage in the early stages of Alzheimer disease [54]. Most blood-based studies have identified differences in DNA methylation associated with pre-symptomatic dementia (PSD) but with little correlation to changes in brain tissue [55], which may imply that they are associated with risk factors for the disease (e.g. chronic inflammation) rather than informing upon epigenetic changes in the brain. Indeed, some of the genes whose differential methylation with PSD are unique to blood have roles in inflammatory processes [56]. However, some genes show disruption in both blood and brain tissue, such as differential methylation of the OXT gene that encodes the neuropeptide oxytocin [56]. Furthermore, in an analysis of blood samples taken from older individuals with T2D, genes with known functional relevance to dementia showed DNA methylation changes that were associated with PSD [31].

In this study, publicly-available Illumina Infinitum 450K methylation datasets were utilised to examine DNA methylation of retrotransposons in blood of older T2D patients with and without PSD, and to examine the potential of supplementation with folic acid and vitamin B12 to offset the epigenetic changes observed in PSD.

Materials and methods

Study design

Publicly available Illumina Infinium 450K datasets from two studies were used to analyse retrotransposon methylation (Fig 1). We used DNA methylation data from the Israel Diabetes and Cognitive Decline (IDCD) study (GSE62003)[31] to identify epigenetic changes in PSD. This study included 36 older T2D patients (mean age = 73.9 years) with a clinical dementia rating (CDR) of 0.0 at baseline, of whom 18 showed a decline in cognition to CDR = 0.5 at 18-months follow-up, while 18 controls remained without dementia (CDR = 0). T2D with PSD patients was age, gender, education, and HbA1C matched to the T2D without PSD (S1 Table). Secondly, data from an intervention study of folic acid and vitamin B12 supplementation (GSE74548)[57] were used to determine the effect of these nutrients on methylation of retrotransposons. This study was a part of the B-PROOF study and recruitment criteria have been described in previous study [58]. Briefly, 44 older participants (mean age = 70.8 years) were supplemented with 400 μg/day folic acid and 500 μg/day vitamin B12 over two years and 43 participants constituted the placebo group. Both groups were non-smokers (25 and 31 former smokers in supplemented and placebo groups, respectively). No excessive alcohol users were recruited. Levels of the C-reactive protein (CRP) at baseline was ≤ 10 mg/L. In both studies, DNA was extracted from peripheral blood samples and DNA methylation was analysed using the Illumina Infinium 450K methylation microarray platform at two time points (baseline and 18-month follow-up in the IDCD study; and baseline and two-year follow-up in the folic acid and vitamin B12 intervention study). MTHFR genotype data were available for the dietary intervention study (22 participants with 677CC and 22 participants with 677TT). Ethical approval for the longitudinal IDCD study was granted by the Institutional Review Board of Mount Sinai and the Helsinki committees of Sheba and MHS [59], and for the dietary intervention study by the Academic Hospital Maastricht [57].

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Fig 1. Study design.

https://doi.org/10.1371/journal.pone.0234578.g001

Data analysis

Datasets from the intervention study and IDCD study were normalised using the wateRmelon method, respectively [31, 57]. Data from the two studies were analysed separately and therefore normalisation of the two datasets together was not required. After data filtering and quality control, 15 subjects who developed dementia and 13 who had normal cognitive function were retained from within the IDCD dataset. Probes on the Illumina Infinium 450K methylation microarray mapping to LINE-1 and Alu elements were extracted using RepeatMasker and categorised according to evolutionary age of subfamilies into oldest (L1M; AluJ), intermediate (L1P and L1PB; AluS), and youngest (L1HS and L1PA; AluY) [20]. Top differentially methylated positions (DMPs) were identified in PSD patients by paired-sample t-tests and ANOVA, with correction for multiple hypothesis testing using the Benjamini-Hochberg method and significance defined as PFDR < 0.05. The genomic locations (TSS200, TSS1500, 5’UTR, 3’ UTR, 1st Exon, and gene body) of probes were identified through the Illumina annotation. The pathway analysis with significantly differentially methylated loci was performed using WebGestalt (WEB-based Gene SeT AnaLysis Toolkit) [60].

Statistical analysis

Differentially methylated loci were identified by paired-sample t-tests and ANOVA. Paired t-test was used to identify significant changes from baseline in DNA methylation of retrotransposons in both PSD and supplementation datasets. Fisher’s exact test was used to identify enrichment by genomic location and evolutionary age of retrotransposons. ANOVA was conducted to assess changes in DNA methylation by genomic location. Correlations between DNA methylation and plasma homocysteine and serum vitamin B12 concentrations were assessed by Pearson’s correlation coefficient. The impact of MTHFR genotype upon the effects of folate supplementation was assessed by paired t-test. All analyses were performed using IBM SPSS statistical software program (version 24) and R Studio (version 1.1.442). Data are presented as means ± SD unless otherwise stated. Probabilities (P) were adjusted for multiple hypothesis testing by the Benjamini-Hochberg method, with PFDR < 0.05 considered significant.

Results

Distribution of retrotransposon (LINE-1 and Alu) probes by subfamily and genomic location

A total of 9,139 probes mapping to LINE-1 elements and 12,339 probes mapping to Alu sequences on the 450K array were analysed in relation to PSD. Of the LINE-1 probes, 7,389 map to L1M (old) elements, 1,460 to L1P and L1PB (intermediate) elements, and 290 to L1HS and L1PA (youngest) elements (Fig 2A). Of the Alu probes, 3,456 map to AluJ (oldest) elements, 7,440 map to AluS (intermediate) elements, and 1,443 to AluY (youngest) elements. The majority of the interrogated repetitive element loci were located within gene bodies (50%), while 30% were in TSS1500 and 3% in TSS200 (Fig 2B); the rest of the elements were located in the 5’UTR (13%) and 3’UTR (4%). DNA methylation across all retrotransposons by genomic location did not significantly differ between PSD and non-PSD cases (Fig 2C).

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Fig 2. Distribution and methylation changes of LINE-1 and Alu probes.

(A) Number of total probes by evolutionary age of LINE-1 and Alu elements. (B) Number of probes by genomic location. (C) Alterations in DNA methylation of retrotransposons at the 18-month follow-up in non-pre-symptomatic dementia and pre-symptomatic dementia by genomic location.

https://doi.org/10.1371/journal.pone.0234578.g002

DNA methylation changes within LINE-1 and Alu elements in PSD

Changes in DNA methylation of retrotransposons at the 18-month follow-up compared with baseline were examined for all participants. Among the 21,478 of retrotransposon loci, there were 714 significant differentially methylated positions (DMPs; PFDR < 0.05) in PSD at follow-up (Fig 3A and S2 Table), corresponding to 2.4% of all LINE-1 and 3.8% of all Alu probes analysed, and enriched significantly within the AluJ and AluS families (p < 0.0001). Of these, only three probes were also significantly different in non-PSD subjects at follow-up. The majority of the loci were hypermethylated (424 Alu loci and 155 LINE-1 loci; PFDR < 0.05), while 62 Alu loci and 73 LINE-1 loci were significantly hypomethylated (PFDR < 0.05) (Fig 3B and 3C). The DNA methylation changes (follow-up vs baseline) by retrotransposon subfamily evolutionary age are shown in Fig 3D. The oldest LINE-1 subfamilies (L1M) demonstrated the largest variation in magnitude of DNA methylation changes (Δβ) within LINE-1 elements [standard deviation (SD) = 0.041] and tended to be hypomethylated at the 18-month follow-up, while the youngest Alu subfamilies (AluY) had the greatest variation in methylation (SD = 0.016) of all Alu elements (Fig 3D). We did not observe changes in DNA methylation at non-retrotransposon probes mapping in close proximity to the DMPs, suggesting that these changes are highly loci specific.

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Fig 3. Differentially methylated positions in pre-symptomatic dementia (PSD) at 18-month follow-up.

(A) Manhattan plot of retrotransposon loci displaying significant changes in DNA methylation between type 2 diabetes patients with and without PSD at follow-up. B-C) Volcano plots of changes in retrotransposon methylation (Δβ) in PSD by evolutionary age of Alu (B) and LINE-1 (C) elements. D) Changes in DNA methylation (Δβ) by evolutionary age of LINE-1 and Alu elements. The Red line represents PFDR = 0.05.

https://doi.org/10.1371/journal.pone.0234578.g003

Gene functions and pathway analysis

The DMPs in PSD mapped to gene bodies (47% of total loci), TSS1500 (34%), 5’UTR (13%), 3’UTR (4%), TSS200 (2%) and 1st Exon (< 0.1%), and demonstrated enrichment at TSS1500 regions (p = 0.013) (Fig 4A). Pathway analysis incorporating the DMPs showed that aberrantly methylated retrotransposon loci were involved in multiple pathways relating to dementia (Fig 4B and 4C); the most significant pathway (by p value) was the muscarinic acetylcholine receptor 1 and 3 signalling pathway (p = 0.007), which is implicated in AD development and cognitive decline. Additionally, the Alzheimer disease-amyloid secretase (p = 0.012), metabotropic glutamate receptor group 3 and group 1 (p = 0.015 and p = 0.017, respectively), beta 3 adrenergic receptor signalling (p = 0.019), interferon-gamma signalling (p = 0.025), corticotropin releasing factor receptor signalling (p = 0.028), apoptosis signalling (p = 0.030), 5HT4 type receptor mediated signalling (p = 0.030) and opioid proenkephalin (p = 0.030) pathways were also significantly enriched using Over Representation Analysis in WebGestalt (S3 Table).

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Fig 4. Pathway analysis for the 714 differentially methylated positions.

(A) Number of probes by genomic location. B-C) Pathway analysis for the 432 genes associated with the 714 DMPs by biological process categories (B) and molecular function categories (C).

https://doi.org/10.1371/journal.pone.0234578.g004

Within pathways related to dementia development, AluS elements mapping to TSS1500 regions within the Protein Kinase N3 (PKN3; cg14036226) and G Protein Subunit β 5 (GNB5; cg24202638) genes (Fig 5A and 5B) and L1M elements (cg22023664 and cg02849894) within the 5’UTR of G Protein Subunit γ 7 (GNG7) (Fig 5C) were differentially methylated.

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Fig 5. Genomic location of significant differentially methylated retrotransposons.

(A) Protein Kinase N3 (PNK3). (B) G Protein Subunit β 5 (GNB5). C) G Protein Subunit γ 7 (GNG7). Red arrows indicate DMPs identified by the study.

https://doi.org/10.1371/journal.pone.0234578.g005

The effects of folic acid and vitamin B12 supplementation on DNA methylation at DMPs of PSD

To assess the effects of supplementation with folic acid and vitamin B12 on DNA methylation of the 714 PSD-associated DMPs, an independent intervention study dataset was used (supplementation group: n = 44; placebo group: n = 43). DNA methylation at 85 of the 714 loci were significantly altered (PFDR < 0.05) following the two-year intervention. An additional 12 loci which overlapped with the placebo group were excluded from further analysis. Methylation at 15 DMPs, nine of which mapped to L1M elements that were hypomethylated in the PSD group, significantly increased (PFDR < 0.05) after folic acid and vitamin B12 supplementation (Fig 6A, top-left quarter and Table 1). Four of these 15 loci were also related to AD: cg14051544 of HAL1-2a-MD in the 5’UTR of Solute Carrier Family 7 Member 14 (SLC7A14); cg22023664 of L1M in the 5’UTR of GNG7; cg23342367 of L1M in the gene body of Tumor Protein D52 (TPD52); and cg23304647 of L1M in the gene body of G Protein Subunit Alpha 12 (GNA12). An additional 29 probes within AluJ (35%), AluS (24%), AluY (7%), of L1M (24%), L1PA (7%) and L1PB (1%) elements were positively correlated with the development of PSD and displayed significantly decreased DNA methylation (paired t-test, PFDR < 0.05) following dietary intervention (Fig 6A, bottom-right quarter and S4 Table). However, another 29 loci were hypermethylated both in the vitamin-supplemented and PSD groups (Fig 6A, top-right quarter and S5 Table). When examined by MTHFR genotypes (677CC and 677TT), DNA methylation levels of 71 of the 714 PSD-associated DMPs were significantly altered in participants with the MTHFR CC genotype (8 hypomethylated, 19 hypermethylated) (Fig 6B), whereas 89 loci were significantly different in participants carrying the MTHFR TT genotype (61 hypomethylated, 6 hypermethylated) after intervention (Fig 6C).

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Fig 6. DNA methylation changes between B-vitamins intervention and pre-symptomatic dementia development.

Changes in DNA methylation (Δβ) in the two studies are presented in all participants (A) and stratified by those healthy individuals in the intervention study with the MTHFR 677CC (B) and TT (C) genotypes. X-axis represents Δβ DNA methylation of pre-symptomatic dementia in T2D patients and Y-axis represents Δβ DNA methylation of supplementation group with folic acid and vitamin B12 intervention.

https://doi.org/10.1371/journal.pone.0234578.g006

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Table 1. Hypermethylated CpG sites after folic acid and vitamin B12 supplementation.

https://doi.org/10.1371/journal.pone.0234578.t001

A threshold of Δβ value = ±0.05 was used to identify loci displaying substantial changes in methylation levels following dietary supplementation. For all participants, methylation at 10 repetitive element loci increased significantly while one decreased significantly following supplementation (S6 Table), which corresponded to DMPs that were hypomethylated (10 loci) and hypermethylated (1 locus) in PSD. With both the CC and TT genotypes of MTHFR, methylation of cg05310486 (AluS) and cg23911433 (L1M) increased by Δβ > 0.05. However, in participants with the CC genotype, methylation of 10 other loci (cg27324781, cg23304647, cg14567424, cg15980656, cg26381210, cg12785183, cg10959668, cg24534583, cg06305891, and cg23342367), increased by Δβ > 0.05 after vitamin supplementation and had lower methylation within the PSD group, while methylation of cg01168028 was increased by supplementation and within PSD patients (Fig 6B). In those with the TT genotype only, methylation of three CpG loci (cg23489236, cg10675515, and cg27133230) decreased by Δβ > 0.05 following dietary supplementation and methylation at these loci correlated inversely with DNA methylation changes in PSD. In addition, methylation of cg07291836 decreased both in the PSD group and after intervention (Fig 6C).

Association between differentially methylated retrotransposon loci and serum/plasma concentrations of B-vitamins and homocysteine

We investigated the relationship between DNA methylation of the 15 significantly hypermethylated DMPs and concentrations of serum folate, vitamin B12 and plasma homocysteine in participants in the intervention study. We observed inverse correlations between DNA methylation and homocysteine concentration for 9 of the 15 loci displaying hypermethylation after supplementation with B-vitamins; cg23304647 (r = -0.290, p = 0.006), cg22023664 (r = -0.314, p = 0.003), cg23342367 (r = -0.374, p < 0.001), cg06305891 (r = -0.306, p = 0.004), cg05310486 (r = -0.302, p = 0.004), cg27609217 (r = -0.244, p = 0.022), cg23911433 (r = -0.338, p = 0.001), cg15980656 (r = -0.269, p = 0.011), cg14567424 (r = -0.312, p = 0.003) (Fig 7). Moreover, at six of these nine loci, there were positive correlations between methylation and serum vitamin B12 concentration; cg22023664 (r = 0.212, p = 0.048), cg23342367 (r = 0.222, p = 0.037), cg06305891 (r = 0.223, p = 0.037), cg05310486 (r = 0.219, p = 0.040), cg27609217 (r = 0.244, p = 0.022), cg14567424 (r = 0.211, p = 0.048) (S1 Fig). There were no significant correlations between methylation and serum folate concentration.

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Fig 7. Correlation of DNA methylation and plasma homocysteine levels in healthy participants.

https://doi.org/10.1371/journal.pone.0234578.g007

Discussion

In this study, we identified 714 loci mapping to retrotransposons (LINE-1 and Alu) that were differentially methylated in T2D patients with PSD compared to those with normal cognitive function, with such changes enriched within older families (L1M, AluJ, and AluS). LINE-1 elements are enriched within intergenic regions of the genome while Alu elements are preferentially integrated upstream of genes and within introns [61], but for both there are extensive reports on their impact upon gene expression via cis- and trans-regulation. In concordance with their genomic distribution, the probes on the Illumina Infinium 450K mapping to retrotransposons predominantly correspond to TSS1500, gene bodies and intergenic regions, with relative depletion close to transcriptional start sites and within exons [20]. As changes at those probes mapping to TSS1500 are more likely to have a functional impact upon gene expression, such as through promoter hypomethylation, we observed enrichment of DMPs at TSS1500. This finding supports the hypothesis that changes in retrotransposon DNA methylation may have influence through mediation of neighbour gene expression. Further, we observed that a number of PSD-associated DMPs showed inverse changes in methylation with folic acid and vitamin B12 supplementation. To our knowledge, this is the first study to analyse methylation of retrotransposons by their evolutionary age in people with T2D-associated PSD and in response to dietary intervention.

Changes in methylation of LINE-1 or Alu elements during development and ageing may cause DNA damage and double-strand DNA breaks that contribute to the process of neurodegeneration [62, 63]. Moreover, our locus-specific analysis revealed changes in elements mapping to genes associated with dementia including GNB5, GNG7, and PKN3. Specifically, we have identified hypermethylation of an AluSx element at the 5’ region of the GNB5 promoter, and an AluSg element within the PKN3 promoter. We observed enrichment of DMPs within AluJ and AluS sequences. While the reasons for this are not currently clear, it may suggest that such elements are implicated in PSD not through retrotransposition, but rather through modifying the expression of proximal genes. Younger repetitive element subfamilies such as L1HS and AluY are known to be more active in retrotransposition [12, 64], and therefore the differential methylation of AluJ and AluS elements are unlikely to result in somatic retrotransposition events. Loss of GNG7 is associated with dysregulation of the adenylyl cyclase signalling pathway that is associated with a number of neurodegenerative disorders [65]. GNB5 is similarly implicated in regulation of adenylyl cyclase signalling, and genetic variants within the gene are associated with impaired cognition [66], while Gnb5 knockout mice display severe impairment of development and motor co-ordination [67]. PKN3 activity increases in response to insulin signalling [68] and may have a neuroprotective effect in response to hypoxia [69]. Furthermore, PKN family members have previously been implicated in the biology of AD [70]. Our study has therefore identified epigenetic changes within retrotransposons mapping to genes with critical functions in neuronal biology and the development of neurodegenerative disorders. However, further functional studies will be required to examine the subsequent impact upon the expression of these genes and fully elucidate the role of retrotransposons in dementia biology.

Genome-wide hypomethylation of LINE-1 and Alu elements causes loss of genomic integrity [71, 72]. Folic acid and vitamin B12 are key players in one-carbon metabolism which generates SAM [73, 74], the universal methyl group donor used for DNA methylation. We observed that these nutrients modified DNA methylation of retrotransposons, including PSD-associated DMPs. Although these nutrients increased methylation of some CpG sites within retrotransposons that are also hypermethylated in PSD (Fig 6), this effect was small for most of the analysed loci (e.g. the change in methylation of cg02276269 and cg19764326 was below 0.05). Interestingly, nine of the 15 loci displaying hypermethylation after supplementation with B-vitamins were negatively correlated with plasma homocysteine concentrations, while DNA methylation at six loci were positively correlated with serum vitamin B12 levels. Repetitive elements display differential sensitivity to environmental exposures [23], and it may be that epigenetic changes within repetitive elements in response to internal stimuli or environmental factors can serve to modify the expression of genes implicated in PSD development. DNA methylation of old LINE-1 subfamily (L1M) seems to be vulnerable to dietary exposure than younger subfamilies.

Additionally, we observed differences in retrotransposon DNA methylation by MTHFR genotype following dietary supplementation with folic acid and vitamin B12. Specifically, higher methylation levels were observed at some loci in in participants with the MTHFR CC genotype (the most common variant of MTHFR), whereas lower levels were observed at the same loci in participants with the MTHFR TT genotype. In those carrying the MTHFR TT genotype, MTHFR enzyme activity is lower leading to decreased SAM production and, potentially, resulting in hypomethylation events. Therefore, and in concurrence with our previous study [35], individuals with the MTHFR CC genotype may show greater benefit from supplementation with folic acid and vitamin B12 than those with the MTHFR TT genotype.

Our study has limitations. The number of participants in each of the two studies was relatively small (38 participants for analysis of changes in PSD and 44 participants receiving dietary supplementation). Despite the measures in the study design and our analysis to increase statistical power and limit the risk of yielding false positives, we cannot exclude the possibility that some of the DMPs identified in this study may be artefacts. Our results will need to be confirmed in independent cohorts, and the role of retrotransposon methylation in the initiation of dementia will need to be examined further through in vitro studies. Secondly, the data on effects of folic acid and vitamin B12 supplementation were obtained from healthy older people and not in T2D patients. Due to the absence of cognition data, we cannot exclude the possibility that some of the participants within the dietary supplementation study may have PSD; therefore, care must be taken in extrapolating the results to the development of PSD in those with T2D. However, both studies were undertaken in older people and the intervention and follow-up periods were of similar duration (i.e. one-and-a-half and two years respectively), the resulting data may be compatible.

To the best of our knowledge, there are no publicly-available RNA-seq datasets available to examine the link between altered DNA methylation and gene expression to understand the underlying mechanisms of PSD in T2D. Future studies may require such analysis to reveal the functionality of these DMRs in the aetiology of PSD in T2D patients.

Conclusions

Our study is the first to report that locus-specific changes in DNA methylation within retrotransposons is associated with PSD incidence in T2D patients, and that the methylation of these sites might be modifiable by dietary supplementation with folic acid and vitamin B12. Further, we observed that the effects of these nutrients on DNA methylation differ by MTHFR genotype. If confirmed in future larger studies, these findings may contribute to the identification of epigenetic biomarkers of dementia risk in those with T2D and will strengthen the evidence for dietary intervention to reduce the risk of dementia among high-risk T2D patients.

Supporting information

S1 Table. Clinical dementia rating (CDR) in T2D with and without PSD.

https://doi.org/10.1371/journal.pone.0234578.s001

(XLSX)

S2 Table. 714 significant differentially methylated positions.

https://doi.org/10.1371/journal.pone.0234578.s002

(XLSX)

S3 Table. Pathway analysis.

https://doi.org/10.1371/journal.pone.0234578.s003

(XLSX)

S4 Table. List of loci in Fig 6A, bottom-right quarter.

https://doi.org/10.1371/journal.pone.0234578.s004

(XLSX)

S5 Table. List of loci in Fig 6A, top-right quarter.

https://doi.org/10.1371/journal.pone.0234578.s005

(XLSX)

S6 Table. Overlapped loci between PSD patients and dietary intervention study.

https://doi.org/10.1371/journal.pone.0234578.s006

(XLSX)

S1 Fig.

https://doi.org/10.1371/journal.pone.0234578.s007

(JPG)

References

  1. 1. Shaw JE, Sicree RA, Zimmet PZ. Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pract. 2010;87(1):4–14. Epub 2009/11/10. pmid:19896746.
  2. 2. Strachan MW, Deary IJ, Ewing FM, Frier BM. Is type II diabetes associated with an increased risk of cognitive dysfunction? A critical review of published studies. Diabetes Care. 1997;20(3):438–45. pmid:9051402.
  3. 3. Ott A, Stolk RP, van Harskamp F, Pols HA, Hofman A, Breteler MM. Diabetes mellitus and the risk of dementia: The Rotterdam Study. Neurology. 1999;53(9):1937–42. Epub 1999/12/22. pmid:10599761.
  4. 4. Stewart R, Liolitsa D. Type 2 diabetes mellitus, cognitive impairment and dementia. Diabet Med. 1999;16(2):93–112. pmid:10229302.
  5. 5. Awad N, Gagnon M, Messier C. The relationship between impaired glucose tolerance, type 2 diabetes, and cognitive function. J Clin Exp Neuropsychol. 2004;26(8):1044–80. pmid:15590460.
  6. 6. Brands AM, Biessels GJ, de Haan EH, Kappelle LJ, Kessels RP. The effects of type 1 diabetes on cognitive performance: a meta-analysis. Diabetes Care. 2005;28(3):726–35. pmid:15735218.
  7. 7. Meneilly GS. Diabetes and Dementia in the Elderly. Can J Diabetes. 2018;42(6):579. pmid:30502757.
  8. 8. de la Monte SM, Wands JR. Alzheimer's disease is type 3 diabetes-evidence reviewed. J Diabetes Sci Technol. 2008;2(6):1101–13. pmid:19885299; PubMed Central PMCID: PMC2769828.
  9. 9. Janson J, Laedtke T, Parisi JE, O'Brien P, Petersen RC, Butler PC. Increased risk of type 2 diabetes in Alzheimer disease. Diabetes. 2004;53(2):474–81. pmid:14747300.
  10. 10. Mills RE, Bennett EA, Iskow RC, Devine SE. Which transposable elements are active in the human genome? Trends Genet. 2007;23(4):183–91. pmid:17331616.
  11. 11. Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC, Baldwin J, et al. Initial sequencing and analysis of the human genome. Nature. 2001;409(6822):860–921. Epub 2001/03/10. pmid:11237011.
  12. 12. Beck CR, Collier P, Macfarlane C, Malig M, Kidd JM, Eichler EE, et al. LINE-1 retrotransposition activity in human genomes. Cell. 2010;141(7):1159–70. Epub 2010/07/07. pmid:20602998; PubMed Central PMCID: PMC3013285.
  13. 13. Mandal PK, Ewing AD, Hancks DC, Kazazian HH Jr., Enrichment of processed pseudogene transcripts in L1-ribonucleoprotein particles. Hum Mol Genet. 2013;22(18):3730–48. pmid:23696454; PubMed Central PMCID: PMC3749862.
  14. 14. Deininger P. Alu elements: know the SINEs. Genome Biol. 2011;12(12):236. pmid:22204421; PubMed Central PMCID: PMC3334610.
  15. 15. Wolff EM, Byun HM, Han HF, Sharma S, Nichols PW, Siegmund KD, et al. Hypomethylation of a LINE-1 promoter activates an alternate transcript of the MET oncogene in bladders with cancer. PLoS Genet. 2010;6(4):e1000917. Epub 2010/04/28. pmid:20421991; PubMed Central PMCID: PMC2858672.
  16. 16. Byun HM, Heo K, Mitchell KJ, Yang AS. Mono-allelic retrotransposon insertion addresses epigenetic transcriptional repression in human genome. J Biomed Sci. 2012;19:13. pmid:22300442; PubMed Central PMCID: PMC3315731.
  17. 17. Kines KJ, Belancio VP. Expressing genes do not forget their LINEs: transposable elements and gene expression. Front Biosci (Landmark Ed). 2012;17:1329–44. pmid:22201807; PubMed Central PMCID: PMC3373430.
  18. 18. Guo C, Jeong HH, Hsieh YC, Klein HU, Bennett DA, De Jager PL, et al. Tau Activates Transposable Elements in Alzheimer's Disease. Cell Rep. 2018;23(10):2874–80. pmid:29874575; PubMed Central PMCID: PMC6181645.
  19. 19. Larsen PA, Hunnicutt KE, Larsen RJ, Yoder AD, Saunders AM. Warning SINEs: Alu elements, evolution of the human brain, and the spectrum of neurological disease. Chromosome Res. 2018;26(1–2):93–111. Epub 2018/02/21. pmid:29460123; PubMed Central PMCID: PMC5857278.
  20. 20. Barrow TM, Wong Doo N, Milne RL, Giles GG, Willmore E, Strathdee G, et al. Analysis of retrotransposon subfamily DNA methylation reveals novel early epigenetic changes in chronic lymphocytic leukaemia. Haematologica. 2020. Epub 2020/01/11. pmid:31919093.
  21. 21. Yang AS, Estecio MR, Doshi K, Kondo Y, Tajara EH, Issa JP. A simple method for estimating global DNA methylation using bisulfite PCR of repetitive DNA elements. Nucleic Acids Res. 2004;32(3):e38. Epub 2004/02/20. pmid:14973332; PubMed Central PMCID: PMC373427.
  22. 22. Bernstein I, Byun HM, Mohrbacher A, Douer D, Gorospe G 3rd, Hergesheimer J, et al. A phase I biological study of azacitidine (Vidaza) to determine the optimal dose to inhibit DNA methylation. Epigenetics. 2010;5(8):750–7. Epub 2010/09/24. pmid:20861661.
  23. 23. Byun HM, Motta V, Panni T, Bertazzi PA, Apostoli P, Hou L, et al. Evolutionary age of repetitive element subfamilies and sensitivity of DNA methylation to airborne pollutants. Part Fibre Toxicol. 2013;10:28. Epub 2013/07/17. pmid:23855992; PubMed Central PMCID: PMC3717285.
  24. 24. Lisanti S, Omar WA, Tomaszewski B, De Prins S, Jacobs G, Koppen G, et al. Comparison of methods for quantification of global DNA methylation in human cells and tissues. PLoS One. 2013;8(11):e79044. pmid:24260150; PubMed Central PMCID: PMC3832524.
  25. 25. Guo L, Li PH, Li H, Colicino E, Colicino S, Wen Y, et al. Effects of environmental noise exposure on DNA methylation in the brain and metabolic health. Environ Res. 2017;153:73–82. Epub 2016/12/04. pmid:27914298.
  26. 26. Ayarpadikannan S, Kim HS. The impact of transposable elements in genome evolution and genetic instability and their implications in various diseases. Genomics Inform. 2014;12(3):98–104. pmid:25317108; PubMed Central PMCID: PMC4196381.
  27. 27. Choi SH, Worswick S, Byun HM, Shear T, Soussa JC, Wolff EM, et al. Changes in DNA methylation of tandem DNA repeats are different from interspersed repeats in cancer. Int J Cancer. 2009;125(3):723–9. Epub 2009/05/14. pmid:19437537; PubMed Central PMCID: PMC4086885.
  28. 28. Jones PA. DNA methylation and cancer. Cancer Res. 1986;46(2):461–6. pmid:2416425.
  29. 29. Cordaux R, Batzer MA. The impact of retrotransposons on human genome evolution. Nat Rev Genet. 2009;10(10):691–703. pmid:19763152; PubMed Central PMCID: PMC2884099.
  30. 30. Erichsen L, Beermann A, Arauzo-Bravo MJ, Hassan M, Dkhil MA, Al-Quraishy S, et al. Genome-wide hypomethylation of LINE-1 and Alu retroelements in cell-free DNA of blood is an epigenetic biomarker of human aging. Saudi J Biol Sci. 2018;25(6):1220–6. pmid:30174526; PubMed Central PMCID: PMC6117241.
  31. 31. Lunnon K, Smith RG, Cooper I, Greenbaum L, Mill J, Beeri MS. Blood methylomic signatures of presymptomatic dementia in elderly subjects with type 2 diabetes mellitus. Neurobiol Aging. 2015;36(3):1600 e1–4. Epub 2015/01/15. pmid:25585531; PubMed Central PMCID: PMC5747361.
  32. 32. Baillie JK, Barnett MW, Upton KR, Gerhardt DJ, Richmond TA, De Sapio F, et al. Somatic retrotransposition alters the genetic landscape of the human brain. Nature. 2011;479(7374):534–7. Epub 2011/11/01. pmid:22037309; PubMed Central PMCID: PMC3224101.
  33. 33. Erwin JA, Paquola AC, Singer T, Gallina I, Novotny M, Quayle C, et al. L1-associated genomic regions are deleted in somatic cells of the healthy human brain. Nat Neurosci. 2016;19(12):1583–91. pmid:27618310; PubMed Central PMCID: PMC5127747.
  34. 34. Duncan TM, Reed MC, Nijhout HF. The relationship between intracellular and plasma levels of folate and metabolites in the methionine cycle: a model. Mol Nutr Food Res. 2013;57(4):628–36. Epub 2012/11/13. pmid:23143835; PubMed Central PMCID: PMC3786706.
  35. 35. Sae-Lee C, Corsi S, Barrow TM, Kuhnle GGC, Bollati V, Mathers JC, et al. Dietary Intervention Modifies DNA Methylation Age Assessed by the Epigenetic Clock. Mol Nutr Food Res. 2018;62(23):e1800092. pmid:30350398.
  36. 36. Quadri P, Fragiacomo C, Pezzati R, Zanda E, Forloni G, Tettamanti M, et al. Homocysteine, folate, and vitamin B-12 in mild cognitive impairment, Alzheimer disease, and vascular dementia. Am J Clin Nutr. 2004;80(1):114–22. pmid:15213037.
  37. 37. Scarpa S, Cavallaro RA, D'Anselmi F, Fuso A. Gene silencing through methylation: an epigenetic intervention on Alzheimer disease. J Alzheimers Dis. 2006;9(4):407–14. pmid:16917149.
  38. 38. Diaz-Arrastia R. Homocysteine and neurologic disease. Arch Neurol. 2000;57(10):1422–7. pmid:11030793.
  39. 39. Faeh D, Chiolero A, Paccaud F. Homocysteine as a risk factor for cardiovascular disease: should we (still) worry about? Swiss Med Wkly. 2006;136(47–48):745–56. Epub 2007/01/17. doi: 2006/47/smw-11283 pmid:17225194.
  40. 40. Shenoy V, Mehendale V, Prabhu K, Shetty R, Rao P. Correlation of serum homocysteine levels with the severity of coronary artery disease. Indian J Clin Biochem. 2014;29(3):339–44. Epub 2014/06/27. pmid:24966483; PubMed Central PMCID: PMC4062675.
  41. 41. Hankey GJ, Eikelboom JW. Homocysteine and vascular disease. Lancet. 1999;354(9176):407–13. Epub 1999/08/07. pmid:10437885.
  42. 42. Zhang L, Liu N, Zhang J, Zhang H, Zhang Y. Clinical research of homocysteine, high-sensitive C-reactive protein and D-Dimer in patients with vascular dementia. Pak J Pharm Sci. 2017;30(4(Suppl.)):1445–7. pmid:29043995.
  43. 43. Kovalska M, Tothova B, Kovalska L, Tatarkova Z, Kalenska D, Tomascova A, et al. Association of Induced Hyperhomocysteinemia with Alzheimer's Disease-Like Neurodegeneration in Rat Cortical Neurons After Global Ischemia-Reperfusion Injury. Neurochem Res. 2018;43(9):1766–78. pmid:30003389.
  44. 44. van der Put NM, Gabreels F, Stevens EM, Smeitink JA, Trijbels FJ, Eskes TK, et al. A second common mutation in the methylenetetrahydrofolate reductase gene: an additional risk factor for neural-tube defects? Am J Hum Genet. 1998;62(5):1044–51. Epub 1998/05/23. pmid:9545395; PubMed Central PMCID: PMC1377082.
  45. 45. Malinow MR, Nieto FJ, Kruger WD, Duell PB, Hess DL, Gluckman RA, et al. The effects of folic acid supplementation on plasma total homocysteine are modulated by multivitamin use and methylenetetrahydrofolate reductase genotypes. Arterioscler Thromb Vasc Biol. 1997;17(6):1157–62. Epub 1997/06/01. pmid:9194768.
  46. 46. Nelen WL, Blom HJ, Thomas CM, Steegers EA, Boers GH, Eskes TK. Methylenetetrahydrofolate reductase polymorphism affects the change in homocysteine and folate concentrations resulting from low dose folic acid supplementation in women with unexplained recurrent miscarriages. J Nutr. 1998;128(8):1336–41. Epub 1998/08/04. pmid:9687553.
  47. 47. Byun HM, Siegmund KD, Pan F, Weisenberger DJ, Kanel G, Laird PW, et al. Epigenetic profiling of somatic tissues from human autopsy specimens identifies tissue- and individual-specific DNA methylation patterns. Hum Mol Genet. 2009;18(24):4808–17. Epub 2009/09/25. pmid:19776032; PubMed Central PMCID: PMC4481584.
  48. 48. Jimenez-Garza O, Guo L, Byun HM, Carrieri M, Bartolucci GB, Zhong J, et al. Promoter methylation status in genes related with inflammation, nitrosative stress and xenobiotic metabolism in low-level benzene exposure: Searching for biomarkers of oncogenesis. Food Chem Toxicol. 2017;109(Pt 1):669–76. Epub 2017/08/22. pmid:28823944.
  49. 49. Byun HM, Colicino E, Trevisi L, Fan T, Christiani DC, Baccarelli AA. Effects of Air Pollution and Blood Mitochondrial DNA Methylation on Markers of Heart Rate Variability. J Am Heart Assoc. 2016;5(4). Epub 2016/04/24. pmid:27107129; PubMed Central PMCID: PMC4843532.
  50. 50. Corsi S, Iodice S, Vigna L, Cayir A, Mathers JC, Bollati V, et al. Platelet mitochondrial DNA methylation predicts future cardiovascular outcome in adults with overweight and obesity. Clin Epigenetics. 2020;12(1):29. Epub 2020/02/19. pmid:32066501; PubMed Central PMCID: PMC7026975.
  51. 51. Raut JR, Guan Z, Schrotz-King P, Brenner H. Whole-blood DNA Methylation Markers for Risk Stratification in Colorectal Cancer Screening: A Systematic Review. Cancers (Basel). 2019;11(7). Epub 2019/07/03. pmid:31261771; PubMed Central PMCID: PMC6678372.
  52. 52. Marsit C, Christensen B. Blood-derived DNA methylation markers of cancer risk. Adv Exp Med Biol. 2013;754:233–52. Epub 2012/09/08. pmid:22956505.
  53. 53. Koestler DC, Marsit CJ, Christensen BC, Accomando W, Langevin SM, Houseman EA, et al. Peripheral blood immune cell methylation profiles are associated with nonhematopoietic cancers. Cancer Epidemiol Biomarkers Prev. 2012;21(8):1293–302. Epub 2012/06/21. pmid:22714737; PubMed Central PMCID: PMC3415587.
  54. 54. van de Haar HJ, Burgmans S, Jansen JF, van Osch MJ, van Buchem MA, Muller M, et al. Blood-Brain Barrier Leakage in Patients with Early Alzheimer Disease. Radiology. 2016;281(2):527–35. Epub 2016/10/19. pmid:27243267.
  55. 55. Fransquet PD, Lacaze P, Saffery R, McNeil J, Woods R, Ryan J. Blood DNA methylation as a potential biomarker of dementia: A systematic review. Alzheimers Dement. 2018;14(1):81–103. Epub 2017/11/12. pmid:29127806; PubMed Central PMCID: PMC6810631.
  56. 56. Lardenoije R, Roubroeks JAY, Pishva E, Leber M, Wagner H, Iatrou A, et al. Alzheimer's disease-associated (hydroxy)methylomic changes in the brain and blood. Clin Epigenetics. 2019;11(1):164. Epub 2019/11/30. pmid:31775875; PubMed Central PMCID: PMC6880587.
  57. 57. Kok DE, Dhonukshe-Rutten RA, Lute C, Heil SG, Uitterlinden AG, van der Velde N, et al. The effects of long-term daily folic acid and vitamin B12 supplementation on genome-wide DNA methylation in elderly subjects. Clin Epigenetics. 2015;7:121. pmid:26568774; PubMed Central PMCID: PMC4644301.
  58. 58. van Wijngaarden JP, Dhonukshe-Rutten RA, van Schoor NM, van der Velde N, Swart KM, Enneman AW, et al. Rationale and design of the B-PROOF study, a randomized controlled trial on the effect of supplemental intake of vitamin B12 and folic acid on fracture incidence. BMC Geriatr. 2011;11:80. Epub 2011/12/06. pmid:22136481; PubMed Central PMCID: PMC3266639.
  59. 59. Beeri MS, Ravona-Springer R, Moshier E, Schmeidler J, Godbold J, Karpati T, et al. The Israel Diabetes and Cognitive Decline (IDCD) study: Design and baseline characteristics. Alzheimers Dement. 2014;10(6):769–78. pmid:25150735; PubMed Central PMCID: PMC4330555.
  60. 60. Wang J, Duncan D, Shi Z, Zhang B. WEB-based GEne SeT AnaLysis Toolkit (WebGestalt): update 2013. Nucleic Acids Res. 2013;41(Web Server issue):W77–83. pmid:23703215; PubMed Central PMCID: PMC3692109.
  61. 61. Medstrand P, van de Lagemaat LN, Mager DL. Retroelement distributions in the human genome: variations associated with age and proximity to genes. Genome Res. 2002;12(10):1483–95. Epub 2002/10/09. pmid:12368240; PubMed Central PMCID: PMC187529.
  62. 62. Frappart PO, McKinnon PJ. Mouse models of DNA double-strand break repair and neurological disease. DNA Repair (Amst). 2008;7(7):1051–60. pmid:18458002; PubMed Central PMCID: PMC3831504.
  63. 63. Pornthanakasem W, Kongruttanachok N, Phuangphairoj C, Suyarnsestakorn C, Sanghangthum T, Oonsiri S, et al. LINE-1 methylation status of endogenous DNA double-strand breaks. Nucleic Acids Res. 2008;36(11):3667–75. pmid:18474527; PubMed Central PMCID: PMC2441779.
  64. 64. Konkel MK, Walker JA, Hotard AB, Ranck MC, Fontenot CC, Storer J, et al. Sequence Analysis and Characterization of Active Human Alu Subfamilies Based on the 1000 Genomes Pilot Project. Genome Biol Evol. 2015;7(9):2608–22. Epub 2015/09/01. pmid:26319576; PubMed Central PMCID: PMC4607524.
  65. 65. Schwindinger WF, Betz KS, Giger KE, Sabol A, Bronson SK, Robishaw JD. Loss of G protein gamma 7 alters behavior and reduces striatal alpha(olf) level and cAMP production. J Biol Chem. 2003;278(8):6575–9. Epub 2002/12/19. pmid:12488442.
  66. 66. Shamseldin HE, Masuho I, Alenizi A, Alyamani S, Patil DN, Ibrahim N, et al. GNB5 mutation causes a novel neuropsychiatric disorder featuring attention deficit hyperactivity disorder, severely impaired language development and normal cognition. Genome Biol. 2016;17(1):195. Epub 2016/09/30. pmid:27677260; PubMed Central PMCID: PMC5037613.
  67. 67. Zhang JH, Pandey M, Seigneur EM, Panicker LM, Koo L, Schwartz OM, et al. Knockout of G protein beta5 impairs brain development and causes multiple neurologic abnormalities in mice. J Neurochem. 2011;119(3):544–54. Epub 2011/09/03. pmid:21883221; PubMed Central PMCID: PMC3192915.
  68. 68. Leenders F, Mopert K, Schmiedeknecht A, Santel A, Czauderna F, Aleku M, et al. PKN3 is required for malignant prostate cell growth downstream of activated PI 3-kinase. EMBO J. 2004;23(16):3303–13. Epub 2004/07/30. pmid:15282551; PubMed Central PMCID: PMC514518.
  69. 69. Thauerer B, Zur Nedden S, Baier-Bitterlich G. Protein Kinase C-Related Kinase (PKN/PRK). Potential Key-Role for PKN1 in Protection of Hypoxic Neurons. Curr Neuropharmacol. 2014;12(3):213–8. Epub 2014/05/23. pmid:24851086; PubMed Central PMCID: PMC4023452.
  70. 70. Kawamata T, Taniguchi T, Mukai H, Kitagawa M, Hashimoto T, Maeda K, et al. A protein kinase, PKN, accumulates in Alzheimer neurofibrillary tangles and associated endoplasmic reticulum-derived vesicles and phosphorylates tau protein. J Neurosci. 1998;18(18):7402–10. Epub 1998/09/16. pmid:9736660.
  71. 71. Daskalos A, Nikolaidis G, Xinarianos G, Savvari P, Cassidy A, Zakopoulou R, et al. Hypomethylation of retrotransposable elements correlates with genomic instability in non-small cell lung cancer. Int J Cancer. 2009;124(1):81–7. pmid:18823011.
  72. 72. Richards KL, Zhang B, Baggerly KA, Colella S, Lang JC, Schuller DE, et al. Genome-wide hypomethylation in head and neck cancer is more pronounced in HPV-negative tumors and is associated with genomic instability. PLoS One. 2009;4(3):e4941. pmid:19293934; PubMed Central PMCID: PMC2654169.
  73. 73. Niculescu MD, Zeisel SH. Diet, methyl donors and DNA methylation: interactions between dietary folate, methionine and choline. J Nutr. 2002;132(8 Suppl):2333S–5S. pmid:12163687.
  74. 74. Pirouzpanah S, Taleban FA, Mehdipour P, Atri M. Association of folate and other one-carbon related nutrients with hypermethylation status and expression of RARB, BRCA1, and RASSF1A genes in breast cancer patients. J Mol Med (Berl). 2015;93(8):917–34. pmid:25805039.