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Epigenetic alterations and an increased frequency of micronuclei in women with fibromyalgia.

1. Introduction

Fibromyalgia (FM), which affects at least 10 million American adults [1], is a multisymptom condition resulting in not only widespread chronic pain, but also fatigue, sleep disturbances, and morning stiffness. In addition, many patients experience depression, anxiety, and dyscognition [2, 3]. FM has a significant adverse impact on many individuals' physical and mental health [4, 5] and also leads to reduced workplace productivity and increased health care/disability expenses, with the estimated cost of FM on the US economy being reported to be 12-14 billion dollars [1, 6]. While the adverse impact of this condition is indisputable, its etiology remains enigmatic. Due to the lack of clarity for the underlying cause (s) of FM, it poses a diagnostic challenge, often requiring multiple visits by specialists to render a diagnosis [7]. The lack of understanding of the biological basis of this condition also confounds our ability to develop effective interventions and/or monitor disease progression. FM has been suggested to be a complex, multifactorial trait that is influenced by age, gender (frequency is the highest in middle-aged females), and stress/trauma. Despite showing a strong familial aggregation [8-10], attempts to identify genetic factors associated with FM (primarily through polymorphism association studies) have yielded inconsistent results, with some investigators showing associations between FM and specific genes (including, but not limited to, genes for catechol-O-methyltransferase [11-13], serotonin-2A receptor [14, 15], serotonin transporter gene regulatory region [16, 17], dopamine D4 receptor [18], [beta]-2 adrenergic receptor [19], gamma-aminobutyric acid receptor subunit beta-3, trace amine-associated receptor 1, interferon-induced guanylate-binding protein 1, regulator of G protein signaling 4, cannabinoid receptor type 1, and glutamate receptor 4 [20]), while others failed to identify a relationship [21-25]. Since a consistent, straightforward association with a gene(s) has not yet been forthcoming, scientists have suggested that the familial influence on FM may more likely reflect a genetic susceptibility to environmental events [21, 26, 27]. For example, Klengel and Binder [28] identified differential methylation for a glucocorticoid response element (the FKBP5 gene) that resulted from the presence of both an "at-risk" allele (polymorphism) and the occurrence of childhood trauma in subjects they studied who had posttraumatic stress disorder.

Epigenetics, which refers to the process that affects gene expression independent of actual DNA sequence (such as methylation changes, histone alterations, and micro-RNA expression), has enabled scientists to conceptualize the impact of the environment upon one's genes and one's health [29]. Genes can be turned on or off and display variations in their level of expression, in part, due to epigenetic modifications [30]. Thus, epigenetics provides a biological means for understanding the molecular processes of complex biological networks that connect the brain, behavior, and health outcomes [31]. Given the overlap in symptoms and the medical/adverse social histories present in people who have FM, when compared to other conditions that have been shown to be impacted by somatic epigenetic and genetic alterations (such as depression and stress), it is plausible that similar epigenetic mechanisms may underlie the individual variability in the outcome of genetic and emotional inputs for FM.

Knowing that histone and other epigenetic modifications play a key role in establishing and maintaining chromatin structure, it follows that changes in epigenetic profiles, as a consequence of initiating events (such as stress/environmental exposure), could also lead to an increased frequency of somatic chromosomal changes. Indeed, we have shown that stress levels can impact the frequency of acquired chromosomal abnormalities by demonstrating a significantly increased frequency of somatic cell chromosomal instability in adult women who experienced childhood sexual abuse when compared to their identical cotwins who did not experience childhood sexual abuse (quantified using a micronucleus assay) [32]. Further support that chromosomal instability could arise as a downstream effect following perturbations in methylation comes from studies of individuals who have immunodeficiency, centromeric region instability, and facial anomalies (ICF) syndrome, which is an autosomal recessive condition resulting from a mutation in the methyltransferase gene B. People with this condition have an increased frequency of acquired chromosomal abnormalities [33].

An efficient means for quantifying the frequency of acquired (somatic) chromosomal abnormalities is the cytokinesis block micronucleus (CBMN) assay, which provides information regarding the presence of chromosomal errors in somatic cells with minimal influences attributable to in vitro selective growth pressures [34]. This technique is less labor intensive than conventional cytogenetic studies but provides results that are in close agreement to those obtained using the "gold standard" of metaphase chromosomal analyses [35]. Micronuclei, which are the primary cytological structures scored in the CBMN assay, are thought to contain chromatin (from one or more chromosomes) that was not incorporated ("lagging" or "lost") into the daughter binucleates following nuclear division [34]. Micronuclei frequencies have been shown to increase with age and have been associated with a variety of health conditions [36, 37]. However, to date, no investigators have reported the frequency of MN in women with FM. Based on the symptomatology and comorbidities related to this condition, we hypothesized that women with FM will have an increased frequency of acquired epigenetic and chromosomal alterations. To test this hypothesis, we initiated a pilot study to quantify chromosomal instability levels and genome-wide methylation patterns in women having FM and to compare these genetic/epigenetic values to those present in comparably aged, healthy control women.

2. Materials and Methods

2.1. Study Participant Ascertainment and Specimen Collection. Data for this study were obtained from a subset of participants (n=10), who were randomly recruited by mail from a larger, parent study sample of 64 women diagnosed with fibromyalgia (VCUIRB Protocol number HM12211) (Table 1). In the parent study, the participants completed a two-group randomized, controlled, clinical trial to examine the effect of guided imagery on self-efficacy, perceived stress, pain, fatigue, depression, and neuroendocrine/neuroimmune biomarkers in women with fibromyalgia syndrome [38]. Inclusion criteria for the women having FM were age (at least 18 years old); gender (female); receipt of a physician-confirmed diagnosis of FM based on the 1990 American College of Rheumatology criteria [39]; an ability to understand and sign the consent form; and an ability to understand/ complete the study questionnaires. Exclusion criteria for the women in the FM pilot group included the presence of other systemic rheumatologic conditions; being immunocompromised (e.g., diagnosis of HIV/AIDs); receiving corticosteroid treatments; having a major psychiatric or neurological condition that would interfere with study participation, or being pregnant. Each of the study subjects completed a self-report form to provide information regarding age, race/ethnicity, marital status, length of time since diagnosis of fibromyalgia, height and weight for calculating body mass index (BMI), and lifestyle practices such as history of smoking and alcohol use.

The healthy, comparatively aged control group of women for the MN studies (n = 42) were ascertained through their participation in a study of acquired genetic changes associated with normal aging, the latter of which is a twin study [40] (VCU IRB Protocol number 179). The inclusion criteria for this subset of control subjects were gender (female) and age (range from 36 to 69 years old), with all people from the previous study who met the criteria being included as controls for the current study to avoid sampling biases. The control cohort of women included both cotwin pairs (n=30 women or 15 cotwin pairs) and single twins, whose cotwin did not participate in this normal aging study (n=12 women). Due to cost limitations, DNA methylation studies were limited to a subset (n = 8) of the control women. This subset of women was randomly selected and included unrelated females (no cotwins). All of the control women self-reported their age, race/ethnicity, and lifestyle practices, such as history of smoking and alcohol use.

2.2. Biological Assays. Following the collection of the blood specimens from the patient and control women, the cells were processed to obtain binucleates for the micronuclei studies and DNA for the methylation studies as described in the following section.

2.2.1. Micronucleus Assay. Lymphocytes were collected using Histopaque-1077 (Sigma), stimulated with the mitogen phytohemagglutinin, established in culture, and blocked at cytokinesis according to the protocol of Fenech [35]. Briefly, cytochalasin B (3.0 [micro]g/mL; Sigma, 14930-92-2) was added to the cells 44 hours after culture initiation. At 72 hours, binucleate interphase cells were harvested using standard techniques, which included a 10-minute incubation in hypotonic solution (0.075 M KCl) and serial fixation (three times using a 3: 1 methanol: acetic acid solution). Slides were made following standard procedures. Micronuclei were visualized following Giemsa staining (4% Harleco Giemsa solution) and identified according to the criteria established by Fenech [35](Figure 1). The frequencies of micronuclei observed in the cytochalasin-B-blocked binucleated cells of the women with FM and the healthy control women were calculated by averaging the values obtained from two replicate scores (1000 binucleates were evaluated from two independent areas of the slide) for a total of 2000 binucleates that were evaluated per study participant.

2.2.2. DNA Isolation and Genome-Wide Methylation Assay. Genomic DNA was isolated from whole blood according to standard methods using the Puregene DNA isolation kit (Qiagen). An aliquot (500 ng per study participant) of DNA was then sent to Hudson Alpha Institute for Biotechnology for bisulfite conversion, using standard methods (Zymo Research EZ Methylation Kit) and genome-wide methylation pattern assessment, using the 450 K HumanMethylation Chip, according to the manufacturer's protocol (Illumina). The 450 K HumanMethylation Chip interrogates 485,764 genome-wide targets. Intensity data from the scanned arrays were imported into Illumina's GenomeStudio software and the minfi Bioconductor package in the R programming environment to obtain the [beta] values for each probe.

2.3. Statistical Analyses

2.3.1. Micronuclei Analyses. To test the hypothesis that women with FM have an increased frequency of acquired chromosomal alterations, the frequency of MN was compared between the women diagnosed with FM and the control group women. Given that a portion of the healthy controls were cotwins, a mixed effect model was used to control for familial relationships. MN frequency comparisons between cases and controls were adjusted for age since several studies have demonstrated increases in MN frequency with age [37, 40-42]. The independent effect of age on MN was evaluated using a Spearman correlation. Additional environmental effects were considered that have previously been shown to influence micronuclei frequencies. These included body mass index, alcohol use, and smoking in the women having FM [40]. However, given that values for body mass index, alcohol use, and smoking were not available for the controls (in a format comparable to those for cases), these variables were only assessed for the women with FM.

2.3.2. Genome-Wide Methylation Analyses. Because the 450 K HumanMethylation assay includes both the Infinium I design (which includes two probes for interrogating a CpG site) and the Infinium II design (which includes only one probe), the GC content was plotted separately by Infinium design type for the fully methylated sample, for which all CpG sites are expected to have consistently high [beta] values [43]. Based on these results, probes having a GC content greater than 40 were excluded from further analysis to ensure that the results would not be biased by the "GC" content of the underlying sequence. In addition, since the performance of probes containing single nucleotide polymorphisms (SNPs) can be variable, probes containing SNPs that were present within 10 bases of the target site were also excluded [43]. Because the expression value, [beta], reported for each CpG site represents "proportion methylated" which is constrained to an interval value from 0 to 1, where a [beta] of 1 indicates complete methylation and 0 indicates no methylation, the expression values were transformed using the logit transformation [M = log([beta]/(1 - to promote normality [44]. Prior to the logit transformation, imputation was completed (0.001 for [beta] values that were 0 and 0.999 for [beta] values that were 1) to avoid nonexistent M values. To adjust for the observation that [beta] values from the Infinium II designed probes have a compressed range compared to the [beta] values from the Infinium I design [43, 45, 46], the peak-correction method was applied to the logit transformed [beta] values for the Infinium II designed probes [46].

Statistical analyses were then performed on the peak corrected logit transformed [beta] values from the patient and control samples. For each CpG site, differential methylation between specimens collected from women with FM and controls was tested using the moderated t-test in the limma Bioconductor package [51, 52] in the R programming environment [53]. To adjust for the multiple hypothesis tests, the P values were used to estimate the false discovery rate (FDR) following Benjamini and Hochberg's [54]method. The DAVID gene functional classification tool [55]was used to identify biological relationships among the differentially methylated sites.

3. Results

3.1. Micro-nucleus Assay. As expected, the frequency of MN was correlated with age in both the women having FM (r = 0.717; P = 0.021) and the healthy controls (r = 0.579; P = 4.79 x [10.sup.-5])(Figure 1). After controlling for the effect of age and cotwin status, a significantly increased frequency of MN was observed in the women having FM (51.4 (21.9) (mean (sd)) per 1000 binucleates) compared to controls (15.8 (8.5) (mean (sd)) per 1000 binucleates) ([chi square] = 45.6; df=1; P = 1.49 x [10.sup.-11])(Figure 1). The increased levels of MN in the women having FM were not significantly correlated with their body mass index (range from 19.44 to 45.70; mean (sd) was 29.52 (7.21); P = 0.997), smoking history (4 smokers; 6 nonsmokers; P = 0.75), or alcohol use (6 consumers; 4 nonconsumers; P = 0.93). To assess if there might be a cumulative biological effect associated with experiencing symptoms associated with FM, we compared MN frequencies for the case subjects (n = 10) with the total number of years that had lapsed since these women received their diagnosis of FM. While there was a trend toward a positive correlation between a woman's MN frequency and the number of years since she was diagnosed with FM (ranged from 2 to 19 years), this relationship did not reach significance in this small pilot study (P = 0.134)(Table 1).

3.2. Genome-Wide Methylation Assay. After completion of the quality control assessments that were performed to remove any potential biases associated with probe sequence length, probe GC content, and inclusion of SNPs [56], a total of 381,989 CpG sites were retained. From these, a total of 69 sites were determined to be differentially methylated (DM) between the patients who have FM and the healthy controls, with 63 of these DM sites having higher values in the patients with FM and 6 having lower values (Figure 2). These 69 DM sites included CpG islands (46.4%); north shores (20.3%); south shores (8.7%); as well as north (4.3%) and south (1.4%) shelves and sites that were not annotated into the previously noted categories (18.8%). The DM sites were localized to 47 different genes (Table 2), with 3 genes having multiple sites identified (N-acetyltransferase 15 gene (NAT15) had 4 DM sites; DNAJ (Hsp40) homolog, subfamily C, member 17 (DNAJC17) had 2 DM sites; and SLC17A9 and 2 DM sites). An assessment of potential biologically related clusters of DM sites resulted in the recognition of 15 groups, including gene clusters involved in neuron differentiation and nervous system development (Table 3).

4. Discussion

While the sample size in this pilot study is small, the MN frequency patterns of both the case and control women showed an age-related increase, which is a finding that is in agreement with the age-related increase that has consistently been reported in larger studies [40, 41]. Interestingly, the mean frequency of MN in the women with FM was 3.26 fold higher than the level seen in the healthy controls. In comparison, patients who have cancer have been noted to have 1.37- to 3.13-fold higher frequencies of MN when compared to healthy controls [57, 58]. Given that the risk for cancer has been shown to be predicted by MN levels [37, 41, 58], the results of this preliminary data, if confirmed, suggest that MN frequency assessments may be useful for evaluating/diagnosing women with FM. Indeed, recent assessments of MN frequencies in people evaluated from various areas of biobehavioral science have shown increased levels of acquired chromosomal instability (assessed using MN frequencies) in adult women who experienced childhood sexual abuse [32]; patients who have neurodegenerative conditions, such as Alzheimer's disease and Parkinson's disease [59]; and adults with type 2 diabetes and cardiovascular disease [60]. The presence of acquired chromosomal instability, which could lead to somatic tissue mosaicism, has been conjectured to occur as a global biological process that affects many tissues and contributes to the development of several conditions, including (but not limited to) autism, schizophrenia, autoimmune diseases, and Alzheimer's disease [61]. Given that several of these conditions are age related, one could speculate that there may be a "threshold" level of chromosomal instability required for eliciting a biological consequence. Factors contributing to MN formation are multifold and include both genetic [40] and environmental influences [37, 40, 41]. Environmental exposures that have been shown to increase the frequency of MN include, but are not limited to, diet (especially folate deficiency) [41, 62, 63], hormone levels [64], and exposures to substances/occupational hazards [37]. The biological means whereby these genetic/environmental influences lead to acquired chromosomal instability are likely to be varied but have been noted to reflect the chromatin conformation of the chromosomes [65]. One can speculate that alterations in chromatin conformation, which are likely to arise (at least in part) from epigenetic changes, may compromise the ability of the chromosomes to align, attach to mitotic spindle fibers, and/or separate, thereby leading to their increased frequency of abnormalities [66]. In turn, the presence of acquired chromosomal abnormalities could lead to additional epigenetic alterations.

While limited in number, studies performed to assess the effect of methylation on chromosome segregation have consistently shown an increase in the frequency of cytogenic abnormalities associated with perturbations in the methylation status of chromosomes [67]. In this study, it is interesting to note that DM sites were identified for genes having a function related to chromatin compaction and/or segregation (NAT15; HDAC4; UHRF1). For example, DM sites were observed for the NAT15 gene, which is agene that has been identified to play an important role in normal chromosomal segregation during anaphase [68]. While the results of the genome-wide methylation patterns evaluated in this study are preliminary, it is exciting to note that several of the sites that were DM between the women with FM and controls were localized to genes that have functional relevance to the symptoms seen in patients with FM. Of particular interest was the observation of a significant difference in the methylation pattern of the BDNF gene between patients with FM and controls. The BDNF gene has been noted to play an important neuromodulatory role in pain transduction (eliciting hyperalgesia) [69-71] and has also been recognized as a contributor to learning and memory [72, 73]. A second gene of apparent relevance with which a DM site was associated was the protein kinase C, alpha gene (PRKCA) (Table 3). This gene, which is involved in cell signaling pathways, has been associated with emotional memory formation, posttraumatic stress syndrome, cancer, and aging. A third gene of particular interest that had a DM site is Reticulon 1 (RTN1). RTN1 has been associated with neurological diseases (and cancer) and is thought to influence membrane trafficking in neuroendocrine cells. Overall, genes with which DM sites were associated include (but are not limited to) those having functions in chromatin compaction (NAT15; HDAC4; UHRF1); DNA damage/repair or chromosomal segregation (SOD3; UHRF1; NAT15); muscle contraction (NR4A3; HDAC4; FEZ1; PRKG1; KCNH7); axonal bundling/outgrowth (FEZ1); cell signaling in muscle (NR4A3; PRKG1); neuronal excitability/synaptic transmission (BDNF; BZRAP1; EPHA5; KCNH7); muscle maturation (HDAC4); response to oxidative stress (SOD3); and inflammatory processes (AXL; SH2B2). However, since two of the significant biological clusters that were identified (Table 3) were for polymorphisms and sequence variants, it is important to recognize that this is a pilot study and that a larger number of individuals will need to be evaluated to allow one to determine the extent, if consistently present, of DM on the development or severity of symptoms associated with FM.

The results of genome-wide methylation studies have provided insight regarding the role of genes and environmental influences for a variety of conditions, with many of these investigations focusing on the areas of cancer and psychiatric conditions [74, 75]. However, the epigenomes of diseases causing chronic pain have been less extensively evaluated. In their study of rheumatoid arthritis, Nakano et al. [76] observed several DM sites between patients who have rheumatoid arthritis and controls. They also identified distinct epigenomic signatures when comparing patterns from patients with rheumatoid arthritis and osteoarthritis. Akin to the results of this pilot study, the findings of their investigation led to the recognition of perturbations in the methylation status of several genes having functions related to the symptoms associated with rheumatoid arthritis. Thus, the use of genome-wide epigenetic assessment seems to be a promising tool for evaluating a broad spectrum of conditions, including those associated with chronic pain.

5. Conclusion

In summary, the results of this pilot study suggest that chromosomal instability and alterations in methylation are present in women with FM. If these results can be confirmed, they could provide a basis for improving our understanding of the biological changes leading to the development of FM and may provide a basis for stratifying patients based on their epigenomic and symptom patterns. Moreover, since epigenetic changes demonstrate plasticity [77], the recognition of consistent epigenetic alterations associated with FM could provide a means for developing future therapeutic approaches to reverse these changes, with a goal of alleviating symptoms in people who have FM.

http://dx.doi.org/10.1155/2013/795784

Acknowledgments

This work was supported in part by grants from the National Institute of Nursing Research through Grant (P30NR011403, Grap (PI)) and the National Institute of Environmental Health (R01 ES12074 C Jackson-Cook (PI)). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIEHS, NIH.

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Victoria Menzies, (1) Debra E. Lyon, (1,2) Kellie J. Archer, (3) Qing Zhou, (3) Jenni Brumelle, (4) Kimberly H. Jones, (4,5) G. Gao, (3) Timothy P. York, (6) and Colleen Jackson-Cook (2,4,6)

(1) Virginia Commonwealth University School of Nursing, 1100 East Leigh Street, Richmond, VA 23298-0567, USA

(2) Massey Cancer Center, Virginia Commonwealth University, VA 23298-0037, USA

(3) Department of Biostatistics, Virginia Commonwealth University, 830 East Main Street, Richmond, VA 23298, USA

(4) Department of Pathology, Virginia Commonwealth University, P.O. Box 980662, Richmond, VA 23298-0662, USA

(5) Neodiagnostix, 9700 Great Seneca Highway, Rockville, MD 20850, USA

(6) Department of Human and Molecular Genetics, Virginia Commonwealth University, P.O. Box 980033, Richmond, VA 23298-0003, USA

Correspondence should be addressed to Victoria Menzies; vsmenzies@vcu.edu

Received 30 April 2013; Accepted 14 July 2013

Academic Editor: Susan Dorsey

TABLE 1: MN frequencies and other attributes of women with FM.

Participants with FM         Age         Mean number MN
                                       per 1000 binucleates

1009                          48               32.5
1025                          52               13.5
1030                          61                71
1038                          52               66.5
1042                          45               47.5
1047                          62               77.5
1052                          44                42
1058                          45               27.5
1061                          58               66.5
1066                          56               69.5
FM group mean (sd)        48.2 (6.7)       52.1 (21.9)
(n = 10)
Control group mean (sd)   52.0 (9.8)        15.8 (8.5)
(n = 42) *

Participants with FM      Years since FM   Alcohol use   Smoker
                            diagnosis

1009                            2              Yes         No
1025                            3              Yes        Yes
1030                            7              No          No
1038                            19             No          No
1042                            14             No          No
1047                            19             Yes         No
1052                            1              Yes        Yes
1058                            4              No          No
1061                            2              Yes        Yes
1066                            4              Yes        Yes
FM group mean (sd)
(n = 10)
Control group mean (sd)
(n = 42) *

Participants with FM      Body mass index    Race

1009                           45.7         Other
1025                           19.4         C (1)
1030                           28.3           C
1038                           35.5           C
1042                           30.1         AA (2)
1047                           27.1           C
1052                           30.5           AA
1058                           27.3           AA
1061                           21.1           C
1066                           29.0           AA
FM group mean (sd)         29.52 (7.21)
(n = 10)
Control group mean (sd)
(n = 42) *

* Individual data not shown.

(1) C: Caucasian (white); (2) AA: African American (Black).

TABLE 2: Genes associated with sites differentially
methylated in patients with fibromyalgia.

Gene name              Description of function (1)      Location (2)
(abbreviation)

AXL receptor           Involved in stimulation of       19: 41731934
tyrosine kinase        cell proliferation and
(AXL)                  aggregation; induced by
                       TGF-[beta]1/inflammation; and
                       can block cytokine production

N-Acetyltransferase    Histone acetyltransferase;       16: 3507460
15 (NAT15)             mediates acetylation of free
                       histone H4; also required for
                       normal chromosomal segregation
                       during anaphase

Solute carrier         Vesicular nucleotide             20: 61584072
family 17, member 9    transporter involved in
(SLC17A9)              exocytosis of ATP in secretory
                       vesicles (synaptic vesicles)

Brain-derived          Involved in the regulation of    11: 27740495
neurotrophic factor    stress response and in the
(BDNF)                 biology of mood disorders;
                       major regulator of synaptic
                       transmission and plasticity at
                       adult synapses in many regions
                       of the CNS; contributes to
                       several adaptive neuronal
                       responses including long-term
                       potentiation, long-term
                       depression, certain forms of
                       short-term synaptic
                       plasticity, and homeostatic
                       regulation of intrinsic
                       neuronal excitability

Mahogunin ring         Mediates monoubiquitination at   16: 4714733
finger 1, E3           multiple sites; plays a role
ubiquitin protein      in the regulation of endosome-
ligase (MGRN1)         to-lysosome trafficking.

Plasma glutamate       Involved in hydrolysis of        8: 97657294
carboxypeptidase       circulating peptides Involved
(PGCP)                 in diverse cell signaling
                       pathways; activated by
                       calcium;

Protein kinase C,      associated with cancer;          17: 64787379
alpha (PRKCA)          posttraumatic stress syndrome;
                       emotional memory formation;
                       and aging

Gamma-                 Function not clear and may       22: 24989248
glutamyltransferase    vary; has been associated with
1 (GGT1)               arterial stiffness and
                       coronary artery disease [47]

Reticulon 1 (RTN1)     Involved in secretion or         14: 60097209
                       membrane trafficking in
                       neuroendocrine cells;
                       associated with neurological
                       diseases and cancer

NFXL1 nuclear          Integral to the nucleus and      4: 47917042
transcription          membrane
factor, X-box
binding-like 1
(NFXL1)

Heat shock 70          Member of the heat shock         11: 122933028
kDa protein 8          protein family, functions as a
(HSPA8)                chaperone and facilitates
                       protein folding

Polymeric              Member of the immunoglobulin     1: 207103660
immunoglobulin         superfamily that facilitates
receptor (PIGR)        expression of immunoglobulins
                       A and M; regulated by
                       cytokines

Benzodiazepine         An adaptor molecule known to     17: 56401800
receptor               regulate synaptic transmission
(peripheral)           [48]
associated protein 1
(BZRAP1)

Transmembrane          In vivo function not clearly     19: 41882253
protein 91 (TMEM91)    established

Neuron-derived orphan  Target of [beta]-andrenergic     9: 102588232
receptor 1 (NR4A3)     signaling in skeletal muscle
                       [49]

V-set and              In vivo function not clearly     12: 118541722
immunoglobulin         established
domain containing 10
(VSIG10)

Potassium voltage-     Involved in regulating           2: 163695111
gated channel          neurotransmitter release,
subfamily H member 7   heart rate, insulin secretion,
(KCNH7)                neuronal excitability,
                       epithelial electrolyte
                       transport, smooth muscle
                       contraction, and cell volume.

V-set and              In vivo function not clearly     7: 54609587
transmembrane domain   established
containing 2A
(VSTM2A)

Ephrin type-A          Protein-tyrosine kinase family   1: 16482553
receptor 2 (EPHA2)     member; implicated in
                       mediating developmental
                       events, particularly in the
                       nervous system. A
                       transmembrane receptor of the
                       patched gene family; may
                       function

Patched 2 (PTCH2)      as a tumor suppressor in the     1: 45297445
                       hedgehog signaling pathway;
                       has been associated with
                       several different types of
                       cancer Responsible for the
                       deacetylation of the core
                       histones; gives tag for
                       epigenetic repression; plays
                       important role in
                       transcriptional

Histone deacetylase    regulation, cell cycle           2: 240044021
4, (HDAC4)             progression, and developmental
                       events; also involved in
                       muscle maturation through
                       interaction with the myocyte
                       enhancer factors

ADP-ribosylarginine    Catalyzes removal of mono-       3: 119299162
hydrolase (ADPRH)      ADP-ribose from arginine
                       residues of proteins in the
                       ADP-ribosylation cycle.

Fasciculation and      Involved in normal axonal        11: 125365478
elongation protein     bundling and elongation within
zeta 1 (zygin I)       axon bundles; may also
(FEZ1)                 function in axonal outgrowth.

Superoxide dismutase   Antioxidant enzyme thought to    4: 24801801
3, extracellular       protect the brain, lungs, and
(SOD3)                 other tissues from oxidative
                       stress.

Transcription factor   Transcription factor;            6: 10420079
AP-2 alpha 2           activates the transcription of
(TFAP2A)               some genes while inhibiting
                       the transcription of others

Odz, odd Oz/ten-m      May function as a cellular       4: 183370512
homolog 3 (ODZ3)       signal transducer Mediates
                       developmental events,
                       particularly in the nervous
                       system;

Ephrin type A          plays a role in synaptic         4: 66535145
receptor 5 (EPHA5)     plasticity in adult brain
                       through regulation of
                       synaptogenesis; also mediates
                       communication between
                       pancreatic islet cells to
                       regulate glucose-stimulated
                       insulin secretion

Suppressor of fused    Plays a role in pattern          10: 104393081
homolog (Drosophila)   formation and cellular
(SUFU)                 proliferation during
                       development; encodes a
                       negative regulator of the
                       hedgehog signaling pathway

Rh family, C           Functions as an electroneutral   15: 90039613
glycoprotein (RHCG)    and bidirectional ammonium
                       transporter

DNAJ (Hsp40)           Heat shock protein homolog       15: 41062113
homolog, subfamilyC,
member 17 (DNAJC17)

Autism                 Function not fully known;        7: 70158761
susceptibility         deletions of this gene have
candidate 2 (AUTS2)    been associated with autism
                       and intellectual disability

Deleted in             In vivo function not clearly     13: 51417846
lymphocytic            established
leukemia, 7 (DLEU7)

SH2B adaptor protein   Involved in multiple signaling   7: 101934892
2 (SH2B2)              pathways; may function as a
                       negative regulator of cytokine
                       signaling; suppresses PDGF-
                       induced mitogenesis: may
                       induce cytoskeletal
                       reorganization via interaction
                       with VAV3

Alpha-kinase 3         Recognizes phosphorylation       15: 85360691
(ALPK3)                sites (alpha-helical
                       conformation); may play a role
                       in cardiomyocyte
                       differentiation

VENT homeobox          May function as a                10: 135050326
(VENTX)                transcriptional repressor and
                       influence mesodermal
                       patterning and hemopoietic
                       stem cell maintenance

Lymphocyte antigen 6   Located in the major             6: 31649619
complex, locus G5C     histocompatibility complex
(LY6G5C)               (MHC) region on chromosome 6;
                       may be involved in signal
                       transduction or hematopoietic
                       cell differentiation

Primary ciliary        May function in ciliary          2: 120301847
dyskinesia protein 1   motility
(PCDP1)

Protein kinase,        Involved in signal               10: 52833610
cGMP-dependent, type   transduction processes in
I (PRKG1)              diverse cell types; plays role
                       in regulating cardiovascular
                       and neuronal functions and in
                       relaxing smooth muscle tone,
                       preventing platelet
                       aggregation, and modulating
                       cell growth

MAP7 domain            X-linked imprinted gene that     X: 20134719
containing 2           may affect sex-specific brain
(MAP7D2)               function and-or sex-dependent
                       neurobiological traits [50]

Carboxypeptidase M     Associated with monocyte to      12: 69346994
(CPM)                  macrophage differentiation;
                       may play role in control of
                       peptide hormone and growth
                       factor activity at the cell
                       surface and in the membrane-
                       localized degradation of
                       extracellular proteins

Growth                 Member of TGF-beta               19: 18981378
differentiation        superfamily; may function in
factor 1 (GDF1)/       regulation of cell growth and
LAG1 longevity         differentiation in embryonic
assurance homolog 1    and adult tissues and neural
(LASS1)                development in later
                       embryogenesis; may be involved
                       in aging

Ubiquitin-like,        Recruits a histone deacetylase   19: 4916593
containing PHD and     to regulate gene expression;
RING finger domains,   involved in G1-S transition
1 (UHRF1)              and functions in the p53-
                       dependent DNA damage
                       checkpoint

Anoctamin 3 (AN03)     May act as a calcium-            11: 26353723
                       activated chloride channel

Homeobox protein       DNA-binding transcription        7: 27196790
Hox-A7 (HOXA7)         factor that may regulate gene
                       expression, morphogenesis, and
                       differentiation

Transmembrane          Enriched in the bottom portion   3: 194353554
protein 44 (TMEM44)    of taste buds

Potassium voltage-     Voltage-gated potassium          11: 2554583
gated channel, KQT-    channel required for
like subfamily,        repolarization phase of the
member 1 (KCNQ1)       cardiac action potential;
                       mutations associated with
                       hereditary long QT syndrome 1,
                       the Jervell and Lange-Nielsen
                       syndrome, and familial atrial
                       fibrillation; exhibits tissue-
                       specific imprinting; located
                       in a region associated with
                       the Beckwith-Wiedemann
                       syndrome

Polymerase I and       Regulates rRNA transcription;    17: 40558063
transcript release     thought to modify lipid
factor 1 (PTRF)        metabolism and insulin-
                       regulated gene expression

(1) Functional descriptions obtained from Gene Cards and/or
Wikipedia summations and indicated references. (2) Chromosome:
starting nucleotide position.

TABLE 3: Cluster analysis of genes having significantly
different methylation patterns in women with FM.

Genetic ontology/keyword term          No. of Genes   P value

Anatomical structure development            17        0.0002
System development                          16        0.0003
Developmental process                       18        0.0008
Multicellular organismal development        17        0.0009
Polymorphism                                41        0.0011
Sequence variant                            42        0.0012
Domain: fibronectin type III 1, 2           4         0.0045
Glycosylation site                          20        0.0047
Neuron differentiation                      6         0.0048
Nervous system development                  9         0.0053
Protein metabolic process                   15        0.0067
Autopho sphorylation                        3         0.0069
Glycoprotein                                20        0.0073
Skeletal system development                 5         0.0085
Organ development                           11        0.0097
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Title Annotation:Research Article
Author:Menzies, Victoria; Lyon, Debra E.; Archer, Kellie J.; Zhou, Qing; Brumelle, Jenni; Jones, Kimberly H
Publication:Nursing Research and Practice
Article Type:Report
Date:Jan 1, 2013
Words:7819
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