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<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Endocrinol.</journal-id>
<journal-title>Frontiers in Endocrinology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Endocrinol.</abbrev-journal-title>
<issn pub-type="epub">1664-2392</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fendo.2024.1480274</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Endocrinology</subject>
<subj-group>
<subject>Hypothesis and Theory</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Osteocytes contribute to sex-specific differences in osteoarthritic pain</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Jones</surname>
<given-names>Ryan</given-names>
</name>
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<contrib contrib-type="author">
<name>
<surname>Gilbert</surname>
<given-names>Sophie J.</given-names>
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<contrib contrib-type="author">
<name>
<surname>Christofides</surname>
<given-names>Sarah R.</given-names>
</name>
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<contrib contrib-type="author" corresp="yes">
<name>
<surname>Mason</surname>
<given-names>Deborah J.</given-names>
</name>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
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<aff id="aff1">
<institution>Biomechanics and Bioengineering Research Centre Versus Arthritis, School of Biosciences, Cardiff University</institution>, <addr-line>Cardiff</addr-line>, <country>United Kingdom</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Katherine A. Staines, University of Brighton, United Kingdom</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Karan Mehul Shah, The University of Sheffield, United Kingdom</p>
<p>Zhen Geng, Shanghai University, China</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Deborah J. Mason, <email xlink:href="mailto:masondj@cardiff.ac.uk">masondj@cardiff.ac.uk</email>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>07</day>
<month>11</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>15</volume>
<elocation-id>1480274</elocation-id>
<history>
<date date-type="received">
<day>13</day>
<month>08</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>16</day>
<month>10</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2024 Jones, Gilbert, Christofides and Mason</copyright-statement>
<copyright-year>2024</copyright-year>
<copyright-holder>Jones, Gilbert, Christofides and Mason</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Osteoarthritic (OA) pain affects 18% of females and 9.6% of males aged over 60 worldwide, with 62% of all OA patients being women. The molecular drivers of sex-based differences in OA are unknown. Bone is intricately coupled with the sensory nervous system and one of the only joint tissues known to show changes that correlate with patient pain in OA. There are fundamental sex differences in pain sensation and bone biology which may be intrinsic to OA disease progression, however these differences are vastly under researched. We have utilised three data sets to investigate the hypothesis that potential mediators responsible for sex dependent pain mechanisms displayed in OA are derived from mechanically stimulated osteocytes. Our published dataset of the <italic>in vitro</italic> human osteocyte mechanosome was independently compared with published data from, sex-based gene expression differences in human long bone, the sex-based gene expression differences during the skeletal maturation of the mouse osteocyte transcriptome and sex specific OA risk factors and effector genes in a large human GWAS. 80 of the 377 sex-specific genes identified in the mouse osteocyte transcriptome were mechanically regulated in osteocytes with enrichment associated with neural crest migration and axon extension, and DISEASES analysis enrichment for the rheumatoid arthritis pathway. 3861 mechanically regulated osteocytic genes displayed sex-specific differences in human long bone with enrichment for genes associated with the synapse, sensory perception of pain, axon guidance, immune responses, distal peripheral sensory neuropathy, sensory neuropathy, and poor wound healing. 32 of 77 effector genes and 1 of 3 female specific OA risk factor genes identified in the human GWAS were differentially expressed in the osteocyte mechanosome and male and female bone. This analysis lends support to the hypothesis that mechanically regulated genes in osteocytes could influence sex specific differences in osteoarthritic pain and highlights pain pathways with approved drugs that could potentially treat elevated pain susceptibility in females with OA.</p>
</abstract>
<kwd-group>
<kwd>osteoarthritis</kwd>
<kwd>pain</kwd>
<kwd>osteocyte</kwd>
<kwd>sex differences</kwd>
<kwd>menopause</kwd>
</kwd-group>
<contract-sponsor id="cn001">National Centre for the Replacement, Refinement and Reduction of Animals in Research<named-content content-type="fundref-id">10.13039/501100000849</named-content>
</contract-sponsor>
<contract-sponsor id="cn002">Versus Arthritis<named-content content-type="fundref-id">10.13039/501100012041</named-content>
</contract-sponsor>
<contract-sponsor id="cn003">Wellcome Trust<named-content content-type="fundref-id">10.13039/100010269</named-content>
</contract-sponsor>
<counts>
<fig-count count="6"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="81"/>
<page-count count="14"/>
<word-count count="6275"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Bone Research</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Chronic pain in osteoarthritis (OA) is a severe and debilitating condition affecting an estimated 530 million sufferers worldwide, limiting patient mobility, ability to perform daily activities and live independently (<xref ref-type="bibr" rid="B1">1</xref>). Sex-based differences in the clinical presentation and prevalence of OA has been described for decades but are widely under-researched (<xref ref-type="bibr" rid="B2">2</xref>). Women over the age of 55 have a higher prevalence of knee OA than men of the same age (<xref ref-type="bibr" rid="B3">3</xref>) and a higher prevalence of hand OA (<xref ref-type="bibr" rid="B4">4</xref>). Women with OA also suffer more debilitating pain (<xref ref-type="bibr" rid="B3">3</xref>), more annual articular cartilage loss (<xref ref-type="bibr" rid="B5">5</xref>) and have a more severe radiographic OA when compared to equivalent male patients. Female sex hormones, such as oestrogen, are known to act directly on nociceptors to mitigate pain (<xref ref-type="bibr" rid="B6">6</xref>) and exert protective roles in articular cartilage and subchondral bone (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B7">7</xref>) and more than half of post-menopausal women suffer with OA pain (<xref ref-type="bibr" rid="B8">8</xref>). Therefore, it has been assumed that the differences in male and female OA pain and progression are due to withdrawal of the protective effects of oestrogen (<xref ref-type="bibr" rid="B9">9</xref>) but research results are controversial. In a large cohort study, Cirillo et&#xa0;al. found that oestrogen treatment alone lowered the prevalence of hip replacement but not knee replacement (<xref ref-type="bibr" rid="B10">10</xref>) whereas another study of post-menopausal woman with both symptomatic and radiographic OA receiving hormone therapy, reported a lower prevalence of knee OA (<xref ref-type="bibr" rid="B11">11</xref>).</p>
<p>Bone is sexually dimorphic, displaying different gene expression profiles, sex hormone sensitivities and mechanical responses between males and females. Subchondral bone is also one of the only tissues to show structural changes that correlate to pain in OA patients (<xref ref-type="bibr" rid="B12">12</xref>). The inhibition of bone resorption to prevent OA disease progression in animal models and OA patients is also an emerging research area (reviewed in <xref ref-type="bibr" rid="B13">13</xref>). There are intimate associations between nerves and bone. Skeletal sensory nerve sprouting, invasion and sensitisation are associated with bone pathologies, demonstrated in rodent and human OA joints, and intrinsic to pain responses in animal models of OA (<xref ref-type="bibr" rid="B14">14</xref>), and humans with OA (<xref ref-type="bibr" rid="B15">15</xref>). Densely innervated subchondral bone channels have been shown to accompany sclerotic subchondral bone remodelling in the tibial plateaux and femoral condyles of end-stage OA knees in animal models (<xref ref-type="bibr" rid="B16">16</xref>). Areas of OA structural damage, necrosis and remodelling in the subchondral bone known as bone marrow lesions (BML) are characterised by sensory nerve invasion and correlate with pain (<xref ref-type="bibr" rid="B17">17</xref>). Enlargement of BMLs is associated with worsening joint degeneration and increased pain, whereas reduced BML severity relieves pain (<xref ref-type="bibr" rid="B18">18</xref>). The formation of BMLs is known to be modulated by mechanical loading. Abnormal joint loading through obesity, malalignment, trauma, or joint instability are key risk factors for OA (<xref ref-type="bibr" rid="B19">19</xref>). BML presence and location are associated with joint malalignment (<xref ref-type="bibr" rid="B20">20</xref>); medial BMLs occur mostly in varus knee, lateral in valgus (<xref ref-type="bibr" rid="B20">20</xref>). Absence/regression of BMLs occurs following mechanical (bracing) (<xref ref-type="bibr" rid="B21">21</xref>) or bone sparing pharmaceutical (Zoledronic acid) interventions (<xref ref-type="bibr" rid="B22">22</xref>). Osteocytes, the mechanosensing cells in bone, orchestrate bone remodelling in response to mechanical load, inflammation, and hormones (<xref ref-type="bibr" rid="B23">23</xref>). In a previous study, we developed a human 3D model of osteocytes differentiated from Y201 Mesenchymal Stem Cells in Type I collagen (<xref ref-type="bibr" rid="B24">24</xref>). This model shows dendritic morphology, and expresses osteocyte markers BGLAP SOST, PDPN, OPG, GJA1, C44, FGF23, PHEX and PHOSPHO1 (<xref ref-type="bibr" rid="B24">24</xref>). Pathophysiological (4300 microstrain) (<xref ref-type="bibr" rid="B25">25</xref>) loads applied to this osteocyte model under osteogenic conditions regulated proteins reflecting bone remodelling and inflammation. RNAseq analysis on pathophysiologically loaded versus unloaded osteocytes in this 3D model revealed 7564 differentially expressed genes (DEGs), which we have called the osteocyte mechanosome (<xref ref-type="bibr" rid="B24">24</xref>). The osteocyte mechanosome included genes involved in inflammation, matrix organisation, ageing, ossification, bone morphogenesis, cartilage development, and bone mineralisation (<xref ref-type="bibr" rid="B24">24</xref>) as well as &gt; 200 genes directly involved in nociception, neuropathic pain, nociceptor sensitisation, neuronal axonal guidance, and neuro-sensitivity (<xref ref-type="bibr" rid="B24">24</xref>). We have previously used this model to investigate mechanical and inflammatory mechanisms underlying osteoarthritic pathology (<xref ref-type="bibr" rid="B24">24</xref>). In the current hypothesis and theory paper, we have compared published data with the osteocyte mechanosome to test the notion that genes that are mechanically regulated in osteocytes and differentially expressed in males and females could explain sex-specific susceptibility to pain.</p>
<p>We hypothesise that differences between male and female susceptibility to osteoarthritic pain is influenced by sex-specific responses of osteocytes to mechanical stimulation. To test this, we have performed a meta-analysis of published RNAseq data to determine whether regulated genes in the osteocyte mechanosome are differentially expressed in male and female bone. The resulting sex-specific mechanically regulated genes were compared with OA risk loci from human Genome Wide Association Studies (GWAS) to highlight mediators linked to sex differences in OA. We then investigate whether these sex specific genes in the osteocyte mechanosome are associated with pathways linked to the generation of pain and represent new druggable targets that could treat female heightened susceptibility to osteoarthritic pain.</p>
</sec>
<sec id="s2">
<label>2</label>
<title>Methods and results</title>
<p>Three independent analyses were used to interrogate the above hypothesis; these were then combined to investigate the potential mediators responsible for the osteocyte-derived sex dependent pain mechanisms displayed in OA (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). All analysis was performed using R 4.3.1 (<xref ref-type="bibr" rid="B31">31</xref>) in RStudio 2023.12.0 (<xref ref-type="bibr" rid="B32">32</xref>). Our published dataset (<xref ref-type="bibr" rid="B24">24</xref>) of <italic>in vitro</italic> human osteocyte responses to pathophysiological mechanical loading (&#x2018;osteocyte mechanosome&#x2019;) was independently compared with published data from, sex-based gene expression differences during the skeletal maturation of the mouse osteocyte transcriptome (Analysis 1) (<xref ref-type="bibr" rid="B26">26</xref>), the sex-based gene expression differences in human long bone explant-derived osteoblasts (Analysis 2) from 4 healthy children (a reanalysis of a subset of published dataset in Sex-Associated Gene Database repository number 00129 (<xref ref-type="bibr" rid="B27">27</xref>, <xref ref-type="bibr" rid="B33">33</xref>) and sex specific OA risk factors and effector genes in a large human GWAS of 826,690 individuals from 9 populations (Analysis 3) (<xref ref-type="bibr" rid="B28">28</xref>). The osteocyte transcriptome and SAGD datasets were selected as they represent the only available RNA sequencing datasets detailing sex-regulated gene expression within bone. The GWAS data was selected as the largest OA GWAS currently available worldwide. Log2 fold changes (log2FC) were standardised so that females were always the numerator and males the denominator (<italic>i.e.</italic>, a positive log2FC would correspond to higher expression in females, and a negative log2FC to a higher expression in males. Positive log2FC within the osteocyte mechanosome indicates genes upregulated by mechanical load, whereas negative log2FC indicates downregulation in response to loading.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>RNA sequencing data from mechanically regulated osteocytes (&#x2018;the osteocyte mechanosome&#x2019;) (<xref ref-type="bibr" rid="B24">24</xref>) were independently compared with sex specific differences identified in the mouse osteocyte transcriptome (<xref ref-type="bibr" rid="B26">26</xref>) (Analysis 1) and sex-specific human long bone derived osteoblasts (<xref ref-type="bibr" rid="B27">27</xref>) (Analysis 2), and genes that showed co-regulation taken forward for further analysis. Mechanically regulated genes in the osteocyte mechanosome that also displayed sex regulation in the human long bone derived osteoblasts (Analysis 2) were combined with human GWAS loci associated with increased risk of OA in females and heightened OA pain (<xref ref-type="bibr" rid="B28">28</xref>) (Analysis 3). Sex specific mechanically regulated genes in osteocytes were searched for functional and disease pathway enrichment (<xref ref-type="bibr" rid="B29">29</xref>) and druggable targets (<xref ref-type="bibr" rid="B30">30</xref>).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-15-1480274-g001.tif"/>
</fig>
<p>Protein encoding genes that displayed significant regulation by mechanical loading in the osteocyte mechanosome and by sex in published datasets (Analyses 1 and 2) were used to identify potential mediators of sex-based differences in OA pain (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). GWAS loci associated with heightened OA pain, female specific risk factors and OA effector genes (<xref ref-type="bibr" rid="B28">28</xref>) was combined with the sex-specific mechanically regulated genes identified from Analysis 2 to reveal sex specific OA risk factors in the osteocyte mechanosome (Analysis 3) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>).</p>
<p>The resulting genes from each analysis that displayed significant co-regulation were annotated with GO terms from Ensembl. Over-representation analysis was performed using clusterProfiler (<xref ref-type="bibr" rid="B29">29</xref>) and GO.db (<xref ref-type="bibr" rid="B34">34</xref>), using all genes represented in the osteocyte mechanosome as the enrichment background. Computational prediction of protein-protein network interactions of significantly regulated genes was performed using String.db (<xref ref-type="bibr" rid="B35">35</xref>). The top 1000 protein-protein interactions were generated in R (<xref ref-type="bibr" rid="B31">31</xref>) then uploaded to the string online interface (string-db.org) for STRING network analysis. Gene Ontology, KEGG pathway, human phenotype (Monarch) Disease-gene association (DISEASES) and annotated keyword (UniProt) functional enrichment analyses of the generated network were also performed using this online interface. GO:terms known to be affiliated with the generation of pain responses or joint pathology that were enriched within the dataset were extracted and used to highlight mediator genes in biplot graphs and tables. Within individual biplots, all genes beyond a set Log2-fold change threshold (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;1</bold>
</xref>) were labelled to ensure graph clarity and specific genes of interest outside this range italicised. Sex specific genes in the osteocyte mechanosome were searched for druggable targets (<xref ref-type="bibr" rid="B30">30</xref>) (<ext-link ext-link-type="uri" xlink:href="https://www.dgidb.org">https://www.dgidb.org</ext-link>).</p>
<sec id="s2_1">
<label>2.1</label>
<title>Analysis 2 - the osteocyte mechanosome and sex specific differences in human long bone derived osteoblasts</title>
<p>In Analysis 1 (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>), our osteocyte mechanosome was combined with a published dataset from within the osteocyte transcriptome reflecting DEGs in mouse male and female osteocytes (<xref ref-type="bibr" rid="B26">26</xref>). Differentially expressed osteocyte enriched genes were identified from bones of skeletally mature (16 weeks) and aged (26 weeks) male and female mice. The data from Youlten et&#xa0;al. (<xref ref-type="bibr" rid="B26">26</xref>) was downloaded from the associated GitHub repository (<xref ref-type="bibr" rid="B26">26</xref>) and their analysis recapitulated using their code to regenerate a list of genes associated with the osteocyte transcriptome. In brief, differential expression between male and female mice in their dataset was calculated just for osteocyte-associated genes using <italic>edgeR</italic> (<xref ref-type="bibr" rid="B36">36</xref>) and <italic>limma</italic> (<xref ref-type="bibr" rid="B37">37</xref>). Sex comparisons were carried out separately for 16-week-old and 26-week-old mice.</p>
<p>In total, 80 DEGs in the osteocyte mechanosome were also differentially expressed in mouse osteocytes from males and females at either 16 (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>, <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;2</bold>
</xref>) or 26 (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>, <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;3</bold>
</xref>) weeks of age. In 16-week-old mice, 5 osteocyte mechanosome DEGs also displayed differential expression between males and females: TENM4, SEMA7A, LOXL1, POGK and ACP5 (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>). GO term enrichment of these genes was associated with collagen-containing extracellular matrix and bone morphogenesis and resorption, neural crest migration, and positive regulation of axon extension (<xref ref-type="supplementary-material" rid="SF1">
<bold>Supplementary Figure&#xa0;1</bold>
</xref>). In contrast, in aged, 26-week-old mice, 77 DEGs in the osteocyte mechanosome showed significant differences between male and female osteocytes (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>). Of note, these included TENM4, LOX and CTSK all of which displayed higher expression in females and mechanical regulation (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>, <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Biplot of genes regulated in the osteocyte mechanosome and differentially expressed in osteocytes from male and female 16-week-old skeletally mature mice.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-15-1480274-g002.tif"/>
</fig>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Biplot of genes regulated in the osteocyte mechanosome and differentially expressed in osteocytes from male and female 26-week-old mice. Points highlighted by GO Enrichment analysis. <bold>(A)</bold> Cell projection, <bold>(B)</bold> Extracellular space, <bold>(C)</bold> Bone mineralisation, <bold>(D)</bold> Bone resorption.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-15-1480274-g003.tif"/>
</fig>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Pathways significantly enriched in the top 1000 protein-protein interactions in the genes regulated in the osteocyte mechanosome and by sex in human long bone derived osteoblasts.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="bottom" align="center">Group</th>
<th valign="bottom" align="center">Analysis</th>
<th valign="bottom" align="center">Pathway</th>
<th valign="bottom" align="center">Count</th>
<th valign="bottom" align="center">Strength</th>
<th valign="bottom" align="center">fdr</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" rowspan="17" align="center">Top 1000 protein-protein interactions in genes significantly regulated in Analysis 1</td>
<td valign="middle" rowspan="3" align="center">
<bold>KEGG</bold>
</td>
<td valign="bottom" align="left">rheumatoid arthritis</td>
<td valign="bottom" align="center">13 of 83</td>
<td valign="bottom" align="center">0.49</td>
<td valign="bottom" align="center">0.0129</td>
</tr>
<tr>
<td valign="bottom" align="left">TGF-&#x3b2; signalling</td>
<td valign="bottom" align="center">14 of 91</td>
<td valign="bottom" align="center">0.48</td>
<td valign="bottom" align="center">0.0108</td>
</tr>
<tr>
<td valign="bottom" align="left">complement and coagulation cascades</td>
<td valign="bottom" align="center">14 of 82</td>
<td valign="bottom" align="center">0.53</td>
<td valign="bottom" align="center">0.0056</td>
</tr>
<tr>
<td valign="middle" rowspan="4" align="center">
<bold>DISEASES</bold>
</td>
<td valign="bottom" align="left">bone disease</td>
<td valign="bottom" align="center">54 of 540</td>
<td valign="bottom" align="center">0.29</td>
<td valign="bottom" align="center">0.0066</td>
</tr>
<tr>
<td valign="bottom" align="left">neurodegenerative disease</td>
<td valign="bottom" align="center">47 of 481</td>
<td valign="bottom" align="center">0.28</td>
<td valign="bottom" align="center">0.024</td>
</tr>
<tr>
<td valign="bottom" align="left">musculoskeletal disease</td>
<td valign="bottom" align="center">106 of 1154</td>
<td valign="bottom" align="center">0.26</td>
<td valign="bottom" align="center">&lt;0.0001</td>
</tr>
<tr>
<td valign="bottom" align="left">nervous system disease</td>
<td valign="bottom" align="center">161 of 2275</td>
<td valign="bottom" align="center">0.14</td>
<td valign="bottom" align="center">0.0145</td>
</tr>
<tr>
<td valign="middle" rowspan="6" align="center">
<bold>Monarch</bold>
</td>
<td valign="bottom" align="left">severe generalised osteoporosis</td>
<td valign="bottom" align="center">6 of 11</td>
<td valign="bottom" align="center">1.03</td>
<td valign="bottom" align="center">0.0034</td>
</tr>
<tr>
<td valign="bottom" align="left">distal peripheral sensory neuropathy</td>
<td valign="bottom" align="center">5 of 12</td>
<td valign="bottom" align="center">0.91</td>
<td valign="bottom" align="center">0.0207</td>
</tr>
<tr>
<td valign="bottom" align="left">sensory neuropathy</td>
<td valign="bottom" align="center">14 of 85</td>
<td valign="bottom" align="center">0.51</td>
<td valign="bottom" align="center">0.0078</td>
</tr>
<tr>
<td valign="bottom" align="left">osteolysis of the upper limb</td>
<td valign="bottom" align="center">7 of 19</td>
<td valign="bottom" align="center">0.86</td>
<td valign="bottom" align="center">0.0053</td>
</tr>
<tr>
<td valign="bottom" align="left">osteolysis</td>
<td valign="bottom" align="center">12 of 73</td>
<td valign="bottom" align="center">0.51</td>
<td valign="bottom" align="center">0.0078</td>
</tr>
<tr>
<td valign="bottom" align="left">poor wound healing</td>
<td valign="bottom" align="center">7 of 20</td>
<td valign="bottom" align="center">0.84</td>
<td valign="bottom" align="center">0.0064</td>
</tr>
<tr>
<td valign="middle" rowspan="4" align="center">
<bold>Annotated Keywords (Uniprot)</bold>
</td>
<td valign="bottom" align="left">osteogenesis imperfecta</td>
<td valign="bottom" align="center">8 of 83</td>
<td valign="bottom" align="center">0.26</td>
<td valign="bottom" align="center">0.0022</td>
</tr>
<tr>
<td valign="bottom" align="left">Charcot-Marie-Tooth</td>
<td valign="bottom" align="center">10 of 55</td>
<td valign="bottom" align="center">0.55</td>
<td valign="bottom" align="center">0.0159</td>
</tr>
<tr>
<td valign="bottom" align="left">neuropathy</td>
<td valign="bottom" align="center">17 of 108</td>
<td valign="bottom" align="center">0.49</td>
<td valign="bottom" align="center">0.0027</td>
</tr>
<tr>
<td valign="bottom" align="left">angiogenesis</td>
<td valign="bottom" align="center">20 of 131</td>
<td valign="bottom" align="center">0.48</td>
<td valign="bottom" align="center">0.0013</td>
</tr>
<tr>
<td valign="middle" rowspan="2" align="center">Largest cluster of protein interactions</td>
<td valign="middle" align="center">
<bold>DISEASES</bold>
</td>
<td valign="bottom" align="left">degenerative disc disease</td>
<td valign="bottom" align="center">3 of 13</td>
<td valign="bottom" align="center">1.83</td>
<td valign="bottom" align="center">0.0081</td>
</tr>
<tr>
<td valign="middle" align="center">
<bold>TISSUES</bold>
</td>
<td valign="bottom" align="left">rheumatoid arthritis synovial tissues</td>
<td valign="bottom" align="center">3 of 9</td>
<td valign="bottom" align="center">1.98</td>
<td valign="bottom" align="center">0.00056</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>GO:term enrichment revealed that DEGs in the osteocyte mechanosome and regulated by sex in aged mice bones were predominantly associated with cell projection, extracellular space, bone mineralisation and bone resorption (<xref ref-type="supplementary-material" rid="SF2">
<bold>Supplementary Figure&#xa0;2</bold>
</xref>). No genes associated with the nerve growth factor signalling pathway GO terms were significantly regulated in the dataset.</p>
<p>STRING analysis of all protein interactions that were significantly sex regulated in osteocyte signature and in the osteocyte mechanosome produced a protein interaction network with 25 predicted functional associations compared to the number of expected interactions of 11 (<xref ref-type="supplementary-material" rid="SF3">
<bold>Supplementary Figure&#xa0;3</bold>
</xref>). Functional enrichment analysis of the network showed a protein-protein interaction enrichment P value of &lt; 0.001 and pathways relevant to pain in OA. KEGG pathway analysis revealed the rheumatoid arthritis pathway (count 4 of 83, strength 1.23, fdr 0.0195) and osteoclast differentiation pathway (count 4 of 120, strength 1.07, fdr 0.0280) were enriched in this protein interaction network.</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Analysis 2 - the osteocyte mechanosome and sex specific differences in human long bones</title>
<p>In Analysis 2 (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>), our osteocyte mechanosome was compared with a published dataset containing 9182 DEGs between human male and female long bone explant-derived osteoblasts downloaded from the sex-associated gene database (repository number 00129; SAGD <ext-link ext-link-type="uri" xlink:href="http://bioinfo.life.hust.edu.cn/SAGD">http://bioinfo.life.hust.edu.cn/SAGD</ext-link>, (<xref ref-type="bibr" rid="B27">27</xref>, <xref ref-type="bibr" rid="B33">33</xref>).</p>
<p>3861 of those sex-regulated genes were affected by mechanical load in the osteocyte mechanosome (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;4</bold>
</xref>). GO:term enrichment showed that these co-regulated genes are associated with numerous biological processes including those relevant to mechanical loading of bone and pain, such as collagen containing extracellular matrix (ECM), signal transduction, synapse, neural projection, angiogenesis and integrin, cadherin, and calcium ion binding (<xref ref-type="supplementary-material" rid="SF3">
<bold>Supplementary Figure&#xa0;3</bold>
</xref>, <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;5</bold>
</xref>). The co-regulated genes included 86 associated with neural projection including TENM4 (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4A</bold>
</xref>), 155 associated with the synapse (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4B</bold>
</xref>) 4 genes associated with the sensory perception of pain including PTGES, EDNRB and 8 members of the MAPK signalling pathway (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4B</bold>
</xref>, red), and 44 genes associated with axon guidance including, SEMA3A and SEMA7A (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4C</bold>
</xref>). In&#xa0;addition, co-regulated genes included 88 genes associated with angiogenesis including NOS3 (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4D</bold>
</xref>), 93 genes associated with ubiquitin protein ligase binding (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4E</bold>
</xref>), 39 genes associated with immune responses (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4F</bold>
</xref>) and 108 genes associated with collagen containing ECM (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4G</bold>
</xref>). Out of the 11 GO terms for mechanical regulation, the GO term &#x2018;response to mechanical stimulus&#x2019; identified 17 DEGs in the osteocyte mechanosome that were also differentially regulated in male and female long bones (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4H</bold>
</xref>).</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Biplot of genes regulated in the osteocyte mechanosome and differentially expressed in male and female human long bone derived osteoblasts. Points highlighted by GO: Term. <bold>(A)</bold> Neural Projection, <bold>(B)</bold> Black = Synapse, Red = Sensory perception of pain <bold>(C)</bold>. Axon guidance, <bold>(D)</bold> Angiogenesis, <bold>(E)</bold> Ubiquitin protein binding <bold>(F)</bold> Immune response, <bold>(G)</bold> Collagen-containing extracellular matrix <bold>(H)</bold> Response to mechanical stimulus.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-15-1480274-g004.tif"/>
</fig>
<p>STRING analysis was performed on the top 1000 protein interactions that were significantly sex regulated in human long bone derived osteoblasts and in the osteocyte mechanosome. This produced a protein interaction network with 8786 predicted functional associations (<xref ref-type="supplementary-material" rid="SF2">
<bold>Supplementary Figure&#xa0;2</bold>
</xref>). Functional enrichment analysis of the network showed significant protein-protein interaction enrichment (P &lt; 0.001) and numerous pathways relevant to pain in OA (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). Biological process Gene Ontology enrichment showed a very large number of overrepresented pathways: the highest enrichment was for angiogenesis and blood vessel related genes, including retinal blood vessel morphogenesis, data not shown. The most enriched KEGG pathways were associated with the cell cycle, metabolism, and ECM interactions. Interestingly, the rheumatoid arthritis pathway (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5A</bold>
</xref>), transforming growth factor-&#x3b2; (TGF-&#x3b2;) signalling (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>) and complement and coagulation cascades all showed enrichment. Disease-gene associations (DISEASES) pathway analysis of co-regulated genes identified bone disease (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5C</bold>
</xref>), neurodegenerative disease (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5D</bold>
</xref>), musculoskeletal disease (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5E</bold>
</xref>), and nervous system disease. Human phenotype (Monarch) analysis of the protein interactions within this dataset revealed enrichment of severe generalised osteoporosis, distal peripheral sensory neuropathy (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5F</bold>
</xref>, Black), sensory neuropathy (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5F</bold>
</xref>, Red), osteolysis of the upper limb, osteolysis, and poor wound healing. Analysis of the Annotated Keywords (Uniprot) of the protein interaction network revealed enrichment in pathways of osteogenesis imperfecta, Charcot-Marie-Tooth, Neuropathy, and angiogenesis. MCL clustering of the protein interaction network produced 292 clusters, 29 of which included more than 5 genes. The largest cluster was compiled of 68 genes including CXCL12, CTSK and MMP1-3. and was predominantly associated with degenerative disc disease in disease -gene associations (DISEASES) enrichment and included rheumatoid arthritis disease specific synovial tissues in Tissue expression (TISSUES) analysis (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>).</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Biplot of genes regulated in the osteocyte mechanosome and differentially expressed in male and female human long bone derived osteoblasts. Points highlighted by STRING Enrichment analysis. <bold>(A)</bold> Rheumatoid arthritis, <bold>(B)</bold> TGF-beta signalling pathway, <bold>(C)</bold> Bone disease, <bold>(D)</bold> Neurodegenerative disease, <bold>(E)</bold> Musculoskeletal disease, <bold>(F)</bold> Black = Sensory neuropathy &amp; Red = neuropathy.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-15-1480274-g005.tif"/>
</fig>
<p>Analysis 2 revealed numerous genes associated with cell projection (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6A</bold>
</xref>), extracellular space (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6B</bold>
</xref>) and bone biology (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6C, D</bold>
</xref>), including ASPN and CTSK, that were regulated by mechanical load in the osteocyte mechanosome and by sex. Members of the LOX pathway showed upregulation by mechanical loading in the osteocyte mechanosome and regulation by sex in human long bones. LOX and LOXL2 were increased in males. LOXL1 and LOXL4 conversely were increased in females. No genes associated with the nerve growth factor signalling pathway GO:terms were significantly regulated in the combined dataset. The fold changes and p values of individual genes of interest selected from these GO:term analyses can be found in <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>.</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Biplot of genes regulated in the osteocyte mechanosome and differentially expressed in male and female human long bone derived osteoblasts. Points highlighted by GO Enrichment analysis. <bold>(A)</bold> Cell projection, <bold>(B)</bold> Extracellular space, <bold>(C)</bold> Bone mineralisation, <bold>(D)</bold> Bone resorption.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-15-1480274-g006.tif"/>
</fig>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Genes regulated in the osteocyte mechanosome and by sex in human long bone derived osteoblasts identified as potential mediators linked to pain generation in OA pathology.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="bottom" rowspan="2" align="left">Gene</th>
<th valign="bottom" colspan="2" align="center">Mechanosome</th>
<th valign="bottom" colspan="2" align="center">Human long bone</th>
</tr>
<tr>
<th valign="bottom" align="center">log2FC</th>
<th valign="bottom" align="center">P(adj)</th>
<th valign="bottom" align="center">log2FC</th>
<th valign="bottom" align="center">P(adj)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="bottom" align="left">TENM4</td>
<td valign="bottom" align="right">5.79</td>
<td valign="bottom" align="right">0.001</td>
<td valign="bottom" align="right">1.22</td>
<td valign="bottom" align="right">0.0144</td>
</tr>
<tr>
<td valign="bottom" align="left">PTGES</td>
<td valign="bottom" align="right">-1.39</td>
<td valign="bottom" align="right">0.006</td>
<td valign="bottom" align="right">-0.99</td>
<td valign="bottom" align="right">&lt;0.0001</td>
</tr>
<tr>
<td valign="bottom" align="left">EDNRB</td>
<td valign="bottom" align="right">-0.929</td>
<td valign="bottom" align="right">0.045</td>
<td valign="bottom" align="right">-4.73</td>
<td valign="bottom" align="right">&lt;0.0001</td>
</tr>
<tr>
<td valign="bottom" align="left">UCHL1</td>
<td valign="bottom" align="right">2.24</td>
<td valign="bottom" align="right">0.0308</td>
<td valign="bottom" align="right">-1</td>
<td valign="bottom" align="right">&lt;0.0001</td>
</tr>
<tr>
<td valign="bottom" align="left">SEMA3A</td>
<td valign="bottom" align="right">-1.17</td>
<td valign="bottom" align="right">&lt;0.0001</td>
<td valign="bottom" align="right">-0.949</td>
<td valign="bottom" align="right">&lt;0.0001</td>
</tr>
<tr>
<td valign="bottom" align="left">SEMA7A</td>
<td valign="bottom" align="right">0.945</td>
<td valign="bottom" align="right">0.002</td>
<td valign="bottom" align="right">-1.48</td>
<td valign="bottom" align="right">&lt;0.0001</td>
</tr>
<tr>
<td valign="bottom" align="left">NOS3</td>
<td valign="bottom" align="right">2.7</td>
<td valign="bottom" align="right">0.0007</td>
<td valign="bottom" align="right">-5.36</td>
<td valign="bottom" align="right">0.0034</td>
</tr>
<tr>
<td valign="bottom" align="left">ASPN</td>
<td valign="bottom" align="right">-0.605</td>
<td valign="bottom" align="right">0.196</td>
<td valign="bottom" align="right">3.93</td>
<td valign="bottom" align="right">&lt;0.0001</td>
</tr>
<tr>
<td valign="bottom" align="left">CTSK</td>
<td valign="bottom" align="right">-0.542</td>
<td valign="bottom" align="right">0.001</td>
<td valign="bottom" align="right">5.12</td>
<td valign="bottom" align="right">&lt;0.0001</td>
</tr>
<tr>
<td valign="bottom" align="left">RUNX2</td>
<td valign="bottom" align="right">-0.84</td>
<td valign="bottom" align="right">0.005</td>
<td valign="bottom" align="right">0.924</td>
<td valign="bottom" align="right">&lt;0.0001</td>
</tr>
<tr>
<td valign="bottom" align="left">LOX</td>
<td valign="bottom" align="right">1.16</td>
<td valign="bottom" align="right">0.0125</td>
<td valign="bottom" align="right">-1.76</td>
<td valign="bottom" align="right">&lt;0.0001</td>
</tr>
<tr>
<td valign="bottom" align="left">LOXL1</td>
<td valign="bottom" align="right">0.844</td>
<td valign="bottom" align="right">0.0124</td>
<td valign="bottom" align="right">0.417</td>
<td valign="bottom" align="right">&lt;0.0001</td>
</tr>
<tr>
<td valign="bottom" align="left">LOXL2</td>
<td valign="bottom" align="right">1.79</td>
<td valign="bottom" align="right">&lt;0.0001</td>
<td valign="bottom" align="right">-1.37</td>
<td valign="bottom" align="right">&lt;0.0001</td>
</tr>
<tr>
<td valign="bottom" align="left">LOXL4</td>
<td valign="bottom" align="right">1.18</td>
<td valign="bottom" align="right">0.0212</td>
<td valign="bottom" align="right">1.88</td>
<td valign="bottom" align="right">&lt;0.0001</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>The osteocyte mechanosome and sex specific differences in both human long bone derived osteoblasts and the mouse osteocyte transcriptome signature</title>
<p>Comparisons of the osteocyte mechanosome (<xref ref-type="bibr" rid="B24">24</xref>), with differentially expressed in males and females in the osteocyte transcriptome (<xref ref-type="bibr" rid="B26">26</xref>) (Analysis 1) and genes differentially regulated in males and females in human long bone (<xref ref-type="bibr" rid="B27">27</xref>) (Analysis 2) revealed several genes in common across datasets. Of the five genes regulated in the mouse transcriptome at 16-weeks (Section 2.1, <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>), three (TENM4, LOXL1, and SEMA7A) were also regulated by sex in the human long bone derived osteoblasts (Section 2.1, <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>) (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;6</bold>
</xref>). Furthermore, 58 genes were regulated in the mouse osteocyte transcriptome at 26-weeks (Section 2.1) and by sex in the human long bone dataset (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;7</bold>
</xref>). Of note, the collagen cross-linking enzyme lysyl oxidase (LOX) and its paralogs, LOX-like-1, 2, and -4 were regulated in the osteocyte mechanosome and either Analysis 1 or 2 (<xref ref-type="fig" rid="f4">
<bold>Figures&#xa0;4</bold>
</xref>&#x2013;<xref ref-type="fig" rid="f6">
<bold>6</bold>
</xref>). TENM4 was the only regulated gene in the osteocyte mechanosome that was also sex regulated across all datasets (<xref ref-type="table" rid="T2">
<bold>Tables&#xa0;2</bold>
</xref>, <xref ref-type="table" rid="T3">
<bold>3</bold>
</xref>).</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Genes regulated in the osteocyte mechanosome and differentially expressed by sex in mouse osteocyte transcriptome selected for discussion within text as mediators linked to pain generation in OA pathology.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="bottom" rowspan="2" align="left">Gene</th>
<th valign="middle" colspan="2" align="center">Mechanosome</th>
<th valign="bottom" colspan="2" align="center">16- week Mouse osteocyte</th>
<th valign="bottom" colspan="2" align="center">26- week Mouse osteocyte</th>
</tr>
<tr>
<th valign="bottom" align="center">log2FC</th>
<th valign="bottom" align="center">P(adj)</th>
<th valign="bottom" align="center">log2FC</th>
<th valign="bottom" align="center">P(adj)</th>
<th valign="bottom" align="center">log2FC</th>
<th valign="bottom" align="center">P(adj)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="bottom" align="left">TENM4</td>
<td valign="bottom" align="right">5.79</td>
<td valign="bottom" align="right">0.001</td>
<td valign="bottom" align="right">5.7</td>
<td valign="bottom" align="right">&gt;0.0001</td>
<td valign="bottom" align="right">1.21</td>
<td valign="bottom" align="right">0.014</td>
</tr>
<tr>
<td valign="bottom" align="left">SEMA7A</td>
<td valign="bottom" align="right">0.945</td>
<td valign="bottom" align="right">0.002</td>
<td valign="bottom" align="right">0.945</td>
<td valign="bottom" align="right">0.002</td>
<td valign="bottom" align="right"/>
<td valign="bottom" align="left"/>
</tr>
<tr>
<td valign="bottom" align="left">LOXL1</td>
<td valign="bottom" align="right">0.844</td>
<td valign="bottom" align="right">0.0124</td>
<td valign="bottom" align="right">0.844</td>
<td valign="bottom" align="right">0.012</td>
<td valign="bottom" align="right"/>
<td valign="bottom" align="left"/>
</tr>
<tr>
<td valign="bottom" align="left">POGK</td>
<td valign="bottom" align="right">0.64</td>
<td valign="bottom" align="right">0.01</td>
<td valign="bottom" align="right">0.64</td>
<td valign="bottom" align="right">0.01</td>
<td valign="bottom" align="right"/>
<td valign="bottom" align="left"/>
</tr>
<tr>
<td valign="bottom" align="left">ACP5</td>
<td valign="bottom" align="right">-1.23</td>
<td valign="bottom" align="right">&gt;0.0001</td>
<td valign="bottom" align="right">1.23</td>
<td valign="bottom" align="right">&gt;0.0001</td>
<td valign="bottom" align="left"/>
<td valign="bottom" align="left"/>
</tr>
<tr>
<td valign="bottom" align="left">LOX</td>
<td valign="bottom" align="right">1.16</td>
<td valign="bottom" align="right">0.0125</td>
<td valign="bottom" align="right"/>
<td valign="bottom" align="left"/>
<td valign="bottom" align="right">0.859</td>
<td valign="bottom" align="right">0.0257</td>
</tr>
<tr>
<td valign="bottom" align="left">CTSK</td>
<td valign="bottom" align="right">-0.542</td>
<td valign="bottom" align="right">0.001</td>
<td valign="bottom" align="right"/>
<td valign="bottom" align="left"/>
<td valign="bottom" align="right">1.18</td>
<td valign="bottom" align="right">&gt;0.0001</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Analysis 3 - the osteocyte mechanosome and sex specific OA risk factors</title>
<p>Analysis 3 (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>), compared genes regulated in the osteocyte mechanosome and by sex in human long bone (Analysis 2) with OA risk loci associated with sex-specific OA and OA pain identified by a GWAS meta-analysis across 826,690 individuals, including 177,517 with OA (<xref ref-type="bibr" rid="B28">28</xref>). This study identified 3 sex-specific OA risk loci using a sex-differentiated test of association and a test of heterogeneity in allelic effects, and 11 genes associated with total joint replacement (TJR) surgery which the authors proposed were candidate genes associated with heightened OA pain [<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;5</bold>
</xref>, (<xref ref-type="bibr" rid="B28">28</xref>)].</p>
<p>Of the 3 female specific OA risk loci shown by Boer et&#xa0;al. (<xref ref-type="bibr" rid="B28">28</xref>), FANCL, C8orf34, UBAP2 (<xref ref-type="bibr" rid="B28">28</xref>), only one gene (FANCL) showed significant down regulation by mechanical loading (P(adj)=0.00087, -0.519-log2FC) in the osteocyte mechanosome. FANCL also showed a significant regulation by sex in the human male and female long bones dataset [SAGD_00129, (<xref ref-type="bibr" rid="B27">27</xref>)]. Female long bones showed significantly lower FANCL expression compared with males (P(adj)=0.005, -0.701 - log2FC). Of the 11 genes associated with TJR surgery reflecting heightened OA pain, both PTCH1 (P(adj)=0.02, 1.927 - log2FC), and SERPINA1 (P(adj) 0.007, -3.66 - log2FC) were DEGs in the osteocyte mechanosome, but none showed sex regulation in either the human long bone or mouse osteocyte transcriptome datasets.</p>
<p>Analysis of the 77 OA effector genes published in this GWAS dataset [<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;10</bold>
</xref>, (<xref ref-type="bibr" rid="B28">28</xref>)] revealed 32 effector genes that are mechanically regulated in the osteocyte mechanosome and sex regulated in human long bones (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;8</bold>
</xref>). These genes included: CTSK, RUNX2, NOS3 and members of the TGF-&#x3b2; pathway TGFB1, LTBP1 and LTBP3. No GWAS derived effector genes were significantly regulated by sex in the mouse osteocyte transcriptome.</p>
</sec>
<sec id="s2_5">
<label>2.5</label>
<title>Druggable targets</title>
<p>The genes in the osteocyte mechanosome shown to be sex specific in either GWAS, human long bones or the mouse osteocyte transcriptome were searched on the Drug-Gene Interaction Database to identify potential druggable targets [<ext-link ext-link-type="uri" xlink:href="https://www.dgidb.org">https://www.dgidb.org</ext-link>, (<xref ref-type="bibr" rid="B30">30</xref>)].</p>
<p>In Analysis 1, none of the 5 genes identified in 16-week-old mice were druggable. In 26-week-old mice, 14 of the 58 genes in common represented druggable targets with 9 of these genes having at least one approved drug (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;9</bold>
</xref>).</p>
<p>793 of the 3861 genes regulated by mechanical loading in the osteocyte mechanosome and by sex in the human long bone dataset (Analysis 2) represent druggable targets with 580 of these having at least one approved drug (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;10</bold>
</xref>). In total this represents 4332 approved drugs due to gene target redundancy. GO term analysis of these druggable targets revealed enrichment for genes associated with the extracellular space and protein phosphorylation and kinase activity. Druggable targets included 107 of the 275 ECM associated genes (442 drugs), 39 of the 93 genes associated with ubiquitin ligase (218 drugs), 18 of the 39 genes associated with immune responses (76 drugs), 54 of the 155 synapse genes (321 drugs), and 2 of the 44 axon guidance genes (1 drug).</p>
<p>In Analysis 3, FANCL, the female specific risk variant for OA (<xref ref-type="bibr" rid="B28">28</xref>) that was mechanically downregulated in osteocytes and differentially expressed in male and female human long bones, is also a druggable target with the approved drug Olaparib. Of the 26 GWAS effector genes shown to be significantly regulated by mechanical load in the osteocyte mechanosome and by sex in the human long bone dataset 10 genes had associated drugs with 7 of these being approved.</p>
</sec>
</sec>
<sec id="s3" sec-type="discussion">
<label>3</label>
<title>Discussion</title>
<p>Combining our transcriptome data of the <italic>in vitro</italic> 3D osteocyte response to pathophysiological mechanical load (<xref ref-type="bibr" rid="B24">24</xref>), with published datasets, of osteocyte specific sex-based transcriptome differences (Analysis 1) (<xref ref-type="bibr" rid="B26">26</xref>), human long bone explant-derived osteoblast sex-based transcriptome differences (Analysis 2) [repository number 00129 from (<xref ref-type="bibr" rid="B33">33</xref>)], and patient sex-specific OA risk factors (Analysis 3) (<xref ref-type="bibr" rid="B28">28</xref>), revealed a wide array of sex-regulated genes that are also significantly regulated by pathophysiological loading in osteocytes. Oestrogen deficiency in menopause is thought to contribute to the higher burden of pain experienced by female patients (<xref ref-type="bibr" rid="B38">38</xref>). This may involve both the chondroprotective signalling effect of oestrogen (<xref ref-type="bibr" rid="B39">39</xref>) as well as its well-established role in protecting bone mass.(14) Despite the high association of oestrogen deficiency predisposing to musculoskeletal pain, a causal link is lacking (<xref ref-type="bibr" rid="B8">8</xref>). The disparity between cartilage degradation and pain, and new revelations displaying nociceptor plasticity and invasion of subchondral bone [reviewed in (<xref ref-type="bibr" rid="B16">16</xref>)], and the association of BMLs with pain (<xref ref-type="bibr" rid="B12">12</xref>), suggests a role for bone in explaining sex differences in OA pain sensation.</p>
<p>LOXL1, SEMA7A and TENM4 were the only differentially expressed genes in the osteocyte mechanosome that were also sex regulated genes common across the 16-week-old mouse transcriptome and the human long bone dataset. TENM4 was the only regulated gene present across all datasets. TENM4 was upregulated by mechanical loading in the osteocyte mechanosome and increased in females in all analyses. TENM4 encodes for Teneurin transmembrane protein 4, a protein important in establishing proper neuronal connectivity during development (<xref ref-type="bibr" rid="B40">40</xref>) which has been linked to changes in pain sensitivity (<xref ref-type="bibr" rid="B41">41</xref>). Tenm4 mutant mice (Tenm4<sup>em1(IMPC)Tcp</sup> allele) exhibit sex-specific increased bone mineral content in older female mice [(<xref ref-type="bibr" rid="B42">42</xref>); <ext-link ext-link-type="uri" xlink:href="http://www.mousephenotype.org">www.mousephenotype.org</ext-link>]. LOX was upregulated by mechanical load in the osteocyte mechanosome, and in the female mouse osteocyte transcriptome at 26 weeks but decreased in female long bones. LOX was not detected in the mouse osteocyte transcriptome at 16 weeks. In addition, LOXL1 was upregulated in the mechanosome, female mouse osteocytes and female long bones. LOXL1 was not detected in mouse osteocyte transcriptome at 26 weeks. LOX and LOXL1 were also highlighted in the STRING protein interaction network analysis of the osteocyte mechanosome combined with sex differences in both human long bones and the osteocyte transcriptome. These enzymes are critical for elastin biogenesis and collagen cross-link formation and play roles in matrix remodelling in normal and disease states (<xref ref-type="bibr" rid="B43">43</xref>). Knockouts of LOXL1 have also been shown to induce deterioration of trabecular bone structure in long bones and vertebrae in female mice but not in males (<xref ref-type="bibr" rid="B44">44</xref>). Proteolytic activation of LOX is enhanced by the interaction of periostin and BMP1 (<xref ref-type="bibr" rid="B45">45</xref>). The sex-specific mechano-regulation of the LOX pathway we have reported links to the findings of Zhou et&#xa0;al. who found POSTN, the gene encoding periostin, to be mechanoresponsive and co-regulated in OA and the osteocyte signature (<xref ref-type="bibr" rid="B46">46</xref>). SEMA7A, encoding the neuroimmune axon guidance factor Semaphorin7A was upregulated by load in the osteocyte mechanosome and regulated by sex in our analysis. SEMA7A was down regulated in human female long bones but up regulated in 16-week-old female mouse osteocytes. Semaphorin7A is a signalling ligand that promotes neuron axon elongation and invasion in the developing embryo (<xref ref-type="bibr" rid="B47">47</xref>) and is essential in establishing innervation of the dentin-pulp complex (<xref ref-type="bibr" rid="B48">48</xref>). CTSK, encoding the lysosomal cysteine protease Cathepsin K a marker of osteoclast bone resorption, was down regulated by mechanical loading in the osteocyte mechanosome but up regulated in both the female human long bone dataset and the female mouse osteocyte transcriptome at 26 weeks. CTSK has been implicated in the pathogenesis of osteoporosis and OA [reviewed in (<xref ref-type="bibr" rid="B49">49</xref>)] with inhibition of Cathepsin K delaying OA progression in animal models (<xref ref-type="bibr" rid="B50">50</xref>). CTSK was also found to be an OA effector gene (<xref ref-type="bibr" rid="B28">28</xref>).</p>
<p>Pathophysiological mechanical loading of osteocytes down regulated the expression of FANCL a ubiquitin ligase previously shown to be associated with female specific risk of hip OA (<xref ref-type="bibr" rid="B28">28</xref>). The down regulation of FANCL is associated with cytogenetic instability, hypersensitivity to DNA crosslinking agents, increased chromosomal breakage, and defective DNA repair (<xref ref-type="bibr" rid="B51">51</xref>). Both human genetic studies and mouse gene knockouts (<xref ref-type="bibr" rid="B52">52</xref>) indicate that loss of function mutations in FANCL, cause premature ovary insufficiency, a condition that leads to early menopause (<xref ref-type="bibr" rid="B53">53</xref>). This is of interest as menopausal and post-menopausal females are two times more likely to suffer from joint pain than pre-menopausal females (<xref ref-type="bibr" rid="B54">54</xref>, <xref ref-type="bibr" rid="B55">55</xref>). Our data implicates osteocyte response to mechanical loading as a potential mechanism underlying the heightened susceptibility of females with FANCL mutations to OA.</p>
<p>Interestingly, mechanical loading of osteocytes (<xref ref-type="bibr" rid="B24">24</xref>) regulated numerous genes associated with bone responses which show differential expression by sex. Bone disease and musculoskeletal disease were enriched in disease gene associated analysis of the protein interactions of the osteocyte mechanosome when combined with the sex regulated genes in human long bones. GO:term enrichment showed that both in the mouse osteocyte data and in human long bone data the mechanosome revealed regulated genes associated with bone mineralisation and bone resorption that&#xa0;were&#xa0;differentially expressed by sex. The osteocyte mechanosome&#xa0;and&#xa0;human long bone sex differences dataset also showed&#xa0;regulation&#xa0;of&#xa0;RUNX2 an essential transcription factor in osteoblast differentiation and an OA effector gene in GWAS analysis (<xref ref-type="bibr" rid="B28">28</xref>). Mechanical load down regulated RUNX2, whereas RUNX2 was upregulated in females. This data suggests that the regulation of bone formation and resorption by osteocytes in response to mechanical loading is different in males and females.</p>
<p>39 genes associated with immune responses showed co-regulation by mechanical load in the osteocyte mechanosome and by sex in the human long bone dataset. Differential expression of genes in females also showed enrichment for the rheumatoid arthritis pathway. These data show that pathophysiological loading of osteocytes causes immune factor expression that is significantly differentially expressed in females. Interestingly, NOS3 was identified by Boer et&#xa0;al. as an OA effector gene (<xref ref-type="bibr" rid="B28">28</xref>) and is upregulated by mechanical load and in male human long bones. This endothelium isoform of nitric oxide synthase is the predominant constitutive isoform of NOS within bone (<xref ref-type="bibr" rid="B56">56</xref>), mechanically regulated in osteocytes (<xref ref-type="bibr" rid="B57">57</xref>) and expressed in human osteocytes <italic>in vivo</italic> (<xref ref-type="bibr" rid="B58">58</xref>). It is an important mediator of inflammatory signalling (<xref ref-type="bibr" rid="B59">59</xref>), and plays a role in mediating oestrogen-induced bone formation in female mice (<xref ref-type="bibr" rid="B58">58</xref>). These data suggest that differences in inflammatory and immune signalling in the mechanical responses of females may drive differential immune signalling leading to higher nociceptive signalling in females.</p>
<p>The TGF-&#x3b2; signalling pathway was also shown to be differentially expressed in STRING pathway enrichment analysis of the osteocyte mechanosome and human long bone sex differences combined datasets. Members of this pathway were identified by Boer et&#xa0;al. as effector genes in a large GWAS analysis (<xref ref-type="bibr" rid="B28">28</xref>). TGF-&#x3b2; is a pleiotropic cytokine that is only active in the healthy joint after mechanical loading. In the OA joint, TGF-&#x3b2; signalling is greatly enhanced (<xref ref-type="bibr" rid="B60">60</xref>). Sexual dimorphism in TGF-&#x3b2; responses was demonstrated in mice, where osteocyte specific knockout of the TGF-&#x3b2; receptor II increased subchondral bone thickening in male but not female mice and was associated with cartilage degeneration (<xref ref-type="bibr" rid="B61">61</xref>). The sex-regulation of the TGF-&#x3b2; pathway shown in this analysis reinforces the evidence that differential inflammatory and immune signalling in females may drive differences in OA progression and pain. Asporin acts as a negative regulator of chondrogenesis by inhibiting TGF-&#x3b2; function (<xref ref-type="bibr" rid="B62">62</xref>). Recently, ASPN has been shown to be a disease-relevant gene, contributing to subchondral bone remodelling in OA (<xref ref-type="bibr" rid="B46">46</xref>). ASPORIN (ASPN) is a small leucine-rich repeat proteoglycan (SLRP) with polymorphisms that are strongly associated with OA (<xref ref-type="bibr" rid="B63">63</xref>). It directly binds TGF-&#x3b2;1 and subsequently collagen, playing a role in collagen fibrillogenesis and metabolism (<xref ref-type="bibr" rid="B64">64</xref>, <xref ref-type="bibr" rid="B65">65</xref>). ASPN more highly expressed in female human long bones compared to equivalent male samples but was not significantly regulated in the mouse osteocyte transcriptome by sex.</p>
<p>Comparison of the mechanosome with genes differentially expressed in human male and female long bones highlighted pathways involved in neuronal activity, ECM, immune response, and identified associations with many painful musculoskeletal diseases involving bone and neuropathies. 93 genes associated with ubiquitin protein ligase binding were significantly regulated by sex in the human long bone dataset and significantly regulated in our osteocyte mechanical loading dataset. No genes associated with ubiquitin function were differentially expressed between males and females in the sex specific osteocyte transcriptome when combined the osteocyte mechanosome. Ubiquitin disfunction in OA is an emerging pathway in driving pathology especially in regulating the apoptosis and hypertrophic differentiation of chondrocytes (<xref ref-type="bibr" rid="B66">66</xref>). It is also likely that changes in ubiquitin function contribute to bone changes in OA as it plays an important role in regulating bone remodelling as well as osteocyte apoptosis (<xref ref-type="bibr" rid="B67">67</xref>) with proteosome inhibitors effectively reducing bone turnover and increasing osteocyte viability in multiple myeloma (<xref ref-type="bibr" rid="B68">68</xref>).</p>
<p>155 genes associated with the synapse, 4 genes associated with the sensory perception of pain and 44 genes associated with axon guidance and cell projection were significantly regulated by osteocyte mechanical loading and by sex in the human long bone dataset. The regulation of this number of neuronally associated genes in both datasets provides evidence that the nociceptor bone interface, and the response of osteocytes to pathological load differs in female OA patients compared to that of males. TENM4 and SEMA7A in both the sex differential human long bone and mouse derived osteocyte signature dataset shows that in both mouse models and in human patients, differential axon guidance signalling in males and females may result in differing levels of nociceptor plasticity and sensitivity in females. All the semaphorin signalling ligands displayed higher differential expression in males in human long bones. Axon guidance signalling factors have been shown to regulate sensory nerve sprouting and invasion in mouse models (<xref ref-type="bibr" rid="B69">69</xref>) and to regulate the membrane potential of sensory neurons (<xref ref-type="bibr" rid="B70">70</xref>), with signalling cascades that integrate to the signalling of NGF (<xref ref-type="bibr" rid="B71">71</xref>). The axon guidance signalling pathway has also recently been reported by Zhou et&#xa0;al. to be a significantly enriched pathway in the 223 main contributory genes between the medial OA subchondral bone and lateral plateau in mice OA models (<xref ref-type="bibr" rid="B46">46</xref>). In contrast we saw no differences in NGF signalling in our analyses.</p>
<p>Significantly more DEGs were detected in ageing 26-week-old male and female mouse osteocytes and the osteocyte mechanosome compared with 16-week-old mice. Hyperalgesia lasts longer and is more pronounced in older rats, with aged females exhibiting the most impaired responses (<xref ref-type="bibr" rid="B72">72</xref>). Age also impacts OA pain in humans with clinical studies revealing older woman to have more chronic pain (<xref ref-type="bibr" rid="B73">73</xref>, <xref ref-type="bibr" rid="B74">74</xref>). (<xref ref-type="bibr" rid="B75">75</xref>) hypothesised that brain changes observed in the early stages of monosodium iodoacetate-induced OA in rats may account for the increased risk for ageing females to develop chronic pain. This is supported by our String analysis which revealed the significant enrichment of neurodegenerative diseases in females. GO term analysis revealed regulation of DEGS involved in the immune response in both the mechanosome and osteocytes of aging mice. Studies have linked higher pain scores and lower pain thresholds in woman to enhanced inflammatory responses (<xref ref-type="bibr" rid="B76">76</xref>&#x2013;<xref ref-type="bibr" rid="B78">78</xref>). In addition, sex differences exist in the relationship between individual systemic markers of inflammation and pain in knee osteoarthritis (<xref ref-type="bibr" rid="B79">79</xref>, <xref ref-type="bibr" rid="B80">80</xref>).</p>
</sec>
<sec id="s4">
<label>4</label>
<title>Limitations and conclusions</title>
<p>The greatly reduced number of sex-regulated genes in the mouse osteocyte transcriptome data raises questions as to the similarities between bone-nerve interactions in mouse models compared to patients. It is established that female and male bone display many differences in physiology and intricate associations with the nervous system. Recent research has shown that there are large differences between the peripheral sensory nervous systems in mice and humans (<xref ref-type="bibr" rid="B81">81</xref>). Sensory nerve gene expression, molecular fingerprint, and sensory nerve sub populations have been shown to be different between mouse models and human patients. This analysis therefore raises the possibility that the differential expression of factors that influence sensory nerve changes in animal models limit their effectiveness in studying nociceptor changes in OA. Since the human sex specific long bone data was based on bone explant derived osteoblasts rather than osteocytes <italic>in vivo</italic>, it is also possible that sex specific differences from the human data set are not osteocyte specific.</p>
<p>This analysis has shown a wide array of factors regulated in osteocytes by mechanical loading that are differentially expressed by sex and influence innervation, neural activity and bone remodelling associated with OA pain. It remains to be determined whether these sex specific differences in responses would differentially effect nociceptor populations in males and females. To test this, sex-specific differences in receptor complexes or susceptibility to the differences in osteocyte derived neural signalling would need to be investigated.</p>
<p>Our comparison of the osteocyte mechanosome to published data reflecting sex specific gene expression and susceptibility to OA pain has highlighted pain related pathways potentially responsible for elevated pain susceptibility in females with osteoarthritis. The large number of approved drugs available to target these pathways reveals a great opportunity to modulate mechanically driven osteoarthritic pain particularly in susceptible females.</p>
</sec>
</body>
<back>
<sec id="s5" sec-type="data-availability">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Material</bold>
</xref>. Further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s6" sec-type="author-contributions">
<title>Author contributions</title>
<p>RJ: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing. SG: Data curation, Methodology, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing, Conceptualization, Formal analysis, Funding acquisition, Investigation, Project administration, Supervision, Visualization. SC: Data curation, Methodology, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing, Formal analysis, Investigation, Project administration, Supervision, Validation, Visualization. DM: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing.</p>
</sec>
<sec id="s7" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was funded by NC3Rs CRACK IT Challenge 22: Osteo-chip, NC3Rs Project grant (NC/Y000951/1), Biomechanics and Bioengineering Research Centre Versus Arthritis (EC/20781), Wellcome Trust Collaborative Award (209233/Z/17/Z).</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>We would like to thank Cleo Bonnet for her contribution to the osteocyte model, Sam Evans for his contribution to the loading device design, Peter Giles (Wales Gene Park) for the RNA sequencing and analysis, and Professor Paul Genever (University of York) who kindly provided the Y201 cell line and associated methods.</p>
</ack>
<sec id="s8" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>DM holds patents for the use of glutamate receptor antagonists to prevent osteoarthritis.</p>
<p>The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
<p>The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.</p>
</sec>
<sec id="s9" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s10" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fendo.2024.1480274/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fendo.2024.1480274/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Image1.png" id="SF1" mimetype="image/png">
<label>Supplementary Figure&#xa0;1</label>
<caption>
<p>Bar plot of the significantly enriched GO: Terms produced by GO:term enrichment of genes differentially expressed in both the osteocyte mechanosome and by sex in osteocytes from 16-week-old skeletally mature mice. Bar colour is representative of adjusted p value. Bar length represents the number of genes associated with each GO:term within the dataset.</p>
</caption>
</supplementary-material>
<supplementary-material xlink:href="Image2.png" id="SF2" mimetype="image/png">
<label>Supplementary Figure&#xa0;2</label>
<caption>
<p>Bar plot of the significantly enriched GO: Terms produced by GO:term enrichment of genes differentially expressed in both the osteocyte mechanosome and by sex in osteocytes from 26-week-old skeletally mature mice. Bar colour is representative of adjusted p value. Bar length represents the number of genes associated with each GO:term within the dataset.</p>
</caption>
</supplementary-material>
<supplementary-material xlink:href="Image3.png" id="SF3" mimetype="image/png">
<label>Supplementary Figure&#xa0;3</label>
<caption>
<p>Protein-protein interactions with high confidence interaction score within significantly regulated osteocyte mechanosome and sex differences within mouse osteocyte transcriptome dataset. Coloured nodes represent genes within the dataset within the first shell of interactions. Node content represents predicted protein 3D structure. Connecting lines represent the established protein-protein associations. Line thickness represents the confidence score of these interactions.</p>
</caption>
</supplementary-material>
<supplementary-material xlink:href="Image4.png" id="SF4" mimetype="image/png">
<label>Supplementary Figure&#xa0;4</label>
<caption>
<p>Bar plot of the significantly enriched GO: Terms produced by GO:term enrichment of genes regulated by sex in human long bone derived osteoblasts and mechanical loading in osteocytes. <bold>(A)</bold> All enriched GO: Terms, <bold>(B)</bold> Enriched biological process GO: Terms, <bold>(C)</bold> Enriched Cellular compartment GO: Terms, <bold>(D)</bold> Enriched molecular function GO: Terms. Bar colour is representative of adjusted p value. Bar length represents the number of genes associated with each GO:term within the dataset.</p>
</caption>
</supplementary-material>
<supplementary-material xlink:href="Image5.png" id="SF5" mimetype="image/png">
<label>Supplementary Figure&#xa0;5</label>
<caption>
<p>Protein-protein interactions with high confidence interaction score within significantly regulated osteocyte mechanosome and sex differences within human long bone derived osteoblast dataset. Coloured nodes represent genes within the dataset within the first shell of interactions. Node content represents predicted protein 3D structure. Connecting lines represent the established protein-protein associations. Line thickness represents the confidence score of these interactions.</p>
</caption>
</supplementary-material>
<supplementary-material xlink:href="Table1.csv" id="SM1" mimetype="text/csv"/>
<supplementary-material xlink:href="Table2.csv" id="SM2" mimetype="text/csv"/>
<supplementary-material xlink:href="Table3.csv" id="SM3" mimetype="text/csv"/>
<supplementary-material xlink:href="Table4.csv" id="SM4" mimetype="text/csv"/>
<supplementary-material xlink:href="Table5.csv" id="SM5" mimetype="text/csv"/>
<supplementary-material xlink:href="Table6.csv" id="SM6" mimetype="text/csv"/>
<supplementary-material xlink:href="Table7.csv" id="SM7" mimetype="text/csv"/>
<supplementary-material xlink:href="Table8.csv" id="SM8" mimetype="text/csv"/>
<supplementary-material xlink:href="Table9.docx" id="SM9" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"/>
<supplementary-material xlink:href="Table10.csv" id="SM10" mimetype="text/csv"/>
</sec>
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