<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v2.3 20070202//EN" "journalpublishing.dtd">
<article article-type="research-article" dtd-version="2.3" xml:lang="EN" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">
<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Cell Dev. Biol.</journal-id>
<journal-title>Frontiers in Cell and Developmental Biology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Cell Dev. Biol.</abbrev-journal-title>
<issn pub-type="epub">2296-634X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">1638123</article-id>
<article-id pub-id-type="doi">10.3389/fcell.2025.1638123</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Cell and Developmental Biology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Genome-wide DNA methylation analysis identifies kidney epigenetic dysregulation in a cystinosis mouse model</article-title>
<alt-title alt-title-type="left-running-head">Rossi et al.</alt-title>
<alt-title alt-title-type="right-running-head">
<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fcell.2025.1638123">10.3389/fcell.2025.1638123</ext-link>
</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Rossi</surname>
<given-names>M. N.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/773793/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ciolfi</surname>
<given-names>A.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/903823/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Matteo</surname>
<given-names>V.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2657592/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Pedace</surname>
<given-names>L.</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/682942/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Nardini</surname>
<given-names>C.</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2832366/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Loricchio</surname>
<given-names>E.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2661762/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Caiello</surname>
<given-names>I.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1271443/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Bellomo</surname>
<given-names>F.</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2399015/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Taranta</surname>
<given-names>A.</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>De Leo</surname>
<given-names>E.</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Tartaglia</surname>
<given-names>M.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/30315/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Emma</surname>
<given-names>F.</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>De Benedetti</surname>
<given-names>F.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Miele</surname>
<given-names>E.</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/499323/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Prencipe</surname>
<given-names>G.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/657336/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/supervision/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
<role content-type="https://credit.niso.org/contributor-roles/funding-acquisition/"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Laboratory of Rheumatology, Bambino Ges&#xf9; Children&#x2019;s Hospital, IRCCS</institution>, <addr-line>Rome</addr-line>, <country>Italy</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Science, University of Roma Tre</institution>, <addr-line>Rome</addr-line>, <country>Italy</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Molecular Genetics and Functional Genomics, Bambino Ges&#xf9; Children&#x2019;s Hospital, IRCCS</institution>, <addr-line>Rome</addr-line>, <country>Italy</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Hematology/Oncology and Stem Cell Transplantation, Bambino Ges&#xf9; Children&#x2019;s Hospital, IRCCS</institution>, <addr-line>Rome</addr-line>, <country>Italy</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>Laboratory of Nephrology, Bambino Ges&#xf9; Children&#x2019;s Hospital, IRCCS</institution>, <addr-line>Rome</addr-line>, <country>Italy</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/46328/overview">Roland Wohlgemuth</ext-link>, Lodz University of Technology, Poland</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1543032/overview">Yaochun Zhang</ext-link>, National University of Singapore, Singapore</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1752958/overview">Hwayeong Cheon</ext-link>, University of Ulsan, Republic of Korea</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2733700/overview">Salvatore Cortellino</ext-link>, SSM Scuola Superiore Meridionale, Italy</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: G. Prencipe, <email>giusi.prencipe@opbg.net</email>
</corresp>
</author-notes>
<pub-date pub-type="epub">
<day>21</day>
<month>08</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>13</volume>
<elocation-id>1638123</elocation-id>
<history>
<date date-type="received">
<day>05</day>
<month>06</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>06</day>
<month>08</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Rossi, Ciolfi, Matteo, Pedace, Nardini, Loricchio, Caiello, Bellomo, Taranta, De Leo, Tartaglia, Emma, De Benedetti, Miele and Prencipe.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Rossi, Ciolfi, Matteo, Pedace, Nardini, Loricchio, Caiello, Bellomo, Taranta, De Leo, Tartaglia, Emma, De Benedetti, Miele and Prencipe</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>
<sec>
<title>Introduction</title>
<p>Nephropathic cystinosis is a rare genetic disorder characterized by cystine accumulation in lysosomes that causes early renal dysfunction and progressive chronic kidney disease. Although several metabolic pathways, including oxidative stress and inflammation, have been implicated in the progression of renal parenchyma damage, the precise mechanisms driving its progression are not fully understood. Recent studies suggest that epigenetic modifications, particularly DNA methylation (DNAm), play a critical role in the development of chronic kidney disease. We hypothesized that epigenetic dysregulation may contribute to the progression of kidney disease in cystinosis.</p>
</sec>
<sec>
<title>Methods</title>
<p>To investigate this, we conducted genome-wide DNAm analyses on kidneys harvested from 6-month-old wild type (WT) and <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> mice, a well-established model of cystinosis.</p>
</sec>
<sec>
<title>Results</title>
<p>Our analysis revealed extensive DNAm alterations in cystinotic kidneys, characterized by a significant hypermethylation profile. Interestingly, the majority of differentially methylated CpG sites were located within gene bodies and to a lesser extent in promoter and enhancer regions. Methylation changes were primarily found in genes and pathways crucial for kidney function, particularly those related to the physiology of the proximal tubules. Importantly, DNAm changes correlated with changes in gene expression, as validated by qPCR analyses of key genes. Furthermore, <italic>in vitro</italic> treatment of human proximal tubular epithelial cells with the demethylating agent decitabine resulted in the upregulation of critical transporter genes, suggesting a potential therapeutic approach.</p>
</sec>
<sec>
<title>Conclusions</title>
<p>These findings underscore the role of epigenetic regulation in the progression of kidney damage in cystinosis and suggest that DNAm could serve as a promising target for novel therapeutic strategies.</p>
</sec>
</abstract>
<kwd-group>
<kwd>cystinosis</kwd>
<kwd>DNA methylation</kwd>
<kwd>solute carrier genes</kwd>
<kwd>kidney disease</kwd>
<kwd>proximal tubular epithelial cells</kwd>
</kwd-group>
<contract-sponsor id="cn001">Cystinosis Research Foundation<named-content content-type="fundref-id">10.13039/100005674</named-content>
</contract-sponsor>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Molecular and Cellular Pathology</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction</title>
<p>Nephropathic cystinosis is a rare lysosomal storage disorder presenting early in life with renal Fanconi syndrome that progressively leads to chronic kidney disease (CKD). The disease is caused by variants in the <italic>CTNS</italic> gene, which encodes the lysosomal cystine/H&#x2b; symporter cystinosin. Progressively, cystine and cystine crystals accumulate in all tissues, causing a multisystemic disease. To date, the only approved treatment for cystinosis is cysteamine, a sulfhydryl compound that reduces disulfide bonds, allowing cystine clearance from lysosomes. Cysteamine significantly slows the progression of kidney failure but, unfortunately, cannot prevent it, suggesting that cystine accumulation is not the sole mechanism driving kidney failure. Other proposed mechanisms include increased oxidative stress, mitochondrial function impairment, enhanced apoptosis, and abnormal autophagy (reviewed in <xref ref-type="bibr" rid="B37">Sur et al., 2024</xref>).</p>
<p>Epigenetic modifications, particularly DNA methylation (DNAm) at cytosine-phosphate-guanine (CpG) sites, have emerged as significant contributors to kidney parenchymal damage and CKD (<xref ref-type="bibr" rid="B42">Wanner and Bechtel-Walz, 2017</xref>). Large-scale studies have highlighted the importance of DNAm in preserving kidney health. For example, DNAm has been shown to explain a higher portion of kidney disease heritability than gene expression in high-throughput DNA methylation and transcriptomic profiling of 506 human kidneys (<xref ref-type="bibr" rid="B20">Liu et al., 2022</xref>). Similarly, meta-analysis of epigenome-wide association studies performed in &#x223c;35,000 adults has identified multiple CpG sites with causal links to kidney function, further supporting the role of epigenetic regulation in kidney health and disease (<xref ref-type="bibr" rid="B34">Schlosser et al., 2021</xref>).</p>
<p>DNAm is a reversible process that modulates gene expression without modifying the DNA sequence. Specifically, DNA methylation in the promoter and in the first exon/intron regions can suppress gene expression by recruiting transcriptional repressors or by preventing binding of transcription factors (<xref ref-type="bibr" rid="B1">Anastasiadi et al., 2018</xref>; <xref ref-type="bibr" rid="B4">Bird, 1986</xref>).</p>
<p>Despite the growing understanding of these processes, the mechanisms underlying epigenetic dysregulation in kidney disease remain incompletely defined. Several lines of evidence support a link between the epigenome and cellular metabolism. In particular, recent data point to a critical crosstalk between oxidative stress, inflammation and epigenetic regulation, which may further contribute to the metabolic and inflammatory dysfunction observed in CKD (<xref ref-type="bibr" rid="B20">Liu et al., 2022</xref>; <xref ref-type="bibr" rid="B36">Stenvinkel et al., 2007</xref>). Since oxidative stress and inflammation have been shown to play a pathogenic role in cystinosis (<xref ref-type="bibr" rid="B28">Prencipe et al., 2014</xref>; <xref ref-type="bibr" rid="B31">Rossi et al., 2019</xref>; <xref ref-type="bibr" rid="B41">Vaisbich et al., 2011</xref>), we have hypothesized that epigenetic dysregulation might also contribute to CKD progression. To investigate this hypothesis, we conducted a comprehensive methylation analysis on kidneys harvested from <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> mice, a well-established model for cystinosis (<xref ref-type="bibr" rid="B27">Nevo et al., 2010</xref>).</p>
</sec>
<sec sec-type="materials|methods" id="s2">
<title>Materials and methods</title>
<sec id="s2-1">
<title>Mice care and procedures</title>
<p>The C57BL/6 <italic>Ctns</italic> <sup>&#x2212;/&#x2212;</sup> mice were kindly provided by Prof. Corinne Antignac (<xref ref-type="bibr" rid="B27">Nevo et al., 2010</xref>) and housed alongside their wild-type (WT) C57BL/6 counterparts. Animal care and experimental procedures complied with the European 2010/63/EU on the protection of animals used for scientific purposes and were approved by the Italian Ministry of Health (authorization number 898/2017-PR). Female mice were sacrificed at 6 months of age, and their kidneys were promptly dissected, snap-frozen, or processed in paraffin for further analysis.</p>
</sec>
<sec id="s2-2">
<title>DNA methylation analysis</title>
<p>Genomic DNA was extracted from paraffin-embedded mouse kidney using standard techniques. We adopted a protocol that mitigates fixation artifacts and restores the quality and integrity of degraded DNA from FFPE samples, making it compatible with subsequent steps in the Infinium workflow (Infinium FFPE DNA Restoration Solution, Illumina, cod. WG-321-1002).</p>
<p>DNAm profiling was performed using the Illumina Infinium Mouse Methylation BeadChip array and 500 ng DNA as input material, according to the manufacturer&#x2019;s protocol. BeadChip processing was performed using an Illumina iScan microarray platform.</p>
<p>Data analysis was performed through an in-house pipeline using the R programming language (v.4.1.2), mainly based on the ENmix package (v.1.30.03) for importing IDAT files, performing data quality control, and correcting for background and dye bias noise (<xref ref-type="bibr" rid="B44">Xu et al., 2021</xref>). Methylation levels (beta-values) were converted to M-values, which were used to perform linear regression modelling using empirical Bayes moderated t-statistic (Limma package [v.3.50.3] (<xref ref-type="bibr" rid="B30">Ritchie et al., 2015</xref>) corrected for false discovery rate (Benjamini-Hochberg&#x2019;s FDR) and to identify differentially methylated probes (DMPs),which were considered significant if methylation difference was &#x3e;15% and FDR was &#x3c;0.01. Normalized beta-values for each sample were compared by means of multidimensional scaling (MDS) and Hierarchical clustering (HC) analyses, considering the pair-wise Euclidean distances between samples. Differentially methylated regions (DMRs) were determined using ipdmr function with seed &#x3d; 0.01 (<xref ref-type="bibr" rid="B44">Xu et al., 2021</xref>).</p>
<p>Gene-set enrichment analysis on differentially methylated genes was carried out by means of Enrichr-KG and panther tools using default parameters (<xref ref-type="bibr" rid="B11">Evangelista et al., 2023</xref>; <xref ref-type="bibr" rid="B25">Mi and Thomas, 2009</xref>). Annotation of CpG sites was defined as follows: N_Shelf: Genomic coordinates of a CpG Island North Shelf, where the array has targeted a CpG within the shelf. The definition of a North Shelf is the region 4,000&#x2013;2000 base pairs upstream of a CpG Island start site; N_Shore: Genomic coordinates of a CpG Island North Shore, where the array has targeted a CpG within the shore. The definition of a North Shore is the region 2000&#x2013;0 base pairs upstream of a CpG Island start site; CpG_Island: Genomic coordinates of a CpG Island, where the array has targeted a CpG within the island. CpG Islands are regions greater than 200 base pairs in length with GC content of 50% or greater and have a ratio of &#x3e;0.6 for the observed number of CG dinucleotides to the expected number considering the total number of G and C bases in the genome segment; S_Shelf: Genomic coordinates of a CpG Island South Shelf, where the array has targeted a CpG within the shelf. The definition of a South Shelf is the region 4,000&#x2013;2000 base pairs downstream of a CpG Island start site; S_Shore: Genomic coordinates of a CpG Island South Shore, where the array has targeted a CpG within the shore. South Shore indicates the region 2000&#x2013;0 base pairs downstream of a CpG Island start site.</p>
</sec>
<sec id="s2-3">
<title>RNA isolation and quantitative real-time PCR</title>
<p>Total RNA was extracted from whole mouse kidney tissues snap-frozen immediately after mice sacrifice, using Trizol reagent (Ambion). Total RNA was also extracted from conditionally immortalised proximal tubular epithelial cells (ciPTEC), collecting cells directly in Trizol reagent (Ambion). cDNA was obtained using the Superscript Vilo kit (Invitrogen). Real-time PCR assays were performed using TaqMan Universal PCR Master mix (Applied Biosystems) and the following gene expression assays: mouse <italic>Slc7a7</italic>, <italic>Slc4a4</italic>, <italic>Cubn, Aqp1</italic>, <italic>Hnf1a</italic>, <italic>Hnf4a</italic>; human <italic>SLC7A7</italic>, <italic>AQP1</italic>, and <italic>CUBN</italic>. Gene expression data were normalized using mouse <italic>Hprt1</italic> or human <italic>HPRT1</italic> (Applied Biosystems) as endogenous controls. Data are expressed as arbitrary units (AU), determined using the 2<sup>&#x2212;&#x394;&#x394;CT</sup> method.</p>
</sec>
<sec id="s2-4">
<title>Cell culture and decitabine treatment</title>
<p>A control and a cystinotic (carrying the 57 kb deletion of the <italic>CTNS</italic> gene) conditionally immortalized PTEC lines (ciPTEC) were kindly provided by Prof. Elena Levtchenko and cultured as described in <xref ref-type="bibr" rid="B43">Wilmer et al. (2005)</xref>. Decitabine treatment was performed by adding 4 &#xb5;M decitabine (A3656 Sigma-Aldrich) to the culture media for 24 h and 1 &#xb5;M for the next 4 days. After 5 days of treatment, cells were harvested and lysed for RNA extraction.</p>
</sec>
<sec id="s2-5">
<title>Statistical analyses</title>
<p>Data are presented as mean &#xb1; SDs. Pairwise comparisons were evaluated by the Mann-Whitney U test. Group comparisons were performed by using 2-way Anova, followed by multiple comparison tests.</p>
<p>All statistical analyses were performed using GraphPad Prism IX software. P-values lower than 0.05 were considered statistically significant.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<sec id="s3-1">
<title>DNA methylation analysis in kidneys of cystinotic and wild-type (WT) mice</title>
<p>To investigate epigenetic changes in cystinosis, we conducted a genome-wide DNAm analysis on whole kidneys harvested from <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> mice at the age of 6 months, when kidney parenchyma lesions are still at an early stage (<xref ref-type="bibr" rid="B27">Nevo et al., 2010</xref>), and from age-matched WT mice. Analyses were performed using the Illumina Infinium Methylation Mouse BeadChip array, which covers 862,927 CpG sites. Following data preprocessing and quality controls, including bisulfite conversion efficiency, hybridization, extension, and staining, we obtained the distribution of DNAm levels in each sample, showing the expected bimodal pattern for both beta- and M-values (<xref ref-type="sec" rid="s12">Supplementary Figure S1</xref>).</p>
<p>Normalized beta-values for each sample were then compared by means of multidimensional scaling (MDS) and Hierarchical clustering (HC) analyses to verify genome-wide DNAm levels among different sample groups. Results indicate that 6-month-old WT and cystinotic kidney samples clustered into two distinct groups (<xref ref-type="fig" rid="F1">Figures 1A,B</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Analysis of DNA Methylome of 6-Month-Old <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> and WT mice Kidneys. <bold>(A)</bold> Multidimensional scaling (MDS) of the top 1000 most variable sites from 6-month-old WT and <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> kidneys. <bold>(B)</bold> Hierarchical clustering based on the top 1000 most variable sites, clearly separating <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> and WT kidneys in two distinct groups. <bold>(C)</bold> Volcano plot showing differentially methylated probes (DMPs), with the x- and y-axes showing the percent methylation difference and -log10 (p-value), respectively. Significant DMPs (methylation difference &#x3e;15% and adjusted p-value &#x3c;0.01) are shown in red, while non-significant DMPs are in black. <bold>(D)</bold> Manhattan plot of the statistically significant differentially methylated region. The x-axis represents the chromosomal location of the CpG position, and the y-axis shows the -log10 of p-value.</p>
</caption>
<graphic xlink:href="fcell-13-1638123-g001.tif">
<alt-text content-type="machine-generated">Panel A shows a scatter plot of Beta MDS, highlighting the separation between cyst and WT groups. Panel B presents a heatmap with hierarchical clustering, contrasting gene expression between cyst and WT samples. Panel C illustrates a volcano plot with log2 fold change on the x-axis and -log10 adjusted p-values on the y-axis, highlighting significant gene expression changes. Panel D displays a Manhattan plot, depicting -log10 p values against chromosome locations, pinpointing significant genomic regions.</alt-text>
</graphic>
</fig>
<p>Linear modeling on M-values was used to identify differentially methylated positions (DMPs) (<xref ref-type="fig" rid="F1">Figure 1C</xref>). DMPs were distributed across the entire genome, with occasional hot spots observed on chromosomes 2 and 11 (<xref ref-type="fig" rid="F1">Figure 1D</xref>). Applying stringent criteria (&#x7c;&#x394;&#x3b2;&#x7c; &#x2265; 15% and adjusted p &#x3c; 0.01), we identified in cystinotic kidneys 4,571 DMPs of which 673 (15%) were hypomethylated and 3,898 (85%) were hypermethylated, compared to WT kidneys.</p>
<p>The DMPs were primarily located in the gene body (66.2%) and in non-coding (open sea) genomic regions (22.3%), with only 11.5% of DMPs located in promoter regions (<xref ref-type="fig" rid="F2">Figure 2A</xref>). As reported in <xref ref-type="fig" rid="F2">Figure 2B</xref>, hypermethylated DMP were localized mainly in the gene body (57.8%) and in the open sea (20%). Additionally, 1,478 DMPs were associated with CpG island (CGI) and were distributed as follows: 33.4% within a CGI, 20.9% in the S-shore, 11.8% in the S-shelf, 20.7% in the N-shore, and 13% in the N-shelf (See Materials and Methods for definition of N/S-shelf, N/S-shore) (<xref ref-type="fig" rid="F2">Figure 2C</xref>). Hypermethylated DMP were enriched especially in N-shelf (11.6%), CGI (17.1%) and S-shelf (10.4%) (<xref ref-type="fig" rid="F2">Figure 2D</xref>). Analysis of differentially methylated regions (DMRs) using the <italic>ipDMR</italic> algorithm identified 3,993 DMRs across 1,534 genes, with 84% of these regions resulting hypermethylated in cystinotic kidneys (<xref ref-type="sec" rid="s12">Supplementary Table S1</xref>). Collectively, these results indicate a strong and extensive hypermethylation in the DNA of cystinotic kidneys.</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Genomic features of differential methylated positions (DMPs) in cystinotic mice kidneys. <bold>(A,B)</bold> The 4,571 DMPs were categorized based on their genomic location, including &#x201c;open sea&#x201d; regions, TSS_1500 (1,500 bp upstream of transcription start site), TSS_200 (200 bp upstream of transcription start site), and gene body. <bold>(C,D)</bold> Distribution of the 1,478 DMPs associated with CpG islands. N_Shelf: 4,000&#x2013;2000 base pairs upstream of a CpG Island start site; N_Shore: 2000&#x2013;0 base pairs upstream of a CpG Island start site. CpG_Island (CGI): CpG is within a CpG island; S_Shore: 0&#x2013;2000 base pairs downstream of a CpG Island start site; S_Shelf: 2000&#x2013;4,000 base pairs downstream of a CpG Island start site.</p>
</caption>
<graphic xlink:href="fcell-13-1638123-g002.tif">
<alt-text content-type="machine-generated">Four-part image showing DNA methylation distributions. (A) Pie chart displays DMP distribution relative to genes, with 66.2% in the gene body, 22.3% in open sea, 5.5% in TSS_200, and 6% in TSS_1500. Total is 4571.(B) Bar chart shows percentages of hypomethylated and hypermethylated DMPs relative to gene distribution, with a significant hypermethylation in the gene body.(C) Pie chart depicts DMP distribution relative to CGI, showing 33.4% in CGI, 20.7% in N_shore, 20.9% in S_shore, 13% in N_shelf, and 11.8% in S_shelf. Total is 1478.(D) Bar chart presents hypomethylated and hypermethylated DMP distributions relative to CGI, with notable hypermethylation in CGI.</alt-text>
</graphic>
</fig>
<p>Functional annotation of the DMPs was conducted through gene set enrichment analysis using Enrichr-KG (<xref ref-type="bibr" rid="B11">Evangelista et al., 2023</xref>). We included all the differentially methylated genes, regardless of CpG position. In addition, we analyzed both hyper- and hypomethylated genes, aiming to identify pathways affected by altered methylation, rather than focusing only on directionality or position of the alteration. The &#x201c;Kidney Tubule Cell&#x201d; (&#x201c;<italic>Tabula Muris</italic>&#x201d; annotation) was the most represented network, indicating that most of the epigenetic changes found in the cystinotic kidney occurred in tubular epithelial cells. Overall, the DNA methylation changes in cystinotic kidneys primarily affected genes encoding transporters and channels, cell signalling regulators, and proteins involved in cell-cell and transcriptional regulation (<xref ref-type="fig" rid="F3">Figure 3</xref>; <xref ref-type="sec" rid="s12">Supplementary Table S2</xref>). In line with functional enrichment analysis, which revealed that many differentially methylated genes were involved in the &#x201c;Transport of small molecules&#x201d;, we found that 74 out of 88 (84%) of differentially methylated genes in this pathway were hypermethylated (<xref ref-type="sec" rid="s12">Supplementary Table S3</xref>).</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>Functional annotation analysis of differential methylated positions (DMPs) in 6-month-old cystinotic mice kidneys. Gene-set enrichment analysis of pathways/ontologies associated with DMRs in 6-month-old <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> mice. The Enrichr-KG functional annotation tool was used to identify statistically significant functional associations, linking specific gene subsets to Biological Process categories [Gene Ontology (GO) or Signaling Pathways (KEGG pathway and Reactome databases) or Tabula Muris single-cell transcriptome data compendium].</p>
</caption>
<graphic xlink:href="fcell-13-1638123-g003.tif">
<alt-text content-type="machine-generated">Bar chart displaying various biological processes and pathways with their identifiers. Different pathways such as RHO GTPase Cycle, Adherens Junction, and Cell-Substrate Junction Assembly are shown with associated databases like Reactome, KEGG, and Gene Ontology. Each pathway is represented by a colored bar indicating its length.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s3-2">
<title>Methylation changes in <italic>Ctns</italic> <sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> mouse kidneys reflect altered mRNA gene expression</title>
<p>To analyse the functional effect of the observed differences in DNAm levels, we performed qPCR analysis on kidneys homogenates obtained from 6-month-old WT and <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> mice, focusing on genes critical for kidney function.</p>
<p>We analysed mRNA levels of <italic>Slc7a7</italic> and <italic>Slc4a4,</italic> two key members of the solute carrier (<italic>Slc)</italic> family. These genes encode the y &#x2b; LAT1 transporter and the sodium bicarbonate cotransporter 1 (NBCe1), respectively. Consistent with the presence of five hypermethylated cytosines in <italic>Slc7a7</italic> and six in <italic>Slc4a4</italic>, both genes exhibited significant downregulation at the mRNA level in the kidneys of <italic>Ctns</italic> <sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> mice, compared to WT (<xref ref-type="fig" rid="F4">Figures 4A&#x2013;D</xref>).</p>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption>
<p>Gene expression analysis in 6-month-old mice kidneys. <bold>(A,C,E,G,I,K)</bold> &#x3b2; values of CpG associated to <italic>Slc7a7</italic>, <italic>Slc4a4</italic>, <italic>Cubn</italic>, <italic>Aqp1</italic>, <italic>Hnf1a</italic>, <italic>Hnf4a</italic> in 6-month-old <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> and WT mouse kidneys. <bold>(B,D,F,H,J,L)</bold>. <italic>Slc7a7</italic>, <italic>Slc4a4</italic>, <italic>Cubn</italic>, <italic>Aqp1</italic>, <italic>Hnf1a</italic>, <italic>Hnf4a</italic> mRNA levels were evaluated by qPCR analysis in whole kidneys from 6-month-old WT (n &#x3d; 11) and <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> mice (n &#x3d; 20). Results were obtained after normalization with the housekeeping genes <italic>Hprt1</italic> and are expressed as arbitrary units (AU). Differences between WT and <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> mice were analyzed using the Mann-Whitney U test. &#x2a;p &#x3c; 0.05; &#x2a;&#x2a;p &#x3c; 0.01; &#x2a;&#x2a;&#x2a;p &#x3c; 0.001.</p>
</caption>
<graphic xlink:href="fcell-13-1638123-g004.tif">
<alt-text content-type="machine-generated">Grouped graphs comparing &#x3B2; values and mRNA expression levels for genes Slc7a7, Slc4a4, Cubn, Aqp1, Hnf1a, and Hnf4a between wild type (WT) and Ctns^-/- samples. Panels A, C, E, G, I, K display &#x3B2; values for different CG sites; panels B, D, F, H, J, L show mRNA levels (AU). Significant differences are indicated with asterisks.</alt-text>
</graphic>
</fig>
<p>Additionally, we observed differentially methylated cytosines in <italic>Cubilin (Cubn)</italic> and <italic>Aquaporin 1 (Aqp1)</italic>, genes critical for kidney epithelial cell function, both of which are significantly downregulated in cystinosis (<xref ref-type="bibr" rid="B29">Raggi et al., 2014</xref>). We identified two hypermethylated cytosines in the <italic>Cubn</italic> gene that were associated by qPCR analysis with reduced <italic>Cubn</italic> mRNA expression in <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> kidneys, compared to WT controls (<xref ref-type="fig" rid="F4">Figures 4E,F</xref>). Similar results were observed for the <italic>Aqp1</italic> gene (<xref ref-type="fig" rid="F4">Figures 4G,H</xref>).</p>
<p>Additional analyses revealed hypermethylation of hepatocyte nuclear factor 1 (<italic>Hnf1a)</italic> and <italic>Hnf4a</italic> genes, which encode transcription factors crucial for proximal tubule function. We found three hypermethylated cytosines in each of these genes, with a corresponding strong downregulation of their expression in cystinotic kidneys (<xref ref-type="fig" rid="F4">Figures 4I&#x2013;L</xref>).</p>
<p>In summary, our findings demonstrate that differential methylation in cystinotic kidneys is associated with changes in the expression of numerous genes involved in kidney tubule function, including transporters and transcription factors.</p>
</sec>
<sec id="s3-3">
<title>Demethylating treatment upregulates transporter expression in human conditionally immortalized PTEC</title>
<p>Based on the above results, we investigated whether this epigenetic signature could be reversed pharmacologically. To this end, we treated conditionally immortalized human proximal tubular epithelial cells (ciPTECs) from a healthy donor (HD) and a cystinotic patient (<xref ref-type="bibr" rid="B43">Wilmer et al., 2005</xref>) with the demethylating agent decitabine. At baseline, <italic>AQP1</italic> was the only transporter significantly downregulated in cystinotic ciPTECs compared to HD ciPTECs. However, decitabine treatment significantly upregulated <italic>SLC7A7, CUBN</italic>, and <italic>AQP1</italic> expression in both cell types (<xref ref-type="fig" rid="F5">Figures 5A&#x2013;C</xref>). Notably, the effect was more pronounced for <italic>CUBN</italic> and <italic>AQP1</italic> in cystinotic cells, suggesting that DNA methylation plays a key role in repressing these transporters in cystinosis and that demethylating agents may help restore their expression.</p>
<fig id="F5" position="float">
<label>FIGURE 5</label>
<caption>
<p>Decitabine treatment in ciPTEC. mRNA levels of <italic>SLC7A7</italic> <bold>(A)</bold>, <italic>CBLN</italic> <bold>(B)</bold> and <italic>AQP1</italic> <bold>(C)</bold> were evaluated by qPCR analysis in ciPTEC from a cystinotic patient (cystinotic) and a healthy donor (HD) treated (&#x2b;) or not (&#x2212;) with decitabine for 5 days. Results were obtained after normalization with the housekeeping gene <italic>HPRT1</italic> and are expressed as arbitrary units (AU). Differences between cystinotic and HD ciPTEC were analysed using 2-way Anova, followed by Sidak&#x2019;s multiple comparison test, with a single pool variance. &#x2a;p &#x3c; 0.05; &#x2a;&#x2a;p &#x3c; 0.01; &#x2a;&#x2a;&#x2a;p &#x3c; 0.001.</p>
</caption>
<graphic xlink:href="fcell-13-1638123-g005.tif">
<alt-text content-type="machine-generated">Bar graphs labeled A, B, and C show the mRNA levels of SLC7A7, CBLN, and AQP1, respectively, in human dermal (HD) and cystinotic cells with and without Decitabine treatment. Significant increases in mRNA levels are indicated in the Decitabine-treated cystinotic group in each graph, shown by asterisks denoting statistical significance levels.</alt-text>
</graphic>
</fig>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>The <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> mouse is a well-established model for kidney disease in cystinosis (<xref ref-type="bibr" rid="B27">Nevo et al., 2010</xref>). Mice typically develop evidence of kidney damage, including tubular atrophy, inflammation, and interstitial fibrosis around 6 months of age (<xref ref-type="bibr" rid="B27">Nevo et al., 2010</xref>; <xref ref-type="bibr" rid="B32">Rossi et al., 2024</xref>). In this study, we have performed whole-genome DNAm profiling in 6-month-old kidneys to explore the potential role of epigenetic alterations in cystinosis-related kidney disease. Our results show significant epigenetic differences between <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> and WT mice, with a pronounced hypermethylation profile in cystinotic kidneys, even at this early stage of renal parenchymal damage. These methylation changes were primarily found in genes and pathways crucial for kidney function, particularly those related to the physiology of proximal tubules. Importantly, these methylation alterations correlated with changes in gene expression, as validated by qPCR analyses performed on key selected genes.</p>
<p>DNAm is a key epigenetic mechanism, and abnormal changes have been associated with a wide range of diseases, including cancer, and more recently, kidney diseases (<xref ref-type="bibr" rid="B2">Bechtel et al., 2010</xref>; <xref ref-type="bibr" rid="B17">Ko et al., 2013</xref>; <xref ref-type="bibr" rid="B18">Larkin et al., 2018</xref>; <xref ref-type="bibr" rid="B24">Marumo et al., 2015</xref>; <xref ref-type="bibr" rid="B33">Sagy et al., 2024</xref>; <xref ref-type="bibr" rid="B35">Smyth et al., 2014</xref>; <xref ref-type="bibr" rid="B40">Tampe et al., 2017</xref>; <xref ref-type="bibr" rid="B39">Tampe et al., 2015</xref>; <xref ref-type="bibr" rid="B38">Tampe et al., 2014</xref>; <xref ref-type="bibr" rid="B45">Yan et al., 2024</xref>). In our study, we found both hypermethylation (85% of DMP) and hypomethylation (15% of DMP) in cystinotic kidneys compared to WT kidneys. Both alterations, hypermethylation and hypomethylation, have potential effects in gene expression regulation and have been described in a wide range of pathologies spanning from cancer to neurodegenerative diseases (<xref ref-type="bibr" rid="B9">Ehrlich, 2009</xref>; <xref ref-type="bibr" rid="B22">Lu et al., 2013</xref>). Interestingly, our genome-wide methylation analysis showed that in <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> mice kidneys the majority of differentially methylated CpG sites were located within gene bodies (around 66%), while approximately 11% of DMP was found in promoter and enhancer regions. Previous studies have focused on CpG islands in promoter regions and their role in regulating gene expression (<xref ref-type="bibr" rid="B12">Fernandez et al., 2012</xref>; <xref ref-type="bibr" rid="B26">Nagae et al., 2011</xref>), but increasingly more studies are focusing on differentially methylated regions (DMRs) in gene bodies (<xref ref-type="bibr" rid="B1">Anastasiadi et al., 2018</xref>; <xref ref-type="bibr" rid="B21">Lokk et al., 2014</xref>), where fully methylated CpGs are more often reported (<xref ref-type="bibr" rid="B5">Bontha et al., 2017</xref>; <xref ref-type="bibr" rid="B13">Illingworth and Bird, 2009</xref>; <xref ref-type="bibr" rid="B17">Ko et al., 2013</xref>). Generally, promoter hypermethylation leads to heterochromatin formation, resulting in tightly packed DNA, reduced transcription factor accessibility, and gene silencing; DNA hypomethylation is often associated with gene activation or genomic instability (<xref ref-type="bibr" rid="B13">Illingworth and Bird, 2009</xref>). Conversely, gene-body methylation has been reported to positively correlate with gene expression, although it can also interfere with transcription elongation (<xref ref-type="bibr" rid="B21">Lokk et al., 2014</xref>). Increasingly, it is becoming clear that the relationship between gene-body methylation and mRNA expression levels is more nuanced and complex than initially thought. In our study, we cannot draw broad conclusions on the functional implications of gene-body hypermethylation in <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> kidneys based solely on location data. Nevertheless, when we sampled gene expression, we observed that hypermethylated regions, whether in gene bodies or promoter regions, were consistently associated with reduced mRNA levels. These findings underscore the importance of integrating DNA methylation and gene expression data and performing functional analyses to understand the precise molecular mechanisms underlying cystinosis-related kidney dysfunction.</p>
<p>Pathway enrichment analysis highlighted a significant enrichment of methylation changes in the &#x201c;Kidney Tubule Cell&#x201d; cluster, further emphasizing the critical role of tubular epithelial cells in the pathogenesis of kidney damage in cystinosis (<xref ref-type="bibr" rid="B15">Ivanova et al., 2023</xref>; <xref ref-type="bibr" rid="B37">Sur et al., 2024</xref>). Additionally, functional annotation revealed that many of the differentially methylated genes were predominantly involved in pathways related to &#x201c;Transport of small molecules&#x201d;, a process essential for maintaining renal function and electrolyte balance (<xref ref-type="bibr" rid="B19">Lewis et al., 2021</xref>). Strikingly, we found that 93% (55 out of 57) of differentially methylated <italic>Slc</italic> genes were hypermethylated. Accordingly, we found that key transporters such as <italic>Slc7a7</italic>, <italic>Slc4a4</italic>, as well as <italic>Cubn</italic> and <italic>Aqp1</italic> were not only hypermethylated but also significantly downregulated in cystinotic kidneys, suggesting that epigenetic silencing of transport-related genes could exacerbate tubular dysfunction. Similarly, in the kidneys of <italic>Ctns</italic>
<sup>
<italic>&#x2212;/&#x2212;</italic>
</sup> mice, we found hypermethylation and reduced mRNA expression levels of transcription factors <italic>Hnf1a</italic> and <italic>Hnf4a</italic>, both critical for proximal tubule differentiation and function (<xref ref-type="bibr" rid="B23">Marable et al., 2018</xref>), further supporting the role of epigenetic modifications in disrupting tubular epithelial integrity. Indeed, loss of <italic>Hnf1a</italic> and <italic>Hnf4a</italic> expression has been implicated in the development of proximal tubular dysfunction (<xref ref-type="bibr" rid="B23">Marable et al., 2018</xref>), resulting in glycosuria and polyuria, which are hallmark features of cystinosis. Of note, <xref ref-type="bibr" rid="B24">Marumo et al. (2015)</xref> have observed that diabetes induces aberrant DNAm changes in proximal tubules, in particular in <italic>Hnf4a</italic> gene. Furthermore, recent findings emphasize the central role of DNAm in kidney-specific expression of amino acid transporters and of their master regulator, <italic>Hnf1a</italic> (<xref ref-type="bibr" rid="B16">Kikuchi et al., 2010</xref>). Consistently, our unpublished transcriptomic analyses of cortical kidney sections from 12-month-old mice revealed that 145 <italic>Slc</italic> genes were differentially expressed in cystinotic kidneys compared to WT mice, with 115 genes (79%) downregulated (data not shown). These findings strongly suggest that epigenetic dysregulation of transcription factors and transport-related genes plays a pivotal role in the pathogenesis and progression of cystinosis.</p>
<p>While the precise mechanisms underlying epigenetic dysregulation in kidney diseases remain unclear, emerging evidence points to oxidative stress and inflammation as key contributors (<xref ref-type="bibr" rid="B10">Elmonem et al., 2022</xref>; <xref ref-type="bibr" rid="B14">Ingrosso and Perna, 2020</xref>). Oxidative stress, a known driver of cystinosis-related tubular damage, has been shown to modulate DNAm patterns through alterations in methylation enzymes like DNMTs and TET proteins (<xref ref-type="bibr" rid="B38">Tampe et al., 2014</xref>). This interplay could amplify the hypermethylation observed in genes crucial for tubular cell function. Similarly, chronic inflammation, which characterizes cystinotic kidneys, can induce epigenetic changes that perpetuate inflammatory signaling and tubular injury. On these basis, it would be interesting to investigate whether interventions that have proven effective in preventing or delaying the progression of cystinosis, such as the ketogenic diet (<xref ref-type="bibr" rid="B3">Bellomo et al., 2024</xref>) or flavonoids (<xref ref-type="bibr" rid="B7">De Leo et al., 2024</xref>; <xref ref-type="bibr" rid="B6">De Leo et al., 2023</xref>), both known for their antioxidant and anti-inflammatory properties, exert at least in part, their effects by modulating the epigenetic landscape of cystinotic kidneys in mice.</p>
<p>The reversibility of DNA methylation represents an intriguing therapeutic opportunity for cystinosis. In our study, treatment of cystinotic ciPTECs with the demethylating agent decitabine successfully increased the expression of key transporters, including <italic>SLC7A7</italic>, <italic>AQP1</italic>, and <italic>CUBN</italic>. It is noteworthy that these genes were already transcriptionally active in HD cells, likely making them more responsive to upregulation upon treatment. Decitabine has been FDA-approved for the treatment of myelodysplastic syndrome and acute myeloid leukemia (<xref ref-type="bibr" rid="B8">Derissen et al., 2013</xref>) and, currently, several clinical trials on cancer are testing the efficacy of demethylating drugs (<xref ref-type="bibr" rid="B42">Wanner and Bechtel-Walz, 2017</xref>). Moreover, epidrugs are also effective to slow down the progression of renal fibrosis and inflammation in animals with progressive CKD (<xref ref-type="bibr" rid="B40">Tampe et al., 2017</xref>; <xref ref-type="bibr" rid="B42">Wanner and Bechtel-Walz, 2017</xref>) and decitabine treatment has been successfully used in mouse models of diabetic nephropathy (<xref ref-type="bibr" rid="B18">Larkin et al., 2018</xref>; <xref ref-type="bibr" rid="B46">Zhang et al., 2017</xref>). These findings highlight the therapeutic potential of epigenetic modulation to counteract gene silencing and improve tubular function. However, confirming the effect at the protein level and assessing downstream functional parameters would be essential to establish the real impact on cell physiology. Furthermore, an <italic>in vivo</italic> study using cystinotic mice treated with decitabine would be crucial to understand whether and how demethylation concretely affects disease pathogenesis.</p>
<p>In conclusion, this study provides compelling evidence that epigenetic alterations, particularly hypermethylation, contribute to cystinosis-related renal dysfunction. The identification of differentially methylated genes and pathways, especially those involved in tubular transport and transcriptional regulation, offers new insights into the molecular mechanisms driving disease progression. These findings pave the way for future research into the therapeutic potential of targeting DNAm to mitigate kidney damage in cystinosis. They also show that integrating epigenomic, transcriptomic, and proteomic data is essential to develop a comprehensive understanding of cystinosis-related kidney disease and to identify novel therapeutic targets for intervention.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="s5">
<title>Data availability statement</title>
<p>The datasets presented in this study can be found in online repositories. GEO accession number is GSE293586.</p>
</sec>
<sec sec-type="ethics-statement" id="s6">
<title>Ethics statement</title>
<p>The animal studies were approved by Animal care and experimental procedures complied with the European 2010/63/EU on the protection of animals used for scientific purposes and were approved by the Italian Ministry of Health (authorization number 898/2017-PR). The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent was obtained from the owners for the participation of their animals in this study.</p>
</sec>
<sec sec-type="author-contributions" id="s7">
<title>Author contributions</title>
<p>MR: Investigation, Conceptualization, Methodology, Formal Analysis, Data curation, Writing &#x2013; original draft. AC: Formal Analysis, Writing &#x2013; original draft, Data curation, Conceptualization, Methodology, Investigation. VM: Data curation, Methodology, Investigation, Writing &#x2013; original draft. LP: Investigation, Data curation, Writing &#x2013; original draft, Methodology. CN: Methodology, Investigation, Writing &#x2013; original draft, Data curation. EL: Writing &#x2013; original draft, Investigation, Methodology, Data curation. IC: Data curation, Methodology, Writing &#x2013; original draft, Investigation. Francesco FB: Data curation, Methodology, Writing &#x2013; original draft, Investigation. AT: Methodology, Data curation, Investigation, Writing &#x2013; original draft. ED: Methodology, Data curation, Investigation, Writing &#x2013; original draft. MT: Data curation, Writing &#x2013; original draft, Formal Analysis. FE: Data curation, Writing &#x2013; original draft. FD: Data curation, Writing &#x2013; original draft. Evelina EM: Data curation, Conceptualization, Writing &#x2013; original draft. GP: Supervision, Writing &#x2013; original draft, Funding acquisition, Conceptualization, Methodology, Formal Analysis, Investigation, Data curation.</p>
</sec>
<sec sec-type="funding-information" id="s8">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research and/or publication of this article. This work was supported by the Cystinosis Research Foundation (Grant CRFF-2020-003 to GP) and by the Italian Ministry of Health with &#x201c;Current Research funds&#x201d;.</p>
</sec>
<ack>
<p>We thank Prof. Corinne Antignac for kindly providing the Ctns<sup>&#x2212;/&#x2212;</sup> mouse model and Prof. Elena Levtchenko for kindly providing ciPTEC.</p>
</ack>
<sec sec-type="COI-statement" id="s9">
<title>Conflict of interest</title>
<p>The 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 sec-type="ai-statement" id="s10">
<title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p>
</sec>
<sec sec-type="disclaimer" id="s11">
<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 sec-type="supplementary-material" id="s12">
<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/fcell.2025.1638123/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fcell.2025.1638123/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Table3.xlsx" id="SM1" mimetype="application/xlsx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table2.docx" id="SM2" mimetype="application/docx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="DataSheet1.pdf" id="SM3" mimetype="application/pdf" xmlns:xlink="http://www.w3.org/1999/xlink"/>
<supplementary-material xlink:href="Table1.xlsx" id="SM4" mimetype="application/xlsx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
<ref-list>
<title>References</title>
<ref id="B1">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Anastasiadi</surname>
<given-names>D.</given-names>
</name>
<name>
<surname>Esteve-Codina</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Piferrer</surname>
<given-names>F.</given-names>
</name>
</person-group> (<year>2018</year>). <article-title>Consistent inverse correlation between DNA methylation of the first intron and gene expression across tissues and species</article-title>. <source>Epigenetics Chromatin</source> <volume>11</volume>, <fpage>37</fpage>. <pub-id pub-id-type="doi">10.1186/s13072-018-0205-1</pub-id>
</citation>
</ref>
<ref id="B2">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Bechtel</surname>
<given-names>W.</given-names>
</name>
<name>
<surname>McGoohan</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Zeisberg</surname>
<given-names>E. M.</given-names>
</name>
<name>
<surname>M&#xfc;ller</surname>
<given-names>G. A.</given-names>
</name>
<name>
<surname>Kalbacher</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Salant</surname>
<given-names>D. J.</given-names>
</name>
<etal/>
</person-group> (<year>2010</year>). <article-title>Methylation determines fibroblast activation and fibrogenesis in the kidney</article-title>. <source>Nat. Med.</source> <volume>16</volume>, <fpage>544</fpage>&#x2013;<lpage>550</lpage>. <pub-id pub-id-type="doi">10.1038/nm.2135</pub-id>
</citation>
</ref>
<ref id="B3">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Bellomo</surname>
<given-names>F.</given-names>
</name>
<name>
<surname>Pugliese</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Cairoli</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Krohn</surname>
<given-names>P.</given-names>
</name>
<name>
<surname>De Stefanis</surname>
<given-names>C.</given-names>
</name>
<name>
<surname>Raso</surname>
<given-names>R.</given-names>
</name>
<etal/>
</person-group> (<year>2024</year>). <article-title>Ketogenic diet and progression of kidney disease in animal models of nephropathic cystinosis</article-title>. <source>J. Am. Soc. Nephrol.</source> <volume>35</volume>, <fpage>1493</fpage>&#x2013;<lpage>1506</lpage>. <pub-id pub-id-type="doi">10.1681/ASN.0000000000000439</pub-id>
</citation>
</ref>
<ref id="B4">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Bird</surname>
<given-names>A. P.</given-names>
</name>
</person-group> (<year>1986</year>). <article-title>CpG-rich islands and the function of DNA methylation</article-title>. <source>Nature</source> <volume>321</volume>, <fpage>209</fpage>&#x2013;<lpage>213</lpage>. <pub-id pub-id-type="doi">10.1038/321209a0</pub-id>
</citation>
</ref>
<ref id="B5">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Bontha</surname>
<given-names>S. V.</given-names>
</name>
<name>
<surname>Maluf</surname>
<given-names>D. G.</given-names>
</name>
<name>
<surname>Archer</surname>
<given-names>K. J.</given-names>
</name>
<name>
<surname>Dumur</surname>
<given-names>C. I.</given-names>
</name>
<name>
<surname>Dozmorov</surname>
<given-names>M. G.</given-names>
</name>
<name>
<surname>King</surname>
<given-names>A. L.</given-names>
</name>
<etal/>
</person-group> (<year>2017</year>). <article-title>Effects of DNA methylation on progression to interstitial fibrosis and tubular atrophy in renal allograft biopsies: a multi-omics approach</article-title>. <source>Am. J. Transpl.</source> <volume>17</volume>, <fpage>3060</fpage>&#x2013;<lpage>3075</lpage>. <pub-id pub-id-type="doi">10.1111/ajt.14372</pub-id>
</citation>
</ref>
<ref id="B6">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>De Leo</surname>
<given-names>E.</given-names>
</name>
<name>
<surname>Taranta</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Raso</surname>
<given-names>R.</given-names>
</name>
<name>
<surname>Polishchuk</surname>
<given-names>E.</given-names>
</name>
<name>
<surname>D&#x2019;Oria</surname>
<given-names>V.</given-names>
</name>
<name>
<surname>Pezzullo</surname>
<given-names>M.</given-names>
</name>
<etal/>
</person-group> (<year>2023</year>). <article-title>Genistein improves renal disease in a mouse model of nephropathic cystinosis: a comparison study with cysteamine</article-title>. <source>Hum. Mol. Genet.</source> <volume>32</volume>, <fpage>1090</fpage>&#x2013;<lpage>1101</lpage>. <pub-id pub-id-type="doi">10.1093/hmg/ddac266</pub-id>
</citation>
</ref>
<ref id="B7">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>De Leo</surname>
<given-names>E.</given-names>
</name>
<name>
<surname>Taranta</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Raso</surname>
<given-names>R.</given-names>
</name>
<name>
<surname>Pezzullo</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Piccione</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Matteo</surname>
<given-names>V.</given-names>
</name>
<etal/>
</person-group> (<year>2024</year>). <article-title>Long-term effects of luteolin in a mouse model of nephropathic cystinosis</article-title>. <source>Biomed. Pharmacother.</source> <volume>178</volume>, <fpage>117236</fpage>. <pub-id pub-id-type="doi">10.1016/j.biopha.2024.117236</pub-id>
</citation>
</ref>
<ref id="B8">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Derissen</surname>
<given-names>E. J. B.</given-names>
</name>
<name>
<surname>Beijnen</surname>
<given-names>J. H.</given-names>
</name>
<name>
<surname>Schellens</surname>
<given-names>J. H. M.</given-names>
</name>
</person-group> (<year>2013</year>). <article-title>Concise drug review: azacitidine and decitabine</article-title>. <source>Oncol.</source> <volume>18</volume>, <fpage>619</fpage>&#x2013;<lpage>624</lpage>. <pub-id pub-id-type="doi">10.1634/theoncologist.2012-0465</pub-id>
</citation>
</ref>
<ref id="B9">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Ehrlich</surname>
<given-names>M.</given-names>
</name>
</person-group> (<year>2009</year>). <article-title>Dna hypomethylation in cancer cells</article-title>. <source>Epigenomics</source> <volume>1</volume>, <fpage>239</fpage>&#x2013;<lpage>259</lpage>. <pub-id pub-id-type="doi">10.2217/epi.09.33</pub-id>
</citation>
</ref>
<ref id="B10">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Elmonem</surname>
<given-names>M. A.</given-names>
</name>
<name>
<surname>Veys</surname>
<given-names>K. R. P.</given-names>
</name>
<name>
<surname>Prencipe</surname>
<given-names>G.</given-names>
</name>
</person-group> (<year>2022</year>). <article-title>Nephropathic cystinosis: pathogenic roles of inflammation and potential for new therapies</article-title>. <source>Cells</source> <volume>11</volume>, <fpage>190</fpage>. <pub-id pub-id-type="doi">10.3390/cells11020190</pub-id>
</citation>
</ref>
<ref id="B11">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Evangelista</surname>
<given-names>J. E.</given-names>
</name>
<name>
<surname>Xie</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Marino</surname>
<given-names>G. B.</given-names>
</name>
<name>
<surname>Nguyen</surname>
<given-names>N.</given-names>
</name>
<name>
<surname>Clarke</surname>
<given-names>D. J. B.</given-names>
</name>
<name>
<surname>Ma&#x2019;ayan</surname>
<given-names>A.</given-names>
</name>
</person-group> (<year>2023</year>). <article-title>Enrichr-KG: bridging enrichment analysis across multiple libraries</article-title>. <source>Nucleic Acids Res.</source> <volume>51</volume>, <fpage>W168</fpage>&#x2013;<lpage>W179</lpage>. <pub-id pub-id-type="doi">10.1093/nar/gkad393</pub-id>
</citation>
</ref>
<ref id="B12">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Fernandez</surname>
<given-names>A. F.</given-names>
</name>
<name>
<surname>Assenov</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Martin-Subero</surname>
<given-names>J. I.</given-names>
</name>
<name>
<surname>Balint</surname>
<given-names>B.</given-names>
</name>
<name>
<surname>Siebert</surname>
<given-names>R.</given-names>
</name>
<name>
<surname>Taniguchi</surname>
<given-names>H.</given-names>
</name>
<etal/>
</person-group> (<year>2012</year>). <article-title>A DNA methylation fingerprint of 1628 human samples</article-title>. <source>Genome Res.</source> <volume>22</volume>, <fpage>407</fpage>&#x2013;<lpage>419</lpage>. <pub-id pub-id-type="doi">10.1101/gr.119867.110</pub-id>
</citation>
</ref>
<ref id="B13">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Illingworth</surname>
<given-names>R. S.</given-names>
</name>
<name>
<surname>Bird</surname>
<given-names>A. P.</given-names>
</name>
</person-group> (<year>2009</year>). <article-title>CpG islands &#x2013; &#x2018;A rough guide</article-title>. <source>&#x2019; FEBS Lett.</source> <volume>583</volume>, <fpage>1713</fpage>&#x2013;<lpage>1720</lpage>. <pub-id pub-id-type="doi">10.1016/j.febslet.2009.04.012</pub-id>
</citation>
</ref>
<ref id="B14">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Ingrosso</surname>
<given-names>D.</given-names>
</name>
<name>
<surname>Perna</surname>
<given-names>A. F.</given-names>
</name>
</person-group> (<year>2020</year>). <article-title>DNA methylation dysfunction in chronic kidney disease</article-title>. <source>Genes</source> <volume>11</volume>, <fpage>811</fpage>. <pub-id pub-id-type="doi">10.3390/genes11070811</pub-id>
</citation>
</ref>
<ref id="B15">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Ivanova</surname>
<given-names>O. N.</given-names>
</name>
<name>
<surname>Krasnov</surname>
<given-names>G. S.</given-names>
</name>
<name>
<surname>Snezhkina</surname>
<given-names>A. V.</given-names>
</name>
<name>
<surname>Kudryavtseva</surname>
<given-names>A. V.</given-names>
</name>
<name>
<surname>Fedorov</surname>
<given-names>V. S.</given-names>
</name>
<name>
<surname>Zakirova</surname>
<given-names>N. F.</given-names>
</name>
<etal/>
</person-group> (<year>2023</year>). <article-title>Transcriptome analysis of redox systems and polyamine metabolic pathway in hepatoma and non-tumor hepatocyte-like cells</article-title>. <source>Biomolecules</source> <volume>13</volume>, <fpage>714</fpage>. <pub-id pub-id-type="doi">10.3390/biom13040714</pub-id>
</citation>
</ref>
<ref id="B16">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Kikuchi</surname>
<given-names>R.</given-names>
</name>
<name>
<surname>Yagi</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Kusuhara</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Imai</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Sugiyama</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Shiota</surname>
<given-names>K.</given-names>
</name>
</person-group> (<year>2010</year>). <article-title>Genome-wide analysis of epigenetic signatures for kidney-specific transporters</article-title>. <source>Kidney Int.</source> <volume>78</volume>, <fpage>569</fpage>&#x2013;<lpage>577</lpage>. <pub-id pub-id-type="doi">10.1038/ki.2010.176</pub-id>
</citation>
</ref>
<ref id="B17">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Ko</surname>
<given-names>Y.-A.</given-names>
</name>
<name>
<surname>Mohtat</surname>
<given-names>D.</given-names>
</name>
<name>
<surname>Suzuki</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Park</surname>
<given-names>A. S. D.</given-names>
</name>
<name>
<surname>Izquierdo</surname>
<given-names>M. C.</given-names>
</name>
<name>
<surname>Han</surname>
<given-names>S. Y.</given-names>
</name>
<etal/>
</person-group> (<year>2013</year>). <article-title>Cytosine methylation changes in enhancer regions of core pro-fibrotic genes characterize kidney fibrosis development</article-title>. <source>Genome Biol.</source> <volume>14</volume>, <fpage>R108</fpage>. <pub-id pub-id-type="doi">10.1186/gb-2013-14-10-r108</pub-id>
</citation>
</ref>
<ref id="B18">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Larkin</surname>
<given-names>B. P.</given-names>
</name>
<name>
<surname>Glastras</surname>
<given-names>S. J.</given-names>
</name>
<name>
<surname>Chen</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Pollock</surname>
<given-names>C. A.</given-names>
</name>
<name>
<surname>Saad</surname>
<given-names>S.</given-names>
</name>
</person-group> (<year>2018</year>). <article-title>DNA methylation and the potential role of demethylating agents in prevention of progressive chronic kidney disease</article-title>. <source>FASEB J.</source> <volume>32</volume>, <fpage>5215</fpage>&#x2013;<lpage>5226</lpage>. <pub-id pub-id-type="doi">10.1096/fj.201800205R</pub-id>
</citation>
</ref>
<ref id="B19">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Lewis</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Chen</surname>
<given-names>L.</given-names>
</name>
<name>
<surname>Raghuram</surname>
<given-names>V.</given-names>
</name>
<name>
<surname>Khundmiri</surname>
<given-names>S. J.</given-names>
</name>
<name>
<surname>Chou</surname>
<given-names>C.-L.</given-names>
</name>
<name>
<surname>Yang</surname>
<given-names>C.-R.</given-names>
</name>
<etal/>
</person-group> (<year>2021</year>). <article-title>&#x201c;SLC-omics&#x201d; of the kidney: solute transporters along the nephron</article-title>. <source>Am. J. Physiol.-Cell Physiol.</source> <volume>321</volume>, <fpage>C507</fpage>&#x2013;<lpage>C518</lpage>. <pub-id pub-id-type="doi">10.1152/ajpcell.00197.2021</pub-id>
</citation>
</ref>
<ref id="B20">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Liu</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Doke</surname>
<given-names>T.</given-names>
</name>
<name>
<surname>Guo</surname>
<given-names>D.</given-names>
</name>
<name>
<surname>Sheng</surname>
<given-names>X.</given-names>
</name>
<name>
<surname>Ma</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Park</surname>
<given-names>J.</given-names>
</name>
<etal/>
</person-group> (<year>2022</year>). <article-title>Epigenomic and transcriptomic analyses define core cell types, genes and targetable mechanisms for kidney disease</article-title>. <source>Nat. Genet.</source> <volume>54</volume>, <fpage>950</fpage>&#x2013;<lpage>962</lpage>. <pub-id pub-id-type="doi">10.1038/s41588-022-01097-w</pub-id>
</citation>
</ref>
<ref id="B21">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Lokk</surname>
<given-names>K.</given-names>
</name>
<name>
<surname>Modhukur</surname>
<given-names>V.</given-names>
</name>
<name>
<surname>Rajashekar</surname>
<given-names>B.</given-names>
</name>
<name>
<surname>M&#xe4;rtens</surname>
<given-names>K.</given-names>
</name>
<name>
<surname>M&#xe4;gi</surname>
<given-names>R.</given-names>
</name>
<name>
<surname>Kolde</surname>
<given-names>R.</given-names>
</name>
<etal/>
</person-group> (<year>2014</year>). <article-title>DNA methylome profiling of human tissues identifies global and tissue-specific methylation patterns</article-title>. <source>Genome Biol.</source> <volume>15</volume>, <fpage>r54</fpage>. <pub-id pub-id-type="doi">10.1186/gb-2014-15-4-r54</pub-id>
</citation>
</ref>
<ref id="B22">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Lu</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Liu</surname>
<given-names>X.</given-names>
</name>
<name>
<surname>Deng</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Qing</surname>
<given-names>H.</given-names>
</name>
</person-group> (<year>2013</year>). <article-title>DNA methylation, a hand behind neurodegenerative diseases</article-title>. <source>Front. Aging Neurosci.</source> <volume>5</volume>, <fpage>85</fpage>. <pub-id pub-id-type="doi">10.3389/fnagi.2013.00085</pub-id>
</citation>
</ref>
<ref id="B23">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Marable</surname>
<given-names>S. S.</given-names>
</name>
<name>
<surname>Chung</surname>
<given-names>E.</given-names>
</name>
<name>
<surname>Adam</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Potter</surname>
<given-names>S. S.</given-names>
</name>
<name>
<surname>Park</surname>
<given-names>J.-S.</given-names>
</name>
</person-group> (<year>2018</year>). <article-title>Hnf4a deletion in the mouse kidney phenocopies fanconi renotubular syndrome</article-title>. <source>JCI Insight</source> <volume>3</volume>, <fpage>e97497</fpage>. <pub-id pub-id-type="doi">10.1172/jci.insight.97497</pub-id>
</citation>
</ref>
<ref id="B24">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Marumo</surname>
<given-names>T.</given-names>
</name>
<name>
<surname>Yagi</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Kawarazaki</surname>
<given-names>W.</given-names>
</name>
<name>
<surname>Nishimoto</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Ayuzawa</surname>
<given-names>N.</given-names>
</name>
<name>
<surname>Watanabe</surname>
<given-names>A.</given-names>
</name>
<etal/>
</person-group> (<year>2015</year>). <article-title>Diabetes induces aberrant DNA methylation in the proximal tubules of the kidney</article-title>. <source>J. Am. Soc. Nephrol.</source> <volume>26</volume>, <fpage>2388</fpage>&#x2013;<lpage>2397</lpage>. <pub-id pub-id-type="doi">10.1681/ASN.2014070665</pub-id>
</citation>
</ref>
<ref id="B25">
<citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname>Mi</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Thomas</surname>
<given-names>P.</given-names>
</name>
</person-group> (<year>2009</year>). &#x201c;<article-title>PANTHER pathway: an ontology-based pathway database coupled with data analysis tools</article-title>,&#x201d; in <source>Protein networks and pathway analysis</source>. Editors <person-group person-group-type="editor">
<name>
<surname>Nikolsky</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Bryant</surname>
<given-names>J.</given-names>
</name>
</person-group> (<publisher-loc>Totowa, NJ</publisher-loc>: <publisher-name>Humana Press</publisher-name>), <fpage>123</fpage>&#x2013;<lpage>140</lpage>. <pub-id pub-id-type="doi">10.1007/978-1-60761-175-2_7</pub-id>
</citation>
</ref>
<ref id="B26">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Nagae</surname>
<given-names>G.</given-names>
</name>
<name>
<surname>Isagawa</surname>
<given-names>T.</given-names>
</name>
<name>
<surname>Shiraki</surname>
<given-names>N.</given-names>
</name>
<name>
<surname>Fujita</surname>
<given-names>T.</given-names>
</name>
<name>
<surname>Yamamoto</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Tsutsumi</surname>
<given-names>S.</given-names>
</name>
<etal/>
</person-group> (<year>2011</year>). <article-title>Tissue-specific demethylation in CpG-poor promoters during cellular differentiation</article-title>. <source>Hum. Mol. Genet.</source> <volume>20</volume>, <fpage>2710</fpage>&#x2013;<lpage>2721</lpage>. <pub-id pub-id-type="doi">10.1093/hmg/ddr170</pub-id>
</citation>
</ref>
<ref id="B27">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Nevo</surname>
<given-names>N.</given-names>
</name>
<name>
<surname>Chol</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Bailleux</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Kalatzis</surname>
<given-names>V.</given-names>
</name>
<name>
<surname>Morisset</surname>
<given-names>L.</given-names>
</name>
<name>
<surname>Devuyst</surname>
<given-names>O.</given-names>
</name>
<etal/>
</person-group> (<year>2010</year>). <article-title>Renal phenotype of the cystinosis mouse model is dependent upon genetic background</article-title>. <source>Nephrol. Dial. Transpl.</source> <volume>25</volume>, <fpage>1059</fpage>&#x2013;<lpage>1066</lpage>. <pub-id pub-id-type="doi">10.1093/ndt/gfp553</pub-id>
</citation>
</ref>
<ref id="B28">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Prencipe</surname>
<given-names>G.</given-names>
</name>
<name>
<surname>Caiello</surname>
<given-names>I.</given-names>
</name>
<name>
<surname>Cherqui</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Whisenant</surname>
<given-names>T.</given-names>
</name>
<name>
<surname>Petrini</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Emma</surname>
<given-names>F.</given-names>
</name>
<etal/>
</person-group> (<year>2014</year>). <article-title>Inflammasome activation by cystine crystals: implications for the pathogenesis of cystinosis</article-title>. <source>J. Am. Soc. Nephrol.</source> <volume>25</volume>, <fpage>1163</fpage>&#x2013;<lpage>1169</lpage>. <pub-id pub-id-type="doi">10.1681/ASN.2013060653</pub-id>
</citation>
</ref>
<ref id="B29">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Raggi</surname>
<given-names>C.</given-names>
</name>
<name>
<surname>Luciani</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Nevo</surname>
<given-names>N.</given-names>
</name>
<name>
<surname>Antignac</surname>
<given-names>C.</given-names>
</name>
<name>
<surname>Terryn</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Devuyst</surname>
<given-names>O.</given-names>
</name>
</person-group> (<year>2014</year>). <article-title>Dedifferentiation and aberrations of the endolysosomal compartment characterize the early stage of nephropathic cystinosis</article-title>. <source>Hum. Mol. Genet.</source> <volume>23</volume>, <fpage>2266</fpage>&#x2013;<lpage>2278</lpage>. <pub-id pub-id-type="doi">10.1093/hmg/ddt617</pub-id>
</citation>
</ref>
<ref id="B30">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Ritchie</surname>
<given-names>M. E.</given-names>
</name>
<name>
<surname>Phipson</surname>
<given-names>B.</given-names>
</name>
<name>
<surname>Wu</surname>
<given-names>D.</given-names>
</name>
<name>
<surname>Hu</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Law</surname>
<given-names>C. W.</given-names>
</name>
<name>
<surname>Shi</surname>
<given-names>W.</given-names>
</name>
<etal/>
</person-group> (<year>2015</year>). <article-title>Limma powers differential expression analyses for RNA-sequencing and microarray studies</article-title>. <source>Nucleic Acids Res.</source> <volume>43</volume>, <fpage>e47</fpage>. <pub-id pub-id-type="doi">10.1093/nar/gkv007</pub-id>
</citation>
</ref>
<ref id="B31">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Rossi</surname>
<given-names>M. N.</given-names>
</name>
<name>
<surname>Pascarella</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Licursi</surname>
<given-names>V.</given-names>
</name>
<name>
<surname>Caiello</surname>
<given-names>I.</given-names>
</name>
<name>
<surname>Taranta</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Rega</surname>
<given-names>L. R.</given-names>
</name>
<etal/>
</person-group> (<year>2019</year>). <article-title>NLRP2 regulates proinflammatory and antiapoptotic responses in proximal tubular epithelial cells</article-title>. <source>Front. Cell Dev. Biol.</source> <volume>7</volume>, <fpage>252</fpage>. <pub-id pub-id-type="doi">10.3389/fcell.2019.00252</pub-id>
</citation>
</ref>
<ref id="B32">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Rossi</surname>
<given-names>M. N.</given-names>
</name>
<name>
<surname>Matteo</surname>
<given-names>V.</given-names>
</name>
<name>
<surname>Diomedi-Camassei</surname>
<given-names>F.</given-names>
</name>
<name>
<surname>De Leo</surname>
<given-names>E.</given-names>
</name>
<name>
<surname>Devuyst</surname>
<given-names>O.</given-names>
</name>
<name>
<surname>Lamkanfi</surname>
<given-names>M.</given-names>
</name>
<etal/>
</person-group> (<year>2024</year>). <article-title>Nlrp2 deletion ameliorates kidney damage in a mouse model of cystinosis</article-title>. <source>Front. Immunol.</source> <volume>15</volume>, <fpage>1373224</fpage>. <pub-id pub-id-type="doi">10.3389/fimmu.2024.1373224</pub-id>
</citation>
</ref>
<ref id="B33">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Sagy</surname>
<given-names>N.</given-names>
</name>
<name>
<surname>Meyrom</surname>
<given-names>N.</given-names>
</name>
<name>
<surname>Beckerman</surname>
<given-names>P.</given-names>
</name>
<name>
<surname>Pleniceanu</surname>
<given-names>O.</given-names>
</name>
<name>
<surname>Bar</surname>
<given-names>D. Z.</given-names>
</name>
</person-group> (<year>2024</year>). <article-title>Kidney-specific methylation patterns correlate with kidney function and are lost upon kidney disease progression</article-title>. <source>Clin. Epigenetics</source> <volume>16</volume>, <fpage>27</fpage>. <pub-id pub-id-type="doi">10.1186/s13148-024-01642-w</pub-id>
</citation>
</ref>
<ref id="B34">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Schlosser</surname>
<given-names>P.</given-names>
</name>
<name>
<surname>Tin</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Matias-Garcia</surname>
<given-names>P. R.</given-names>
</name>
<name>
<surname>Thio</surname>
<given-names>C. H. L.</given-names>
</name>
<name>
<surname>Joehanes</surname>
<given-names>R.</given-names>
</name>
<name>
<surname>Liu</surname>
<given-names>H.</given-names>
</name>
<etal/>
</person-group> (<year>2021</year>). <article-title>Meta-analyses identify DNA methylation associated with kidney function and damage</article-title>. <source>Nat. Commun.</source> <volume>12</volume>, <fpage>7174</fpage>. <pub-id pub-id-type="doi">10.1038/s41467-021-27234-3</pub-id>
</citation>
</ref>
<ref id="B35">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Smyth</surname>
<given-names>L. J.</given-names>
</name>
<name>
<surname>McKay</surname>
<given-names>G. J.</given-names>
</name>
<name>
<surname>Maxwell</surname>
<given-names>A. P.</given-names>
</name>
<name>
<surname>McKnight</surname>
<given-names>A. J.</given-names>
</name>
</person-group> (<year>2014</year>). <article-title>DNA hypermethylation and DNA hypomethylation is present at different loci in chronic kidney disease</article-title>. <source>Epigenetics</source> <volume>9</volume>, <fpage>366</fpage>&#x2013;<lpage>376</lpage>. <pub-id pub-id-type="doi">10.4161/epi.27161</pub-id>
</citation>
</ref>
<ref id="B36">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Stenvinkel</surname>
<given-names>P.</given-names>
</name>
<name>
<surname>Karimi</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Johansson</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Axelsson</surname>
<given-names>J.</given-names>
</name>
<name>
<surname>Suliman</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Lindholm</surname>
<given-names>B.</given-names>
</name>
<etal/>
</person-group> (<year>2007</year>). <article-title>Impact of inflammation on epigenetic DNA methylation &#x2013; a novel risk factor for cardiovascular disease?</article-title> <source>J. Intern. Med.</source> <volume>261</volume>, <fpage>488</fpage>&#x2013;<lpage>499</lpage>. <pub-id pub-id-type="doi">10.1111/j.1365-2796.2007.01777.x</pub-id>
</citation>
</ref>
<ref id="B37">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Sur</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Kerwin</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Pineda</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Sansanwal</surname>
<given-names>P.</given-names>
</name>
<name>
<surname>Sigdel</surname>
<given-names>T. K.</given-names>
</name>
<name>
<surname>Sirota</surname>
<given-names>M.</given-names>
</name>
<etal/>
</person-group> (<year>2024</year>). <article-title>Novel mechanism for tubular injury in nephropathic cystinosis</article-title>. <source>Elife</source>. <pub-id pub-id-type="doi">10.7554/eLife.94169.1</pub-id>
</citation>
</ref>
<ref id="B38">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Tampe</surname>
<given-names>B.</given-names>
</name>
<name>
<surname>Tampe</surname>
<given-names>D.</given-names>
</name>
<name>
<surname>M&#xfc;ller</surname>
<given-names>C. A.</given-names>
</name>
<name>
<surname>Sugimoto</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>LeBleu</surname>
<given-names>V.</given-names>
</name>
<name>
<surname>Xu</surname>
<given-names>X.</given-names>
</name>
<etal/>
</person-group> (<year>2014</year>). <article-title>Tet3-Mediated hydroxymethylation of epigenetically silenced genes contributes to bone morphogenic protein 7-Induced reversal of kidney fibrosis</article-title>. <source>J. Am. Soc. Nephrol.</source> <volume>25</volume>, <fpage>905</fpage>&#x2013;<lpage>912</lpage>. <pub-id pub-id-type="doi">10.1681/ASN.2013070723</pub-id>
</citation>
</ref>
<ref id="B39">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Tampe</surname>
<given-names>B.</given-names>
</name>
<name>
<surname>Tampe</surname>
<given-names>D.</given-names>
</name>
<name>
<surname>Zeisberg</surname>
<given-names>E. M.</given-names>
</name>
<name>
<surname>M&#xfc;ller</surname>
<given-names>G. A.</given-names>
</name>
<name>
<surname>Bechtel-Walz</surname>
<given-names>W.</given-names>
</name>
<name>
<surname>Koziolek</surname>
<given-names>M.</given-names>
</name>
<etal/>
</person-group> (<year>2015</year>). <article-title>Induction of Tet3-dependent epigenetic remodeling by low-dose hydralazine attenuates progression of chronic kidney disease</article-title>. <source>EBioMedicine</source> <volume>2</volume>, <fpage>19</fpage>&#x2013;<lpage>36</lpage>. <pub-id pub-id-type="doi">10.1016/j.ebiom.2014.11.005</pub-id>
</citation>
</ref>
<ref id="B40">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Tampe</surname>
<given-names>B.</given-names>
</name>
<name>
<surname>Steinle</surname>
<given-names>U.</given-names>
</name>
<name>
<surname>Tampe</surname>
<given-names>D.</given-names>
</name>
<name>
<surname>Carstens</surname>
<given-names>J. L.</given-names>
</name>
<name>
<surname>Korsten</surname>
<given-names>P.</given-names>
</name>
<name>
<surname>Zeisberg</surname>
<given-names>E. M.</given-names>
</name>
<etal/>
</person-group> (<year>2017</year>). <article-title>Low-dose hydralazine prevents fibrosis in a murine model of acute kidney injury&#x2013;to&#x2013;chronic kidney disease progression</article-title>. <source>Kidney Int.</source> <volume>91</volume>, <fpage>157</fpage>&#x2013;<lpage>176</lpage>. <pub-id pub-id-type="doi">10.1016/j.kint.2016.07.042</pub-id>
</citation>
</ref>
<ref id="B41">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Vaisbich</surname>
<given-names>M. H.</given-names>
</name>
<name>
<surname>Pache De Faria Guimaraes</surname>
<given-names>L.</given-names>
</name>
<name>
<surname>Shimizu</surname>
<given-names>M. H. M.</given-names>
</name>
<name>
<surname>Seguro</surname>
<given-names>A. C.</given-names>
</name>
</person-group> (<year>2011</year>). <article-title>Oxidative stress in cystinosis patients</article-title>. <source>Nephron Extra</source> <volume>1</volume>, <fpage>73</fpage>&#x2013;<lpage>77</lpage>. <pub-id pub-id-type="doi">10.1159/000331445</pub-id>
</citation>
</ref>
<ref id="B42">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Wanner</surname>
<given-names>N.</given-names>
</name>
<name>
<surname>Bechtel-Walz</surname>
<given-names>W.</given-names>
</name>
</person-group> (<year>2017</year>). <article-title>Epigenetics of kidney disease</article-title>. <source>Cell Tissue Res.</source> <volume>369</volume>, <fpage>75</fpage>&#x2013;<lpage>92</lpage>. <pub-id pub-id-type="doi">10.1007/s00441-017-2588-x</pub-id>
</citation>
</ref>
<ref id="B43">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Wilmer</surname>
<given-names>M. J. G.</given-names>
</name>
<name>
<surname>De Graaf-Hess</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Blom</surname>
<given-names>H. J.</given-names>
</name>
<name>
<surname>Dijkman</surname>
<given-names>H. B. P. M.</given-names>
</name>
<name>
<surname>Monnens</surname>
<given-names>L. A.</given-names>
</name>
<name>
<surname>Van Den Heuvel</surname>
<given-names>L. P.</given-names>
</name>
<etal/>
</person-group> (<year>2005</year>). <article-title>Elevated oxidized glutathione in cystinotic proximal tubular epithelial cells</article-title>. <source>Biochem. Biophys. Res. Commun.</source> <volume>337</volume>, <fpage>610</fpage>&#x2013;<lpage>614</lpage>. <pub-id pub-id-type="doi">10.1016/j.bbrc.2005.09.094</pub-id>
</citation>
</ref>
<ref id="B44">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Xu</surname>
<given-names>Z.</given-names>
</name>
<name>
<surname>Xie</surname>
<given-names>C.</given-names>
</name>
<name>
<surname>Taylor</surname>
<given-names>J. A.</given-names>
</name>
<name>
<surname>Niu</surname>
<given-names>L.</given-names>
</name>
</person-group> (<year>2021</year>). <article-title>ipDMR: identification of differentially methylated regions with interval <italic>P</italic> -values</article-title>. <source>Bioinformatics</source> <volume>37</volume>, <fpage>711</fpage>&#x2013;<lpage>713</lpage>. <pub-id pub-id-type="doi">10.1093/bioinformatics/btaa732</pub-id>
</citation>
</ref>
<ref id="B45">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Yan</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Liu</surname>
<given-names>H.</given-names>
</name>
<name>
<surname>Abedini</surname>
<given-names>A.</given-names>
</name>
<name>
<surname>Sheng</surname>
<given-names>X.</given-names>
</name>
<name>
<surname>Palmer</surname>
<given-names>M.</given-names>
</name>
<name>
<surname>Li</surname>
<given-names>H.</given-names>
</name>
<etal/>
</person-group> (<year>2024</year>). <article-title>Unraveling the epigenetic code: human kidney DNA methylation and chromatin dynamics in renal disease development</article-title>. <source>Nat. Commun.</source> <volume>15</volume>, <fpage>873</fpage>. <pub-id pub-id-type="doi">10.1038/s41467-024-45295-y</pub-id>
</citation>
</ref>
<ref id="B46">
<citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname>Zhang</surname>
<given-names>L.</given-names>
</name>
<name>
<surname>Zhang</surname>
<given-names>Q.</given-names>
</name>
<name>
<surname>Liu</surname>
<given-names>S.</given-names>
</name>
<name>
<surname>Chen</surname>
<given-names>Y.</given-names>
</name>
<name>
<surname>Li</surname>
<given-names>R.</given-names>
</name>
<name>
<surname>Lin</surname>
<given-names>T.</given-names>
</name>
<etal/>
</person-group> (<year>2017</year>). <article-title>DNA methyltransferase 1 may be a therapy target for attenuating diabetic nephropathy and podocyte injury</article-title>. <source>Kidney Int.</source> <volume>92</volume>, <fpage>140</fpage>&#x2013;<lpage>153</lpage>. <pub-id pub-id-type="doi">10.1016/j.kint.2017.01.010</pub-id>
</citation>
</ref>
</ref-list>
</back>
</article>