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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Aging Neurosci.</journal-id>
<journal-title>Frontiers in Aging Neuroscience</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Aging Neurosci.</abbrev-journal-title>
<issn pub-type="epub">1663-4365</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fnagi.2021.745046</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Neuroscience</subject>
<subj-group>
<subject>Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>The Potential of Ferroptosis-Targeting Therapies for Alzheimer&#x2019;s Disease: From Mechanism to Transcriptomic Analysis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Majern&#x00ED;kov&#x00E1;</surname> <given-names>Nad&#x2019;a</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1455702/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>den Dunnen</surname> <given-names>Wilfred F. A.</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1573478/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Dolga</surname> <given-names>Amalia M.</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/30978/overview"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Research School of Behavioural and Cognitive Neuroscience, University of Groningen</institution>, <addr-line>Groningen</addr-line>, <country>Netherlands</country></aff>
<aff id="aff2"><sup>2</sup><institution>Department of Pathology and Medical Biology, University Medical Centre Groningen, University of Groningen</institution>, <addr-line>Groningen</addr-line>, <country>Netherlands</country></aff>
<aff id="aff3"><sup>3</sup><institution>Department of Molecular Pharmacology, Groningen Research Institute of Pharmacy, University of Groningen</institution>, <addr-line>Groningen</addr-line>, <country>Netherlands</country></aff>
<aff id="aff4"><sup>4</sup><institution>Research Institute Brain and Cognition, Molecular Neuroscience and Aging Research (MOLAR), University Medical Centre Groningen</institution>, <addr-line>Groningen</addr-line>, <country>Netherlands</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Anne Eckert, University Psychiatric Clinic Basel, Switzerland</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Mitsuru Shinohara, National Center for Geriatrics and Gerontology (NCGG), Japan; Jeff Liddell, The University of Melbourne, Australia</p></fn>
<corresp id="c001">&#x002A;Correspondence: Amalia M. Dolga, <email>a.m.dolga@rug.nl</email></corresp>
<fn fn-type="other" id="fn004"><p>This article was submitted to Alzheimer&#x2019;s Disease and Related Dementias, a section of the journal Frontiers in Aging Neuroscience</p></fn>
</author-notes>
<pub-date pub-type="epub">
<day>20</day>
<month>12</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>13</volume>
<elocation-id>745046</elocation-id>
<history>
<date date-type="received">
<day>21</day>
<month>07</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>18</day>
<month>11</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2021 Majern&#x00ED;kov&#x00E1;, den Dunnen and Dolga.</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Majern&#x00ED;kov&#x00E1;, den Dunnen and Dolga</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p></license>
</permissions>
<abstract>
<p>Alzheimer&#x2019;s disease (AD), the most common form of dementia, currently affects 40&#x2013;50 million people worldwide. Despite the extensive research into amyloid &#x03B2; (A&#x03B2;) deposition and tau protein hyperphosphorylation (p-tau), an effective treatment to stop or slow down the progression of neurodegeneration is missing. Emerging evidence suggests that ferroptosis, an iron-dependent and lipid peroxidation-driven type of programmed cell death, contributes to neurodegeneration in AD. Therefore, how to intervene against ferroptosis in the context of AD has become one of the questions addressed by studies aiming to develop novel therapeutic strategies. However, the underlying molecular mechanism of ferroptosis in AD, when ferroptosis occurs in the disease course, and which ferroptosis-related genes are differentially expressed in AD remains to be established. In this review, we summarize the current knowledge on cell mechanisms involved in ferroptosis, we discuss how these processes relate to AD, and we analyze which ferroptosis-related genes are differentially expressed in AD brain dependant on cell type, disease progression and gender. In addition, we point out the existing targets for therapeutic options to prevent ferroptosis in AD. Future studies should focus on developing new tools able to demonstrate where and when cells undergo ferroptosis in AD brain and build more translatable AD models for identifying anti-ferroptotic agents able to slow down neurodegeneration.</p>
</abstract>
<kwd-group>
<kwd>neurodegeneration</kwd>
<kwd>iron dysregulation</kwd>
<kwd>glutathione</kwd>
<kwd>lipid peroxidation</kwd>
<kwd>amyloid &#x03B2;</kwd>
</kwd-group>
<contract-sponsor id="cn001">Alzheimer Nederland<named-content content-type="fundref-id">10.13039/501100010969</named-content></contract-sponsor>
<contract-sponsor id="cn002">Universitair Medisch Centrum Groningen<named-content content-type="fundref-id">10.13039/501100005075</named-content></contract-sponsor>
<contract-sponsor id="cn003">Rijksuniversiteit Groningen<named-content content-type="fundref-id">10.13039/501100001721</named-content></contract-sponsor>
<counts>
<fig-count count="2"/>
<table-count count="4"/>
<equation-count count="0"/>
<ref-count count="148"/>
<page-count count="14"/>
<word-count count="11548"/>
</counts>
</article-meta>
</front>
<body>
<sec id="S1" sec-type="intro">
<title>Introduction</title>
<p>Alzheimer&#x2019;s disease (AD) is the most prevalent age-related neurodegenerative disorder, affecting over 44 million people worldwide (<xref ref-type="bibr" rid="B47">Gaugler et al., 2016</xref>). In AD, formation of amyloid &#x03B2; (A&#x03B2;) plaques and neurofibrillary tangles (NFTs) are associated with progressive cortical and hippocampal neuronal dysfunction and death (<xref ref-type="bibr" rid="B37">Dugger and Dickson, 2017</xref>). Many cell death mechanisms have been studied in AD pathology. The aggregation of A&#x03B2; was linked with caspase-9 and caspase-3-dependant apoptosis in neurons (<xref ref-type="bibr" rid="B104">Obulesu and Lakshmi, 2014</xref>), autophagy deficiency (<xref ref-type="bibr" rid="B86">Li and Sun, 2017</xref>), necrosis (<xref ref-type="bibr" rid="B125">Tanaka et al., 2020</xref>) and microglia-dependant activation of inflammasome pathway (<xref ref-type="bibr" rid="B60">Heneka et al., 2018</xref>). Despite extensive research into main hallmarks and molecular pathways of cell death in AD, many degenerative processes cannot be explained by these mechanisms alone, resulting in failure of over 200 AD drugs trials aiming at these targets over the past decade (<xref ref-type="bibr" rid="B138">Yiannopoulou et al., 2019</xref>).</p>
<p>In addition to apoptosis and necrosis, ferroptosis, an iron dependent and lipid-peroxidation driven cell death (<xref ref-type="bibr" rid="B32">Dixon, 2017</xref>), seems to be associated with AD (<xref ref-type="bibr" rid="B58">Hambright et al., 2017</xref>). Ferroptosis, the process increasing with aging (<xref ref-type="bibr" rid="B146">Zhou et al., 2020</xref>), is morphologically, genetically, and biochemically different from other types of cell death (<xref ref-type="bibr" rid="B33">Dixon et al., 2012</xref>). Its hallmarks, such as increased iron levels and oxidative stress, have been long noted in the AD brain (<xref ref-type="bibr" rid="B109">Pratic&#x00F2; et al., 2001</xref>; <xref ref-type="bibr" rid="B108">Pratic&#x00F2; and Sung, 2004</xref>; <xref ref-type="bibr" rid="B19">Castellani et al., 2007</xref>; <xref ref-type="bibr" rid="B30">Derry et al., 2020</xref>). It has been shown that formation of A&#x03B2; plaques and NFTs is related to iron overload in AD models and post mortem tissue (<xref ref-type="bibr" rid="B135">Yamamoto et al., 2002</xref>; <xref ref-type="bibr" rid="B105">Peters et al., 2018</xref>). Moreover, iron levels positively correlate with cognitive decline in human subjects (<xref ref-type="bibr" rid="B11">Ayton et al., 2017</xref>), and glutathione peroxidase (GPx4, also known as GPX4), the critical regulator of ferroptosis, is protective in AD mice model (<xref ref-type="bibr" rid="B139">Yoo et al., 2010</xref>).</p>
<p>Human genome-wide association studies (GWAS) support these results by showing a relation between the risk of developing AD and <italic>GPX4</italic> polymorphism (<xref ref-type="bibr" rid="B73">Karch et al., 2016</xref>; <xref ref-type="bibr" rid="B27">da Rocha et al., 2018</xref>). Moreover, <italic>PSEN1/2</italic> mutations identified in Alzheimer patients affected the hypoxic response in mouse embryonic fibroblasts by regulating hypoxia inducible factor-1&#x03B1; (HIF-1&#x03B1;), a driver of vulnerability to ferroptosis in cancer (<xref ref-type="bibr" rid="B74">Kaufmann et al., 2013</xref>; <xref ref-type="bibr" rid="B148">Zou et al., 2019</xref>). These results suggest that higher risk of developing AD is associated with deregulation of ferroptosis-related proteins, and thus ferroptosis inhibitors may have a therapeutic potential in AD (<xref ref-type="bibr" rid="B133">Weiland et al., 2019</xref>). However, the underlying mechanism of ferroptosis in AD, and whether ferroptosis happens at the onset, during or as a consequence of AD remains to be established.</p>
<p>Our aim is to examine the potential of ferroptosis inhibition as a therapeutic strategy for AD. We will first recapitulate ferroptosis pathway and its relation to AD, identify which ferroptosis-related genes are differentially expressed in AD and lastly, discuss the therapeutic options to prevent ferroptosis in AD.</p>
</sec>
<sec id="S2">
<title>Processes Involved in the Underlying Pathway of Ferroptosis</title>
<p>Ferroptosis mechanism can be divided into three parts: (1) iron homeostasis, (2) glutathione (GSH) metabolism and (3) oxidative stress and lipid peroxidation (<xref ref-type="fig" rid="F1">Figure 1</xref>). Disruption of one or more of these mechanisms can induce lipid peroxidation-driven ferroptotic cell death.</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption><p>Molecular mechanisms of ferroptotic cell death. Metabolic pathways such as iron metabolism (left), cysteine and glutathione metabolism (top right), and polyunsaturated fatty acid metabolism (bottom right) play an essential role in the ferroptotic pathway. Well established ferroptosis inducers and inhibitors and their mode of action are depicted in red and green respectively. BSO, Buthionine sulphoximine; DFO, Deferoxamine; DFP, Deferiprone; Fe2 +, Ferrous iron; Fe3 +, Ferric iron; FPN1, Ferroportin; GPx4, Glutathione peroxidase 4; GSH, Glutathione (reduced glutathione form); GS-SG, Glutathione disulfide (oxidized glutathione form); Keap1, Kelch-like ECH-associated protein 1, LOX, Lipoxygenase; NCOA4, Nuclear receptor co-activator 4; NFE2L2, nuclear factor E2 related factor 2 encoding for Nrf2; PL-PUFA(PE)-OH, Polyunsaturated-fatty-acids (phosphatidylethanolamine)-reduced; PL-PUFA(PE)-OOH, Polyunsaturated-fatty-acid-containing-phospholipid hydroperoxides; ROS, Reactive oxygen species; RSL3, (1S,3R)-methyl-2-(2-chloroacetyl)-2,3,4,9-tetrahydro-1-[4-(methoxycarbonyl)phenyl]-1H-pyrido [3,4-b]indole-3-carboxylic acid; RTAs, Radical-trapping antioxidants; Se, Selenocysteine; STEAP3, Six-Transmembrane Epithelial Antigen Of Prostate 3; xCT subunit of system x<sub>c</sub><sup>&#x2013;</sup>, Glutamate/cystine antiporter system; TfR1, Transferrin 1 receptor; Vit E, Vitamin E; &#x03B3;-GCS, Gamma-glutamylcysteine synthetase. This figure was created using Biorender.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fnagi-13-745046-g001.tif"/>
</fig>
<sec id="S2.SS1">
<title>Iron Homeostasis</title>
<p>Iron homeostasis plays a key role in ferroptosis (<xref ref-type="bibr" rid="B136">Yan and Zhang, 2020</xref>). Iron can enter the cell via transferrin 1 receptor (TfR1, also known as TFR1) and be reduced from ferric (Fe<sup>3+</sup>) to ferrous (Fe<sup>2+</sup>) form via metalloreductase STEAP3 in the endosome (<xref ref-type="bibr" rid="B141">Zhang et al., 2012</xref>). In this form, iron can be stored in ferritin, or exported from the cell via ferroportin (FPN1) (<xref ref-type="bibr" rid="B20">Chang, 2019</xref>). Ferritin degradation via the nuclear receptor coactivator 4 (NCOA4) contributes to ferroptosis by increasing the free intracellular iron levels (<xref ref-type="bibr" rid="B63">Hou et al., 2016</xref>). Excessive intracellular iron accumulation can lead to generation of reactive oxygen species (ROS) and oxidative stress via the Fenton reaction (<xref ref-type="bibr" rid="B132">Ward et al., 2014</xref>). Iron accumulation-induced ROS, such as superoxide anion (O<sub>2</sub>-&#x2022;) and hydroxyl radical (&#x2022;OH), possess an unpaired electron at their outer orbit which allows them to react with all cellular components including proteins, lipids and nucleic acid. This results in lipid peroxidation, oxidative damage to membranes and other lipid-containing molecules, and ultimately to cellular damage and ferroptotic cell death (<xref ref-type="bibr" rid="B8">Aprioku, 2013</xref>).</p>
</sec>
<sec id="S2.SS2">
<title>Glutathione Metabolism</title>
<p>On the other hand, inhibition of glutamate/cystine antiporter (system x<sub>c</sub><sup>&#x2013;</sup>, xc-, with xCT as the functional subunit of system x<sub>c</sub><sup>&#x2013;</sup>) and depletion of GSH cause inactivation of GPx4, the critical antioxidant enzyme and regulator of ferroptosis (<xref ref-type="bibr" rid="B114">Seibt et al., 2019</xref>). This can lead to ferroptotic cell death through increased lipid peroxidation and accumulation of ROS (<xref ref-type="bibr" rid="B130">Wang et al., 2020</xref>). GPx4 reduces hydroperoxides of polyunsaturated-fatty-acid-containing-phospholipids (PL-PUFA(PE)-OOH) to polyunsaturated-fatty-acids (phosphatidylethanol amine)-reduced (PL-PUFA(PE)-OH) (<xref ref-type="bibr" rid="B114">Seibt et al., 2019</xref>). GPx4 uses GSH as a reducing substrate and converts it into oxidized form, also referred to as glutathione disulphide (GS-SG) (<xref ref-type="bibr" rid="B24">Cozza et al., 2017</xref>). Apart from nuclear factor erythroid 2-related factor 2 (Nrf2, coded by <italic>NFE2L2</italic> gene) (<xref ref-type="bibr" rid="B57">Habib et al., 2015</xref>), the xCT mRNA can be positively regulated by the activation of transcription factor 4 (ATF4) under oxidative stress (<xref ref-type="bibr" rid="B112">Sato et al., 2004</xref>), while its negative regulation by p53 results in cysteine deprivation and increased susceptibility to ferroptosis (<xref ref-type="bibr" rid="B68">Jiang et al., 2015</xref>).</p>
</sec>
<sec id="S2.SS3">
<title>Oxidative Stress and Lipid Peroxidation</title>
<p>Oxidative stress occurs due to the imbalance between generation of free radicals and the ability to neutralize or eliminate them through antioxidants (<xref ref-type="bibr" rid="B14">Birben et al., 2012</xref>). One of the main drivers of ferroptosis is ROS-mediated lipid peroxidation, which can result in oxidative stress (<xref ref-type="bibr" rid="B79">Kuang et al., 2020</xref>). Inhibition of GPx4 and decrease in GSH levels lead to activation of 12/15-lipoxygenase (12/15-LOX, which is the protein product of the ALOX15 gene). The association of Fe<sup>2+</sup> with lipoxygenases (LOX, a dioxygenase containing non-heme iron) can lead to oxygenation of polyunsaturated-fatty-acids (PUFA), such as arachidonic acid present in phospholipids, and trigger lipid peroxidation-induced ferroptosis (<xref ref-type="bibr" rid="B71">Kagan et al., 2017</xref>). The LOX nomenclature is defined by the specific site of their oxygenation product: in humans there are six LOX isoforms 15-LOX-1, 15-LOX-2, 12-LOX-1, 12-LOX-2, E3-LOX, and 5-LOX, of which 12/15-LOX (15-LOX) are the most abundant. 12/15-LOX are considered as one of the key regulators of ferroptotic cell death (<xref ref-type="bibr" rid="B137">Yang et al., 2016</xref>; <xref ref-type="bibr" rid="B71">Kagan et al., 2017</xref>). Although, this has been supported by the findings that pharmacological inhibition of 15-LOX-1 exerts a cytoprotective effect (<xref ref-type="bibr" rid="B115">Seiler et al., 2008</xref>; <xref ref-type="bibr" rid="B39">Eleftheriadis et al., 2016</xref>), some off-target effects of lipoxygenase inhibitors have also been reported (<xref ref-type="bibr" rid="B116">Shah et al., 2018</xref>).</p>
<p>In addition to iron accumulation-induced generation of ROS, mitochondria also contribute to ROS production. Electrons leak from complex I and III of the electron transport chain (ETC) located on the inner membrane of mitochondria (<xref ref-type="bibr" rid="B144">Zhao et al., 2019</xref>). This can result in the formation of ROS such as O<sub>2</sub>-&#x2022; and hydrogen peroxides (H<sub>2</sub>O<sub>2</sub>), and potentially can lead to loss of mitochondrial membrane potential (&#x0394;&#x03A8;m) (<xref ref-type="bibr" rid="B46">Gao et al., 2019</xref>). Reduced &#x0394;&#x03A8;m was associated with ferroptosis and involves different regulatory mechanisms than apoptosis (<xref ref-type="bibr" rid="B79">Kuang et al., 2020</xref>). GSH depletion-induced activation of 12/15-LOX can increase cytosolic Ca<sup>2+</sup> via both (1) the import from the extracellular compartment and (2) release from mitochondria and endoplasmic reticulum (<xref ref-type="bibr" rid="B90">Maher et al., 2018</xref>). Decrease in GSH levels can also lead to dysregulation of Ca<sup>2+</sup> transport in and out of mitochondria by voltage dependant anion channels (VDAC) and mitochondrial Ca<sup>2+</sup> uniporter (MCU) (<xref ref-type="bibr" rid="B147">Zorov et al., 2014</xref>; <xref ref-type="bibr" rid="B28">DeHart et al., 2018</xref>). This results in mitochondrial Ca<sup>2+</sup> overload and collapse of the mitochondrial function which activates Ca<sup>2+</sup>-dependant proteases (<xref ref-type="bibr" rid="B147">Zorov et al., 2014</xref>; <xref ref-type="bibr" rid="B28">DeHart et al., 2018</xref>; <xref ref-type="bibr" rid="B93">Marmolejo-Garza and Dolga, 2021</xref>). Consequently, ROS-induced transactivation of BH3 interacting-domain death agonist (BID) to mitochondria and Ca<sup>2+</sup>overload-induced translocation of apoptosis-inducing factor (AIF) from mitochondria to the nucleus causes the cell to die (<xref ref-type="bibr" rid="B102">Neitemeier et al., 2017</xref>). This caspase-independent process is accompanied by mitochondrial fragmentation and enlarged cristae (<xref ref-type="bibr" rid="B33">Dixon et al., 2012</xref>). The rescue of mitochondria (<xref ref-type="bibr" rid="B66">Jelinek et al., 2018</xref>), decrease of mitochondria-associated endoplasmic reticulum membranes (MAMs) interaction (<xref ref-type="bibr" rid="B55">Guo et al., 2019</xref>) and small conductance calcium-activated potassium (K<sub>Ca</sub>2/SK) channel activation have the potential to protect from ferroptotic cell death (<xref ref-type="bibr" rid="B78">Krabbendam et al., 2020</xref>).</p>
</sec>
</sec>
<sec id="S3">
<title>Contributions of Ferroptosis to Alzheimer&#x2019;s Disease</title>
<sec id="S3.SS1">
<title>Iron Homeostasis</title>
<p>Advanced age is associated with iron dysregulation affecting most of our organs (<xref ref-type="bibr" rid="B134">Xu et al., 2012</xref>; <xref ref-type="bibr" rid="B106">Picca et al., 2019</xref>). Many studies show that iron dysregulation can also contribute to AD pathology (<xref ref-type="bibr" rid="B18">Bush, 2013</xref>; <xref ref-type="bibr" rid="B103">Nu&#x00F1;ez and Chana-Cuevas, 2018</xref>). With aging, iron deposits in the brain (<xref ref-type="bibr" rid="B1">Acosta-Cabronero et al., 2016</xref>), which can increase the formation of A&#x03B2; plaques (<xref ref-type="bibr" rid="B13">Becerril-Ortega et al., 2014</xref>) and tau hyperphosphorylation in AD transgenic mouse brain (<xref ref-type="bibr" rid="B53">Guo et al., 2013</xref>). Imaging and histological experiments support this by showing increased iron deposition in AD-specific brain regions (<xref ref-type="bibr" rid="B5">Altamura and Muckenthaler, 2009</xref>; <xref ref-type="bibr" rid="B18">Bush, 2013</xref>; <xref ref-type="bibr" rid="B7">Apostolakis and Kypraiou, 2017</xref>; <xref ref-type="bibr" rid="B84">Lee and Lee, 2019</xref>). Magnetic resonance imaging (MRI) studies revealed increased iron levels in the putamen, pulvinar thalamus, red nucleus, hippocampus, and temporal cortex of AD patients (<xref ref-type="bibr" rid="B81">Langkammer et al., 2014</xref>). Later, quantitative susceptibility mapping showed higher iron levels in caudate and putamen nucleus of AD patients than in controls. Interestingly, the increased iron level in the left caudate nucleus correlated with the degree of cognitive impairment (<xref ref-type="bibr" rid="B36">Du et al., 2018</xref>). Finally, higher iron levels in the frontal cortex were associated with AD severity (<xref ref-type="bibr" rid="B16">Bulk et al., 2018b</xref>). This evidence suggested that iron contributes to AD pathology and presented an important avenue for therapy development (<xref ref-type="bibr" rid="B94">Masaldan et al., 2019</xref>).</p>
</sec>
<sec id="S3.SS2">
<title>Glutathione Metabolism</title>
<p>Ferroptosis can be induced by compounds interfering with system x<sub>c</sub><sup>&#x2013;</sup>, such as erastin, which induces cysteine deprivation, GSH depletion, endoplasmic reticulum stress, and cell death (<xref ref-type="bibr" rid="B33">Dixon et al., 2012</xref>, <xref ref-type="bibr" rid="B34">2014</xref>; <xref ref-type="bibr" rid="B113">Sato et al., 2018</xref>). System x<sub><italic>c</italic></sub><sup>&#x2013;</sup> can also be inhibited by adding small concentrations of sorafenib (<xref ref-type="bibr" rid="B80">Lachaier et al., 2014</xref>), glutamate (<xref ref-type="bibr" rid="B69">Jiang et al., 2020</xref>) and sulfasalazine (<xref ref-type="bibr" rid="B140">Yu et al., 2019</xref>) to the extracellular compartment. Inhibition of gamma-glutamylcysteine synthetase (&#x03B3;<italic>-</italic>GCS) by buthionine sulphoximine (BSO) results in GSH depletion and can lead to ferroptosis (<xref ref-type="bibr" rid="B50">Griffith, 1982</xref>). Irreversible and direct inhibition of GPx4 by the (1S,3R)-RSL3 (RSL3), causes the production of polyunsaturated-fatty-acid-containing-phospholipid hydroperoxides, which leads to lipid peroxidation and ferroptotic cell death (<xref ref-type="bibr" rid="B87">Liang et al., 2019</xref>). In addition to pharmacological compounds, genetic modifications targeting regulators of the system x<sub>c</sub><sup>&#x2013;</sup> can induce ferroptosis. The <italic>Gpx4</italic>BI-KO mouse was generated by a conditional deletion of <italic>Gpx4</italic> in forebrain neurons by administration of tamoxifen. In this mouse model, 75&#x2013;85% decrease of <italic>Gpx4</italic> was shown to induce hippocampal neuronal loss, lipid peroxidation, neuroinflammation and spatial learning deficits (<xref ref-type="bibr" rid="B58">Hambright et al., 2017</xref>). Similarly, the knockout of <italic>Gpx1</italic>, facilitated memory impairment induced by &#x03B2;-Amyloid in mice (<xref ref-type="bibr" rid="B70">Joo et al., 2020</xref>). The Western blot analysis of AD post mortem brain tissue revealed enhanced expression of the light-chain subunit of the xCT (<xref ref-type="bibr" rid="B9">Ashraf et al., 2020</xref>). These results suggest that impaired GSH metabolism might play a role in ferroptosis during AD pathology (<xref ref-type="bibr" rid="B9">Ashraf et al., 2020</xref>).</p>
</sec>
<sec id="S3.SS3">
<title>Oxidative Stress and Lipid Peroxidation</title>
<p>The brain is the most vulnerable organ to oxidative stress. It represents only 2% of the body but uses 20% of the total oxygen supply (<xref ref-type="bibr" rid="B117">Sokoloff, 1999</xref>). Oxidative stress plays a key role in AD pathology by initiating the generation and enhancing of both A&#x03B2; plaques and hyperphosphorylation of Tau (p-Tau) (<xref ref-type="bibr" rid="B64">Huang et al., 2016</xref>; <xref ref-type="bibr" rid="B101">Nassireslami et al., 2016</xref>). Oxidative stress can be enhanced in AD via metal accumulation. In addition to iron, the A&#x03B2; precursor protein (APP) has a high affinity to binding zinc and copper at the N terminal metal-binding sites (<xref ref-type="bibr" rid="B12">Barnham et al., 2003</xref>). Additionally, high concentrations of these metals were also found in A&#x03B2; plaques in mouse and human brain (<xref ref-type="bibr" rid="B107">Plascencia-Villa et al., 2016</xref>; <xref ref-type="bibr" rid="B65">James et al., 2017</xref>). As copper is the potent mediator of &#x2022;OH, and the binding of zinc leads to production of toxic A&#x03B2; and further uncontrolled zinc release, these metals can contribute to the increase of oxidative stress in AD (<xref ref-type="bibr" rid="B122">Strozyk et al., 2009</xref>). Post mortem tissue from AD patients shows higher levels of oxidized bases in the frontal, parietal and temporal lobes compared to control subjects (<xref ref-type="bibr" rid="B129">Wang et al., 2005</xref>), which correlates with imbalanced levels of copper, zinc and iron (<xref ref-type="bibr" rid="B29">Deibel et al., 1996</xref>). Other studies have shown higher level of lipid peroxidation, in diseased regions of AD brain compared to controls (<xref ref-type="bibr" rid="B99">Montine et al., 1998</xref>; <xref ref-type="bibr" rid="B89">Lovell et al., 2001</xref>; <xref ref-type="bibr" rid="B15">Bradley-Whitman and Lovell, 2015</xref>). These results support that oxidative stress might be an important factor contributing to the development and progression of AD (<xref ref-type="bibr" rid="B145">Zhao and Zhao, 2013</xref>).</p>
</sec>
</sec>
<sec id="S4">
<title>Differential Expression of Ferroptosis-Related Genes in Alzheimer&#x2019;s Disease</title>
<p>Many AD differentially expressed genes (DEGs) have been identified in animal and human studies. Using available RNAseq datasets of AD mouse models, AD patients and age-matched controls, we analyzed which of the 44 ferroptosis-related genes are differentially expressed in AD (<xref ref-type="supplementary-material" rid="S11">Supplementary Table 1</xref>). To this end, we analyzed the expression of ferroptosis-related genes in one mouse [Alzmap (<xref ref-type="bibr" rid="B21">Chen et al., 2020</xref>)] and three human datasets of AD-DEGs [scREAD (<xref ref-type="bibr" rid="B95">Mathys et al., 2019</xref>), ACTA (<xref ref-type="bibr" rid="B48">Gerrits et al., 2021</xref>), AMPA-AD (<xref ref-type="bibr" rid="B127">Wan et al., 2020</xref>)]. All four datasets were available to the public and compared the gene expression between cell types, stages of disease progression and gender.</p>
<p>We first used the Alzmap gene retrieving function to make a qualitative assessment of the expression of three representative ferroptosis-related genes. We included (i) <italic>Gpx4</italic>, as it can suppress phospholipid peroxidation, an important process during ferroptosis, (ii) <italic>Gss</italic>, as it can facilitate the production of GSH, and (iii) <italic>Acsl4</italic> for its role in supporting the incorporation of long PUFAs into lipid membranes, a process associated with ferroptosis (<xref ref-type="fig" rid="F2">Figure 2</xref>). We choose t-distributed stochastic neighbor embedding (TSNE) statistical method to visualize the representative genes in a high-dimensional dataset (<xref ref-type="fig" rid="F2">Figure 2</xref>). However, Alzmap website offers other modes of analysis and visualization tools such as the principal component analysis (PCA) and uniform manifold approximation and projections for dimension reduction (UMAP). The distribution and visualization of the chosen genes might render different output since these methods of visualization and reduction tools are based on specific clustering algorithms, i.e., unsupervised linear dimensionality reduction and data visualization technique for very high dimensional data for PCA, while t-SNE is based on a non-linear statistical method, calculating the similarity probability score in a low dimensional space. Therefore, visualization of genes could appear to render various outcomes. The alterations observed in the ferroptosis-related genes generated by Alzmap are purely based on a qualitative assessment. These data can be freely accessible on the <ext-link ext-link-type="uri" xlink:href="https://alzmap.org/website">https://alzmap.org/website</ext-link>.</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption><p>Differential expression of ferroptosis related genes in AD mice model compared to WT mice. Heatmap representing the difference in expression of ferroptosis-related genes between 18 months old WT (orange) and AD mice (light blue) <bold>(A)</bold>. The heatmap depicts gene expression from low/white to high/dark blue. Each point indicates one spatial transcriptomic spot defining one tissue domain on the slide. Glutathione peroxidase 4 (Gpx4) is upregulated with pathology <bold>(B)</bold>, while glutathione synthase (Gss) <bold>(C)</bold> and acyl-CoA synthetase long-chain family member (Acsl4) <bold>(D)</bold> are downregulated with the pathology. This data is freely accessible online, Alzmap (<xref ref-type="bibr" rid="B21">Chen et al., 2020</xref>).</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fnagi-13-745046-g002.tif"/>
</fig>
<p>In the Alzmap study, one left and one right hemisphere was collected for each experimental group and analyzed according to the spatial transcriptomic manual (Stockholm, Sweden) (<xref ref-type="bibr" rid="B120">St&#x00E5;hl et al., 2016</xref>) using Fiji groovy script package (<xref ref-type="bibr" rid="B21">Chen et al., 2020</xref>). Our analysis revealed <italic>Gpx4</italic> upregulation and <italic>Gss</italic> and <italic>Acsl4</italic> downregulation in <italic>App<sup>NL-G-F</sup></italic> knock-in AD mice compared to WT mice. Although this analysis shows that these ferroptosis-related genes are differentially expressed in <italic>App<sup>NL-G-F</sup></italic> knock-in AD mice, it is known that downregulation of <italic>Gpx4</italic> and upregulation of <italic>Acsl4</italic> can induce ferroptosis (<xref ref-type="bibr" rid="B33">Dixon et al., 2012</xref>). Our observation from the TSNE analysis can be explained by cells trying to increase resistance against ferroptosis by increasing the generation of antioxidants (from the observation of increased <italic>Gpx4</italic>) and depleting the substrates for lipid peroxidation (as <italic>Acsl4</italic> gene expression was found decreased) (<xref ref-type="bibr" rid="B121">Stockwell et al., 2017</xref>).</p>
<p>In the second study containing the scREAD dataset (<xref ref-type="bibr" rid="B95">Mathys et al., 2019</xref>), 48 participants were divided into early and late stage groups based on nine clinical pathological traits. Data was acquired by single-nucleus RNA sequencing (snRNAseq)-based differential expression analysis and assessed by Wilcoxon rank-sum test and false discovery rate (FDR) multiple-testing correction (<xref ref-type="bibr" rid="B95">Mathys et al., 2019</xref>). Our analysis revealed that ferroptosis-related genes in excitatory neurons from human brains are mostly downregulated at an early clinical stage of AD, while they are upregulated at a later clinical stage of the disease relative to early stage (<xref ref-type="table" rid="T1">Table 1</xref>). The same was observed with inhibitory neurons, astrocytes and glia cells. For instance, genes which are important for ferroptosis resistance [e.g., <italic>ACSL3</italic>, ferritin heavy chain (<italic>FTH1</italic>), <italic>GPX4</italic>, <italic>GSS</italic> and voltage-dependent anion channel 2 and 3 (<italic>VDAC2/3</italic>)] are downregulated in an early stage of AD pathology but upregulated at later AD stage. This could imply that ferroptosis already happens at early stages of the diseases. The shift from downregulation to upregulation at later stages can be explained by cells trying to compensate and rescue the ferroptotic cell death by increasing the expression of antioxidant proteins and enzymes. Furthermore, the observation that neurons show a higher number of ferroptosis DEGs in AD than astrocytes and oligodendrocytes suggests that ferroptosis affects neurons and glia cells differently (<xref ref-type="bibr" rid="B77">Kim et al., 2021</xref>). Although it seems from this dataset that ferroptosis gene expression changes primarily in neurons, it might be because glia cells were not primarily sorted out in this study. Therefore, next we analyzed a dataset that specifically looked at glia cells.</p>
<table-wrap position="float" id="T1">
<label>TABLE 1</label>
<caption><p>Log2-fold change of ferroptosis-related DEGs related to AD.</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<tbody>
<tr>
<td valign="top" align="left"><graphic xlink:href="fnagi-13-745046-t001.jpg"/></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p><italic>Decreased (blue) and increased (red) expression of ferroptosis-related genes in neurons (Exc, Excitatory and Inh, Inhibitory) and glia cells (Ast, Astrocytes and Olig, Oligodendrocytes) in AD brain. White space corresponds to unchanged gene expression. Participants were divided into early and late stage groups based on 9 clinico-pathological traits. Early AD is associated with decrease and late AD with increase in ferroptosis-related gene expression.</italic></p></fn>
<fn><p><italic>bACSL3, Long-chain-fatty-acid-CoA ligase 3; ACSL4, Long-chain-fatty-acid-CoA ligase 4; ACSL5, Long-chain-fatty-acid-CoA ligase 5; ALOX15, coding for arachidonate 15-lipoxygenase/15-lipoxygenase-1; DHODH, Dihydroorotate dehydrogenase; FTH1, Ferritin heavy chain; FTL, Ferritin light chain; GCLC, Glutamate-cysteine ligase catalytic subunit; GPx4, Glutathione peroxidase 4; GSS, Glutathione synthetase; LPCAT3, Lysophosphatidylcholine acyltransferase 3; MAP1LC3A, Microtubule associated protein 1 light chain 3 Alpha; MAP1LC3B, Microtubule associated protein 1 light chain 3 Beta; MAP1LC3B2, Microtubule associated protein 1 light chain 3 Beta 2; NCOA4, Nuclear receptor coactivator 4; PCBP1, Poly(rC)-binding protein 1; PCBP2, Poly(rC)-binding protein 2; PRNP, prion protein; SAT1, Spermidine/spermine N1-acetyltransferase 1; SAT2, Spermidine/spermine N1-acetyltransferase 2; SLC11A2, Solute carrier family 11 member 2; TF, Transferrin; TFRC, Transferrin receptor; TP53BP2, Tumor protein p53 binding protein, 2; TP53I11, TP53 inducible protein; TP53RK, TP53 regulating kinase; TP53TG5, Tumor protein 53 target 5; VDAC2, Voltage-dependent anion channel 2; VDAC3, Voltage-dependent anion channel 3.</italic></p></fn>
<fn><p><italic>The criteria to determine if the change of the gene was significant included the false discovery rate (FDR)-corrected p &#x003C; 0.01 in a two-sided Wilcoxon-rank sum test, absolute log<sub>2</sub> &#x003E; 0.25, and FDR-corrected P &#x003C; 0.05 in a Poisson mixed model. Data was analyzed based on <xref ref-type="bibr" rid="B95">Mathys et al. (2019)</xref>.</italic></p></fn>
</table-wrap-foot>
</table-wrap>
<p>To further investigate how ferroptosis could affect glia cells in AD, we looked at the difference in expression of ferroptosis-related genes in microglia between control and AD brains containing only amyloid-&#x03B2; plaques in the occipital cortex (OC) and both amyloid-&#x03B2; and tau pathology in the occipitotemporal cortex (OTC) (<xref ref-type="bibr" rid="B48">Gerrits et al., 2021</xref>). In this study, the differential expression analysis was performed using a logistic regression and adjusted <italic>p</italic>-value below 0.05 was used to determine the significance (<xref ref-type="bibr" rid="B48">Gerrits et al., 2021</xref>). Microglia belonging to different subclusters (homeostatic, A&#x03B2;-related = AD1 and tau-related = AD2) showed changes in the expression of ferroptosis-related genes between AD and control subjects (<xref ref-type="table" rid="T2">Table 2</xref>). Microglia affected by A&#x03B2; pathology alone, or the combination of A&#x03B2; and tau pathology showed more DEGs than cells in the homeostatic subcluster. Microglia in the A&#x03B2;-related subcluster showed increase in the expression of ferroptosis-related genes, while microglia in tau pathology-related subcluster showed decrease in the expression of these genes. As the presence of tau pathology in OC is typical for later stages of the diseases, these results could suggest that there seem to be a difference between the expression of ferroptosis-related genes between early and late stages of AD. However, whether glia cells die via ferroptotic cell death at later stages of AD should be investigated further.</p>
<table-wrap position="float" id="T2">
<label>TABLE 2</label>
<caption><p>Log-fold change of ferroptosis-related DEGs in glia cells in AD.</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<tbody>
<tr>
<td valign="top" align="left"><graphic xlink:href="fnagi-13-745046-t002.jpg"/></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p><italic>Data in this table represent the Log-fold change per gene per subcluster. Decreased (blue) and increased (red) expression of ferroptosis-related genes in microglia nuclei isolated from CTR and AD brain tissues. Microglia were clustered into 13 subclusters, that were categorized as follows: 1. homeostatic, 2. A&#x03B2;-plaque associated (-AD1) and 3. Tau-associated (AD2), and other subclusters were related to pro-inflammatory responses, cellular stress and proliferation. White space corresponds to unchanged gene expression. ACSL, Long-chain-fatty-acid&#x2013;CoA ligase; ALOX15, coding for Arachidonate 15-lipoxygenase/15-lipoxygenase-1; ATG, Autophagy related gene; FTH1, Ferritin heavy chain; FTL, Ferritin light chain; GCH1, Guanosine triphosphate cyclohydrolase-1; GCLC, Glutamate-cysteine ligase catalytic subunit; HMOX1, Heme oxygenase 1; NCOA4, Nuclear receptor coactivator 4; SAT1, Spermidine/spermine N1-acetyltransferase; SLC, Solute carrier family; STEAP3, STEAP3 Metalloreductase, TFRC, Transferrin receptor; TP53, tumor protein 53. The differential expression analysis was performed using a logistic regression from which we included ferroptosis-related genes with an adjusted p-value &#x003C; 0.05. Differential gene expression results were extracted from supplementary table 2 from <xref ref-type="bibr" rid="B48">Gerrits et al. (2021)</xref>.</italic></p></fn>
<fn><p><italic>ACSL, Long-chain-fatty-acid&#x2014;CoA ligase; ALOX15, coding for Arachidonate 15-lipoxygenase/15-lipoxygenase-1; ATG, Autophagy related gene; FTH1, Ferritin heavy chain; FTL, Ferritin light chain; GCH1, Guanosine triphosphate cyclohydrolase-1; GCLC, Glutamate-cysteine ligase catalytic subunit; GCLM, Glutamate-cysteine ligase modifier subunit; LPCAT3, Lysophosphatidylcholine acyltransferase 3; MAP1LC3B2, Microtubule associated protein 3 light chain 2 Beta; NCOA4, Nuclear receptor coactivator 4; PRNP, Prion protein; SAT1, Spermidine/spermine N1-acetyltransferase; SLC, Solute carrier family; STEAP3, STEAP3 Metalloreductase, TF, Transferrin; TFRC, Transferrin receptor; TP53, tumor protein 53.</italic></p></fn>
<fn><p><italic>The differential expression of genes was determined using a &#x2018;chisq.test&#x2019; function in R and &#x2018;anova_test&#x2019; function from the rstatix package (Moran&#x2019;s I test, q-value &#x003C; 0.05). Data was analyzed based on <xref ref-type="bibr" rid="B48">Gerrits et al. (2021)</xref>.</italic></p></fn>
</table-wrap-foot>
</table-wrap>
<p>Previous analysis of the whole brain human DEGs in AD revealed more AD-DEGs in women than men (<xref ref-type="bibr" rid="B127">Wan et al., 2020</xref>). To see whether this is also specifically true for ferroptosis-related genes, we analyzed the 44 ferroptosis-related genes in the AMPA-AD dataset where AD-DEGs were compared between genders (<xref ref-type="table" rid="T3">Table 3</xref>). The sample size included 478 AD (female: 318, male: 160) and 300 control (female: 148, male: 152) cases on which sex-stratified meta-analysis (<xref ref-type="bibr" rid="B127">Wan et al., 2020</xref>). Our analysis revealed three downregulated genes in both men and women while only <italic>GSS</italic> was downregulated in both. Only one gene, Cytochrome B-245 Beta Chain (<italic>CYBB</italic>), was upregulated in men while eleven genes were upregulated in women (<xref ref-type="table" rid="T3">Table 3</xref>). The analysis of the dataset available in this study indicates that like AD-DEGs, ferroptosis-related genes seem to be more differentially expressed in women than men. Finally, nine of the 44 ferroptosis-related genes were not differentially expressed in any of the analyzed datasets (<xref ref-type="supplementary-material" rid="S11">Supplementary Table 1</xref>).</p>
<table-wrap position="float" id="T3">
<label>TABLE 3</label>
<caption><p>Comparison of ferroptosis-related DEGs in AD between genders.</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<td/>
<td valign="top" align="center">Men</td>
<td valign="top" align="center">Women</td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Downregulated</td>
<td valign="top" align="center"><italic>GSS, SLC11A2, TFRC</italic></td>
<td valign="top" align="center"><italic>GSS, MAP1LC3A, VDAC3</italic></td>
</tr>
<tr>
<td valign="top" align="left">Upregulated</td>
<td valign="top" align="center"><italic>CYBB</italic></td>
<td valign="top" align="center"><italic>ACSL1, ALOX15B, FTL, HMOX1, NCOA4, SLC7A11, STEAP3, TF, TP53BP2, TP53I3, TP53RK</italic></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p><italic>ACSL1, Long-chain-fatty-acid-CoA ligase 1; ALOX15, Arachidonate 15-lipoxygenase/15-lipoxygenase-1; CYBB, Cytochrome B-245 Beta chain; FTL, Ferritin light chain; GSS, Glutathione synthetase; HMOX1, Heme oxygenase 1; MAP1LC3A, Microtubule associated protein 1 Light chain 3 Alpha; NCOA4, Nuclear receptor coactivator 4; SLC11A2, Solute carrier family 11 member 2; SLC7A11, Solute carrier family 7 member 11; STEAP3, STEAP3 Metalloreductase; TF, Transferrin; TFRC, Transferrin receptor; TP53BP2, Tumor protein p53 binding protein, 2; TP53I3, TP53 inducible protein; TP53RK, TP53 regulating kinase; VDAC3, Voltage-dependent anion channel 3.</italic></p></fn>
<fn><p><italic>The differentially expressed genes were determined as those with FDR P &#x003C; 0.05 using weighted fixed/mixed effect linear models using the &#x2018;voom-limma&#x2019; R package. Data was analyzed based on <xref ref-type="bibr" rid="B127">Wan et al. (2020)</xref>.</italic></p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="S5">
<title>Inhibition of Ferroptosis to Treat Alzheimer&#x2019;s Disease</title>
<p>An increasing amount of literature suggests that anti-ferroptotic therapies may be efficient in AD (<xref ref-type="bibr" rid="B9">Ashraf et al., 2020</xref>; <xref ref-type="bibr" rid="B85">Li et al., 2020</xref>; <xref ref-type="table" rid="T4">Table 4</xref>).</p>
<table-wrap position="float" id="T4">
<label>TABLE 4</label>
<caption><p>Characteristics of included articles assessing therapeutic options to prevent ferroptosis in AD stratified by mechanisms involved in ferroptosis.</p></caption>
<table cellspacing="5" cellpadding="5" frame="hsides" rules="groups">
<thead>
<tr>
<td valign="top" align="left">Author (year)</td>
<td valign="top" align="center" colspan="3">AD model<hr/></td>
<td valign="top" align="center">Compound</td>
<td valign="top" align="center" colspan="3">Administration<hr/></td>
<td valign="top" align="center" colspan="4">Positive effect<hr/></td>
</tr>
<tr>
<td/>
<td valign="top" align="left">Species</td>
<td valign="top" align="center">Sex</td>
<td valign="top" align="left">Age (year)</td>
<td/>
<td valign="top" align="center">Form</td>
<td valign="top" align="left">Time (months)</td>
<td valign="top" align="center">Amount</td>
<td valign="top" align="center">A&#x03B2;</td>
<td valign="top" align="center">pTau</td>
<td valign="top" align="center">Inflamation</td>
<td valign="top" align="center">Cognition</td>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left" colspan="12">Iron homeostasis</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B3">Adlard et al., 2011</xref></td>
<td valign="top" align="left">Tg2576 mice</td>
<td valign="top" align="center">&#x2640;</td>
<td valign="top" align="center">1.2</td>
<td valign="top" align="center">PBT2</td>
<td valign="top" align="center">o</td>
<td valign="top" align="center">0.4</td>
<td valign="top" align="center">30 mg/kg/d</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B4">Adlard et al., 2008</xref></td>
<td valign="top" align="left">Tg2576 and APP/PS1 mice</td>
<td valign="top" align="center">&#x2642;, &#x2640;</td>
<td valign="top" align="center">1.5&#x2013;1.8</td>
<td valign="top" align="center">PBT2</td>
<td valign="top" align="center">o</td>
<td valign="top" align="center">0.4</td>
<td valign="top" align="center">30 mg/kg/d</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B22">Cherny et al., 2001</xref></td>
<td valign="top" align="left">Tg2576 mice</td>
<td valign="top" align="center">&#x2642;, &#x2640;</td>
<td valign="top" align="center">1.75</td>
<td valign="top" align="center">PBT1</td>
<td valign="top" align="center">o</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">2 mg/kg/d</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B26">Crouch et al., 2011</xref></td>
<td valign="top" align="left">A&#x03B2;-induced SH&#x2212;SY5Y cells</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">PBT2</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">1 h</td>
<td valign="top" align="center">10&#x2013;20 &#x03BC;M</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B42">Fine et al., 2012</xref></td>
<td valign="top" align="left">TgP301L mice</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">0.7</td>
<td valign="top" align="center">DFO</td>
<td valign="top" align="center">in</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center">3 &#x00D7; 2.4 mg/w</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B52">Grossi et al., 2009</xref></td>
<td valign="top" align="left">TgCRND8 mice</td>
<td valign="top" align="center">&#x2642;, &#x2640;</td>
<td valign="top" align="center">0.3</td>
<td valign="top" align="center">PBT1</td>
<td valign="top" align="center">o</td>
<td valign="top" align="center">1.2</td>
<td valign="top" align="center">30 mg/kg/d</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B54">Guo et al., 2015</xref></td>
<td valign="top" align="left">APP/PS1 mice</td>
<td valign="top" align="center">&#x2642;</td>
<td valign="top" align="center">0.5</td>
<td valign="top" align="center">DFO</td>
<td valign="top" align="center">in</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">200 mg/kg/2d</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B53">Guo et al., 2013</xref></td>
<td valign="top" align="left">APP/PS1 mice</td>
<td valign="top" align="center">&#x2642;</td>
<td valign="top" align="left">0.5</td>
<td valign="top" align="center">DFO</td>
<td valign="top" align="center">in</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">200 mg/kg/2d</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B98">McLachlan et al., 1993</xref></td>
<td valign="top" align="left">AD patients</td>
<td valign="top" align="center">&#x2642;, &#x2640;</td>
<td valign="top" align="center">80</td>
<td valign="top" align="center">DFO</td>
<td valign="top" align="center">im</td>
<td valign="top" align="center">24</td>
<td valign="top" align="center">300 mg/d/5d/w</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B97">McLachlan et al., 1991</xref></td>
<td valign="top" align="left">AD patients</td>
<td valign="top" align="center">&#x2642;, &#x2640;</td>
<td valign="top" align="center">80</td>
<td valign="top" align="center">DFO</td>
<td valign="top" align="center">im</td>
<td valign="top" align="center">24</td>
<td valign="top" align="center">300 mg/d/5d/w</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B111">Ritchie et al., 2003</xref></td>
<td valign="top" align="left">AD patients</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">PBT1</td>
<td valign="top" align="center">o</td>
<td valign="top" align="center">8.3</td>
<td valign="top" align="center">300&#x2013;750mg/d</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left" colspan="12">Glutathione metabilism</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B38">Dumont et al., 2009</xref></td>
<td valign="top" align="left">Tg19959 mice</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">0.1</td>
<td valign="top" align="center">CDDO-MA</td>
<td valign="top" align="center">o</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">800 mg/kg chow</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B43">Fragoulis et al., 2017</xref></td>
<td valign="top" align="left">APP/PS1 mice</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">0.5</td>
<td valign="top" align="center">Methysticin</td>
<td valign="top" align="center">o</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">6 mg/kg/w</td>
<td valign="top" align="center">N</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B72">Kanninen et al., 2009</xref></td>
<td valign="top" align="left">APP/PS1 mice</td>
<td valign="top" align="center">&#x2642;</td>
<td valign="top" align="center">0.75</td>
<td valign="top" align="center">LV-Nrf2</td>
<td valign="top" align="center">icv</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">2-&#x03BC;L</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B75">Kerr et al., 2017</xref></td>
<td valign="top" align="left">ArcA&#x03B2;42 flies</td>
<td valign="top" align="center">&#x2642;, &#x2640;</td>
<td valign="top" align="center">7d</td>
<td valign="top" align="center">LiCl</td>
<td valign="top" align="center">o</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">100 mM</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B76">Kim et al., 2013</xref></td>
<td valign="top" align="left">A&#x03B2;-induced ICR mice</td>
<td valign="top" align="center">&#x2642;</td>
<td valign="top" align="center">0.4</td>
<td valign="top" align="center">SFN</td>
<td valign="top" align="center">ip</td>
<td valign="top" align="center">4d</td>
<td valign="top" align="center">30mg/kg/d</td>
<td valign="top" align="center">N</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B88">Lipton et al., 2016</xref></td>
<td valign="top" align="left">hAPP-J20 and 3xTg mice</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">0.3&#x2013;0.5</td>
<td valign="top" align="center">CA</td>
<td valign="top" align="center">in</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">2 &#x00D7; 10mg/kg/w</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B101">Nassireslami et al., 2016</xref></td>
<td valign="top" align="left">A&#x03B2;-induced wistar rats</td>
<td valign="top" align="center">&#x2642;</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">SA</td>
<td valign="top" align="center">icv</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">5&#x2013;100 nM</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B128">Wang et al., 2016</xref></td>
<td valign="top" align="left">APP/PS1 mice</td>
<td valign="top" align="center">&#x2642;</td>
<td valign="top" align="center">0.3</td>
<td valign="top" align="center">Dl-NBP</td>
<td valign="top" align="center">o</td>
<td valign="top" align="center">5</td>
<td valign="top" align="center">60 mg/kg/d</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left" colspan="12">Oxidative stress and lipid peroxidation</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B2">Adair et al., 2001</xref></td>
<td valign="top" align="left">AD patients</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NAC</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">6</td>
<td valign="top" align="center">50 mg/kg/day</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">N</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B10">Ates et al., 2020</xref></td>
<td valign="top" align="left">APPswe/PS1&#x0394;E9 mice</td>
<td valign="top" align="center">&#x2642;</td>
<td valign="top" align="center">0.75</td>
<td valign="top" align="center">CMS121</td>
<td valign="top" align="center">o</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">34 mg/kg/d</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td/>
<td valign="top" align="left">A&#x03B2;-induced MC65 cells</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">CMS121</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B23">Cong et al., 2019</xref></td>
<td valign="top" align="left">A&#x03B2;-induced SH&#x2212;SY5Y cells</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">Chal.14a-c</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center">25&#x03BC;M</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NA</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B44">Fu et al., 2006</xref></td>
<td valign="top" align="left">A&#x03B2;-induced kunming mice</td>
<td valign="top" align="center">&#x2642;</td>
<td valign="top" align="center">0.3</td>
<td valign="top" align="center">NAC</td>
<td valign="top" align="center">ip</td>
<td valign="top" align="center">7d</td>
<td valign="top" align="center">50&#x2013;200 mg/kg/d</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B96">McCaddon and Davies, 2005</xref></td>
<td valign="top" align="left">AD patients</td>
<td valign="top" align="center">&#x2642;</td>
<td valign="top" align="center">65</td>
<td valign="top" align="center">NAC</td>
<td valign="top" align="center">o</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">600 mg/d</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B110">Remington et al., 2009</xref></td>
<td valign="top" align="left">AD patients</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NAC</td>
<td valign="top" align="center">o</td>
<td valign="top" align="center">6&#x2013;9</td>
<td valign="top" align="center">600 mg/d</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B142">Zhang et al., 2018</xref></td>
<td valign="top" align="left">P301S mice</td>
<td valign="top" align="center">&#x2640;</td>
<td valign="top" align="center">0.4</td>
<td valign="top" align="center">LA</td>
<td valign="top" align="center">ip</td>
<td valign="top" align="center">2.3</td>
<td valign="top" align="center">3&#x2013;10 mg/kg/d/5d/w</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B143">Zhang et al., 2017</xref></td>
<td valign="top" align="left">3xTg mice</td>
<td valign="top" align="center">&#x2642;, &#x2640;</td>
<td valign="top" align="center">0.7</td>
<td valign="top" align="center">Se-Met</td>
<td valign="top" align="center">o</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">6 &#x03BC;g/ml</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">Y</td>
</tr>
<tr>
<td valign="top" align="left"><xref ref-type="bibr" rid="B119">Sripetchwandee et al., 2016</xref></td>
<td valign="top" align="left">Wistar rats on HI diet</td>
<td valign="top" align="center">&#x2642;</td>
<td valign="top" align="center">0.2</td>
<td valign="top" align="center">DFO</td>
<td valign="top" align="center">ip</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center">75-mg/kg/d</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">Y</td>
<td valign="top" align="center">NR</td>
<td valign="top" align="center">NR</td>
</tr>
<tr>
<td/>
<td/>
<td/>
<td/>
<td valign="top" align="center">NAC</td>
<td/>
<td valign="top" align="center">2</td>
<td valign="top" align="center">100 mg/kg/d</td>
<td/>
<td/>
<td/>
<td/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p><italic>Articles are sorted in alphabetical order and from more to less recent.</italic></p></fn>
<fn><p><italic>(hAPP)-J20; mouse expressing the human amyloid precursor protein, 3xTg AD; mutant mouse with PS1M146V gene, APP/PS1; [B6C3-Tg(APPswe,PSEN1 dE9)85Dbo/J], APPswe/PS1&#x0394;E9; transgenic mice express a mouse/human chimeric APPswe and a mutant human presinilin 1 (PS1&#x0394;E9), ArcA&#x03B2;42; A&#x03B2;42-expressing drosophila, CA; carnosic acid, Chal. 14a-c; Chalcones 14a, DFO, deferoxamine, FASN; fatty acid synthase, HI; high iron, LA; &#x03B1;-Lipoic acid, LV-Nrf2; human Nrf2 lentiviral vector, LiCl; lithium, N; no, NA; not applicable, NR; not reported, P301S; [B6C3-Tg (Prnp-MAPT&#x002A;P301S) PS19 Vle/J], PBT1; clioquinol, SA; sodium arsenite, SFN; sulforaphane, SH-SY5Y; human neuroblastoma cells, Se-Met; selenomethionine, Tg2576; mouse line encoding human APP695 with Lys670-Asn and Met671-Leu mutations, Y; yes, d; day, icv; intracerebroventricular, im; intramuscular, in; intranasal, ip; intraperitoneal, o; oral, w; week, y; year.</italic></p></fn>
</table-wrap-foot>
</table-wrap>
<sec id="S5.SS1">
<title>Iron Homeostasis</title>
<p>Our transcriptomic analysis revealed that <italic>FTH1</italic>, component responsible for iron storage, is differentially expressed in early and late stages of AD. Furthermore, excessive iron deposition in specific brain areas contributes to AD pathology (<xref ref-type="bibr" rid="B6">Antharam et al., 2012</xref>; <xref ref-type="bibr" rid="B100">Moon et al., 2016</xref>). Therefore, an increased interest in the development of therapeutic strategies targeting iron has emerged in the past years. In animal models, DFO treatment decreased AD hallmarks, iron overload, iron-induced kinase activity [cyclin-dependent kinase 5 (CDK5), glycogen synthase kinase 3&#x03B2; (GSK3&#x03B2;)], mitochondrial dysfunction, synaptic loss, and neuronal damage (<xref ref-type="bibr" rid="B42">Fine et al., 2012</xref>; <xref ref-type="bibr" rid="B53">Guo et al., 2013</xref>, <xref ref-type="bibr" rid="B54">2015</xref>; <xref ref-type="bibr" rid="B119">Sripetchwandee et al., 2016</xref>). DFO increased expression of transferrin receptor (TfR1) and brain-derived neurotrophic factor (BDNF), leading to reduced iron-induced memory deficits in rodents (<xref ref-type="bibr" rid="B42">Fine et al., 2012</xref>; C. <xref ref-type="bibr" rid="B53">Guo et al., 2013</xref>, <xref ref-type="bibr" rid="B54">2015</xref>; <xref ref-type="bibr" rid="B119">Sripetchwandee et al., 2016</xref>). In a clinical trial, DFO slowed down the progression of AD in patients (<xref ref-type="bibr" rid="B97">McLachlan et al., 1991</xref>, <xref ref-type="bibr" rid="B98">1993</xref>). However, the dosing regimens need to be standardized before DFO could be implemented in the clinical setting (<xref ref-type="bibr" rid="B40">Farr and Xiong, 2021</xref>). In addition, to reduce DFO-related cytotoxicity and prolong its presence into circulation, new DFO component-containing nanogels were proposed as promising alternatives for iron-chelation in AD (<xref ref-type="bibr" rid="B131">Wang et al., 2018</xref>). Besides AD, DFO alone or co/treatment with ferrostatin (Fer-1, inhibitor of lipid peroxidation) also improved &#x03B1;-synuclein-induced pathology in a PD animal model (<xref ref-type="bibr" rid="B41">Febbraro et al., 2013</xref>). PBT1, a drug inhibiting zinc and copper ions from binding to A&#x03B2;, reduced A&#x03B2; deposition, attenuated astrogliosis and prevented memory impairment in AD animal models AD (<xref ref-type="bibr" rid="B22">Cherny et al., 2001</xref>; <xref ref-type="bibr" rid="B52">Grossi et al., 2009</xref>). In pilot-phase 2 clinical trial, PBT1 reduced A&#x03B2; plasma levels and, when looked specifically on severely affected AD patients, PBT1 was able to slow down the clinical decline (<xref ref-type="bibr" rid="B111">Ritchie et al., 2003</xref>). PBT2, a second-generation 8-hydroxyquinoline analog produced as a successor to clioquinol, induced GSK3&#x03B2; phosphorylation and prevented formation of A&#x03B2; in neuroblastoma SH-SY5Y cells (<xref ref-type="bibr" rid="B26">Crouch et al., 2011</xref>). In animal models of AD, PBT2 induced A&#x03B2; plaque degradation, decreased p-tau, rescued decreased spine density, increased brain-levels of BDNF and improved cognitive performance (<xref ref-type="bibr" rid="B4">Adlard et al., 2008</xref>, <xref ref-type="bibr" rid="B3">2011</xref>). PBT2 was also assessed in a phase 2 clinical trial, where it lead to reduced levels of A&#x03B2; in cerebrospinal fluid and improved executive function compared to placebo (<xref ref-type="bibr" rid="B82">Lannfelt et al., 2008</xref>). However, PBT2 did not show any significant effect on cognition. Currently, deferiprone (DFP), a compound that alleviates symptoms related to PD pathology (<xref ref-type="bibr" rid="B31">Devos et al., 2014</xref>; <xref ref-type="bibr" rid="B51">Grolez et al., 2015</xref>; <xref ref-type="bibr" rid="B56">Gutbier et al., 2020</xref>), is evaluated a in phase 2 randomized placebo-controlled clinical trial with AD patients (NCT03234686). As previously reported, iron chelators can attenuate symptoms and slow down the progression of AD, which shows the potential for novel therapeutic approaches (<xref ref-type="bibr" rid="B103">Nu&#x00F1;ez and Chana-Cuevas, 2018</xref>).</p>
</sec>
<sec id="S5.SS2">
<title>Glutathione Metabolism</title>
<p>The revealed differential gene expression of <italic>GPX4</italic> and <italic>GSS</italic> suggests that modifying the expression or/and the activity of these gene-encoded proteins might be beneficial to treat AD. The expression of GPx4 can be directly upregulated by &#x03B1;-Lipoic acid (LA) (<xref ref-type="bibr" rid="B142">Zhang et al., 2018</xref>). LA treatment on P301S Tau transgenic mice enhanced the activity of system x<sub>c</sub><sup>&#x2013;</sup>, GPx4, superoxide dismutase 1 (Sod1), CDK5, GSK3&#x03B2;, TfR1 and FPN1 (<xref ref-type="bibr" rid="B142">Zhang et al., 2018</xref>). LA reduced the hippocampal levels of glial fibrillary acidic protein (GFAP), tumor necrosis factor &#x03B1; (TNF-&#x03B1;), interleukin 1&#x03B2; (IL-1&#x03B2;), as well as the calcium (Ca<sup>2+</sup>) content, p-tau, calpain1 levels, and synaptic loss. As a result, these processes led to enhanced memory function (<xref ref-type="bibr" rid="B142">Zhang et al., 2018</xref>). Apart from LA, GPx4 can be activated in an indirect manner through Nrf2. Nrf2 plays an important role in neurodegeneration and ferroptosis by regulating a wide range of genes (<xref ref-type="bibr" rid="B118">Song and Long, 2020</xref>). In addition to the activation of GPx4 and GSH synthesis (<xref ref-type="bibr" rid="B35">Dodson et al., 2019</xref>), it can also affect the activity of glucose-6-phosphate dehydrogenase, GSH reductase, glutamate-cysteine ligase modifier subunit (GLCM), solute carrier family 7 member 11 (SLC7A11) and others as previously summarized by <xref ref-type="bibr" rid="B118">Song and Long (2020)</xref>. Nrf2 can be upregulated using a human lentiviral vector or compounds such as sodium arsenite, triterpenoid, 2-cyano-3,12-dioxooleana-1,9-dien-28-oic acid-methylamide (CDDO-MA), dl-3-n-butylphthalide (DI-NBP), kavalactone methysticin, carnosic acid (CA) and sulforaphane (SFN). Nrf2 upregulation increased heme oxygenase-1 (HMOX1) levels and decreased AD hallmarks, hippocampal inflammation, oxidative stress, and A&#x03B2;-induced memory deficits in AD mouse models (<xref ref-type="bibr" rid="B38">Dumont et al., 2009</xref>; <xref ref-type="bibr" rid="B72">Kanninen et al., 2009</xref>; <xref ref-type="bibr" rid="B76">Kim et al., 2013</xref>; <xref ref-type="bibr" rid="B88">Lipton et al., 2016</xref>; <xref ref-type="bibr" rid="B101">Nassireslami et al., 2016</xref>; <xref ref-type="bibr" rid="B128">Wang et al., 2016</xref>; <xref ref-type="bibr" rid="B43">Fragoulis et al., 2017</xref>). Finally, genetic downregulation of Kelch-like ECH-associated protein 1 (<italic>Keap1</italic>), the negative regulator of Nrf2, in ArcA&#x03B2;42 flies, activated Nrf2, induced A&#x03B2;42 degradation, prevented neuronal toxicity in response to A&#x03B2;42 peptide, rescued neuronal-specific motor defects and increased life span (<xref ref-type="bibr" rid="B75">Kerr et al., 2017</xref>).</p>
<p>Altogether, these results suggest that inhibition of ferroptosis by targeting GSH metabolism is an important avenue for the development of new therapies for AD (<xref ref-type="bibr" rid="B9">Ashraf et al., 2020</xref>).</p>
</sec>
<sec id="S5.SS3">
<title>Oxidative Stress and Lipid Peroxidation</title>
<p>Lipid peroxidation represents an important hallmark of AD (<xref ref-type="bibr" rid="B123">Sultana et al., 2013</xref>), which was also supported by the observed differential expression of <italic>ACSL3</italic> and 4 in the course of the pathology (<xref ref-type="table" rid="T1">Tables 1</xref>, <xref ref-type="table" rid="T2">2</xref>). In many studies, oxidative stress was targeted to reduce neuronal damage and alleviate symptoms related to AD pathology. Anti-ferroptotic compounds that reduce oxidative stress include liproxstatin 1 (Lip-1) (inhibitor of ROS and lipid peroxidation), chalcones 14a-c (inhibitor of A&#x03B2; and lipid peroxidation), Selenomethionine (Se-Met) (inhibitor of lipid peroxidation), CMC121 (fatty acid synthase inhibitor), <italic>N</italic>-acetylcysteine (NAC) (free radical scavenger), Vitamin E (Vit E) and PD146176 (15-LOX-1 inhibitor). Studies using <italic>in vitro</italic> and <italic>in vivo</italic> models of AD have shown that targeting oxidative stress has a positive effect on neural degeneration, inflammation, A&#x03B2;1-42 aggregation, p-tau formation, GSH levels, iron overload, mitochondrial function, motor dysfunction and learning and memory (<xref ref-type="bibr" rid="B44">Fu et al., 2006</xref>; <xref ref-type="bibr" rid="B119">Sripetchwandee et al., 2016</xref>; <xref ref-type="bibr" rid="B58">Hambright et al., 2017</xref>; <xref ref-type="bibr" rid="B143">Zhang et al., 2017</xref>; <xref ref-type="bibr" rid="B23">Cong et al., 2019</xref>; <xref ref-type="bibr" rid="B10">Ates et al., 2020</xref>). In concordance with these results, clinical trials have shown that NAC and co-treatment of NAC, Vit E and Se-Met improved behavioral symptoms, general well-being, and neuropsychiatric and cognitive scores of AD patients (<xref ref-type="bibr" rid="B2">Adair et al., 2001</xref>; <xref ref-type="bibr" rid="B96">McCaddon and Davies, 2005</xref>; <xref ref-type="bibr" rid="B110">Remington et al., 2009</xref>). Although Vitamin E treatment had no beneficial effect on patients with mild cognitive impairment (<xref ref-type="bibr" rid="B92">Marder, 2005</xref>), it was able to improve symptoms related to other neurodegenerative diseases such as PD (<xref ref-type="bibr" rid="B124">Taghizadeh et al., 2017</xref>) and cerebellar ataxia (<xref ref-type="bibr" rid="B45">Gabsi et al., 2001</xref>). Considering the lack of adverse events of these antioxidants, ferroptosis inhibition by targeting oxidative stress is a new promising therapeutic strategy for AD.</p>
</sec>
</sec>
<sec id="S6" sec-type="discussion">
<title>Discussion</title>
<p>Improved understanding of underlying mechanisms of ferroptosis in AD may lead to the development and application of anti-ferroptotic strategies to slow down or prevent AD progression (<xref ref-type="bibr" rid="B59">Han et al., 2020</xref>). Iron accumulation (<xref ref-type="bibr" rid="B17">Bulk et al., 2018a</xref>), lipid peroxidation (<xref ref-type="bibr" rid="B91">Majern&#x00ED;kov&#x00E1; et al., 2020</xref>) and mitochondrial dysfunction (<xref ref-type="bibr" rid="B62">Horowitz and Greenamyre, 2010</xref>), the main hallmarks of ferroptosis, are observed early in AD pathology, suggesting that targeting ferroptosis in AD may lead to the prevention of symptoms manifestation such as cognitive decline at advanced stages of AD.</p>
<p>Our analysis of DEGs in AD revealed that differential expression of ferroptosis-related genes in AD affects mostly neurons and that the changes observed in glia cells could be related to both tau phosphorylation and A&#x03B2; accumulation. This may explain the difference in the expression of ferroptotic markers between early (A&#x03B2;) and late (A&#x03B2; + p-tau) stages of AD. Even though this review has shed more light on the role of different brain cell types in ferroptosis during AD, whether ferroptosis in glia cells is related to later stages of the pathology should be investigated further.</p>
<p>While it is known that AD brain shows ferroptosis characteristics, it is unknown what is the causal relationship between AD and ferroptosis. Plasma ferritin increases with increasing age and A&#x03B2; deposition. Recent work on the inhibition of lipid peroxidation and iron accumulation in <italic>C. elegans</italic> revealed extended life- and health-span independently of other mechanisms (<xref ref-type="bibr" rid="B67">Jenkins et al., 2020</xref>). This evidence suggests that ferroptosis may be an age-related as well as disease-related process (<xref ref-type="bibr" rid="B49">Goozee et al., 2018</xref>; <xref ref-type="bibr" rid="B83">Larric et al., 2020</xref>). Therefore, ferroptosis inhibition may not only lead to slowing down the neurodegeneration but also contribute to longer health-span (<xref ref-type="bibr" rid="B83">Larric et al., 2020</xref>).</p>
<p>Iron dysregulation aggravates formation and aggregation of both A&#x03B2; and p-tau protein forming plaques and NFT respectively (<xref ref-type="bibr" rid="B30">Derry et al., 2020</xref>). Even though the link between ferroptosis and A&#x03B2; has been extensively studied, much less is known about its role in NFT formation. Therefore, future studies should try to investigate the role of ferroptosis in hyperphosphorylation of tau protein and formation of fibrillary tangles independently of A&#x03B2; pathology. This could be achieved by comparing the characteristics of ferroptotic cell death in AD with patients with primary age-related tauopathy (PART) (<xref ref-type="bibr" rid="B25">Crary et al., 2014</xref>).</p>
<p>Further research should also address the effect of ferroptosis on the interactions between different cell types in AD context. Although cell-cell interactions are dysregulated in AD brain (<xref ref-type="bibr" rid="B61">Henstridge et al., 2019</xref>), this feature of AD is often overlooked in <italic>in vitro</italic> studies. The brain-on-a-chip platform using induced pluripotent stem cells (iPSCs) -derived neurons and glia from AD patients could allow a high throughput screening of the effect of anti-ferroptotic drugs in AD, while mimicking the cell-cell interactions in AD context (<xref ref-type="bibr" rid="B126">Trombetta-Lima et al., 2021</xref>). Moreover, this model is easily reproducible and thanks to the use of iPSCs from AD patients, also more translatable to humans compared to well-established animal models.</p>
</sec>
<sec id="S7" sec-type="conclusion">
<title>Conclusion</title>
<p>This review summarizes the evidence supporting the important role of ferroptosis in AD pathology and presents what is known about the targets for its inhibition for a potential treatment. Ferroptosis-related genes are differentially expressed in AD, supporting our hypothesis that ferroptosis inhibition could slow down the AD progression and memory decline, however, many questions remain unanswered. Developing new AD models allowing us to study how ferroptosis effects cell-cell interaction is needed to understand the causal relationship and timing of ferroptosis in AD. Future efforts should be directed toward developing detection techniques of ferroptosis <italic>in vivo</italic> and organizing large, randomized clinical trials of anti-ferroptotic drugs in early and late stages of AD progression.</p>
</sec>
<sec id="S8">
<title>Author Contributions</title>
<p>NM, AD, and WD designed the theme of the manuscript. NM contributed by writing all the sections and creating all tables and figures. AD and WD conducted critical revisions of the manuscript. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec id="conf1" sec-type="COI-statement">
<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>
</sec>
<sec id="pudiscl1" sec-type="disclaimer">
<title>Publisher&#x2019;s Note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
</body>
<back>
<sec id="S9" sec-type="funding-information">
<title>Funding</title>
<p>NM received a De Cock research grant and a fellowship from the Behavioural and Cognitive Neuroscience Graduate School, University Medical Centre Groningen. AD is the recipient of an Alzheimer Nederland grant (WE.03- 2018-04, Netherlands), and a Rosalind Franklin Fellowship co-funded by the European Union and the University of Groningen.</p>
</sec>
<ack>
<p>We thank Alejandro Marmolejo-Garza for the support on the transcriptomic analysis.</p>
</ack>
<sec id="S11" sec-type="supplementary-material">
<title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fnagi.2021.745046/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fnagi.2021.745046/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Table_1.docx" id="TS1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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