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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Nutr.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Nutrition</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Nutr.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2296-861X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fnut.2026.1820240</article-id>
<article-version article-version-type="Corrected Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Opinion</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Precision nutrition in MASLD should incorporate metabolic and inflammatory phenotyping</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name><surname>Ntikoudi</surname> <given-names>Anastasia</given-names></name>
<xref ref-type="aff" rid="aff1"/>
<xref ref-type="corresp" rid="c001"><sup>&#x0002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/3409654"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
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</contrib>
</contrib-group>
<aff id="aff1"><institution>Department of Nursing, University of West Attica</institution>, <city>Athens</city>, <country country="gr">Greece</country></aff>
<author-notes>
<corresp id="c001"><label>&#x0002A;</label>Correspondence: Anastasia Ntikoudi, <email xlink:href="mailto:antikoudi@uniwa.gr">antikoudi@uniwa.gr</email></corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-06-11">
<day>11</day>
<month>06</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="corrected" iso-8601-date="2026-07-29">
<day>29</day>
<month>07</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2026</year>
</pub-date>
<volume>13</volume>
<elocation-id>1820240</elocation-id>
<history>
<date date-type="received">
<day>28</day>
<month>02</month>
<year>2026</year>
</date>
<date date-type="rev-recd">
<day>18</day>
<month>05</month>
<year>2026</year>
</date>
<date date-type="accepted">
<day>27</day>
<month>05</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x000A9; 2026 Ntikoudi.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Ntikoudi</copyright-holder>
<license>
<ali:license_ref start_date="2026-06-11">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. 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.</license-p>
</license>
</permissions>
<kwd-group>
<kwd>inflammatory</kwd>
<kwd>MASLD</kwd>
<kwd>metabolic</kwd>
<kwd>nutrition</kwd>
<kwd>phenotyping</kwd>
</kwd-group>
<funding-group>
  <funding-statement>The author(s) declared that financial support was not received for this work and/or its publication.</funding-statement>
</funding-group>
<counts>
<fig-count count="0"/>
<table-count count="0"/>
<equation-count count="0"/>
<ref-count count="34"/>
<page-count count="4"/>
<word-count count="3119"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Nutrition and Metabolism</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="s1">
<label>1</label>
<title>Introduction</title>
<p>Metabolic dysfunction-associated steatotic liver disease (MASLD) is now recognized as the hepatic manifestation of systemic metabolic dysregulation and represents the most prevalent chronic liver disorder globally. Contemporary clinical practice guidelines emphasize lifestyle modification, particularly dietary intervention and sustained weight reduction, as the cornerstone of management (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>). Evidence consistently demonstrates that the magnitude of weight loss correlates with improvement in steatohepatitis features and fibrosis regression in a subset of patients (<xref ref-type="bibr" rid="B3">3</xref>). Comprehensive reviews further reinforce that structured dietary modification and physical activity can improve hepatic steatosis and cardiometabolic risk parameters (<xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B5">5</xref>). Despite this robust evidence base, clinical response to dietary interventions remains heterogeneous, even among individuals achieving comparable weight reduction.</p>
<p>This variability reflects the biological heterogeneity of MASLD. While insulin resistance is widely recognized as a central pathogenic driver, systemic inflammation, dyslipidemia, adipose tissue dysfunction, and intrahepatic metabolic remodeling contribute in varying degrees to disease progression. Mechanistic studies have demonstrated that liver, muscle, and adipose tissue insulin action is directly related to intrahepatic triglyceride content, highlighting the tight coupling between hepatic fat accumulation and systemic insulin resistance (<xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B7">7</xref>). At a molecular level, insulin resistance promotes hepatic <italic>de novo</italic> lipogenesis, increases substrate oversupply, and disrupts lipid partitioning, reinforcing steatosis and metabolic injury (<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B8">8</xref>). In parallel, inflammatory signaling and immune-mediated pathways amplify hepatocellular damage and fibrogenesis (<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B10">10</xref>).</p>
<p>Beyond intrahepatic mechanisms, MASLD reflects a systemic metabolic disorder characterized by complex interactions between insulin resistance, dyslipidemia, adipose tissue dysfunction, and chronic low-grade inflammation (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B8">8</xref>, <xref ref-type="bibr" rid="B10">10</xref>). These interconnected processes contribute not only to hepatic steatosis and progression to steatohepatitis, but also to broader cardiometabolic risk, including increased cardiovascular disease burden (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B4">4</xref>). The relative contribution of these mechanisms varies across individuals, giving rise to clinically heterogeneous phenotypes with potentially different therapeutic responses (<xref ref-type="bibr" rid="B8">8</xref>, <xref ref-type="bibr" rid="B10">10</xref>). This biological variability provides a strong rationale for moving beyond uniform dietary prescriptions toward phenotype-informed nutritional strategies (<xref ref-type="bibr" rid="B4">4</xref>).</p>
<p>Taken together, these interacting metabolic and inflammatory processes generate clinically distinct phenotypic expressions of MASLD, which may reasonably be expected to influence therapeutic responsiveness. However, most dietary trials apply uniform nutritional regimens without stratifying participants according to baseline metabolic or inflammatory burden. Such an approach may dilute signals in responsive subgroups and limit progress toward precision nutrition.</p>
<p>This Opinion argues that metabolic and inflammatory phenotyping, grounded in accessible clinical biomarkers such as insulin resistance indices, triglyceride-to-HDL cholesterol (TG/HDL-C) ratio, and high-sensitivity C-reactive protein (hs-CRP), should inform dietary strategy selection and future MASLD trial design.</p>
</sec>
<sec id="s2">
<label>2</label>
<title>Insulin resistance as a heterogeneous driver of MASLD</title>
<p>Insulin resistance is a defining feature of MASLD pathophysiology. Early metabolic investigations demonstrated that insulin action in liver, skeletal muscle, and adipose tissue declines proportionally with increasing intrahepatic triglyceride content, underscoring the systemic nature of hepatic steatosis (<xref ref-type="bibr" rid="B6">6</xref>). At a molecular level, impaired insulin signaling enhances hepatic <italic>de novo</italic> lipogenesis through activation of lipogenic transcription factors while reducing suppression of adipose tissue lipolysis, thereby increasing free fatty acid flux to the liver (<xref ref-type="bibr" rid="B8">8</xref>, <xref ref-type="bibr" rid="B10">10</xref>). This metabolic environment promotes triglyceride accumulation within hepatocytes and contributes to progression toward steatohepatitis.</p>
<p>More recent studies provide direct evidence that insulin resistance drives hepatic <italic>de novo</italic> lipogenesis in MASLD. Korenblat et al. (<xref ref-type="bibr" rid="B6">6</xref>) and Smith et al. (<xref ref-type="bibr" rid="B7">7</xref>) demonstrated that hepatic <italic>de novo</italic> lipogenesis is markedly increased in insulin-resistant individuals and strongly correlated with intrahepatic triglyceride content. These findings support the concept that hyperinsulinaemia and hyperglycaemia are not merely associated features but active drivers of hepatic lipid synthesis. Importantly, the contribution of <italic>de novo</italic> lipogenesis to hepatic fat appears particularly pronounced in metabolically dysregulated states.</p>
<p>Dietary macronutrient composition directly influences these pathways. Excessive intake of simple carbohydrates, particularly fructose, stimulates <italic>de novo</italic> lipogenesis, whereas saturated fat intake contributes to lipotoxicity and mitochondrial dysfunction (<xref ref-type="bibr" rid="B11">11</xref>). A comprehensive review of dietary carbohydrates and fats in NAFLD emphasized that macronutrient quality and metabolic context critically shape hepatic lipid handling (<xref ref-type="bibr" rid="B11">11</xref>). However, MASLD is not synonymous with uniform insulin resistance severity. Comparative analyses of surrogate indices, including HOMA-IR, the triglyceride-glucose index, and TG/HDL-C ratio, demonstrated heterogeneity in their discriminative performance across populations (<xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B13">13</xref>). Some individuals exhibit profound insulin resistance and atherogenic dyslipidemia, whereas others present with hepatic steatosis despite comparatively modest systemic metabolic impairment.</p>
<p>This heterogeneity has direct implications for nutritional strategy. Interventions primarily targeting glycemic load and insulin sensitivity may yield greater benefit in metabolically dominant phenotypes than in individuals whose disease trajectory is more strongly influenced by inflammatory or genetic mechanisms. Routine reporting of baseline insulin resistance metrics, or validated lipid-based surrogates such as TG/HDL-C ratio, would enhance interpretability of dietary trials and facilitate phenotype-stratified analyses.</p>
</sec>
<sec id="s3">
<label>3</label>
<title>Systemic inflammation as a critical stratification axis</title>
<p>Chronic low-grade inflammation is increasingly recognized as a pivotal contributor to MASLD progression. Adipose tissue macrophage infiltration, dysregulated adipokine secretion, and cytokine-mediated signaling promote hepatocellular injury and fibrogenesis (<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B10">10</xref>). The pathogenesis of MASLD has been comprehensively reviewed as a convergence of metabolic overload and inflammatory activation, in which lipotoxic intermediates, oxidative stress, and immune signaling drive progression from steatosis to steatohepatitis (<xref ref-type="bibr" rid="B10">10</xref>).</p>
<p>High-sensitivity CRP, although not liver-specific, provides a widely available measure of systemic inflammatory tone. A recent population-based, cross-sectional analysis across steatotic liver disease phenotypes demonstrated variation in hs-CRP levels, supporting its relevance for clinical characterization (<xref ref-type="bibr" rid="B14">14</xref>). Associations between CRP levels, histological, and elastographic indices of NAFLD in individuals with severe obesity further reinforce the role of inflammatory burden in disease severity (<xref ref-type="bibr" rid="B15">15</xref>). Importantly, inflammatory markers do not consistently parallel insulin resistance severity, suggesting partially distinct mechanistic trajectories.</p>
<p>Dietary modulation of inflammation is biologically plausible. Mediterranean-style dietary patterns rich in fiber, polyphenols, and unsaturated fats have demonstrated favorable effects in NAFLD populations (<xref ref-type="bibr" rid="B16">16</xref>). Moreover, a systematic evaluation of randomized controlled trials comparing low-fat and low-carbohydrate calorie-restricted diets indicates that while weight reduction remains the principal driver of improvement in liver enzymes and hepatic fat content, no clear consensus exists regarding optimal macronutrient composition, underscoring persistent uncertainty in dietary prescription (<xref ref-type="bibr" rid="B17">17</xref>). Given the established links between diet composition, insulin signaling, and inflammatory pathways (<xref ref-type="bibr" rid="B11">11</xref>), incorporation of inflammatory stratification into dietary trials represents a logical extension of precision nutrition principles.</p>
</sec>
<sec sec-type="discussion" id="s4">
<label>4</label>
<title>Discussion</title>
<p>A pragmatic approach to precision nutrition in MASLD may be operationalized through a two-axis stratification model incorporating insulin resistance and systemic inflammatory burden. Such an approach reflects the biological heterogeneity of MASLD and provides a clinically accessible framework to support more targeted dietary strategies.</p>
<p>Insulin resistance may be approximated using surrogate indices such as lipid-derived markers, including the triglyceride-to-HDL cholesterol (TG/HDL-C) ratio, which has been associated with insulin resistance and cardiometabolic risk across diverse populations (<xref ref-type="bibr" rid="B18">18</xref>&#x02013;<xref ref-type="bibr" rid="B20">20</xref>). Where feasible, the homeostasis model assessment of insulin resistance (HOMA-IR) may provide additional insight, although its clinical utility is limited by the requirement for fasting insulin measurement and the absence of universally accepted thresholds (<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B22">22</xref>). In parallel, systemic inflammatory burden may be approximated using high-sensitivity C-reactive protein (hs-CRP), with established cardiovascular risk categories (&#x0003C; 1 mg/L, 1&#x02013;3 mg/L, &#x0003E;3 mg/L) offering a pragmatic framework for stratification in clinically stable individuals (<xref ref-type="bibr" rid="B23">23</xref>). Although non-specific, hs-CRP reflects low-grade inflammation that is central to the pathophysiology of steatotic liver disease and its cardiometabolic complications (<xref ref-type="bibr" rid="B24">24</xref>).</p>
<p>Integrating these axes yields a pragmatic four-phenotype framework comprising metabolic-dominant, inflammatory-dominant, mixed, and low-burden profiles. This classification is not intended as a rigid taxonomy, but rather as a tool to contextualize inter-individual variability in disease expression and therapeutic responsiveness. This framework is intended as a hypothesis-generating clinical tool rather than a definitive classification system. From a practical perspective, these phenotypes may inform dietary emphasis. Within this framework, dietary strategies may be qualitatively tailored. Individuals with metabolically dominant profiles may derive greater benefit from interventions targeting glycaemic load and insulin sensitivity, whereas inflammatory-dominant phenotypes may respond preferentially to dietary patterns with established anti-inflammatory properties, such as Mediterranean-style diets (<xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B16">16</xref>, <xref ref-type="bibr" rid="B25">25</xref>). Mixed phenotypes may require combined strategies that address both metabolic and inflammatory drivers.</p>
<p>These phenotype-informed approaches should complement, rather than replace, established lifestyle recommendations. The magnitude of weight loss remains the principal determinant of histological improvement in MASLD, with consistent evidence demonstrating that greater weight reduction is associated with higher likelihood of steatohepatitis resolution and fibrosis improvement (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B3">3</xref>). Accordingly, stratification should be viewed as a means of refining dietary composition within a shared therapeutic foundation centered on weight reduction.</p>
<p>From a research perspective, incorporation of baseline metabolic and inflammatory phenotyping into dietary intervention trials may enhance interpretability and reduce apparent heterogeneity in outcomes. Standardized reporting of insulin resistance markers, lipid ratios, and hs-CRP would enable pre-specified subgroup analyses and facilitate exploration of effect modification. Such an approach aligns MASLD nutritional research with broader precision medicine paradigms and may improve identification of phenotype-specific responses to dietary interventions.</p>
<p>A further dimension reinforcing the systemic nature of MASLD is its applicable association with subclinical vascular disease. Accumulating evidence indicates that hepatic steatosis is linked to early atherosclerotic changes through shared mechanisms including insulin resistance, chronic inflammation, oxidative stress, and atherogenic dyslipidemia (<xref ref-type="bibr" rid="B26">26</xref>&#x02013;<xref ref-type="bibr" rid="B29">29</xref>). Carotid intima-media thickness (cIMT) is a widely used, non-invasive surrogate marker of subclinical atherosclerosis and cardiovascular risk, and has been shown to be increased in individuals with hepatic steatosis (<xref ref-type="bibr" rid="B30">30</xref>). While several studies suggest associations between hepatic steatosis severity, inflammatory mediators, and vascular remodeling, the strength and independence of these relationships vary across populations and study designs (<xref ref-type="bibr" rid="B31">31</xref>&#x02013;<xref ref-type="bibr" rid="B34">34</xref>). From a clinical perspective, dietary interventions that improve insulin sensitivity and reduce hepatic fat content may concurrently attenuate systemic inflammation and vascular risk, extending the impact of nutritional strategies beyond the liver.</p>
</sec>
<sec sec-type="conclusion" id="s5">
<label>5</label>
<title>Conclusion</title>
<p>Overall, MASLD represents a biologically heterogeneous condition characterized by variable contributions of insulin resistance and systemic inflammation, mechanisms that are unlikely to respond uniformly to identical dietary prescriptions. Continued reliance on non-stratified nutritional strategies risks obscuring phenotype-dependent responsiveness and limiting therapeutic precision. A pragmatic metabolic-inflammatory phenotyping framework grounded in accessible clinical biomarkers offers a feasible pathway toward operationalizing precision nutrition in MASLD. Prospective validation within stratified clinical trials should therefore be considered a methodological priority to determine whether such an approach enhances therapeutic alignment and improves the interpretability of dietary intervention studies.</p>
</sec>
</body>
<back>
<sec sec-type="author-contributions" id="s6">
<title>Author contributions</title>
<p>AN: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing &#x02013; original draft, Writing &#x02013; review &#x00026; editing.</p>
</sec>
<sec sec-type="COI-statement" id="conf1">
<title>Conflict of interest</title>
<p>The author(s) declared that the article was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="correction-note" id="s200">
<title>Correction note</title>
<p>This article has been corrected with minor changes. These changes do not impact the scientific content of the article.</p>
</sec>
<sec sec-type="ai-statement" id="s8">
<title>Generative AI statement</title>
<p>The author(s) declared that generative AI was used in the creation of this manuscript. Generative AI was used in the language editing of this manuscript.</p>
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<title>Publisher&#x00027;s note</title>
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</sec>
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<fn fn-type="custom" custom-type="edited-by" id="fn0001">
<p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2673729/overview">Berenice M. Rom&#x000E1;n Calleja</ext-link>, National Institute of Medical Sciences and Nutrition Salvador Zubir&#x000E1;n, Mexico</p>
</fn>
<fn fn-type="custom" custom-type="reviewed-by" id="fn0002">
<p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/58411/overview">Giovanni Tarantino</ext-link>, University of Naples Federico II, Italy</p>
<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3157509/overview">Saiful Anuar Bin Singar</ext-link>, Old Dominion University, United States</p>
</fn>
</fn-group>
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