Fibrosis and birthweight correlated with telomere shortening in paediatric metabolic dysfunction-associated steatotic liver disease

Fibrosis and birthweight correlated with telomere shortening in paediatric metabolic dysfunction-associated steatotic liver disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Fibrosis and birthweight correlated with telomere shortening in paediatric metabolic dysfunction-associated steatotic liver disease Anna Alisi, Maria Rita Braghini, Salvatore Daniele Bianco, Marzia Bianchi, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7427772/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Metabolic dysfunction-associated steatotic liver disease (MASLD) is an emerging health concern in both children and adults. A few studies have suggested that dysregulation of telomere-maintaining processes may be a molecular mechanism involved in the disease; however, data in paediatric patients are controversial. This study aimed to evaluate the relationship between telomere length (TL) and hepato-metabolic features in a cohort of children with MASLD. Methods In all, 212 paediatric patients with biopsy-proven MASLD and 31 controls were enrolled in the Hepatology Unit of Bambino Gesù Children's Hospital. TL of leukocytes (LTL) and hepatic cells (HTL) was measured by quantitative polymerase chain reaction (qPCR). Telomerase reverse transcriptase (TERT) mRNA and protein levels were evaluated in a subgroup of liver samples using qPCR and immunofluorescence analyses. TL data association with hepato-metabolic and perinatal features was evaluated using different approaches. Results Our results revealed that children with MASLD had significantly lower LTL and HTL than the control children. TL shortening worsened in more advanced phases of the disease (MASH) and was associated with fibrosis grade. TERT expression was lower in the liver of patients than in controls. LTL was significantly associated with preterm birth and birthweight, and a general linear model highlighted the impact of MASH, fibrosis, and being born small for gestational age on LTL decrease. Conclusion In conclusion, our study demonstrated for the first time a strong relationship between TL and pediatric MASLD-related features, mainly fibrosis. Further studies are needed to clarify the causal relationship between MASH, fibrosis, birthweight and TL. Health sciences/Gastroenterology Health sciences/Gastroenterology/Hepatology/Liver diseases/Non-alcoholic fatty liver disease MASLD MASH fibrosis telomeres children Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction The recently established definitions of metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH), which replaced the term non-alcoholic fatty liver disease (NAFLD), align more closely with the underlying cardiometabolic mechanisms that occur alongside liver steatosis in both adult and child populations [ 1 , 2 ]. The global prevalence of MASLD among adults is around 38% in the general population, rising to 60% among individuals who are obese and/or have type 2 diabetes (T2D). Meanwhile, 7–14% of children and adolescents have MASLD [ 3 , 4 ]. The increased MASLD prevalence is, therefore, a real concern, and although recent clinical trials have identified some drugs for adults that could reduce this escalation in the coming years, the complications associated with this multifaceted disease highlight the need for a more holistic approach [ 3 , 5 , 6 ]. In recent years, in addition to the well-known genetic susceptibility, an increasing number of studies have highlighted the involvement of epigenetics in the complex MASLD inheritance [ 7 ]. Indeed, it has been reported that several prenatal and in-utero epigenetic processes may be associated with disease susceptibility by producing long-term changes in gene transcription [ 8 ]. Moreover, the association between epigenetic changes, lifestyle, and environmental exposure can define patterns that contribute to MASLD development and progression by altering transcriptional networks implicated in redox and lipid homeostasis maintenance, peroxisome and mitochondria function, and inflammation and insulin resistance [ 9 , 10 ]. Therefore, a deeper understanding of epigenetic processes may be relevant for identifying new biomarkers and/or epigenetic-based therapies. A still poorly investigated epigenetic trait in MASLD patients is telomere length (TL) that depends on both the expression of a telomerase reverse transcriptase (TERT) and parental inheritance [ 11 , 12 ]. Telomeres are nucleoprotein structures located at the end of each chromosome and consist of a highly conserved hexameric (TTAGGG) tandem repeat DNA sequence that is necessary for maintaining genome stability. In fact, during DNA replication, owing to the mechanism of action of DNA polymerase, the length of DNA is lost at the 5′ end of the chromosomes. The control of TL is dictated by the action of a ribonucleoprotein complex consisting of a TERT catalytic subunit that synthesises new telomeric repeats by copying its RNA component [ 13 ]. Reduced TL was also reported to be uncoupled from ageing but was associated with various diseases, including MASLD. In particular, clinical studies in adults have found an association between shorter leukocyte TL (LTL) and the prevalence of MASLD [ 14 – 17 ], while a few studies have demonstrated that TL is also correlated with liver damage [ 15 , 18 , 19 ]. However, clear evidence of the correlation of LTL shortening and MASLD in children is still lacking. Here, we firstly analysed LTL in 212 children with biopsy-proven MASLD compared to 31 children with a healthy liver, and then evaluated the potential association between LTL and anthropological, clinical, histological, and perinatal features in paediatric MASLD. Patients and methods Patients This study included 212 children with biopsy-proven MASLD and 31 children with no evidence of MASLD evaluated by ultrasonography. Patients were enrolled at the Hepatology Unit of the "Bambino Gesù" Children's Hospital from March 2019 to April 2023. In particular, for the present retrospective observational study, according to the approved protocol, samples and data were collected at the Research Unit of Genetics of Complex Phenotypes at the Hospital, and written informed consent for future use was obtained from each child's parent or legal guardian at the time of enrolment. The study was conducted in accordance with the principles of the Declaration of Helsinki and approved by the Ethics Committee of Bambino Gesù Children's Hospital (protocol number: 417, April 6, 2023). Patients' height, weight, waist circumference and body mass index (BMI) were assessed at the time of enrolment using standard procedures. Triglycerides, total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, alanine aminotransferase (ALT), aspartate aminotransferase (AST), and gamma-glutamyl transpeptidase (GGT) levels were measured using standard laboratory methods. The homeostasis model assessment of insulin resistance (HOMA-IR) was calculated using the following formula: fasting insulin x fasting glucose/22.5. Liver histology Liver biopsies were performed in all patients using an automatic core biopsy needle (16 or 18 gauge) under general anaesthesia and ultrasound guidance. Histological evaluation and grading of fibrosis were performed according to the NASH- Clinical Research Network CRN criteria [20]. Diagnosis of MASH was defined according to the algorithm recently suggested in the Delphi consensus [1]. In particular, MASH was defined with a NAS≥ 5, or with a NAS≥ 4 plus fibrosis F>1. A definitive diagnosis of MASH or non-MASH was reached only when the two pathologists agreed on the diagnosis. Assessment of TL For the assessment of LTL leucocytes, DNA was extracted from peripheral blood using the QIAmp DNA Blood Mini Kit (Qiagen, Hilden, Germany), while for the assessment of HTL, DNA was extracted from liver tissues using the AllPrep DNA/RNA/Protein Mini Kit (Qiagen). Next, TL was determined using the Real-Time quantitative Polymerase Chain Reaction (qPCR) method, as reported by O'Callaghan and Fenech [21]. In particular, qPCR assay was performed by a QuantStudio 7 Pro Real-Time PCR System (Applied Biosystems-Thermo Fisher Scientific, Waltham, MA, USA) using the following primers: Telomere forward (Fwd) (CGGTTTGTTTGGGTTTGGGTTTGGGTTTGGGTTTGGGTT) and Telomere reverse (Rev) (GGCTTGCCTTACCCTTACCCTTACCCTTACCCTTACCCT). To normalise DNA input, the gene 36B4 (acid ribosomal protein 36B4) was used as a single-copy gene, and was measured using the following primers: 36B4 Fwd (CAGCAAGTGGGAAGGTGTAATCC) and 36B4 Rev (CCCATTCTATCATCAACGGGTACAA). The measure of telomeres and single-copy genes was determined by generating a standard curve on each plate by performing a serial dilution of a known amount of oligomer standard for either telomere (TTAGGG)14 and 36B4 gene (CAGCAAGTGGGAAGGTGTAATCCGTCTCCACAGACAAGGCCAGGACTCGTTTGTACCCGTTGATGATAGAATGGG). All primers were used at a final concentration of 0.1μM and were purchased from Merck (Rahway, NJ, USA). Nucleic acid extraction and qPCR in liver tissue samples This method was reported in the Supplementary Information file. Immunofluorescence in liver tissue samples This method was reported in the Supplementary Information file. Sample size estimation Assuming a mean clinically relevant difference of 0.07 kb between the two groups as previously reported for young adults by Kim et al. [15], the estimated minimum sample size was 26 subjects per group using a two-sided significance level (α) of 0.05 and a statistical power of 95%. For the comparison between MASH and non-MASH, the estimate was of at least 66 subjects per group using a two-sided significance level (α) of 0.05 and a statistical power of 85%. Statistics Differences between groups were assessed using the Mann-Whitney U or one-way ANOVA. Spearman correlation and simple linear regression analyses were used to assess associations between telomere length (TL) and clinical or perinatal variables using GraphPad Prism version 8.4.3 (GraphPad Software, La Jolla, CA, USA).tests and were Multiple linear regression analyses were performed to assess the relationship between TL and anthropometric, biochemical, and histological variables. These were conducted using Python version 3.12 in Google Colab with the Pandas (v2.2.3) and Statsmodels (v0.14.4) libraries. The models were fitted using the ordinary least squares method. In analyses assessing the impact of fibrosis, portal inflammation, and perinatal categories (SGA, AGA, LGA) on TL, a Generalized Linear Model (GLM) was also fitted with TL as the dependent variable. Model coefficients were tested using Wald tests. All statistical analyses were considered significant at a p-value<0.05. Results LTL in children and adolescents with MASLD The characteristics of the study population are reported in Table S1 . Briefly, the control group (CTRL) included 31 children with healthy livers and no evidence of MASLD, as assessed by ultrasonography, comprising 16 males and 15 females, with a median age of 8 years (range, 2–18 years). The patient cohort consisted of 212 children with MASLD, comprising 131 males and 81 females, with a median age of 13.7 years (range, 5.2–17.9 years). As highlighted in Table S1 , the MASLD cohort exhibited significantly higher values for BMI, triglycerides, HDL cholesterol, and ALT than the control group (p < 0.01). As shown in Fig. 1 A-B, LTL was reported either as the natural logarithm of TL in kb per human diploid genome (log-TL) or as the natural logarithm of Telomere/Single copy gene ratio (log-T/S), which was significantly shorter in patients with MASLD than in CTRL (p < 0.001). The shortened LTL was further validated through analysis of a subgroup of age-matched controls (CTRL AM) and patients with MASLD (MASLD AM) (Fig. 1 C-D). LTL in paediatric MASLD stratified for the presence of MASH According to the Delphi consensus guidelines for the diagnosis of MASH [ 1 ], our cohort of patients with MASLD was divided into non-MASH (67 patients, 31.6%) and MASH (145 patients, 68.4%) groups. Biochemical and anthropometric variables of the patients are shown in Table 1 . Briefly, patients with MASH had significantly higher (p < 0.0001) levels of ALT, AST, GGT, and HOMA-IR and significantly lower (p = 0.0001) levels of LDL cholesterol than those without MASH. The histological characteristics of the MASH and non-MASH groups are presented in Table S2 . Table 1 Biochemical and anthropometrical characteristics of paediatric patients with MASLD without or with MASH. Variable non-MASH (n = 67) MASH (n = 145) p value Gender (M/F) 36/31 95/50 0.1282 Age (years) 13 (5–18) 14 (6–18) 0.5834 BMI (kg/m 2 ) 28.2 (16.5–47.4) 29.1 (21.2-39-9) 0.5842 WC (cm) 89 (67–134) 86 (60–112) 0.5468 Triglycerides (mg/dL) 100 (39–225) 89 (35–277) 0.2038 Total cholesterol (mg/dL) 154 (93–210) 156 (91–298) 0.5044 HDL cholesterol (mg/dL) 47 (21–114) 48 (20–112) 0.5685 LDL cholesterol (mg/dL) 97 (48–153) 73 (33–145) 0.0001 ALT (IU/mL) 25 (8–82) 40 (16–265) < 0.0001 AST (IU/mL) 25 (12–40) 31 (19–109) < 0.0001 GGT (IU/mL) 14 (3–43) 23 (9-101) < 0.0001 HOMA-IR 3.7 (0.2–10.4) 4.2 (2.1–15.8) < 0.0001 Values are expressed as median and range (minimum – maximum). Fisher’s exact test for gender distribution and the Mann-Whitney test for continuous variables. Abbreviations: MASH, metabolic dysfunction-associated steatohepatitis; M, males; F, females; WC, waist circumference; BMI, body mass index; HDL, high-density lipoprotein; LDL, low-density lipoprotein; ALT, alanine transaminase; AST, aspartate transaminase; GGT, gamma glutamyl transpeptidase; HOMA-IR, homeostasis model assessment of insulin resistance. When we analysed the differences in LTL in these groups, it emerged that patients with MASH had a significantly shorter LTL than non-MASH patients (p < 0.001) (Fig. 2 A-B). Moreover, Spearman’s correlation analysis confirmed an inverse association between the presence of MASH and LTL (r=-0.64, p < 0.001). As the values of LTL expressed in kb or as the T/S ratio followed the same trend, in the following analyses, we only show LTL expressed as the natural logarithm of TL in kb per human diploid genome (log-TL). LTL correlation with anthropometric, metabolic and histological parameters in patients with MASLD To further investigate the significance of the LTL decrease in patients with MASH, we conducted a multiple linear regression analysis considering log-TL as the dependent variable and anthropometric and biochemical parameters as independent variables. As shown in Table S3 , neither anthropometric nor biochemical features had a significant impact on LTL regardless of whether adjustments were made for BMI and age. In contrast, when we used histological features (i.e., steatosis, portal inflammation, lobular inflammation, ballooning, and fibrosis) and NAS as independent variables, we found that LTL was significantly correlated with fibrosis (p < 0.001) (Table 2 ). Indeed, LTL significantly decreased with increasing fibrosis severity in MASLD patients (p < 0.001) (Fig. 3 A). Among all patients with MASLD, those with fibrosis grade 0 had a mean log-TL of 5.440, those with fibrosis grade 1 had a mean log-TL of 3.720, and those with fibrosis grade 2 had a mean log-TL of 3.483 (Fig. 3 A). The same decreasing trend was observed in the subgroup of patients with MASH, with mean log-TL values of 4.190, 3.611, and 3.483 for F0, F1, and F2, respectively (Fig. 3 B). Table 2 Multiple linear regression analysis of LTL estimates in patients with MASLD. Dependent variable: log-TL Model β SE p value Intercept 328.705 50.595 0.000 Steatosis -85.017 140.732 0.547 Portal Inflammation 14.486 22.864 0.527 Lobular Inflammation -117.743 144.066 0.415 Ballooning -85.264 144.878 0.557 Fibrosis -104.990 19.583 0.000 NAS 62.469 141.732 0.660 Model R 2 = 0.350. Abbreviations: log-TL, natural logarithm of telomere length in kilobases; β, regression coefficient; SE, standard error, NAS, NAFLD activity score. TL evaluation in the liver of patients with MASLD Next, we analysed HTL in a sub-cohort of 15 patients with MASLD (MASLD) for whom liver biopsy tissue was available in our laboratory and three healthy liver donors (CTRL). We found that the mean log-HTL of patients with MASLD was 3.463, while that of controls was 3.725 (p = 0.002) (Fig. 4 A). To further investigate the molecular mechanisms underlying telomere shortening, we analysed the expression of the enzyme TERT responsible for telomere maintenance. Interestingly, qPCR analysis revealed a decrease in TERT gene (Fig. 4 B) and protein expression in the MASLD group compared to that in the CTRL group (Fig. 4 C-D). Finally, multiple linear regression analysis was conducted with log-HTL as the dependent variable and the histological features of steatosis, portal inflammation, lobular inflammation, ballooning, fibrosis, and NAS score as independent variables, confirming the significant association between fibrosis and TL even at the hepatic level (SE = 0.064, β=-0.169, R 2 = 0.605, p = 0.037). Interestingly, portal inflammation was also significantly correlated with log-HTL (SE = 0.100, β=-0.265, R 2 = 0.605, p = 0.038). LTL association with gestational age and breastfeeding data of patients with MASLD The relationship between MASLD-related damage and LTL in an adult setting may be attributed to chronic low-grade inflammation, multiple tissue inflammation, and lymphocyte senescence [ 17 ]. However, it remains to be explained why LT shortening also occurs in paediatric MASLD. One hypothesis is that TL dynamics during childhood could be predetermined before birth by early life factors, as suggested by previous studies [ 22 , 23 ]. Therefore, we investigated the possible association between LTL and early life factors, including birthweight, gestational age, mode of delivery (natural or caesarean), and preterm and breastfeeding status, in our cohort of patients with MASLD. Spearman correlation analysis revealed that LTL was significantly associated with birthweight (r = 0.163, p = 0.017), gestational age (r = 0.138, p = 0.044), and preterm birth (r=-0.169, p = 0.014). Simple linear regression analyses (Fig. 5 A-C) confirmed significant associations between LTL and birth weight (p = 0.022) and preterm birth (p = 0.006) as well as a nearly significant association with gestational age (p = 0.059). To further investigate the relationship between LTL, birthweight, gestational age, and MASLD pattern, the patients were divided into three groups based on whether they were born with a weight that was small, appropriate, or large for their gestational age (SGA, AGA, or LGA). Interestingly, multiple comparisons between the groups revealed significant differences in log-TL between patients born SGA and LGA (p = 0.004) (Fig. 5 D). Construction of a generalized linear model with emerging histological and perinatal features as predictors of LTL Finally, we evaluated the relationship between the presence of fibrosis, portal inflammation, MASH, and SGA/AGA/LGA pattern with log-TL. Pairwise Spearman correlation analysis showed that log-TL was significantly inversely correlated with both fibrosis (r=–0.66, p = 2.06×10⁻²⁷) and MASH (r=–0.64, p = 1.69×10⁻²⁵). As expected, fibrosis and MASH were positively correlated (r = 0.69, p = 3.27×10⁻³¹) (Fig. 6 A). We then fitted a Generalized Linear Model (GLM) with log-TL as the dependent variable and fibrosis, MASH, portal inflammation, and SGA/AGA/LGA classification as predictors. Both fibrosis and MASH were significantly negatively associated with log-TL (Wald tests: p = 2.09×10⁻²⁶ and p = 5.71×10⁻⁹, respectively), while being born LGA was significantly associated with higher log-TL values (Wald test: p = 0.009). No significant association was observed for portal inflammation (Wald test: p = 0.568) (Fig. 6 B). Discussion In this study, we evaluated TL from peripheral blood leukocytes and in the liver in a cohort of paediatric patients with biopsy-proven MASLD compared to healthy controls. To date, only a few studies have analysed TL in children and adolescents with MASLD; however, data are controversial [ 24 – 26 ]. Our results demonstrated that the LTL was lower in patients with MASLD than in healthy controls. Interestingly, LTL shortening worsened with the progression of liver damage. Indeed, patients with MASH had a shorter LTL than patients in the early phases of the disease (non-MASH). These findings align with those of previous studies in adult patients with MASLD, which suggest that telomere shortening is involved in liver disease progression [ 17 , 27 , 28 ]. In addition, studies in adult patients have demonstrated that shortened telomeres are associated with more advanced fibrosis stages [ 15 , 19 , 29 , 30 ]. Our data are consistent with this observation. We found a significant negative correlation between fibrosis grade, as evaluated by biopsy, and LTL, with a decreasing trend in LTL accompanied by increasing fibrosis stage. According to the leukocyte data, TL was decreased in the liver of patients with MASLD compared to that in healthy liver donors. As observed in the case of LTL, HTL was negatively correlated with the fibrosis grades of the patients, thus reinforcing the hypothesis of a possible causal relationship between MASLD-related liver damage and TL shortening. Moreover, HTL was also associated with the severity of portal inflammation, which is a specific hallmark of tissue necro-inflammation in the paediatric population [ 31 ]. To evaluate whether telomere shortening at the hepatic level was associated with dysregulation of the factors involved in preserving their integrity, we assessed TERT gene/protein expression in a sub-cohort of MASLD liver samples. We found that patients with MASLD had statistically lower mRNA and protein levels of TERT compared with control healthy livers. A previous study demonstrated that TERT deficiency, causing accelerated telomere shortening, was a predisposing factor for cirrhosis development, suggesting that telomere dysfunction may be a molecular event in the pathophysiology of fibrosis and then cirrhosis [ 32 ]. In line with these findings, Donati et al. [ 33 ] demonstrated that LTL decreased with liver disease progression from healthy controls to cirrhosis to hepatocellular carcinoma (HCC) in a MASLD background. The authors hypothesised that the progressive LTL decrease may promote the consumption of the stem cell pool, senescence and fibrosis of adult cells, thus favouring genomic instability and HCC onset. Possible mechanisms of TERT gene down-regulation in MASLD and particularly in fibrosis progression, including epigenetic control and telomere position effects, deserve further exploration [ 34 ]. Even if it was reported that telomere attrition rate slows in childhood and adolescence, and telomeres then continue to shorten at a slower rate across adulthood, it is conceivable that early life factors could be particularly relevant in predicting TL shortening in paediatric patients with MASLD. Among early life factors, birthweight, gestational age, type of delivery and breastfeeding could have an effect on LTL, as well as on MASLD severity in a paediatric setting [ 8 , 35 , 36 ]. Indeed, when we investigated the possible association between perinatal features, including birthweight, gestational age, birth type, and breastfeeding with LTL, we found a significant association of LTL with preterm birth and birth weight, but more importantly, we demonstrated that the presence of fibrosis and MASH, and being born SGA may predict lower TL in paediatric MASLD. These findings allow us to speculate that the intrauterine state induces epigenetic adaptations that significantly influence TL attrition at birth, thus increasing the risk of MASLD in later life and influencing the risk of advanced fibrosis and all-cause mortality, as recently reported by Kim et al [ 37 ]. This study has two significant limitations, including the small size of the control group and the lack of an independent cohort of children with biopsy-proven MASLD. Nonetheless, our pilot study highlights for the first time a significant reduction in TL among children with MASLD compared with controls, with telomere shortening enhanced in patients with MASH and fibrosis. Further studies are needed to validate our results and to investigate potential causal relationships between TL, the severity of disease, and birthweight. In conclusion, our research revealed a correlation between epigenetic regulation of TL and hepatic damage in paediatric MASLD, primarily MASH and fibrosis, which may potentially support the identification of high-risk children who may develop a progressive disease at a later age. Declarations Conflicts of interest: nothing to report. Author contributions: M.R.B. contributed to the conceptualisation of the study, execution of the experiments, analysis of the data and writing of the manuscript; S.D.B. contributed to the analysis of the data; M.B. contributed to the execution of the experiments; G.A. contributed to the execution of the experiments; A.M. contributed to the patients’ enrolment and data collection; C.D.S. contributed to the execution of the experiments; M.P. contributed to the execution of the experiments; P.F. contributed to the critical review and editing of the manuscript; C.B. contributed to the critical review and editing of the manuscript; L.M. contributed to the critical review and editing of the manuscript; T.M. contributed to the analysis of the data and critical review and editing of the manuscript; A.A. contributed to the conceptualisation of the study, analysis of the data, and writing, critical review and editing of the manuscript. All authors read and approved the final manuscript. Acknowledgments A.A. discloses support for the research of this work from the Italian Ministry of Health with “Ricerca Finalizzata” (grant number RF-2021-12372565) and “Current Research” funds. M.R.B. discloses support for publication of this work from “AISF Associazione Italiana per lo Studio del Fegato” for a one-year fellowship. Data availability: The dataset used in this study may be obtained from the corresponding author upon reasonable request. References Rinella, M.E. et al . A multisociety Delphi consensus statement on new fatty liver disease nomenclature. J. Hepatol . 79, 1542–1556 (2023). Zhang, L. et al . An international multidisciplinary consensus on pediatric metabolic dysfunction-associated fatty liver disease. Med. 5, 797–815 (2024). Miao, L., Targher, G., Byrne, C.D., Cao, Y.Y. & Zheng, M.H. Current status and future trends of the global burden of MASLD. Trends Endocrinol. Metab. 35, 697–707 (2024). Younossi, Z.M., Kalligeros, M. & Henry, L. 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Dogan, F. & Forsyth, N.R. Telomerase Regulation: A Role for Epigenetics. Cancers (Basel) . 13, 1213 (2021). Bugianesi, E. et al . Low Birthweight Increases the Likelihood of Severe Steatosis in Pediatric Non-Alcoholic Fatty Liver Disease. Am. J. Gastroenterol . 112, 1277–1286 (2017). Ebrahimi, F. et al . Birth Weight, Gestational Age, and Risk of Pediatric-Onset MASLD. JAMA Netw. Open . 7, e2432420 (2024). Kim, D., Danpanichkul, P., Wijarnpreecha, K., Cholankeril, G. & Ahmed, A. Leukocyte telomere shortening in metabolic dysfunction-associated steatotic liver disease and all-cause/cause-specific mortality. Clin. Mol. Hepatol. 30, 982–986 (2024). Additional Declarations There is NO Competing Interest. Supplementary Files BraghinietalsupplementaryinformationCommMedicine.docx Supplementary data Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7427772","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":512546230,"identity":"431882d4-8f15-4d78-9118-b05815d8f9c9","order_by":0,"name":"Anna Alisi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYPACCx4GZuYDDIwNxGuRAGphS4BqYSZOCxDzGBCnhX9278EPDDUSMvLtPB8fF+6oZTBn7z+A3/g755IlGI5J8Bgc5t1sPPPMcQbLnsMEnHQjx0CCgQ2ohZl3mzRv2zEGgxvJ+HXI38gx/sHwT4JHvpnnGUTL/cf4tRjcyDGTYGwDhthhHjaglhqgCAHvGwK1WCT2gfzCZgz0ywEegzPJBni1yAEdduPDNxt7+f7DD4EhVidncPzgA/zWgEAClAa66DAPYeXIAKiljjQdo2AUjIJRMCIAAMXFP1shSlUfAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-7241-6329","institution":"Bambino Gesù Children's Hospital and IRCCS","correspondingAuthor":true,"prefix":"","firstName":"Anna","middleName":"","lastName":"Alisi","suffix":""},{"id":512546231,"identity":"26b13cc1-3b30-4664-82be-1a747e58fa38","order_by":1,"name":"Maria Rita Braghini","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Rita","lastName":"Braghini","suffix":""},{"id":512546232,"identity":"7098bf85-0119-41df-81a9-c22c2b400204","order_by":2,"name":"Salvatore Daniele Bianco","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Salvatore","middleName":"Daniele","lastName":"Bianco","suffix":""},{"id":512546233,"identity":"6e209a30-d715-4a7d-8cb5-37e1b40fcda5","order_by":3,"name":"Marzia Bianchi","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Marzia","middleName":"","lastName":"Bianchi","suffix":""},{"id":512546234,"identity":"c019a53b-69e6-41bc-a6c7-f101eda22387","order_by":4,"name":"Giulia Andolina","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Giulia","middleName":"","lastName":"Andolina","suffix":""},{"id":512546235,"identity":"8f463929-4aa7-4c45-9cba-fbdd55794157","order_by":5,"name":"Antonella Mosca","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Antonella","middleName":"","lastName":"Mosca","suffix":""},{"id":512546236,"identity":"98f5c3bb-3f4b-4acd-ba8b-d972649abdd4","order_by":6,"name":"Cristiano De Stefanis","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Cristiano","middleName":"","lastName":"De Stefanis","suffix":""},{"id":512546237,"identity":"528ac966-f148-4fe0-9ebe-532ccb1a1984","order_by":7,"name":"Michela Piccione","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Michela","middleName":"","lastName":"Piccione","suffix":""},{"id":512546238,"identity":"0dacc9d7-311b-4972-bd8e-53b7bb2929d6","order_by":8,"name":"Paola Francalanci","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Paola","middleName":"","lastName":"Francalanci","suffix":""},{"id":512546239,"identity":"1b84ebc1-e760-413f-8400-16d6793446aa","order_by":9,"name":"Clara Balsano","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Clara","middleName":"","lastName":"Balsano","suffix":""},{"id":512546240,"identity":"8fdbfc39-cd8d-4c20-b8c1-c2ef492196e2","order_by":10,"name":"Luca Miele","email":"","orcid":"https://orcid.org/0000-0003-3464-0068","institution":"Policlinico Gemelli Roma","correspondingAuthor":false,"prefix":"","firstName":"Luca","middleName":"","lastName":"Miele","suffix":""},{"id":512546241,"identity":"114c7f52-52e6-4bdb-a5cc-039c18b3b285","order_by":11,"name":"Tommaso Mazza","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Tommaso","middleName":"","lastName":"Mazza","suffix":""}],"badges":[],"createdAt":"2025-08-21 15:46:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7427772/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7427772/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91510225,"identity":"6311ce28-40c6-4b35-a720-be04dcd07127","added_by":"auto","created_at":"2025-09-17 08:43:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":270364,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLTL lowered in paediatric patients with MASLD with respect to controls. \u003c/strong\u003eViolin plots reporting the mean log-TL (\u003cstrong\u003eA\u003c/strong\u003e) and log-T/S (\u003cstrong\u003eB\u003c/strong\u003e) in CTRL and in patients with MASLD (p\u0026lt;0.001); and reporting the mean log-TL (\u003cstrong\u003eC\u003c/strong\u003e) and log-T/S (\u003cstrong\u003eD\u003c/strong\u003e) in the subgroups of CTRL and patients with MASLD age-matched (AM) (p\u0026lt;0.001).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7427772/v1/e7702cff569e601d23a4cf54.png"},{"id":91510228,"identity":"07ede0fe-ab9d-468b-ab50-10efe1ae4e62","added_by":"auto","created_at":"2025-09-17 08:43:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":141546,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvaluation of LTL in paediatric patients with MASLD non-MASH and MASH. \u003c/strong\u003eViolin plots reporting the (\u003cstrong\u003eA\u003c/strong\u003e) mean log-TL and (\u003cstrong\u003eB\u003c/strong\u003e) log-T/S in patients with MASLD non-MASH and MASH (p\u0026lt;0.001).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7427772/v1/53773430093c9ed4a2b32ec0.png"},{"id":91510227,"identity":"1fbfdf0d-9cdb-4510-af3f-7b5b05576708","added_by":"auto","created_at":"2025-09-17 08:43:37","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":116285,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLTL is associated with liver fibrosis grade. \u003c/strong\u003eViolin plots reporting the mean log-TL in (\u003cstrong\u003eA\u003c/strong\u003e) all patients with MASLD and in (\u003cstrong\u003eB\u003c/strong\u003e) the subgroup of patients with MASH and fibrosis grade 0, 1, and 2.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7427772/v1/59e078d272c4b2e97d694447.png"},{"id":91511610,"identity":"d45b287c-a67e-4db5-b7ab-bb2eb7fabf2e","added_by":"auto","created_at":"2025-09-17 08:51:37","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1209532,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHTL and TERT expression in the liver of patients with MASLD. \u003c/strong\u003eHistograms reporting the (\u003cstrong\u003eA\u003c/strong\u003e) mean values of log-HTL, (\u003cstrong\u003eB\u003c/strong\u003e) \u003cem\u003eTERT\u003c/em\u003e mRNA relative expression, and (\u003cstrong\u003eC\u003c/strong\u003e) TERT mean fluorescence intensity in CTRL and MASLD groups. *p\u0026lt;0.05, **p\u0026lt;0.01. (\u003cstrong\u003eD\u003c/strong\u003e) Representative immunofluorescence by confocal imaging of TERT protein in CTRL and MASLD. The technical control of secondary antibody staining is reported (Ab II). 40× magnification.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7427772/v1/1de693cd630d49a5058e7954.png"},{"id":91510232,"identity":"4ab9f149-748d-4e58-9c5d-affa5d1109d8","added_by":"auto","created_at":"2025-09-17 08:43:37","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":463248,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLTL association with gestation and birth features of patients with MASLD. \u003c/strong\u003eSimple linear regression analyses between log-TL and (\u003cstrong\u003eA\u003c/strong\u003e) birthweight, (\u003cstrong\u003eB\u003c/strong\u003e) preterm birth and (\u003cstrong\u003eC\u003c/strong\u003e) gestational age in patients with MASLD. (\u003cstrong\u003eD\u003c/strong\u003e) Violin plots reporting the mean log-TL in patients with MASLD grouped for being born SGA, AGA and LGA. One-way ANOVA test between, **p\u0026lt;0.01.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7427772/v1/be76cf0b867dafa27e90c04e.png"},{"id":91510236,"identity":"0824f26d-4495-4d8b-91b1-667f15a0be73","added_by":"auto","created_at":"2025-09-17 08:43:37","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1030887,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(A)\u003c/strong\u003e Pairwise Spearman correlations between clinical variables. \u003cstrong\u003e(B)\u003c/strong\u003e Point estimates (vertical ticks) and 95% confidence intervals (horizontal lines) represent the coefficients from a Generalised Linear Model (GLM) fitted to log-TL as a function of the following clinical variables: Appropriate for Gestational Age (continuous), Portal Inflammation, Fibrosis, and MASH (all categorical). A vertical dashed line at 0 indicates no effect on log-TL.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7427772/v1/629e1aa9ed035e1d63136796.png"},{"id":101943139,"identity":"df3ae6cf-7e99-4a29-b3a1-5e82699653b4","added_by":"auto","created_at":"2026-02-05 09:40:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4107125,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7427772/v1/3c952a8b-36d0-47d9-9c6e-b377afdffd14.pdf"},{"id":91511608,"identity":"9c802c9c-8138-4f28-ac46-4dcef625a53d","added_by":"auto","created_at":"2025-09-17 08:51:37","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":29908,"visible":true,"origin":"","legend":"Supplementary data","description":"","filename":"BraghinietalsupplementaryinformationCommMedicine.docx","url":"https://assets-eu.researchsquare.com/files/rs-7427772/v1/06e12ab3568feba3a1de3c1a.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Fibrosis and birthweight correlated with telomere shortening in paediatric metabolic dysfunction-associated steatotic liver disease","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe recently established definitions of metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH), which replaced the term non-alcoholic fatty liver disease (NAFLD), align more closely with the underlying cardiometabolic mechanisms that occur alongside liver steatosis in both adult and child populations [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe global prevalence of MASLD among adults is around 38% in the general population, rising to 60% among individuals who are obese and/or have type 2 diabetes (T2D). Meanwhile, 7\u0026ndash;14% of children and adolescents have MASLD [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The increased MASLD prevalence is, therefore, a real concern, and although recent clinical trials have identified some drugs for adults that could reduce this escalation in the coming years, the complications associated with this multifaceted disease highlight the need for a more holistic approach [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In recent years, in addition to the well-known genetic susceptibility, an increasing number of studies have highlighted the involvement of epigenetics in the complex MASLD inheritance [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Indeed, it has been reported that several prenatal and \u003cem\u003ein-utero\u003c/em\u003e epigenetic processes may be associated with disease susceptibility by producing long-term changes in gene transcription [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Moreover, the association between epigenetic changes, lifestyle, and environmental exposure can define patterns that contribute to MASLD development and progression by altering transcriptional networks implicated in redox and lipid homeostasis maintenance, peroxisome and mitochondria function, and inflammation and insulin resistance [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Therefore, a deeper understanding of epigenetic processes may be relevant for identifying new biomarkers and/or epigenetic-based therapies.\u003c/p\u003e\u003cp\u003eA still poorly investigated epigenetic trait in MASLD patients is telomere length (TL) that depends on both the expression of a telomerase reverse transcriptase (TERT) and parental inheritance [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Telomeres are nucleoprotein structures located at the end of each chromosome and consist of a highly conserved hexameric (TTAGGG) tandem repeat DNA sequence that is necessary for maintaining genome stability. In fact, during DNA replication, owing to the mechanism of action of DNA polymerase, the length of DNA is lost at the 5\u0026prime; end of the chromosomes. The control of TL is dictated by the action of a ribonucleoprotein complex consisting of a TERT catalytic subunit that synthesises new telomeric repeats by copying its RNA component [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Reduced TL was also reported to be uncoupled from ageing but was associated with various diseases, including MASLD. In particular, clinical studies in adults have found an association between shorter leukocyte TL (LTL) and the prevalence of MASLD [\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], while a few studies have demonstrated that TL is also correlated with liver damage [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. However, clear evidence of the correlation of LTL shortening and MASLD in children is still lacking.\u003c/p\u003e\u003cp\u003eHere, we firstly analysed LTL in 212 children with biopsy-proven MASLD compared to 31 children with a healthy liver, and then evaluated the potential association between LTL and anthropological, clinical, histological, and perinatal features in paediatric MASLD.\u003c/p\u003e"},{"header":"Patients and methods","content":"\u003cp\u003e\u003cem\u003ePatients\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study included 212 children with biopsy-proven MASLD and 31 children with no evidence of MASLD evaluated by ultrasonography. Patients were enrolled at the Hepatology Unit of the \u0026quot;Bambino Ges\u0026ugrave;\u0026quot; Children\u0026apos;s Hospital from March 2019 to April 2023. In particular, for the present retrospective observational study, according to the approved protocol, samples and data were collected at the Research Unit of Genetics of Complex Phenotypes at the Hospital, and written informed consent for future use was obtained from each child\u0026apos;s parent or legal guardian at the time of enrolment. The study was conducted in accordance with the principles of the Declaration of Helsinki and approved by the Ethics Committee of Bambino Ges\u0026ugrave; Children\u0026apos;s Hospital (protocol number: 417, April 6, 2023). Patients\u0026apos; height, weight, waist circumference and body mass index (BMI) were assessed at the time of enrolment using standard procedures. Triglycerides, total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, alanine aminotransferase (ALT), aspartate aminotransferase (AST), and gamma-glutamyl transpeptidase (GGT) levels were measured using standard laboratory methods. The homeostasis model assessment of insulin resistance (HOMA-IR) was calculated using the following formula: fasting insulin x fasting glucose/22.5.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLiver histology\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eLiver biopsies were performed in all patients using an automatic core biopsy needle (16 or 18 gauge) under general anaesthesia and ultrasound guidance. Histological evaluation and grading of fibrosis were performed according to the NASH- Clinical Research Network CRN criteria [20]. Diagnosis of MASH was defined according to the algorithm recently suggested in the Delphi consensus [1]. In particular, MASH was defined with a NAS\u0026ge; 5, or with a NAS\u0026ge; 4 plus fibrosis F\u0026gt;1. A definitive diagnosis of MASH or non-MASH was reached only when the two pathologists agreed on the diagnosis.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAssessment of TL\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFor the assessment of LTL leucocytes, DNA was extracted from peripheral blood using the QIAmp DNA Blood Mini Kit (Qiagen, Hilden, Germany), while for the assessment of HTL, DNA was extracted from liver tissues using the AllPrep DNA/RNA/Protein Mini Kit (Qiagen). Next, TL was determined using the Real-Time quantitative Polymerase Chain Reaction (qPCR) method, as reported by O\u0026apos;Callaghan and Fenech [21]. In particular, qPCR assay was performed by a QuantStudio 7 Pro Real-Time PCR System (Applied Biosystems-Thermo Fisher Scientific, Waltham, MA, USA) using the following primers: Telomere forward (Fwd) (CGGTTTGTTTGGGTTTGGGTTTGGGTTTGGGTTTGGGTT) and Telomere reverse (Rev) (GGCTTGCCTTACCCTTACCCTTACCCTTACCCTTACCCT). To normalise DNA input, the gene \u003cem\u003e36B4\u003c/em\u003e (acid ribosomal protein 36B4) was used as a single-copy gene, and was measured using the following primers: 36B4 Fwd (CAGCAAGTGGGAAGGTGTAATCC) and 36B4 Rev (CCCATTCTATCATCAACGGGTACAA). The measure of telomeres and single-copy genes was determined by generating a standard curve on each plate by performing a serial dilution of a known amount of oligomer standard for either telomere (TTAGGG)14 and \u003cem\u003e36B4\u003c/em\u003e gene (CAGCAAGTGGGAAGGTGTAATCCGTCTCCACAGACAAGGCCAGGACTCGTTTGTACCCGTTGATGATAGAATGGG). All primers were used at a final concentration of 0.1\u0026mu;M and were purchased from Merck (Rahway, NJ, USA).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNucleic acid extraction and qPCR in liver tissue samples\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis method was reported in the Supplementary Information file.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eImmunofluorescence in liver tissue samples\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis method was reported in the Supplementary Information file.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSample size estimation\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAssuming a mean clinically relevant difference of 0.07 kb between the two groups as previously reported for young adults by Kim et al. [15], the estimated minimum sample size was 26 subjects per group using a two-sided significance level (\u0026alpha;) of 0.05 and a statistical power of 95%. For the comparison between MASH and non-MASH, the estimate was of at least 66 subjects per group using a two-sided significance level (\u0026alpha;) of 0.05 and a statistical power of 85%.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStatistics\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eDifferences between groups were assessed using the Mann-Whitney U or one-way ANOVA. Spearman correlation and simple linear regression analyses were used to assess associations between telomere length (TL) and clinical or perinatal variables using GraphPad Prism version 8.4.3 (GraphPad Software, La Jolla, CA, USA).tests and were \u0026nbsp;Multiple linear regression analyses were performed to assess the relationship between TL and anthropometric, biochemical, and histological variables. These were conducted using Python version 3.12 in Google Colab with the Pandas (v2.2.3) and Statsmodels (v0.14.4) libraries. The models were fitted using the ordinary least squares method. In analyses assessing the impact of fibrosis, portal inflammation, and perinatal categories (SGA, AGA, LGA) on TL, a Generalized Linear Model (GLM) was also fitted with TL as the dependent variable. Model coefficients were tested using Wald tests. All statistical analyses were considered significant at a p-value\u0026lt;0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eLTL in children and adolescents with MASLD\u003c/h2\u003e\u003cp\u003eThe characteristics of the study population are reported in \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e. Briefly, the control group (CTRL) included 31 children with healthy livers and no evidence of MASLD, as assessed by ultrasonography, comprising 16 males and 15 females, with a median age of 8 years (range, 2\u0026ndash;18 years). The patient cohort consisted of 212 children with MASLD, comprising 131 males and 81 females, with a median age of 13.7 years (range, 5.2\u0026ndash;17.9 years). As highlighted in \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e, the MASLD cohort exhibited significantly higher values for BMI, triglycerides, HDL cholesterol, and ALT than the control group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA-B, LTL was reported either as the natural logarithm of TL in kb per human diploid genome (log-TL) or as the natural logarithm of Telomere/Single copy gene ratio (log-T/S), which was significantly shorter in patients with MASLD than in CTRL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The shortened LTL was further validated through analysis of a subgroup of age-matched controls (CTRL AM) and patients with MASLD (MASLD AM) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC-D).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eLTL in paediatric MASLD stratified for the presence of MASH\u003c/h2\u003e\u003cp\u003eAccording to the Delphi consensus guidelines for the diagnosis of MASH [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], our cohort of patients with MASLD was divided into non-MASH (67 patients, 31.6%) and MASH (145 patients, 68.4%) groups. Biochemical and anthropometric variables of the patients are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Briefly, patients with MASH had significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) levels of ALT, AST, GGT, and HOMA-IR and significantly lower (p\u0026thinsp;=\u0026thinsp;0.0001) levels of LDL cholesterol than those without MASH. The histological characteristics of the MASH and non-MASH groups are presented in \u003cb\u003eTable S2\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBiochemical and anthropometrical characteristics of paediatric patients with MASLD without or with MASH.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eVariable\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003enon-MASH (n\u0026thinsp;=\u0026thinsp;67)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eMASH (n\u0026thinsp;=\u0026thinsp;145)\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep value\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eGender (M/F)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36/31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e95/50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.1282\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAge (years)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (5\u0026ndash;18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (6\u0026ndash;18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.5834\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBMI (kg/m\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.2 (16.5\u0026ndash;47.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.1 (21.2-39-9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.5842\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eWC (cm)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e89 (67\u0026ndash;134)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86 (60\u0026ndash;112)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.5468\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eTriglycerides (mg/dL)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100 (39\u0026ndash;225)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e89 (35\u0026ndash;277)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.2038\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eTotal cholesterol (mg/dL)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e154 (93\u0026ndash;210)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e156 (91\u0026ndash;298)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.5044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHDL cholesterol (mg/dL)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47 (21\u0026ndash;114)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48 (20\u0026ndash;112)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.5685\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLDL cholesterol (mg/dL)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e97 (48\u0026ndash;153)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73 (33\u0026ndash;145)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.0001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eALT (IU/mL)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (8\u0026ndash;82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40 (16\u0026ndash;265)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAST (IU/mL)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (12\u0026ndash;40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31 (19\u0026ndash;109)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eGGT (IU/mL)\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (3\u0026ndash;43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (9-101)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eHOMA-IR\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.7 (0.2\u0026ndash;10.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.2 (2.1\u0026ndash;15.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.0001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eValues are expressed as median and range (minimum \u0026ndash; maximum). Fisher\u0026rsquo;s exact test for gender distribution and the Mann-Whitney test for continuous variables.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eAbbreviations: MASH, metabolic dysfunction-associated steatohepatitis; M, males; F, females; WC, waist circumference; BMI, body mass index; HDL, high-density lipoprotein; LDL, low-density lipoprotein; ALT, alanine transaminase; AST, aspartate transaminase; GGT, gamma glutamyl transpeptidase; HOMA-IR, homeostasis model assessment of insulin resistance.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWhen we analysed the differences in LTL in these groups, it emerged that patients with MASH had a significantly shorter LTL than non-MASH patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-B). Moreover, Spearman\u0026rsquo;s correlation analysis confirmed an inverse association between the presence of MASH and LTL (r=-0.64, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). As the values of LTL expressed in kb or as the T/S ratio followed the same trend, in the following analyses, we only show LTL expressed as the natural logarithm of TL in kb per human diploid genome (log-TL).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eLTL correlation with anthropometric, metabolic and histological parameters in patients with MASLD\u003c/h2\u003e\u003cp\u003eTo further investigate the significance of the LTL decrease in patients with MASH, we conducted a multiple linear regression analysis considering log-TL as the dependent variable and anthropometric and biochemical parameters as independent variables. As shown in \u003cb\u003eTable S3\u003c/b\u003e, neither anthropometric nor biochemical features had a significant impact on LTL regardless of whether adjustments were made for BMI and age. In contrast, when we used histological features (i.e., steatosis, portal inflammation, lobular inflammation, ballooning, and fibrosis) and NAS as independent variables, we found that LTL was significantly correlated with fibrosis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Indeed, LTL significantly decreased with increasing fibrosis severity in MASLD patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Among all patients with MASLD, those with fibrosis grade 0 had a mean log-TL of 5.440, those with fibrosis grade 1 had a mean log-TL of 3.720, and those with fibrosis grade 2 had a mean log-TL of 3.483 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The same decreasing trend was observed in the subgroup of patients with MASH, with mean log-TL values of 4.190, 3.611, and 3.483 for F0, F1, and F2, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultiple linear regression analysis of LTL estimates in patients with MASLD.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eDependent variable: log-TL\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eModel\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eβ\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep value\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eIntercept\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e328.705\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e50.595\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eSteatosis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-85.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e140.732\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.547\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePortal Inflammation\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14.486\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22.864\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.527\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLobular Inflammation\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-117.743\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e144.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.415\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBallooning\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-85.264\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e144.878\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.557\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eFibrosis\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-104.990\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19.583\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eNAS\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e62.469\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e141.732\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.660\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eModel R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.350.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eAbbreviations: log-TL, natural logarithm of telomere length in kilobases; β, regression coefficient; SE, standard error, NAS, NAFLD activity score.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eTL evaluation in the liver of patients with MASLD\u003c/h2\u003e\u003cp\u003eNext, we analysed HTL in a sub-cohort of 15 patients with MASLD (MASLD) for whom liver biopsy tissue was available in our laboratory and three healthy liver donors (CTRL). We found that the mean log-HTL of patients with MASLD was 3.463, while that of controls was 3.725 (p\u0026thinsp;=\u0026thinsp;0.002) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). To further investigate the molecular mechanisms underlying telomere shortening, we analysed the expression of the enzyme TERT responsible for telomere maintenance. Interestingly, qPCR analysis revealed a decrease in \u003cem\u003eTERT\u003c/em\u003e gene (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB) and protein expression in the MASLD group compared to that in the CTRL group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC-D). Finally, multiple linear regression analysis was conducted with log-HTL as the dependent variable and the histological features of steatosis, portal inflammation, lobular inflammation, ballooning, fibrosis, and NAS score as independent variables, confirming the significant association between fibrosis and TL even at the hepatic level (SE\u0026thinsp;=\u0026thinsp;0.064, β=-0.169, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.605, p\u0026thinsp;=\u0026thinsp;0.037). Interestingly, portal inflammation was also significantly correlated with log-HTL (SE\u0026thinsp;=\u0026thinsp;0.100, β=-0.265, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.605, p\u0026thinsp;=\u0026thinsp;0.038).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eLTL association with gestational age and breastfeeding data of patients with MASLD\u003c/h2\u003e\u003cp\u003eThe relationship between MASLD-related damage and LTL in an adult setting may be attributed to chronic low-grade inflammation, multiple tissue inflammation, and lymphocyte senescence [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, it remains to be explained why LT shortening also occurs in paediatric MASLD. One hypothesis is that TL dynamics during childhood could be predetermined before birth by early life factors, as suggested by previous studies [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Therefore, we investigated the possible association between LTL and early life factors, including birthweight, gestational age, mode of delivery (natural or caesarean), and preterm and breastfeeding status, in our cohort of patients with MASLD. Spearman correlation analysis revealed that LTL was significantly associated with birthweight (r\u0026thinsp;=\u0026thinsp;0.163, p\u0026thinsp;=\u0026thinsp;0.017), gestational age (r\u0026thinsp;=\u0026thinsp;0.138, p\u0026thinsp;=\u0026thinsp;0.044), and preterm birth (r=-0.169, p\u0026thinsp;=\u0026thinsp;0.014). Simple linear regression analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-C) confirmed significant associations between LTL and birth weight (p\u0026thinsp;=\u0026thinsp;0.022) and preterm birth (p\u0026thinsp;=\u0026thinsp;0.006) as well as a nearly significant association with gestational age (p\u0026thinsp;=\u0026thinsp;0.059).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo further investigate the relationship between LTL, birthweight, gestational age, and MASLD pattern, the patients were divided into three groups based on whether they were born with a weight that was small, appropriate, or large for their gestational age (SGA, AGA, or LGA). Interestingly, multiple comparisons between the groups revealed significant differences in log-TL between patients born SGA and LGA (p\u0026thinsp;=\u0026thinsp;0.004) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConstruction of a generalized linear model with emerging histological and perinatal features as predictors of LTL\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFinally, we evaluated the relationship between the presence of fibrosis, portal inflammation, MASH, and SGA/AGA/LGA pattern with log-TL. Pairwise Spearman correlation analysis showed that log-TL was significantly inversely correlated with both fibrosis (r=\u0026ndash;0.66, p\u0026thinsp;=\u0026thinsp;2.06\u0026times;10⁻\u0026sup2;⁷) and MASH (r=\u0026ndash;0.64, p\u0026thinsp;=\u0026thinsp;1.69\u0026times;10⁻\u0026sup2;⁵). As expected, fibrosis and MASH were positively correlated (r\u0026thinsp;=\u0026thinsp;0.69, p\u0026thinsp;=\u0026thinsp;3.27\u0026times;10⁻\u0026sup3;\u0026sup1;) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). We then fitted a Generalized Linear Model (GLM) with log-TL as the dependent variable and fibrosis, MASH, portal inflammation, and SGA/AGA/LGA classification as predictors. Both fibrosis and MASH were significantly negatively associated with log-TL (Wald tests: p\u0026thinsp;=\u0026thinsp;2.09\u0026times;10⁻\u0026sup2;⁶ and p\u0026thinsp;=\u0026thinsp;5.71\u0026times;10⁻⁹, respectively), while being born LGA was significantly associated with higher log-TL values (Wald test: p\u0026thinsp;=\u0026thinsp;0.009). No significant association was observed for portal inflammation (Wald test: p\u0026thinsp;=\u0026thinsp;0.568) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we evaluated TL from peripheral blood leukocytes and in the liver in a cohort of paediatric patients with biopsy-proven MASLD compared to healthy controls. To date, only a few studies have analysed TL in children and adolescents with MASLD; however, data are controversial [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Our results demonstrated that the LTL was lower in patients with MASLD than in healthy controls. Interestingly, LTL shortening worsened with the progression of liver damage. Indeed, patients with MASH had a shorter LTL than patients in the early phases of the disease (non-MASH). These findings align with those of previous studies in adult patients with MASLD, which suggest that telomere shortening is involved in liver disease progression [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In addition, studies in adult patients have demonstrated that shortened telomeres are associated with more advanced fibrosis stages [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Our data are consistent with this observation. We found a significant negative correlation between fibrosis grade, as evaluated by biopsy, and LTL, with a decreasing trend in LTL accompanied by increasing fibrosis stage.\u003c/p\u003e\u003cp\u003eAccording to the leukocyte data, TL was decreased in the liver of patients with MASLD compared to that in healthy liver donors. As observed in the case of LTL, HTL was negatively correlated with the fibrosis grades of the patients, thus reinforcing the hypothesis of a possible causal relationship between MASLD-related liver damage and TL shortening. Moreover, HTL was also associated with the severity of portal inflammation, which is a specific hallmark of tissue necro-inflammation in the paediatric population [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. To evaluate whether telomere shortening at the hepatic level was associated with dysregulation of the factors involved in preserving their integrity, we assessed TERT gene/protein expression in a sub-cohort of MASLD liver samples. We found that patients with MASLD had statistically lower mRNA and protein levels of TERT compared with control healthy livers. A previous study demonstrated that \u003cem\u003eTERT\u003c/em\u003e deficiency, causing accelerated telomere shortening, was a predisposing factor for cirrhosis development, suggesting that telomere dysfunction may be a molecular event in the pathophysiology of fibrosis and then cirrhosis [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In line with these findings, Donati et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] demonstrated that LTL decreased with liver disease progression from healthy controls to cirrhosis to hepatocellular carcinoma (HCC) in a MASLD background. The authors hypothesised that the progressive LTL decrease may promote the consumption of the stem cell pool, senescence and fibrosis of adult cells, thus favouring genomic instability and HCC onset. Possible mechanisms of TERT gene down-regulation in MASLD and particularly in fibrosis progression, including epigenetic control and telomere position effects, deserve further exploration [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eEven if it was reported that telomere attrition rate slows in childhood and adolescence, and telomeres then continue to shorten at a slower rate across adulthood, it is conceivable that early life factors could be particularly relevant in predicting TL shortening in paediatric patients with MASLD. Among early life factors, birthweight, gestational age, type of delivery and breastfeeding could have an effect on LTL, as well as on MASLD severity in a paediatric setting [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Indeed, when we investigated the possible association between perinatal features, including birthweight, gestational age, birth type, and breastfeeding with LTL, we found a significant association of LTL with preterm birth and birth weight, but more importantly, we demonstrated that the presence of fibrosis and MASH, and being born SGA may predict lower TL in paediatric MASLD. These findings allow us to speculate that the intrauterine state induces epigenetic adaptations that significantly influence TL attrition at birth, thus increasing the risk of MASLD in later life and influencing the risk of advanced fibrosis and all-cause mortality, as recently reported by Kim et al [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study has two significant limitations, including the small size of the control group and the lack of an independent cohort of children with biopsy-proven MASLD. Nonetheless, our pilot study highlights for the first time a significant reduction in TL among children with MASLD compared with controls, with telomere shortening enhanced in patients with MASH and fibrosis. Further studies are needed to validate our results and to investigate potential causal relationships between TL, the severity of disease, and birthweight.\u003c/p\u003e\u003cp\u003eIn conclusion, our research revealed a correlation between epigenetic regulation of TL and hepatic damage in paediatric MASLD, primarily MASH and fibrosis, which may potentially support the identification of high-risk children who may develop a progressive disease at a later age.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflicts of interest:\u003c/h2\u003e\u003cp\u003enothing to report.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor contributions:\u003c/h2\u003e\u003cp\u003eM.R.B. contributed to the conceptualisation of the study, execution of the experiments, analysis of the data and writing of the manuscript; S.D.B. contributed to the analysis of the data; M.B. contributed to the execution of the experiments; G.A. contributed to the execution of the experiments; A.M. contributed to the patients\u0026rsquo; enrolment and data collection; C.D.S. contributed to the execution of the experiments; M.P. contributed to the execution of the experiments; P.F. contributed to the critical review and editing of the manuscript; C.B. contributed to the critical review and editing of the manuscript; L.M. contributed to the critical review and editing of the manuscript; T.M. contributed to the analysis of the data and critical review and editing of the manuscript; A.A. contributed to the conceptualisation of the study, analysis of the data, and writing, critical review and editing of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eA.A. discloses support for the research of this work from the Italian Ministry of Health with \u0026ldquo;Ricerca Finalizzata\u0026rdquo; (grant number RF-2021-12372565) and \u0026ldquo;Current Research\u0026rdquo; funds. M.R.B. discloses support for publication of this work from \u0026ldquo;AISF Associazione Italiana per lo Studio del Fegato\u0026rdquo; for a one-year fellowship.\u003c/p\u003e\u003ch2\u003eData availability:\u003c/h2\u003e\u003cp\u003eThe dataset used in this study may be obtained from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRinella, M.E. \u003cem\u003eet al\u003c/em\u003e. A multisociety Delphi consensus statement on new fatty liver disease nomenclature. \u003cem\u003eJ. Hepatol\u003c/em\u003e. 79, 1542\u0026ndash;1556 (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhang, L. \u003cem\u003eet al\u003c/em\u003e. An international multidisciplinary consensus on pediatric metabolic dysfunction-associated fatty liver disease. \u003cem\u003eMed.\u003c/em\u003e 5, 797\u0026ndash;815 (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMiao, L., Targher, G., Byrne, C.D., Cao, Y.Y. \u0026amp; Zheng, M.H. Current status and future trends of the global burden of MASLD. \u003cem\u003eTrends Endocrinol. Metab.\u003c/em\u003e 35, 697\u0026ndash;707 (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYounossi, Z.M., Kalligeros, M. \u0026amp; Henry, L. Epidemiology of metabolic dysfunction-associated steatotic liver disease. \u003cem\u003eClin. Mol. Hepatol\u003c/em\u003e. 31, S32-S50 (2025).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePowell, E.E. 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Hepatol\u003c/em\u003e. 73, 1590\u0026ndash;1592 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWu, Y.L. \u003cem\u003eet al\u003c/em\u003e. Epigenetic regulation in metabolic diseases: mechanisms and advances in clinical study. \u003cem\u003eSignal Transduct. Target Ther\u003c/em\u003e. 8, 98 (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCaputo, V., Tarantino, G., Santini, S.J., Fracassi, G. \u0026amp; Balsano, C. The Role of Epigenetic Control of Mitochondrial (Dys)Function in MASLD Onset and Progression. \u003cem\u003eNutrients.\u003c/em\u003e 15, 4757 (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNjajou, O.T. \u003cem\u003eet al\u003c/em\u003e. Telomere length is paternally inherited and is associated with parental lifespan. \u003cem\u003eProc. Natl. Acad. Sci. 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Telomerase Regulation: A Role for Epigenetics. \u003cem\u003eCancers (Basel)\u003c/em\u003e. 13, 1213 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBugianesi, E. \u003cem\u003eet al\u003c/em\u003e. Low Birthweight Increases the Likelihood of Severe Steatosis in Pediatric Non-Alcoholic Fatty Liver Disease. \u003cem\u003eAm. J. Gastroenterol\u003c/em\u003e. 112, 1277\u0026ndash;1286 (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEbrahimi, F. \u003cem\u003eet al\u003c/em\u003e. Birth Weight, Gestational Age, and Risk of Pediatric-Onset MASLD. \u003cem\u003eJAMA Netw. Open\u003c/em\u003e. 7, e2432420 (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim, D., Danpanichkul, P., Wijarnpreecha, K., Cholankeril, G. \u0026amp; Ahmed, A. Leukocyte telomere shortening in metabolic dysfunction-associated steatotic liver disease and all-cause/cause-specific mortality. \u003cem\u003eClin. Mol. Hepatol.\u003c/em\u003e 30, 982\u0026ndash;986 (2024).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"MASLD, MASH, fibrosis, telomeres, children","lastPublishedDoi":"10.21203/rs.3.rs-7427772/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7427772/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMetabolic dysfunction-associated steatotic liver disease (MASLD) is an emerging health concern in both children and adults. A few studies have suggested that dysregulation of telomere-maintaining processes may be a molecular mechanism involved in the disease; however, data in paediatric patients are controversial. This study aimed to evaluate the relationship between telomere length (TL) and hepato-metabolic features in a cohort of children with MASLD.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn all, 212 paediatric patients with biopsy-proven MASLD and 31 controls were enrolled in the Hepatology Unit of Bambino Ges\u0026ugrave; Children's Hospital. TL of leukocytes (LTL) and hepatic cells (HTL) was measured by quantitative polymerase chain reaction (qPCR). Telomerase reverse transcriptase (TERT) mRNA and protein levels were evaluated in a subgroup of liver samples using qPCR and immunofluorescence analyses. TL data association with hepato-metabolic and perinatal features was evaluated using different approaches.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOur results revealed that children with MASLD had significantly lower LTL and HTL than the control children. TL shortening worsened in more advanced phases of the disease (MASH) and was associated with fibrosis grade. TERT expression was lower in the liver of patients than in controls. LTL was significantly associated with preterm birth and birthweight, and a general linear model highlighted the impact of MASH, fibrosis, and being born small for gestational age on LTL decrease.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn conclusion, our study demonstrated for the first time a strong relationship between TL and pediatric MASLD-related features, mainly fibrosis. Further studies are needed to clarify the causal relationship between MASH, fibrosis, birthweight and TL.\u003c/p\u003e","manuscriptTitle":"Fibrosis and birthweight correlated with telomere shortening in paediatric metabolic dysfunction-associated steatotic liver disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-17 08:43:32","doi":"10.21203/rs.3.rs-7427772/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9b0f907b-5a2c-41c6-a33f-634ecc61f070","owner":[],"postedDate":"September 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":54443096,"name":"Health sciences/Gastroenterology"},{"id":54443097,"name":"Health sciences/Gastroenterology/Hepatology/Liver diseases/Non-alcoholic fatty liver disease"}],"tags":[],"updatedAt":"2026-02-04T18:16:30+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-17 08:43:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7427772","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7427772","identity":"rs-7427772","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}