Diagnostic Performance of Biomarker-Based Scores as Predictors of Metabolic Dysfunction-Associated Fatty Liver Disease Risk in Healthy Children
Abstract
:1. Introduction
2. Materials and Methods
2.1. Laboratory and Anthropometric Measurements
2.2. Decision Criteria for Study Participants
2.3. Statistical Analysis
3. Results
3.1. General Characteristics of Study Group
3.2. Biomarker-Based Scores for Prediction of MAFLD Occurrence
3.3. Diagnostic Performance of Biomarker-Based Scores for Prediction of Metabolic (Dysfunction)-Associated Fatty Liver Disease (MAFLD)
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Eslam, M.; Alkhouri, N.; Vajro, P.; Baumann, U.; Weiss, R.; Socha, P.; Marcus, C.; Lee, W.S.; Kelly, D.; Porta, G.; et al. Defining Paediatric Metabolic (Dysfunction)-Associated Fatty Liver Disease: An International Expert Consensus Statement. Lancet Gastroenterol. Hepatol. 2021, 6, 864–873. [Google Scholar] [CrossRef] [PubMed]
- Kim, D.; Kim, W.R. Nonobese Fatty Liver Disease. Clin. Gastroenterol. Hepatol. 2017, 15, 474–485. [Google Scholar] [CrossRef] [PubMed]
- Eslam, M.; Sanyal, A.J.; George, J.; Sanyal, A.; Neuschwander-Tetri, B.; Tiribelli, C.; Kleiner, D.E.; Brunt, E.; Bugianesi, E.; Yki-Järvinen, H.; et al. MAFLD: A Consensus-Driven Proposed Nomenclature for Metabolic Associated Fatty Liver Disease. Gastroenterology 2020, 158, 1999–2014. [Google Scholar] [CrossRef] [PubMed]
- Lin, Y.C.; Wu, C.C.; Ni, Y.H. New Perspectives on Genetic Prediction for Pediatric Metabolic Associated Fatty Liver Disease. Front. Pediatr. 2020, 8, 603654. [Google Scholar] [CrossRef] [PubMed]
- Neri, C.R.; Scapaticci, S.; Chiarelli, F.; Giannini, C. Liver Steatosis: A Marker of Metabolic Risk in Children. Int. J. Mol. Sci. 2022, 23, 4822. [Google Scholar] [CrossRef]
- Mandato, C.; Miele, L.; Socha, P.; Vajro, P. Editorial: The broader aspects of non-alcoholic fatty liver disease in children. Front. Pediatr. 2022, 10, 1034306. [Google Scholar] [CrossRef]
- Papachristodoulou, A.; Kavvadas, D.; Karamitsos, A.; Papamitsou, T.; Chatzidimitriou, M.; Sioga, A. Diagnosis and Staging of Pediatric Non-Alcoholic Fatty Liver Disease: Is Classical Ultrasound the Answer? Pediatr. Rep. 2021, 13, 312–321. [Google Scholar] [CrossRef]
- Canivet, C.M.; Boursier, J. Screening for Liver Fibrosis in the General Population: Where Do We Stand in 2022? Diagnostics 2023, 13, 91. [Google Scholar] [CrossRef]
- Kwon, Y.; Kim, E.S.; Choe, Y.H.; Kim, M.J. Stratification by Non-invasive Biomarkers of Non-alcoholic Fatty Liver Disease in Children. Front. Pediatr. 2022, 10, 846273. [Google Scholar] [CrossRef]
- Takahashi, Y. Histopathology of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis. World J. Gastroenterol. 2014, 20, 15539. [Google Scholar] [CrossRef]
- Wang, J.; Qin, T.; Sun, J.; Li, S.; Cao, L.; Lu, X. Non-invasive methods to evaluate liver fibrosis in patients with non-alcoholic fatty liver disease. Front. Physiol. 2022, 13, 1046497. [Google Scholar] [CrossRef] [PubMed]
- Mosca, A.; Mantovani, A.; Crudele, A.; Panera, N.; Comparcola, D.; De Vito, R.; Bianchi, M.; Byrne, C.D.; Targher, G.; Alisi, A. Higher Levels of Plasma Hyaluronic Acid and N-terminal Propeptide of Type III Procollagen Are Associated with Lower Kidney Function in Children with Non-alcoholic Fatty Liver Disease. Front. Pediatr. 2022, 10, 917714. [Google Scholar] [CrossRef] [PubMed]
- Bilinski, W.J.; Stefanska, A.; Szternel, L.; Bergmann, K.; Siodmiak, J.; Krintus, M.; Paradowski, P.T.; Sypniewska, G. Relationships between bone turnover markers and factors associated with metabolic syndrome in prepubertal girls and boys. Nutrients. 2022, 14, 1205. [Google Scholar] [CrossRef] [PubMed]
- Bilinski, W.J.; Szternel, L.; Siodmiak, J.; Krintus, M.; Paradowski, P.T.; Domagalski, K.; Sypniewska, G. Effect of fasting hyperglycemia and insulin resistance on bone turnover markers in children aged 9–11 years. J. Diabetes Complicat. 2021, 35, 108000. [Google Scholar] [CrossRef] [PubMed]
- Koot, B.G.; Van Der Baan-Slootweg, O.H.; Bohte, A.E.; Nederveen, A.J.; Van Werven, J.R.; Tamminga-Smeulders, C.L.; Merkus, M.P.; Schaap, F.G.; Jansen, P.L.; Stoker, J.; et al. Accuracy of Prediction Scores and Novel Biomarkers for Predicting Nonalcoholic Fatty Liver Disease in Obese Children. Obesity 2013, 1, 583–590. [Google Scholar] [CrossRef] [PubMed]
- Szternel, L.; Krintus, M.; Bergmann, K.; Derezinski, T.; Sypniewska, G. Non- fasting lipid profile detetrmination in presumably healthy children: Impact on the assessment of lipid abnormalities. PLoS ONE 2018, 13, e0198433. [Google Scholar] [CrossRef]
- Adeli, K.; Higgins, V.; Trajcevski, K.; White-Al Habeeb, N. The Canadian laboratory initiative on pediatric reference intervals: A CALIPER white paper. Crit. Rev. Clin. Lab. Sci. 2017, 54, 358–413. [Google Scholar] [CrossRef]
- Shashaj, B.; Luciano, R.; Contoli, B.; Morino, G.S.; Spreghini, M.R.; Rustico, C.; Sforza, R.W.; Dallapiccola, B.; Manco, M. Reference ranges of HOMA-IR in normal-weight and obese young Caucasians. Acta Diabetol. 2016, 53, 251–260. [Google Scholar] [CrossRef]
- Riekki, H.; Aitokari, L.; Kivelä, L.; Lahti, S.; Hiltunen, P.; Vuorela, N.; Huhtala, H.; Lakka, T.A.; Kurppa, K. Prevalence and associated factors of metabolic-associated fatty liver disease in overweight Finish children and adolescents. Front. Endocrinol. 2023, 14, 1090344. [Google Scholar] [CrossRef]
- Geurtsen, M.L.; Santos, S.; Felix, J.F.; Duijts, L.; Vernooij, M.W.; Gaillard, R.; Jaddoe, V.W.V. Liver Fat and Cardiometabolic Risk Factors Among School-Age Children. Hepatology 2020, 72, 119–128. [Google Scholar] [CrossRef]
- Mann, J.P.; De Vito, R.; Mosca, A.; Alisi, A.; Armstrong, M.J.; Raponi, M.; Baumann, U.; Nobili, V. Portal inflammation is independently associated with fibrosis and metabolic syndrome in pediatric nonalcoholic fatty liver disease. Hepatology 2016, 63, 745–753. [Google Scholar] [CrossRef] [PubMed]
- Ma, X.; Liu, S.; Zhang, J.; Dong, M.; Wang, Y.; Wang, M.; Xin, Y. Proportion of NAFLD patients with normal ALT value in overall NAFLD patients: A systematic review and metaanalysis. BMC Gastroenterol. 2020, 20, 10. [Google Scholar] [CrossRef] [PubMed]
- Molleston, J.P.; Schwimmer, J.B.; Yates, K.P.; Murray, K.F.; Cummings, O.W.; Lavine, J.E.; Brunt, E.M.; Scheimann, A.O.; Unalp-Arida, A. Histological abnormalities in children with nonalcoholic fatty liver disease and normal or mildly elevated alanine aminotransferase levels. J. Pediatr. 2014, 164, 707–713.e3. [Google Scholar] [CrossRef] [PubMed]
- You, S.C.; Kim, K.J.; Kim, S.U.; Kim, B.K.; Park, J.Y.; Kim, D.Y.; Ahn, S.H.; Lee, W.J.; Han, K.-H. Factors associated with significant liver fibrosis assessed using transient elastography in general population. World J. Gastroenterol. 2015, 21, 1158–1166. [Google Scholar] [CrossRef]
- Long, M.T.; Gandhi, S.; Loomba, R. Advances in non-invasive biomarkers for the diagnosis and monitoring of non-alcoholic fatty liver disease. Metabolism 2020, 111S, 154259. [Google Scholar] [CrossRef]
- Ferraioli, G.; Calcaterra, V.; Lissandrin, R.; Guazzotti, M.; Maiocchi, L.; Tinelli, C.; De Silvestri, A.; Regalbuto, C.; Pelizzo, G.; Larizza, D.; et al. Noninvasive assessment of liver steatosis in children: The clinical value of controlled attenuation parameter. BMC Gastroenterol. 2017, 17, 61. [Google Scholar] [CrossRef]
- Rigamonti, A.E.; Bondesan, A.; Rondinelli, E.; Cella, S.G.; Sartorio, A. The Role of Aspartate Transaminase to Platelet Ratio Index (APRI) for the Prediction of Non-Alcoholic Fatty Liver Disease (NAFLD) in Severely Obese Children and Adolescents. Metabolites 2022, 12, 155. [Google Scholar] [CrossRef]
- Mosca, A.; Volpe, L.D.; Alisi, A.; Veraldi, S.; Francalanci, P.; Maggiore, G. Non-Invasive Diagnostic Test for Advanced Fibrosis in Adolescents with Non-Alcoholic Fatty Liver Disease. Front. Pediatr. 2022, 10, 885576. [Google Scholar] [CrossRef]
- Luger, M.; Kruschitz, R.; Kienbacher, C.; Traussnigg, S.; Langer, F.B.; Schindler, K.; Würger, T.; Wrba, F.; Trauner, M.; Prager, G.; et al. Prevalence of Liver Fibrosis and its Association with Non-invasive Fibrosis and Metabolic Markers in Morbidly Obese Patients with Vitamin D Deficiency. Obesity Surg. 2016, 26, 2425–2432. [Google Scholar] [CrossRef]
- Bedogni, G.; Bellentani, S.; Miglioli, L.; Masutti, F.; Passalacqua, M.; Castiglione, A.; Tiribelli, C. The Fatty Liver Index: A simple and accurate predictor of hepatic steatosis in the general population. BMC Gastroenterol. 2006, 6, 33. [Google Scholar] [CrossRef]
- Lee, J.-H.; Kim, D.; Kim, H.J.; Lee, C.-H.; Yang, J.I.; Kim, W.; Kim, Y.J.; Yoon, J.-H.; Cho, S.-H.; Sung, M.-W.; et al. Hepatic steatosis index: A simple screening tool reflecting nonalcoholic fatty liver disease. Dig. Liver Dis. 2010, 42, 503–508. [Google Scholar] [CrossRef] [PubMed]
- Deng, H.; Dai, Y.; Lu, H.; Li, S.S.; Gao, L.; Zhu, D.L. Analysis of the correlation between non-alcoholic fatty liver disease and bone metabolism indicators in healthy middle-aged men. Eur. Rev. Med. Pharmacol. Sci. 2018, 22, 1457–1462. [Google Scholar] [CrossRef] [PubMed]
- Veidal, S.S.; Vassiliadis, E.; Bay-Jensen, A.C.; Tougas, G.; Vainer, B.; Karsdal, M.A. Procollagen type I Nterminal propeptide (PINP) is a marker for fibrogenesis in bile duct ligation-induced fibrosis in rats. Fibrogenesis Tissue Repair. 2010, 3, 5. [Google Scholar] [CrossRef] [PubMed]
- Geserick, M.; Vogel, M.; Eckelt, F.; Schlingmann, M.; Hiemisch, A.; Baber, R.; Thiery, J.; Körner, A.; Kiess, W.; Kratzsch, J. Children and adolescents with obesity have reduced serum bone turnover markers and 25-hydroxyvitamin D but increased parathyroid hormone con-centrations-results derived from new pediatric reference ranges. Bone 2020, 132, 115124. [Google Scholar] [CrossRef]
- Vos, M.B.; Abrams, S.H.; Barlow, S.E.; Caprio, S.; Daniels, S.R.; Kohli, R.; Mouzaki, M.; Sathya, P.; Schwimmer, J.B.; Sundaram, S.S.; et al. NASPGHAN Clinical Practice Guideline for the Diagnosis and Treatment of Nonalcoholic Fatty Liver Disease in Children: Recommendations from the Expert Committee on NAFLD (ECON) and the North American Society of Pediatric Gastroenterology, Hepatology and Nutrition (NASPGHAN). J. Pediatr. Gastroenterol. Nutr. 2017, 64, 319–334. [Google Scholar] [CrossRef]
- Zhu, C.; Huang, D.; Ma, H.; Qian, C.; You, H.; Bu, L.; Qu, S. High-Sensitive CRP Correlates with the Severity of Liver Steatosis and Fibrosis in Obese Patients with Metabolic Dysfunction Associated Fatty Liver Disease. Front. Endocrinol. 2022, 13, 848937. [Google Scholar] [CrossRef]
- de Silva, M.H.A.D.; Hewawasam, R.P.; Kulatunge, C.R.; Chamika, R.M.A. The accuracy of fatty liver index for the screening of overweight and obese children for non-alcoholic fatty liver disease in resource limited settings. BMC Pediatr. 2022, 22, 511. [Google Scholar] [CrossRef]
- Cohen, C.C.; Castillo-Leon, E.; Farris, A.B.; Caltharp, S.A.; Cleeton, R.L.; Sinclair, E.M.; Shevell, D.E.; Karsdal, M.A.; Nielsen, M.J.F.; Leeming, D.J.; et al. PRO-C3, a Serological Marker of Fibrosis, During Childhood and Correlations with Fibrosis in Pediatric NAFLD. Hepatol. Commun. 2021, 5, 1860–1872. [Google Scholar] [CrossRef]
Variables | Girls | Boys | ||||
---|---|---|---|---|---|---|
MAFLD+ (n = 14) | MAFLD− (n = 60) | p | MAFLD+ (n = 29) | MAFLD− (n = 41) | p | |
Age (years) | 9 (9–10) | 10 (9–10.5) | 0.035 | 10 (9–10) | 10 (9–11) | 0.748 |
BMI centile | 85 (64–95) | 54 (19–70) | <0.001 | 95 (71–96) | 38 (21–43) | <0.001 |
BMI centile ≥ 85 (%) | 57.1 | 6.7 | 0.015 | 65.5 | 7.3 | 0.002 |
WC (cm) | 74 (63–80) | 66 (59.5–70) | 0.008 | 78 (69–86) | 63 (59–67) | <0.001 |
Central obesity * (%) | 42.9 | 5.0 | <0.001 | 41.4 | 4.9 | <0.001 |
Glucose (mg/dL) | 91 (86–95) | 93 (87–100) | 0.252 | 92 (85–97) | 97 (91–103) | 0.018 |
HOMA-IR | 2.3 (1.8–3.5) | 1.8 (1.2–2.7) | 0.187 | 2.8 (2.1–4.4) | 1.7 (1.1–2.7) | 0.001 |
HOMA-IR > 3.0 (%) | 28.6 | 21.7 | 0.581 | 44.8 | 21.9 | 0.042 |
SBP (mmHg) | 110 (106–114) | 110 (103–114) | 0.644 | 116 (103–120) | 109 (103–115) | 0.201 |
TG (mg/dL) | 98 (84–110) | 67 (51–84) | 0.002 | 105 (65–157) | 56 (41–74) | <0.001 |
HDL-C (mg/dL) | 53 (47–62) | 60 (54–69) | 0.095 | 51 (47–58) | 61 (55–73) | 0.001 |
TG/HDL-C > 2.25 (%) | 28.5 | 8.3 | 0.037 | 51.7 | 0.0 | <0.001 |
CRP (mg/L) | 1.58 (0.46–2.63) | 0.41 (0.16–1,11) | 0.032 | 1.33 (0.49–2.60) | 0.20 (0.12–0.65) | <0.001 |
CRP > 2.0 mg/L (%) | 28.6 | 11.7 | 0.110 | 41.4 | 0.0 | <0.001 |
ALP (U/L) | 206 (161–243) | 184 (145–234) | 0.366 | 211 (155–225) | 175 (148–222) | 0.567 |
GGT (U/L) | 20 (15–23) | 12 (10–14) | <0.001 | 17 (13–21) | 10 (9–13) | <0.001 |
GGT ** (%) | 71.4 | 6.7 | <0.001 | 62.1 | 9.8 | <0.001 |
ALT (U/L) | 16 (9–22) | 6 (4–8) | <0.001 | 13 (8–16) | 6 (3–7) | <0.001 |
ALT ** (%) | 28.6 | 2.1 | 0.005 | 6.9 | 0.0 | 0.088 |
AST (U/L) | 36 (32–40) | 28 (26–30) | <0.001 | 32 (30–35) | 29 (28–32) | 0.007 |
AST ** (%) | 50.0 | 3.3 | <0.001 | 24.1 | 12.2 | 0.740 |
FLI | 13.3 (3.1–20) | 1.4 (0.9–2.5) | <0.001 | 11.9 (5.5–23) | 0.95 (0.63–1.4) | <0.001 |
HSI | 0.08 (0.05–0.17) | 0.02 (0.01–0.03) | <0.001 | 0.13 (0.03–0.30) | 0.01 (0.008–0.02) | <0.001 |
Variables | Girls | Boys | ||||
---|---|---|---|---|---|---|
MAFLD+ (n = 14) | MAFLD− (n = 60) | p | MAFLD+ (n = 29) | MAFLD− (n = 41) | p | |
CTX (ng/mL) | 1.52 (0.96–2.15) | 1.43 (1.11–2.09) | 0.907 | 1.44 (1.05–1.92) | 1.45 (1.03–1.96) | 0.962 |
P1NP (ng/mL) | 1368 (1218–1488) | 1423 (1246–2481) | 0.482 | 1289 (1208–1396) | 1254 (1169–1443) | 0.849 |
BTI | 0.29 (−0.47–0.92) | 0.38 (−0.25–1.20) | 0.512 | 0.10 (−0.76–0.44) | −0.11 (−0.53–0.55) | 0.990 |
P1NP/ALP | 7.3 (5.8–10.7) | 8.7 (6.4–12.4) | 0.207 | 7.3 (5.6–8.6) | 7.9 (6.0–8.8) | 0.273 |
P1NP/ALPxALT | 123 (66–169) | 51 (29–90) | 0.004 | 87 (71–120) | 45 (17–80) | <0.0501 |
P1NP/ALPxCRP | 11.81 (3.52–19.18) | 3.18 (1.54–10.77) | <0.043 | 9.69 (3.04–17.83) | 1.58 (0.81–4.71) | <0.001 |
Variables | Girls (n = 74) | Boys (n = 70) | ||
---|---|---|---|---|
p | OR (95% CI) * | p | OR (95% CI) * | |
CRP | 0.042 | 1.02 (1.00–1.05) | <0.001 | 1.17 (1.08–1.27) |
HOMA-IR | 0.444 | 1.01 (0.98–1.04) | 0.002 | 1.07 (1.02–1.11) |
P1NP/ALP | 0.287 | 0.92 (0.78–1.08) | 0.315 | 0.92 (0.77–1.09) |
FLI | <0.001 | 1.30 (1.14–1.49) | <0.001 | 1.70 (1.28–2.26) |
HSI | <0.001 | 1.23 (1.09–1.38) | 0.005 | 1.08 (1.02–1.13) |
P1NP/ALPxCRP | 0.063 | 1.02 (1.0–1.04) | <0.001 | 1.14 (1.05–1.24) |
Variables | Girls n = 74 | Boys n = 70 | ||||||
---|---|---|---|---|---|---|---|---|
AUC (95% CI) | Sensitivity/Specificity (%) | PPV/NPV (%) | p | AUC (95% CI) | Sensitivity/Specificity (%) | PPV/NPV (%) | p | |
FLI | 0.85 | 86/75 | 44/96 | <0.001 | 0.95 | 93/83 | 79/94 | <0.001 |
(0.74–0.92) | (0.87–0.99) | |||||||
HSI | 0.84 | 86/87 | 60/96 | <0.001 | 0.89 | 83/83 | 77/87 | <0.001 |
(0.74–0.92) | (0.80–0.95) | |||||||
CRP | 0.69 | 64/75 | 38/90 | 0.038 | 0.81 | 59/90 | 81/76 | <0.001 |
(0.57–0.79) | (0.70–0.90) | |||||||
HOMA-IR | 0.61 | 86/42 | 26/93 | 0.124 | 0.74 | 86/56 | 58/85 | 0.001 |
(0.49–0.73) | (0.62–0.83) | |||||||
P1NP/ALP | 0.61 | 64/63 | 29/88 | 0.192 | 0.58 | 62/59 | 51/69 | 0.269 |
(0.45–0.77) | (0.44–0.72) | |||||||
P1NP/ALP xCRP | 0.68 | 64/75 | 38/90 | 0.041 | 0.79 | 86/59 | 60/86 | <0.001 |
(0.56–0.78) | (0.67–0.88) |
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Bergmann, K.; Stefanska, A.; Krintus, M.; Szternel, L.; Bilinski, W.J.; Paradowski, P.T.; Sypniewska, G. Diagnostic Performance of Biomarker-Based Scores as Predictors of Metabolic Dysfunction-Associated Fatty Liver Disease Risk in Healthy Children. Nutrients 2023, 15, 3667. https://doi.org/10.3390/nu15163667
Bergmann K, Stefanska A, Krintus M, Szternel L, Bilinski WJ, Paradowski PT, Sypniewska G. Diagnostic Performance of Biomarker-Based Scores as Predictors of Metabolic Dysfunction-Associated Fatty Liver Disease Risk in Healthy Children. Nutrients. 2023; 15(16):3667. https://doi.org/10.3390/nu15163667
Chicago/Turabian StyleBergmann, Katarzyna, Anna Stefanska, Magdalena Krintus, Lukasz Szternel, Wojciech J. Bilinski, Przemyslaw T. Paradowski, and Grazyna Sypniewska. 2023. "Diagnostic Performance of Biomarker-Based Scores as Predictors of Metabolic Dysfunction-Associated Fatty Liver Disease Risk in Healthy Children" Nutrients 15, no. 16: 3667. https://doi.org/10.3390/nu15163667
APA StyleBergmann, K., Stefanska, A., Krintus, M., Szternel, L., Bilinski, W. J., Paradowski, P. T., & Sypniewska, G. (2023). Diagnostic Performance of Biomarker-Based Scores as Predictors of Metabolic Dysfunction-Associated Fatty Liver Disease Risk in Healthy Children. Nutrients, 15(16), 3667. https://doi.org/10.3390/nu15163667