ORIGINAL RESEARCH published: 29 June 2022 doi: 10.3389/fendo.2022.868795 Role of NAFLD on the Health Related QoL Response to Lifestyle in Patients Edited by: Marwan El Ghoch, With Metabolic Syndrome: The Beirut Arab University, Lebanon PREDIMED Plus Cohort Reviewed by: Ferdinando Carlo Sasso, Diego Martı́nez-Urbistondo 1*, Rodrigo San-Cristóbal 2, Paula Villares 1, Università della Campania Luigi Vanvitelli, Miguel Ángel Martı́nez-González 3,4,5, Nancy Babio 4,6,7, Dolores Corella 4,8, José Luis del Val 4,9, Italy José Ma Ordovás 10,11, Ángel M. Alonso-Gómez 4,12, Julia Wärnberg 4,13, Jesús Vioque 14,15, Mario Luca Morieri, Dora Romaguera 4,16, José López-Miranda 4,17, Ramon Estruch 4,18, University of Padua, Italy Francisco J. Tinahones 4,19, José Lapetra 4,20, J. Luı́s Serra-Majem 4,21, *Correspondence: Aurora Bueno-Cavanillas 14,22, Josep A. Tur 4,23, Alba Marcos 14,24, Xavier Pintó 4,25, Diego Martı´nez-Urbistondo Miguel Delgado-Rodrı́guez 14,26, Pilar Matı́a-Martı́n 27, Josep Vidal 28,29, Dmurbistondo@gmail.com Clotilde Vázquez 4,30, Emilio Ros 4,29, Marı́a Vanessa Bullón Vela 3,4, Antoni Palau 4,6,7, Jose V. Sorli 4,8, Marta Masagué 4,9, Itziar Abete 4,31, Anai Moreno-Rodrı́guez 4,12, Specialty section: Inma Candela-Garcı́a 32, Jadwiga Konieczna 4,16, Antonio Garcı́a-Rı́os 4,17, This article was submitted to Oscar Lecea Juárez 3,4, Olga Portolés 4,8, Paco Martı́n 4,6,7, Albert Goday 4,9,33, Obesity, M Ángeles Zulet 4,31, Jessica Vaquero-Luna 4,12, Marı́a del Carmen Sayón Orea 3,4, a section of the journal Isabel Megı́as 4,6,7, Enric Baltasar 4,9, J. Alfredo Martı́nez 2,4,31 and Lidia Daimiel 34 Frontiers in Endocrinology 1 Internal Medicine Department, Hospital HM Sanchinarro, HM Hospitales, Madrid, Spain, 2 Cardiometabolic Nutrition Group, Received: 08 February 2022 Precision Nutrition and Cardiometabolic Health Program, Instituto Madrileño de Estudios Avanzados (IMDEA) Food, Centro de Accepted: 26 April 2022 Excelencia en Investigación (CEI) Universidad Autónoma de Madrid (UAM) + Centro Superior de Investigaciones Científicas Published: 29 June 2022 (CSIC), Madrid, Spain, 3 Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain, Citation: 4 Consorcio CIBER, M.P. Fisiopatologı´a de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII). Madrid, Martı´nez-Urbistondo D, Spain, 5 Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, United States, 6 Universitat Rovira i San-Cristóbal R, Villares P, Virgili, Departament de Bioquı´mica i biotecnologia, Unitat de Nutrició Humana, Reus, Spain, 7 Institut d’Investigació Sanitària Pere Martı´nez-González MÁ, Babio N, Virgili (IISPV), Hospital Universitari San Joan de Reus. Human Nutrition unit, Reus, Spain, 8 Department of Preventive Medicine, Corella D, del Val JL, Ordovás JM, University of Valencia, Valencia, Spain, 9 Cardiovascular Risk and Nutrition Research Group (CARIN), Hospital del Mar Medical Alonso-Gómez ÁM, Wärnberg J, Research Institute (IMIM), Barcelona, Spain, 10 Nutritional Genomics and Epigenomics Group, Precision Nutrition and Obesity Vioque J, Romaguera D, Program. Instituto Madrileño de Estudios Avanzados (IMDEA) Food, Centro de Excelencia en Investigación (CEI) Universidad López-Miranda J, Estruch R, Autónoma de Madrid (UAM) + Centro Superior de Investigaciones Científicas (CSIC), Madrid, Spain, 11 Nutrition and Genomics Tinahones FJ, Lapetra J, Laboratory, Jean Mayer United States Department of Agriculture (JM_USDA) Human Nutrition Research Center on Aging, Tufts Serra-Majem JL, Bueno-Cavanillas A, University, Boston, MA, United States, 12 Bioaraba Health Research Institute, Osakidetza Basque Health Service, Araba Tur JA, Marcos A, Pintó X, University Hospital, University of the Basque Country Universidad del Paı´s Vasco/Euskal Herriko Unibertsitatea (UPV/EHU), Delgado-Rodrı´guez M, Matı´a-Martı´n P, Vitoria-Gasteiz, Spain, 13 Department of Nursing, School of Health Sciences, University of Málaga, Instituto de Investigación Vidal J, Vázquez C, Ros E, Biomédica de Málaga (IBIMA), Málaga, Spain, 14 Centro de Investigación Biomédica en Red de Epidemiologı´a y Salud Pública Bullón Vela MV, Palau A, Sorli JV, (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain, 15 Instituto de Investigación Sanitaria y Biomédica de Alicante. Masagué M, Abete I, Universidad Miguel Hernández (ISABIAL-UMH). Alicante, Spain, 16 Research Group on Nutritional Epidemiology & Cardiovascular Moreno-Rodrı´guez A, Physiopathology (NUTRECOR). Health Research Institute of the Balearic Islands (IdISBa), University Hospital Son Espases Candela-Garcı´a I, Konieczna J, (HUSE), Palma de Mallorca, Spain, 17 Lipids and Atherosclerosis Unit, Department of Internal Medicine, Maimonides Biomedical Garcı´a-Rı´os A, Juárez OL, Portolés O, Research Institute of Cordoba (IMIBIC), Reina Sofia University Hospital, University of Cordoba, Córdoba, Spain, 18 Department of Martı´n P, Goday A, Zulet MÁ, Internal Medicine, Instituto de Investigaciones Biomédicas August Pi i Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Vaquero-Luna J, Orea MdCS, Barcelona, Spain, 19 Department of Endocrinology, Instituto de Investigación Biomédica de Málaga (IBIMA), Virgen de la Victoria Megı´as I, Baltasar E, Martı´nez JA Hospital, University of Málaga, Málaga, Spain, 20 Department of Family Medicine, Research Unit, Distrito Sanitario Atención and Daimiel L (2022) Primaria Sevilla, Sevilla, Spain, 21 Research Institute of Biomedical and Health Sciences Instituto Universitario de Investigaciones Role of NAFLD on the Health Related Biomédicas y Sanitarias (IUIBS), University of Las Palmas de Gran Canaria, Preventive Medicine Service, Centro Hospitalario QoL Response to Lifestyle in Patients Universitario Insular Materno Infantil (CHUIMI), Canarian Health Service, Las Palmas, Spain, 22 Department of Preventive With Metabolic Syndrome: The Medicine and Public Health, University of Granada, Granada, Spain, 23 Research Group on Community Nutrition & Oxidative PREDIMED Plus Cohort. Stress, University of Balearic Islands, Palma de Mallorca, Spain, 24 Institute of Biomedicine (IBIOMED), University of León, León, Front. Endocrinol. 13:868795. Spain, 25 Lipids and Vascular Risk Unit, Internal Medicine, Hospital Universitario de Bellvitge, Hospitalet de Llobregat, Barcelona, doi: 10.3389/fendo.2022.868795 Frontiers in Endocrinology | www.frontiersin.org 1 June 2022 | Volume 13 | Article 868795 Martı´nez-Urbistondo et al. NAFLD Impact Over Lifestyle Changes Spain, 26 Departamento de Ciencias de la Salud, Centro de Estudios Avanzados en Olivar y Aceites de Oliva, Universidad de Jaén, Jaén, Spain, 27 Department of Endocrinology and Nutrition, Instituto de Investigación Sanitaria Hospital Clı´nico San Carlos (IdISSC), Madrid, Spain, 28 Biomedical Research Centre for Diabetes and Metabolic Diseases Network (CIBERDEM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain, 29 Endocrinology and Nutrition Service, Instituto de Investigaciones Biomédicas August Pi i Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain, 30 Department of Endocrinology and Nutrition, Hospital Fundación Jimenez Dı´az, Instituto de Investigaciones Biomédicas IISFJD. University Autónoma, Madrid, Spain, 31 Department of Nutrition, Food Sciences and Physiology, University of Navarra, Pamplona, Spain, 32 Centro de Salud San Pola, Alicante, Spain, 33 Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain, 34 Nutritional Control of the Epigenome Group. Precision Nutrition and Obesity Program. Instituto Madrileño de Estudios Avanzados (IMDEA) Food, Centro de Excelencia en Investigación (CEI) Universidad Autónoma de Madrid (UAM) + Centro Superior de Investigaciones Científicas (CSIC), Madrid, Spain Objective: To evaluate the effect of Non-alcoholic fatty liver disease (NAFLD) status in the impact of lifestyle over Health-related quality of life (HRQoL) in patients with metabolic syndrome (MetS). Methods: Baseline and 1 year follow up data from the PREDIMED-plus cohort (men and women, 55-75 years old with overweight/obesity and MetS) were studied. Adherence to an energy-restricted Mediterranean Diet (er-MeDiet) and Physical Activity (PA) were assessed with a validated screeners. Hepatic steatosis index (HSI) was implemented to evaluate NAFLD while the SF-36 questionnaire provided HRQoL evaluation. Statistical analyses were performed to evaluate the influence of baseline NAFLD on HRQoL as affected by lifestyle during 1 year of follow up. Results: Data from 5205 patients with mean age of 65 years and a 48% of female participants. Adjusted linear multivariate mixed regression models showed that patients with lower probability of NAFLD (HSI < 36 points) were more responsive to er-MeDiet (b 0.64 vs b 0.05 per er-MeDiet adherence point, p< 0.01) and PA (b 0.05 vs b 0.01 per MET-h/week, p = 0.001) than those with high probability for NAFLD in terms Physical SF- 36 summary in the 1 year follow up. 10 points of er-MeDiet adherence and 50 MET-h/ week were thresholds for a beneficial effect of lifestyle on HRQoL physical domain in patients with lower probability of NAFLD. Conclusion: The evaluation of NAFLD by the HSI index in patients with MetS might identify subjects with different prospective sensitivity to lifestyle changes in terms of physical HRQoL (http://www.isrctn.com/ISRCTN89898870). Keywords: NAFLD, metabolic syndrome, mediterranean diet, physical activity, HRQoL INTRODUCTION monitoring of patients and an objective quantitation of the effect of therapeutic measures on NAFLD status. The prevalence of Non-alcoholic Fatty Liver Disease (NAFLD) is Weight loss is a major target in patients with fatty liver disease raising worldwide (1). Indeed, lipid metabolism associated (13). In this context, changes in lifestyle have an impact on disorders are the most rapidly increasing cause of morbidity NAFLD status (7). Among dietary patterns, the Mediterranean and mortality among hepatic patients in Western countries (2). Diet (MedDiet) provides a balanced nutrient composition, which NAFLD can be considered a manifestation of the metabolic should be strongly deemed in treating this disease (14). syndrome (MetS) burden in the liver (3, 4). In terms of Furthermore, moderate physical activity (PA) has shown a pathogenesis, fatty liver disease is the result of the clustering of healthy potential in the reduction of NAFLD morbid severity genetic inheritance, lifestyle factors, ageing, hepatotoxic drugs, through the improvement of insulin resistance, anti-inflammatory co-morbidities and gut microbiota (5–11). effects and antioxidant mechanisms. In this context, non-invasive assessment of liver steatosis using Likewise, both MedDiet and PA are closely related to quality indexes, such as Hepatic Steatosis Index (HSI) were developed to of life (QoL) in patients with MetS (15, 16). The SF-36 index is select patients at a higher risk of NAFLD in population studies widely used, being sensitive to changes and has been validated for (12). These scales could provide a non-invasive longitudinal the Spanish population, separating information through mental Frontiers in Endocrinology | www.frontiersin.org 2 June 2022 | Volume 13 | Article 868795 Martı´nez-Urbistondo et al. NAFLD Impact Over Lifestyle Changes and physical components of QoL and providing a precision score for each category of the SF36-HRQL tests as well as for medicine approach to Health-Related Quality of life (HRQoL). the physical component dimension were evaluated as continuous The physical aggregated component of SF-36 (PCS) mainly variables. Data among quartiles were compared using ANOVA. accounts for categories related to physical function, physical For longitudinal analyses, data from volunteers with missing or role, vitality, body pain and general health perceptions. Thus, the implausible values for the defined variables at 1 year of follow-up PCS is relevant in the clinical setting for the screening of physical were excluded, including 3902 participants (Figure 1). factors that influence medical issues in QoL (17, 18). Longitudinal analysis for the variation of the SF-36 components The personalization of indications and the linkage between were analyzed with correlation panels. Afterwards, linear mixed lifestyle intervention and a short-term benefit in terms of quality model with individual random effect adjusted by age, sex, of life could improve the adherence to healthy habits, which may recruitment center, daily alcohol consumption, total caloric benefit NAFLD patients. In this context, the objective of the intake, waist circumference and number of metabolic syndrome present study is the longitudinal evaluation of the impact of features were applied to evaluate and compare the response of SF- MedDiet and Physical activity on Health-related Quality of Life 36 PCS depending on er-MeDiet and PA adherence in both HSI < according to a baseline non-invasive evaluation of the NAFLD 36 and HSI ≥ 36 subgroups. Contrasts were performed including status based on the HSI score in patients with MetS from the the interaction between modifiable factors (Mediterranean diet PREDIMED-Plus trial. adherence and physical activity) as an independent variable in the model. Two-tailed level of 0.05 were considered as a threshold for statistical significance. All analyses were conducted with data from METHODS database version 202012220958_PREDIMEDplus_2anys_2020- 12-22. “R-Studio1.4.17” (RStudio Team. PBC, Boston, MA) was Study Design and Participants used for analysis. This analysis was based on baseline and 1 year data of the multicenter PREDIMED-Plus trial. The study protocol, including study design and data collection, has been published (19) and can be found at the PREDIMED-Plus website (https:// RESULTS www.predimedplus.com/en/). The detailed description of design and aims of the study could be found in Appendix 1. All authors Population Description and Liver Status had access to the study data and had reviewed and approved the Assessment at Baseline final manuscript. A total of 5,021 patients fulfilled the inclusion criteria and were analyzed in the study (Figure 1). At baseline, the mean age of the Hepatic Steatosis Index study sample was 65.10 ± 4.91 years with a 48.1% of female The liver status in terms of risk of NAFLD was measured with participants. Demographic, anthropometric, lifestyle characteristics the Hepatic Steatosis Index (HSI), which was calculated using the and MetS features are described by HSI quartiles (Table 1) and by described formula: HSI validated cut-off values HSI >36 and HSI < 36 (Supplementary Table 1). As expected, participants with higher HSI index showed ALT higher levels of glucose, tryglicerides and liver enzymes. They also HSI = 8 x AST showed higher BMI and waist perimeter and lower HDL levels. They also showed a worse lifestyle indicated by a lower adherence to + BMI ð+ 2 if type 2 diabetes yes, + 2 if femaleÞ a MedDiet, lower PA and higher sedentarism. A poor control of the (1) risk factors included in MetS was found to be directly related to the A cut-off value of 36 points was used to select patients with a HSI score with statistical signification, except for hypertension (p < higher risk of NAFLD as described in previous reports (20). 0.05) (Supplementary Figure 1). Health-Related Quality of Life Health Related Quality of Life Distribution An adapted version of previously published 36-items HRQL at Baseline questionnaire (SF36-HRQL) was used. This scale is validated The levels of HRQoL were described as the result of the 8 for the Spanish population and extensively used to measure the categories of SF-36 and the 2 validated physical and mental subjective awareness of health and capability or physical summaries among HSI quartiles. These results are shown divided constraints to manage with daily tasks. The PCS SF-36 index by HSI quartiles (Table 2). Quality of life showed a statistically was calculated according to previously published coefficients (18). significant inverse association to HSI score quartile among all categories and both summaries (p< 0,001). Statistical Analyses Data from 5021 participants were included (Figure 1). The Longitudinal Evaluation of NAFLD Status patient’s characteristics were defined as mean ± SD for in the Influence of Lifestyle on HRQoL quantitative variables and as proportions for qualitative For a longitudinal evaluation of the influence of NAFLD in the variables. Participants were stratified according to the HSI effect of Lifestyle on HRQoL, a raw correlation analysis was quartiles and regarding the 36-point cut-off at baseline. The performed featuring the increase in HRQoL and both the er- Frontiers in Endocrinology | www.frontiersin.org 3 June 2022 | Volume 13 | Article 868795 Martı´nez-Urbistondo et al. NAFLD Impact Over Lifestyle Changes FIGURE 1 | Flowchart of the PREDIMED-Plus participants. MeDiet and PA adherence after one year follow-up, dividing probability of NAFLD (HSI ≥ 36 points) including baseline and 1 patients between those with a HSI score below 36 (lower year of follow up data. probability of liver steatosis) and those with 36 points or more In the evaluation of er-MeDiet, differences were found in the HSI score (higher probability of liver steatosis). Both models between both subgroups in physical role, and PCS after showed a different response in terms of HRQoL to lifestyle adjustment by age, sex, recruitment node, total calory intake, changes depending on liver status in both er-MeDiet and PA alcohol consumption, waist circumference, number of items of adherence (p < 0.05 respectively). This data are shown in Figure 2. the MetS and PA. The PCS response to er-MeDiet adherence was According to these results, mixed multivariate regression found to be higher in patients with lower HSI (b 0.58 CI 95% models were developed to evaluate the consequences of er- 0.27-1.00) in comparison with those with a HSI ≥ 36 points (b MeDiet adherence and PA in patients with lower probability of 0.07 CI 95% -0.06-0.16) as shown (Table 3A). These results were liver steatosis according to HSI < 36 points and those with a high not replicated when stratifying patients in the different Frontiers in Endocrinology | www.frontiersin.org 4 June 2022 | Volume 13 | Article 868795 Martı´nez-Urbistondo et al. NAFLD Impact Over Lifestyle Changes TABLE 1 | Population characteristics at baseline. Variable Global HSI p < 25 HSI p26 - p50 HSI p51 – p75 HSI > p75 p HSI interval [min - max] [30.95 - 39.62] [39.62 - 42.68] [42.69 - 46.31] [46.31 - 192.54] NA n 5021 1256 1255 1255 1255 Age, years (SD) 65.10 (4.91) 65.48 (5.08) 65.63 (4.88) 64.76 (4.91) 64.53 (4.71) <0.001 Sex, female (%) 2417 (48.1) 455 (36.2) 565 (45.0) 657 (52.4) 740 (59.0) <0.001 Civil status (%) 0.052 Single 248 (4.9) 61 (4.9) 56 (4.5) 61 (4.9) 70 (5.6) Married 3857 (77.0) 989 (78.9) 970 (77.5) 977 (78.0) 921 (73.6) Widowed/divorced 906 (18.1) 204 (16.3) 226 (18.1) 215 (17.2) 261 (20.8) Education level (%) 0.001 Primary 2479 (49.4) 570 (45.4) 606 (48.3) 657 (52.4) 646 (51.5) Secondary 1461 (29.1) 369 (29.4) 373 (29.7) 352 (28.0) 367 (29.2) College 1081 (21.5) 317 (25.2) 276 (22.0) 246 (19.6) 242 (19.3) Working status, inactive (%) 4005 (80.1) 1005 (80.3) 1017 (81.2) 974 (78.0) 1009 (80.7) 0.192 Body mass index, kg/m2, (SD) 32.51 (3.42) 29.20 (1.58) 31.23 (1.98) 33.26 (2.27) 36.36 (2.71) <0.001 Waist circumference, cm, (SD) 107.48 (9.55) 101.21 (7.36) 105.08 (7.85) 108.91 (8.45) 114.71 (8.83) <0.001 Adherence to MeDiet, 0-17, (SD) 8.48 (2.64) 8.57 (2.73) 8.60 (2.64) 8.45 (2.62) 8.33 (2.58) 0,042 Physical activity, METs-min/week, (SD) 2519.35 (2322.82) 2972.26 (2457.73) 2625.55 (2299.09) 2470.96 (2392.26) 2008.27 (2016.13) <0.001 Sedentarism, Yes (%) 2193 (43.7) 462 (36.8) 495 (39.5) 581 (46.3) 655 (52.2) <0.001 Energy intake reported, Kcal/day, (SD) 2351.48 (552.16) 2383.52 (550.77) 2354.77 (541.46) 2322.94 (557.01) 2344.64 (558.17) 0.05 Alcohol intake, g/day, (SD) 10.90 (14.86) 12.23 (15.08) 11.19 (14.89) 10.92 (15.25) 9.27 (14.08) <0.001 Fasting blood glucosa, mg/dl, (SD) 113.44 (27.30) 105.11 (19.19) 110.90 (25.18) 115.80 (28.37) 121.97 (31.98) <0.001 Fasting blood tryglicerides, mg/dl, (SD) 140.88 (52.93) 132.94 (52.38) 138.51 (51.98) 145.23 (53.09) 146.83 (53.15) <0.001 Fasting High-density lipoprotein, mg/dl, (SD) 48.01 (11.63) 48.86 (12.49) 47.86 (10.95) 47.67 (11.12) 47.65 (11.88) 0,027 Alanin aminotransferase, UI/L, (SD) 26.71 (15.05) 20.36 (8.19) 24.39 (12.83) 28.24 (14.35) 33.86 (19.24) <0.001 Aspartate aminotransferase, UI/L, (SD) 23.10 (9.52) 22.72 (8.54) 22.68 (9.05) 23.57 (10.06) 23.42 (10.30) 0,029 Hepatic steatosis index, points (SD) 43.28 (5.80) 37.41 (1.63) 41.15 (0.88) 44.42 (1.05) 50.15 (6.53) <0.001 Systolic blood pressure (mmHg) 139.72 (16.87) 138.51 (16.59) 140.00 (17.23) 139.65 (16.70) 140.74 (16.91) 0.01 Diastolic blood pressure (mmHg) 80.64 (9.86) 80.46 (9.05) 80.54 (9.99) 80.94 (10.06) 80.62 (10.30) 0.644 Diagnosed hypertension (%) 4187 (84.0) 1037 (83.3) 1037 (83.0) 1036 (83.5) 1077 (86.3) 0.085 Diagnosed diabetes (%) 1358 (27.1) 176 (14.1) 289 (23.1) 388 (31.0) 505 (40.3) <0.001 Liver esteatosis HSI > 36 points (%) 4777 (95.1) 1012 (80.6) 1255 (100.0) 1255 (100.0) 1255 (100.0) <0.001 HSI, Hepatic steatosis index; SD, Standard deviation; MeDiet, Mediterranean Diet. Bold for p values < 0.05. NA, Not applicable. components of the HSI (ALT/AST ratio, BMI, fasting blood to be resistant to increases in er-MeDiet adherence, while glucose > 100 mg/dl and sex) or by age (Supplementary patients with lower NAFLD risk are very sensitive to dietary Tables 1, 2). Data were plotted to show the influence of er- changes in terms of HRQoL aggregated physical domain. MeDiet adherence in terms of HRQoL variation (Figure 3A). Beyond, patients below a 10-point adherence to er-MeDiet, In this figure, the linear mixed model predicts the annual tended to lose HRQoL PCS while those with a score of 10 increase of HRQoL depending on the er-MeDiet score points or higher, improved HRQoL PCS in the 1-year follow- providing that patients with high probability of NAFLD tend up (Figure 3A). TABLE 2 | Score of the SF-36 Quality of Life categories among HSI baseline levels. Variable (0-100 points) HSI p < 25 HSI p26 - p50 HSI p51 – p75 HSI > p75 p HSI interval [min - max] [30.95 - 39.62] [39.62 - 42.68] [42.69 - 46.31] [46.31 - 192.54] NA Physical status, (SD) 82.01 (16.78) 77.43 (18.84) 75.57 (18.75) 69.12 (21.64) <0.001 Physical role, points, (SD) 81.28 (32.79) 77.23 (35.09) 76.71 (35.23) 70.81 (37.94) <0.001 Body pain, points, (SD) 69.69 (25.25) 65.20 (25.95) 62.46 (26.07) 57.47 (27.48) <0.001 General health, points, (SD) 65.74 (17.01) 63.51 (18.67) 61.89 (18.38) 58.62 (19.63) <0.001 Vitality, points, (SD) 68.53 (19.95) 65.41 (21.13) 63.51 (21.16) 58.64 (22.57) <0.001 Social role, points, (SD) 89.30 (17.88) 87.19 (20.01) 86.22 (21.20) 82.44 (23.54) <0.001 Emotional role, points, (SD) 89.74 (27.37) 88.19 (28.58) 87.56 (29.74) 83.67 (33.24) <0.001 Mental health, points, (SD) 77.00 (18.10) 76.08 (18.74) 74.62 (19.48) 71.58 (20.75) <0.001 Physical SF-36 summary, points, (SD) 47.39 (8.16) 45.51 (8.62) 44.79 (8.67) 42.60 (9.61) <0.001 Mental SF-36 summary, points, (SD) 52.11 (9.59) 51.91 (9.86) 51.47 (10.45) 50.23 (11.49) <0.001 HSI, Hepatic steatosis index; SD, Standard deviation; MeDiet, Mediterranean Diet. Bold for p values < 0.05. NA, Not applicable. Frontiers in Endocrinology | www.frontiersin.org 5 June 2022 | Volume 13 | Article 868795 Martı´nez-Urbistondo et al. NAFLD Impact Over Lifestyle Changes A B FIGURE 2 | (A) Correlation of HRQoL increase and er-MeDiet adherence modification in patients with higher NAFLD probability and lower NAFLD probability. (B) Correlation of HRQoL increase and Physical activity modification in patients with higher NAFLD probability and lower NAFLD probability. In the evaluation of PA, patients with a higher improvement After this analysis, the regression model was replicated among in physical role, body pain and vitality scores in response to quartiles of HSI to provide information about progressive increases in PA were associated to a lower HSI after previously response of HRQoL depending on lifestyle. Although no described adjustments (Table 3B). In the evaluation of PA, the important statistically significant results were found in this HSI influence on HRQoL evolution was not replicated when approach, a trend towards statistical significance was found in stratifying patients in the different components of the HSI (ALT/ the Physical Activity adherence group (Supplementary AST ratio, BMI, diabetes and sex) or by age (Supplementary Tables 4, 5). Tables 2, 3). The PCS response to PA was found to improve more in patients with lower HSI (b 0.05 CI 95% 0.03-0.07) in comparison with those with a HSI ≥ 36 points (b 0.03 CI 95% DISCUSSION 0.01-0.02) as described (Table 3B and Figure 3B). Besides, patients performing less than 50 MET-h/week of PA, tended to The results from the current research evidence the capacity of a lose HRQoL while those accomplishing more PA, improved non-invasive evaluation of NAFLD to modify the effect of HRQoL in the 1-year follow-up (Figure 3B). Additional lifestyle over Health-related Quality of Life. The increase in the information for the interpretation of this results about the adherence to a er-MedDiet pattern and PA might lead to more predicted PCS year increase depending on different levels of than a 5-fold increase in the aggregated physical domain of PA and er-MeDiet are also provided (Supplementary Figure 2). HRQoL depending on the presence of NAFLD, using previously Frontiers in Endocrinology | www.frontiersin.org 6 June 2022 | Volume 13 | Article 868795 Martı´nez-Urbistondo et al. NAFLD Impact Over Lifestyle Changes TABLE 3A | Mixed multivariate model on the effect of Mediterranean diet adherence on SF-36 components after 1-year follow up. Indeterminate probability of NAFLD High probability of NAFLDHSI > 36 p for non-NAFLD vs. NAFLD patients (HSI < 36) b 95% Conf. Interval b 95% Conf. Interval Pyisical status, points, (SD) 0.70 -0.15 1.55 -0.12 -0.35 0.11 0.067 Physical role, points, (SD) 2.63 0.77 4.49 0.34 -0.17 0.85 0.020 Body pain, points, (SD) 1.14 -0.18 2.46 -0.02 -0.37 0.34 0.097 General health, points, (SD) 0.96 0.10 1.83 0.44 0.21 0.67 0.255 Vitality, points, (SD) 0.46 -0.51 1.42 0.18 -0.08 0.44 0.588 Social role, points, (SD) 0.03 -1.05 1.10 0.21 -0.08 0.50 0.744 Emotional role, points, (SD) 0.41 -1.20 2.02 0.30 -0.15 0.74 0.893 Mental health, points, (SD) 0.22 -0.66 1.11 0.13 -0.11 0.37 0.845 Physical SF-36 summary, points, (SD) 0.58 0.16 1.00 0.04 -0.07 0.15 0.014 Mental SF-36 summary, points, (SD) -0.11 -0.62 0.41 0.11 -0.03 0.25 0.426 er-MeDiet adherence. Adjusted by: Age (years), sex, recruitment node, physical activity (METs/h/week), daily alcohol consumption (g/day), total caloric intake (kcal/day), waist circumference and number of Metabolic Syndrome components. HSI, Hepatic steatosis index; SD, Standard deviation. Bold for p values < 0.05. validated and easy to fulfill scores such as SF-36 and HSI (18, 20). further evidence on the association of HSI score and the MetS In this context, different methods of detection of liver steatosis features (3). Furthermore, these results reinforce the impact of have been previously validated, such as ultrasound, controlled liver steatosis in QoL (20) and might support previous evidence attenuation parameters of FibroScan©. Among them, HSI has on the use of non-invasive methods for the individualization of demonstrated adequacy in the epidemiological study of liver patients with MetS in the clinical setting (23–25). Thus, the disease (21), while demonstrating a high similar discrimination apparent resistance of patients with NAFLD to lifestyle measures power than other more expensive or less available detection in terms of HRQoL in the longitudinal analysis could adequate methods (22). Besides, our results provide a clinically relevant the prescription of the therapeutic armamentarium in these objectives in terms of er-MeDiet adherence and PA to improve patients, bringing forward more aggressive treatments in HRQoL in patients with MetS and lower probability of NAFLD. selected subjects, such as GLP-1 analogs and bariatric surgery To our knowledge, this is the first investigation to proof the (26, 27). Beyond, the 10 point er-MeDiet adherence and 50 differential effect of lifestyle measures in patients with MetS MET-h/week thresholds for the improvement of HRQoL in depending on a non-invasive assessment of liver steatosis. patients with lower probability of NAFLD may provide a goal Interestingly, in our cohort, the HSI score was associated to a of lifestyle change in these patients as well as an objective lower adherence to er-MeDiet and PA performance and to a evaluation and counselling in the clinical setting. Therefore, higher prevalence and of the components of MetS at baseline. our study could contribute to the development of new lifestyle- These findings are endorsed by indirect findings and provide based intervention guidelines for patients with MetS according to TABLE 3B | Physical activity performance. Lower probability of NAFLD (HSI < 36) Higher probability of NAFLDHSI > 36 p for non-NAFLD vs. NAFLD patients b 95% Conf. Interval b 95% Conf. Interval Pyisical status, points, (SD) 0.030 -0.027 0.086 0.015 -0.001 0.031 0.619 Physical role, points, (SD) 0.179 0.054 0.304 0.034 -0.002 0.070 0.030 Body pain, points, (SD) 0.123 0.035 0.211 0.021 -0.004 0.046 0.031 General health, points, (SD) 0.012 -0.046 0.069 0.015 -0.001 0.031 0.907 Vitality, points, (SD) 0.050 -0.014 0.114 -0.003 -0.021 0.015 0.126 Social role, points, (SD) -0.001 -0.073 0.071 0.007 -0.014 0.028 0.845 Emotional role, points, (SD) -0.035 -0.144 0.073 -0.0004 -0.032 0.031 0.545 Mental health, points, (SD) -0.033 -0.092 0.026 -0.002 -0.018 0.015 0.323 Physical SF-36 summary, points, (SD) 0.046 0.018 0.073 0.011 0.003 0.019 0.019 Mental SF-36 summary, points, (SD) -0.026 -0.061 0.008 -0.004 -0.014 0.005 0.229 Adjusted by: Age (years), sex, recruitment node, Mediterranean diet score, daily alcohol consumption (g/day), total caloric intake (kcal/day), waist circumference and number of Metabolic Syndrome components. HSI, Hepatic steatosis index; SD, Standard deviation. Bold for p values < 0.05. Frontiers in Endocrinology | www.frontiersin.org 7 June 2022 | Volume 13 | Article 868795 Martı´nez-Urbistondo et al. NAFLD Impact Over Lifestyle Changes A B FIGURE 3 | (A) Prediction of effect of Mediterranean diet adherence on SF-36 components after 1-year follow up adjusted by age, sex, recruitment node, daily alcohol consumption, total caloric intake, waist circumference and aggregated MetS features. a: percentile 20 for er-MEDAS MedDiet score (8 points) of participants with HSI < 36; b: percentile 40 for er-MEDAS MedDiet score (10 points) of participants with HSI < 36; c: percentile 60 for er-MEDAS MedDiet score (12 points) of participants with HSI < 36; d: percentile 80 for er-MEDAS MedDiet score (15 points) of participants with HSI < 36; * cutoff point (10 points) with the x axis (D Physical SF-36 summary = 0) from which patients with HSI < 36 benefit from er-MeDiet adherence in terms of physical HRQoL. (B) Prediction of effect of Physical activity on SF-36 components after 1-year follow up adjusted by age, sex, recruitment node, daily alcohol consumption, total caloric intake, hip-waist circumference and aggregated MetS features. a: percentile 20 for METs*hour/week (25 METs*hour/week) of participants with HSI < 36; b: percentile 40 for METs*hour/week (40 METs*hour/week) of participants with HSI ;< 36 c: percentile 60 for METs*hour/week (62 METs*hour/week) of participants with HSI < 36; d: percentile 80 for METs*hour/week (94 METs*hour/week) of participants with HSI < 36; * cutoff point (50 METs*hour/week) with the x axis (D Physical SF-36 summary = 0) from which patients with HSI < 36 benefit from PA changes in terms of physical HRQoL. the liver status which in fact, may also provide further benefits in cohort (31). Similar results were found on PA relationship to the cardiovascular disease scenario, due to the association of HRQoL, with a direct relationship to the control of MetS and NAFLD and atherosclerotic disease development (28, 29). HRQoL. However, the concept of a modulation of NAFLD status With regard of the impact of Mediterranean diet and PA in in the impact of er-MeDiet and PA on HRQoL is new. In fact, HRQoL depending on the liver status, some aspects should be interventions tend to be maximized in patients at higher risk emphasized. The effect of Mediterranean diet has been (32). Thus, the capacity of HSI to identify patients with a better previously related to the MetS prevention and control after response to lifestyle as measured with HRQoL parameters might 1 year follow up (30). Besides, MedDiet pattern has also been be related to the NAFLD morbidity burden (33). Other factor related to HRQoL in previous series and in the present that could contribute to our results is the severity of the MetS Frontiers in Endocrinology | www.frontiersin.org 8 June 2022 | Volume 13 | Article 868795 Martı´nez-Urbistondo et al. NAFLD Impact Over Lifestyle Changes among progressive HSI values. This fact might be related to a MeDiet adherence and 50 MET-h/week, providing precision poorer metabolic flexibility of patients with NAFLD in terms of medicine prescriptions depending on liver condition status. body composition (34), insulin resistance (35), microbioma (9) and redox/equilibrium (36) and thus, a reduction on the sensitivity to lifestyle change of this population due to a DATA AVAILABILITY STATEMENT reduction in homeostasis capability (37). In the methodological arena, the design quality of There are restrictions on data availability for the PREDIMED- PREDIMED plus provides strength to the present results in Plus trial due to the signed consent agreements around data terms of inclusion criteria fulfillment, anthropometric and sharing, which only allow access to external researchers for laboratory tests and adherence to er-MeDiet and PA patterns studies following the project purposes. Requestors wishing assessment (19). Besides, the SF-36 Physical summary and the to access the PREDIMED-Plus trial data used in this study can HSI index are well validated and universally used indexes in the make a request to the PREDIMED-Plus trial Steering Committee evaluation of both HRQoL and liver steatosis (18, 20). Even chair: jordi.salas@urv.cat. The request will then be passed though, some limitations should be addressed. First, the cohort to members of the PREDIMED-Plus Steering Committee recruitment was designed to evaluate the effect of the for deliberation. intervention on dietary patterns and PA in patients with MetS. Then, the present findings should be externally validated in a different cohort. In this context, the present analysis does not ETHICS STATEMENT follow the original strategy of the cohort, resembling to a per- protocol evaluation by using patient information about erMeDiet The studies involving human participants were reviewed and and PA adherence according to patient declaration and not due approved by Predimed Plus trial. The patients/participants to the distribution between the control and intervention provided their written informed consent to participate in branches. Although the characteristics of the full PREDIMED this study. plus trial do not allow to uncover the intervention and control groups, no differences were found in the proportion of patients in the intervention and control groups among HSI < 36 and HSI > AUTHOR CONTRIBUTIONS 36 (p > 0.05). Besides, although HSI is a remarkable non-invasive tool in the detection of NAFLD, this index is not designed for MAM-G, NB, DC, JLV, AMA-G, JW, JesV, DR, JL-M, RE, FT, JL, NAFLD staging. In fact, biopsy directed studies have JS-M, AB-C, JT, AM, XP, MD-R, PMM, JosV, MM, IA, AM-R, demonstrated a different distribution of NASH in patients with IC-G, JK, AG-R, OL, OP, AG, MZ, JV-L, MCSO, IM, EB, JAM, MetS than in those with type 2 diabetes mellitus (38). Although JO and LD designed and conducted the research. DM-U, RS-C, the NAFLD staging may exceed the objective of the present PV, JM and LD conceived the study idea and the analysis design. study, this feature could be addressed in future studies. Yet, the LD supervised the research and DM-U and RS-C carried out the present results are valuable from the clinical point of view, analysis procedures, bibliographic research, data preparation, providing remarkably similar assessment of the influence of statistical analysis and wrote initial drafts. RS-C assisted with adherence to healthy lifestyle patterns in patients’ health as statistical analysis and R programming. PV and JO participated that of the consultation room. The longitudinal multivariate in the scientific discussion of experimental results. All the analysis and adjustments, using features related to HRQoL such authors assisted in manuscript revision for intellectual content as waist circumference obesity, MetS features (39), alcohol and approved it. consumption (40) and total caloric intake (41, 42) provide plausibility to the present results. In summary, the demonstration of the influence of NAFLD in the response to lifestyle modifications might represent an FUNDING interesting tool for personalization and precision medicine in the cardiovascular risk epidemiological and clinical scenarios The present study received funding from coordinated FIS project emphasizing the mediation of liver status in the therapeutical official Spanish institutions for funding scientific biomedical response. The present findings could encourage future research research, CIBER Fisiopatología de la Obesidad y Nutrición in the individualization of treatment of patients with MetS based (CIBEROBN) and Instituto de Salud Carlos III (ISCIII) on liver condition. through the Fondo de Investigación para la Salud (FIS) which is co-funded by the European Regional Development Fund (including the following projects: PI13/00673, PI13/00492, PI13/ CONCLUSION 00272, PI13/01123, PI13/00462, PI13/00233, PI13/02184, PI13/00728, PI13/01090, PI13/01056, PI14/01722, PI14/00636, The detection of NAFLD by the HSI index in patients with MetS PI14/00618, PI14/00696, PI14/01206, PI14/01919, PI14/ might identify subjects with lower sensitivity to lifestyle changes 00853, PI14/01374, PI14/00972, PI14/00728, PI14/01471, in terms of HRQoL. Patients with lower NAFLD probability PI16/00473, PI16/00662, PI16/01873, PI16/01094, PI16/00501, begun to obtain improvement on HRQoL at 10 points of er- PI16/00533, PI16/00381, PI16/00366, PI16/01522, PI16/ Frontiers in Endocrinology | www.frontiersin.org 9 June 2022 | Volume 13 | Article 868795 Martı´nez-Urbistondo et al. NAFLD Impact Over Lifestyle Changes 01120, PI17/00764, PI17/01183, PI17/00855, PI17/01347, PI17/ (RTI2018-095569-B-I00) and «PROGRAMACIÓN 00525, PI17/01827, PI17/00532, PI17/00215, PI17/01441, PI17/ CONJUNTA INTERNACIONAL» (PCI2018-093009). 00508, PI17/01732, PI17/00926, PI19/00957, PI19/00386, PI19/ 00309, PI19/01032, PI19/00576, PI19/00017, PI19/01226, PI19/ 00781, PI19/01560, PI19/01332, PI20/01802, PI20/00138, PI20/ 01532, PI20/00456, PI20/00339, PI20/00557, PI20/00886, PI20/ ACKNOWLEDGMENTS 01158), the Special Action Project “Implementación y evaluación de una intervención intensiva sobre la actividad física Cohorte We thank the PREDIMED-Plus trial volunteers who donated PREDIMED-Plus”, the Recercaixa (grant number blood for their participation in this study, the PREDIMED-Plus 2013ACUP00194) funding and the grants from the Consejería personnel for their support, and the personnel from associated de Salud de la Junta de Andalucía (PI0458/2013; PS0358/2016; primary health care centers for their exceptional effort. CIBEROBN PI0137/2018), the SEMERGEN grant; Department of Health of is an initiative of ISCIII, Spain. Jordi Salas-Salvadó and Montse Fitó the Government of Navarra (61/2015), the Fundació La Marató contributed to the design and conduction of the research. de TV (Ref. 201630.10), the coordinated grant supported by the European Research Council (Advanced Research grant 2014– 2019; agreement #340918), the grant of support to research SUPPLEMENTARY MATERIAL groups 35/2011 (Balearic Islands Government; FEDER funds). This study has been carried out thanks to the funds provided by The Supplementary Material for this article can be found online at: Ministerio de Ciencia e Investigación through grants from https://www.frontiersin.org/articles/10.3389/fendo.2022.868795/ PROYECTOS DE I+D+I «RETOS INVESTIGACIÓN» full#supplementary-material Systems in Patients With Non-Alcoholic Fatty Liver Disease. J Hepatol REFERENCES (2021) 75(4):786–94. doi: 10.1016/j.jhep.2021.05.008 1. 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Aguilar-Olivos NE, Almeda-Valdes P, Aguilar-Salinas CA, Uribe M, Mé ndez- Sá nchez N. The Role of Bariatric Surgery in the Management of Nonalcoholic Conflict of Interest: Author JS-S reports grants from CIBEROBN, ISCIII (Spain), Fatty Liver Disease and Metabolic Syndrome. Metabolism (2016) 65(8):1196– during the conduct of the study; non-financial support from Nut and Dried Fruit 207. doi: 10.1016/j.metabol.2015.09.004 Foundation, personal fees from Instituto Danone Spain, grants from Nut and 28. Rinaldi L, Pafundi PC, Galiero R, Caturano A, Morone MV, Silvestri C, et al. Dried Fruit Foundation to this institution, grants from Eroski Distributors and Mechanisms of Non-Alcoholic Fatty Liver Disease in the Metabolic personal fees from Nut and Dried Fruit Foundation, outside the submitted work. Syndrome. A Narrat Rev Antiox (Basel) (2021) 10(2):270. doi: 10.3390/ Moreover, he gratefully acknowledges the financial support by ICREA under the antiox10020270 ICREA Academia program. The author DR declares the funding of the 29. Galiero R, Caturano A, Vetrano E, Cesaro A, Rinaldi L, Salvatore T, et al. AstraZeneca Young Investigators Award in Category of Obesity and T2D 2017. Pathophysiological Mechanisms and Clinical Evidence of Relationship The author RS-C acknowledges financial support from the Juan de la Cierva Between Nonalcoholic Fatty Liver Disease (NAFLD) and Cardiovascular Program Training Grants of the Spanish State Research Agency of the Spanish Disease. Rev Cardiovasc Med (2021) 22(3):755–68. doi: 10.31083/ Ministerio de Ciencia e Innovación y Ministerio de Universidades (FJC2018- j.rcm2203082 038168- I). The author ER reports grants, personal fees, non-financial support and 30. Salas-Salvadó J, Ferná ndez-Ballart J, Ros E, Martı́nez-Gonzá lez MA, Fitó M, other from California Walnut Commission, grants, personal fees, non-financial Estruch R, et al. Effect of a Mediterranean Diet Supplemented With Nuts on support and other from Alexion, personal fees, non-financial support and other Metabolic Syndrome Status: One-Year Results of the PREDIMED from Ferrer International, personal fees from Amarin, personal fees, non-financial Randomized Trial. Arch Intern Med (2008) 168(22):2449–58. doi: 10.1001/ support and other from Danone, outside the submitted work. The author JL-M archinte.168.22.2449 reports personal fees and non-financial support from AMGEN, personal fees and 31. Landaeta-Dı́az L, Ferná ndez JM, Da Silva-Grigoletto M, Rosado-Alvarez D, non-financial support from SANOFI, personal fees from MSD, personal fees from Gó mez-Garduño A, Gó mez-Delgado F, et al. Mediterranean Diet, Moderate- Laboratorios Dr. Esteve, and personal fees from NOVO-NORDISK, outside the to-High Intensity Training, and Health-Related Quality of Life in Adults With submitted work. Metabolic Syndrome. Eur J Prev Cardiol (2013) 20(4):555–64. doi: 10.1177/ 2047487312445000 The remaining authors declare that the research was conducted in the absence of 32. Cuende JI. Vascular Age Versus Cardiovascular Risk: Clarifying Concepts. Rev any commercial or financial relationships that could be construed as a potential Esp Cardiol (Engl Ed) (2016) 69(3):243–6. doi: 10.1016/j.rec.2015.10.019 conflict of interest. 33. Younossi Z, Anstee QM, Marietti M, Hardy T, Henry L, Eslam M, et al. Global Burden of NAFLD and NASH: Trends, Predictions, Risk Factors and Publisher’s Note: All claims expressed in this article are solely those of the authors Prevention. Nat Rev Gastroenterol Hepatol (2018) 15(1):11–20. and do not necessarily represent those of their affiliated organizations, or those of doi: 10.1038/nrgastro.2017.109 the publisher, the editors and the reviewers. Any product that may be evaluated in 34. Samala N, Desai A, Vilar-Gomez E, Smith ER, Gawrieh S, Kettler CD, et al. this article, or claim that may be made by its manufacturer, is not guaranteed or Decreased Quality of Life Is Significantly Associated With Body Composition endorsed by the publisher. in Patients With Nonalcoholic Fatty Liver Disease. Clin Gastroenterol Hepatol (2020) 18(13):2980–8.e4. doi: 10.1016/j.cgh.2020.04.046 ́ Copyright © 2022 Martınez-Urbistondo, San-Cristob́ al, Villares, Martınez-Gonza ́ ĺ ez, 35. Kitade H, Chen G, Ni Y, Ota T. Nonalcoholic Fatty Liver Disease and Insulin Babio, Corella, del Val, Ordovaś , Alonso-Gom ́ ez, Wärnberg, Vioque, Romaguera, Resistance: New Insights and Potential New Treatments. Nutrients (2017) 9 Loṕ ez-Miranda, Estruch, Tinahones, Lapetra, Serra-Majem, Bueno-Cavanillas, Tur, (4):387. doi: 10.3390/nu9040387 Marcos, Pinto,́ Delgado-Rodrıguez,́ ́ Matıa-Martı n, ́ Vidal, Vaź quez, Ros, Bulloń Vela, 36. Marra F, Svegliati-Baroni G. Lipotoxicity and the Gut-Liver Axis in NASH Palau, Sorli, Masague,́ Abete, Moreno-Rodrıguez, ́ Candela-Garcıa, ́ Konieczna, Pathogenesis. J Hepatol (2018) 68(2):280–95. doi: 10.1016/j.jhep.2017.11.014 ́ os, Garcıa-Rı ́ Juaŕ ez, Portoleś , Martın, ́ Goday, Zulet, Vaquero-Luna, Orea, Megıas, ́ 37. Yamazaki H, Wang J, Tauchi S, Dohke M, Hanawa N, Katanuma A, et al. ́ and Daimiel. This is an open-access article distributed under the Baltasar, Martınez Inverse Association Between Fatty Liver at Baseline Ultrasonography and terms of the Creative Commons Attribution License (CC BY). The use, distribution or Remission of Type 2 Diabetes Over a 2-Year Follow-Up Period. Clin reproduction in other forums is permitted, provided the original author(s) and the Gastroenterol Hepatol (2021) 19(3):556–64.e5. doi: 10.1016/j.cgh.2020.06.032 copyright owner(s) are credited and that the original publication in this journal is 38. Masarone M, Rosato V, Aglitti A, Bucci T, Caruso R, Salvatore T, et al. Liver cited, in accordance with accepted academic practice. No use, distribution or Biopsy in Type 2 Diabetes Mellitus: Steatohepatitis Represents the Sole reproduction is permitted which does not comply with these terms. Frontiers in Endocrinology | www.frontiersin.org 11 June 2022 | Volume 13 | Article 868795