nutrients Article Adherence to a Supplemented Mediterranean Diet Drives Changes in the Gut Microbiota of HIV-1-Infected Individuals Roque Pastor-Ibáñez 1 , Juan Blanco-Heredia 2,3,4 , Florencia Etcheverry 1,5 , Sonsoles Sánchez-Palomino 1 , Francisco Díez-Fuertes 1 , Rosa Casas 6,7 , María Ángeles Navarrete-Muñoz 8,9 , Sara Castro-Barquero 6,7 , Constanza Lucero 1 , Irene Fernández 1,5 , Lorna Leal 1,5 , José Miguel Benito 8,9 , Marc Noguera-Julian 10 , Roger Paredes 10 , Norma Rallón 8,9 , Ramón Estruch 6,7 , David Torrents 11,12 and Felipe García 1,5, * 1 AIDS Research Group, IDIBAPS, Hospital Clinic, University of Barcelona, 08036 Barcelona, Spain; rpastor@clinic.cat (R.P.-I.); MFETCHEV@clinic.cat (F.E.); ssanchez@clinic.cat (S.S.-P.); frandifu@icloud.com (F.D.-F.); MCLUCERO@clinic.cat (C.L.); IFERNANDEZC@clinic.cat (I.F.); LALEAL@clinic.cat (L.L.) 2 IrsiCaixa AIDS Research Institute, Germans Trias i Pujol University Hospital, 08916 Badalona, Spain; jblancoh@irsicaixa.es 3 Germans Trias i Pujol Research Institute (IGTP), 08916 Badalona, Spain 4 Barcelona Supercomputing Center, 08034 Barcelona, Spain 5 Infectious Diseases Department, Hospital Clínic, IDIBAPS, University of Barcelona, 08036 Barcelona, Spain 6 Department of Internal Medicine, Hospital Clinic, Institut d’Investigació Biomèdica August Pi i Sunyer (IDIBAPS), University of Barcelona, Villarroel, 170, 08036 Barcelona, Spain;  RCASAS1@clinic.cat (R.C.); SACASTRO@clinic.cat (S.C.-B.); RESTRUCH@clinic.cat (R.E.)  7 CIBER 06/03: Fisiopatología de la Obesidady la Nutrición, Instituto de Salud Carlos III, 28029 Madrid, Spain Citation: Pastor-Ibáñez, R.; 8 HIV and Viral Hepatitis Research Laboratory, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz, Blanco-Heredia, J.; Etcheverry, F.; Universidad Autónoma de Madrid (IIS-FJD, UAM), 28040 Madrid, Spain; Sánchez-Palomino, S.; Díez-Fuertes, mangelesnm94@gmail.com (M.Á.N.-M.); jbenito1@hotmail.com (J.M.B.); normaibon@yahoo.com (N.R.) 9 Hospital Universitario Rey Juan Carlos, Móstoles, 28933 Madrid, Spain F.; Casas, R.; Navarrete-Muñoz, M.Á.; 10 Hospital Universitari Germans Trias i Pujol, IrsiCaixa, 08916 Badalona, Spain; Castro-Barquero, S.; Lucero, C.; mnoguera@irsicaixa.es (M.N.-J.); rparedes@irsicaixa.es (R.P.) Fernández, I.; et al. Adherence to a 11 Computational Genomics Groups, Barcelona Supercomputing Center (BSC), 08034 Barcelona, Spain; Supplemented Mediterranean Diet david.torrents@bsc.es Drives Changes in the Gut Microbiota 12 Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain of HIV-1-Infected Individuals. * Correspondence: fgarcia@clinic.cat; Tel.: +34-932275586; Fax: +34-934514438 Nutrients 2021, 13, 1141. https://doi.org/10.3390/nu13041141 Abstract: Objective: The health effects of a supplemented Mediterranean diet (SMD) with extra-virgin olive oil (EVOO) and nuts are well documented in non-HIV-infected individuals. We hypothesised Academic Editor: Martina Barchitta that the benefits of an SMD could be mediated by changes in the gut microbiota, even in those with an altered intestinal microbiota such as people living with HIV. Design: Individuals living with HIV Received: 23 February 2021 Accepted: 24 March 2021 (n = 102) were randomised to receive an SMD with 50 g/day of EVOO and 30 g/day of walnuts Published: 30 March 2021 (SMD group) or continue with their regular diet (control group) for 12 weeks. Methods: Adherence to the Mediterranean diet was assessed using the validated 14-item MD-Adherence-Screener (MEDAS) Publisher’s Note: MDPI stays neutral from the PREDIMED study. A sub-study classifying the participants according to their MEDAS scores with regard to jurisdictional claims in was performed. Results: The lipid profile was improved in the SMD group vs. that in the control published maps and institutional affil- group (delta-total cholesterol and delta-B-lipoprotein). The immune activation (CD4+HLADR+CD38+ iations. and CD8+HLADR+CD38+ cells) and IFN-γ-producing T-cells significantly decreased at week 12 compared to the baseline in the SMD group but not in the control group. The gut microbiota in those from the high-adherence group presented significantly high diversity and richness at the end of the intervention. Succinivibrio and Bifidobacterium abundances were influenced by the adherence to Copyright: © 2021 by the authors. the MD and significantly correlated with Treg cells. Conclusion: The Mediterranean diet improved Licensee MDPI, Basel, Switzerland. metabolic parameters, immune activation, Treg function, and the gut microbiota composition in This article is an open access article HIV-1-infected individuals. Further, Mediterranean diet increased the Bifidobacterium abundances distributed under the terms and after the intervention, and it was associated to a beneficial profile. conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Nutrients 2021, 13, 1141. https://doi.org/10.3390/nu13041141 https://www.mdpi.com/journal/nutrients Nutrients 2021, 13, 1141 2 of 18 Keywords: gut microbiota; supplemented Mediterranean diet; lipids; lymphocyte subsets; HIV-1; Treg cells 1. Background Antiretroviral therapy (ART) has contributed to a significant decrease in the morbidity and mortality associated with acquired immune deficiency syndrome (AIDS) in human immunodeficiency virus 1(HIV-1) infected individuals [1]. However, people with chronic HIV infection have an increased risk of death due to non-AIDS events when compared to non-infected individuals [2–4]. This increase in morbidity and mortality is related to cardio- vascular diseases, malignancies, dementia, osteoporosis, and also a rise in comorbidities such as high blood pressure, diabetes, bone fractures, and kidney failure [5]. The mech- anisms driving these non-AIDS events are chronic immune activation and inflammation. Immune activation is a good independent predictor of morbidity and mortality in HIV infection [6]. It has been suggested that microbial translocation from the intestinal lumen to the systemic circulation plays a key role in the persistence of immune activation [7,8]. The destruction of gut-associated lymphoid tissue (GALT) has been postulated to underlie this microbial translocation. A rapid depletion of CD4+ T-cells at mucosal sites takes place dur- ing the first weeks of infection and persists in chronic infections. Regarding the composition of the microbiota, some studies suggest that an HIV-1 infection induces dysbiosis in the gut composition, reducing microbial richness and diversity [9,10]. It is evident that the composi- tion of the microbiota depends on nutritional habits. Bacteria that ferment proteins produce some toxic products that drive inflammatory processes, while microbes that ferment fibre inhibit inflammation [11]. The Mediterranean diet (MD) is commonly characterised by a high consumption of olive oil (OO), fruits, vegetables, legumes, nuts, and whole grain cere- als, as well as a moderate consumption of dairy products, fish, poultry meat, and red wine, accompanied by a low intake of red meat, processed meat, and sugars [12]. Extra virgin olive oil (EVOO) and walnuts contain bioactive compounds, such as monounsaturated fatty acids (MUFAs); α-tocopherol; polyunsaturated fatty acids (PUFAs), e.g., omega-3 and omega-6 fatty acids; polyphenols; and other phytochemicals, which have antioxidant and anti-inflammatory properties [13]. Data published to date and from the PREDIMED study have revealed that an MD supplemented with EVOO or nuts delays the appearance of cardiovascular disease, atrial fibrillation, cancer, and neurodegenerative disease in high-risk populations [14,15]. Moreover, the MD induces shifts in the gut microbiota [16]. However, there is a lack of robust evidence linking the effects of an MD on microbiota composition in HIV-1-infected individuals receiving ART. This information could help us understand the relationship between HIV infection and the immune-activation-driven non-AIDS events. Thus, the main aim of this study was to evaluate the composition of the microbiota of HIV-1-infected subjects based on their adherence to the supplemented Mediterranean diet (SMD), correlating this with clinical parameters, bacterial translocation, inflammatory markers, and different T-cell subsets. 2. Methods 2.1. Study Design A single-centre randomised controlled open-label clinical study was performed. HIV- infected individuals on successful ART were randomised to either receive the SMD or continue with their regular diet (control group) for 12 weeks. The inclusion criteria are shown in the Supplementary Methods. At the time of enrolment and after 12 weeks at follow-up, data on the demographic and clinical variables were collected for each participant (see Supplementary Methods). After the participants provided their signed informed consent, they were randomly assigned to one of two study groups: the SMD group receiving the MD supplemented with EVOO and walnuts or the control group continuing with their regular diet. Randomisa- Nutrients 2021, 13, 1141 3 of 18 tion was performed by random assignment. Participants in the SMD group were given supplementary foods at no cost: EVOO (1 L/week) and walnuts (30 g/day). The validated 14-item MD Adherence Screener (MEDAS) from the PREDIMED study was used, which produces a score ranging from 0 to 14, with a higher score indicating better adherence [14]. All participants had a face-to-face interview with a dietitian at baseline and after 12 weeks to determine their adherence to the intervention. The MEDAS score was obtained at baseline (week 0) and at the end of the intervention (week 12). However, only the participants in the SMD group received a thorough dietary and nutritional assessment. All the study participants were classified into three groups based on their adherence to the MD as follows: those with a MEDAS ≥ 10 points were placed in the high-adherence group, those with a MEDAS ≥ 7 points and MEDAS < 10 points were placed in the medium-adherence group, and those with a MEDAS < 7 points were put in the low-adherence group. All participants provided written informed consent before entering the study. The study was approved by the Institutional Review Board of the Hospital Clinic of Barcelona (Spain). The trial was registered (NCT03846206). 2.2. Nutritional Biomarkers and Polyphenols To ensure diet compliance, both at baseline and after 12 weeks, α-linolenic acid levels (as a measure of adherence to walnut consumption recommendations) in plasma as well as tyrosol and hydroxytyrosol levels (as a measure of adherence to EVOO consumption recommendations) in urine were assessed by gas chromatography coupled with mass spec- trometry. In addition, dietary polyphenol intake was estimated as described elsewhere [17]. 2.3. Markers of Inflammation and Bacterial Translocation Ultrasensitive C-reactive protein (uCRP) levels were determined with a latex enhanced immunoturbidimetric assay (Advia 2400; Siemens Diagnostics, Germany). Interleukin-6 (IL- 6) levels were measured by an immunoenzymatic assay with solid-phase amplification on microtitration plates (DIAsource, Nivelles, Belgium). D-dimer levels were measured with a turbidimetric method (Innovance; Siemens Diagnostics, Marburg, Germany) in a BCS XP (Siemens Diagnostics) automated coagulation system. Bacterial translocation was evaluated by measuring the levels of lipopolysaccharide-binding protein (LBP), sCD14, and EndoCAb in peripheral blood using the enzyme-linked immunosorbent assay (ELISA) technique. 2.4. T-Lymphocyte Subsets Activation status and Th17 and Treg cell subsets were analysed by multiparametric flow cytometry using the Cytomics FC500 flow cytometer (Beckman Coulter). For this purpose, three different panels of monoclonal antibodies were designed to stain peripheral blood mononuclear cells (PBMCs). Each panel included five different monoclonal antibod- ies to measure the level of activation of CD4+ and CD8+ T lymphocytes, as well as Th17 cell subset levels and Treg cell subset levels. Th17 cells were defined as CD4+ T-cells producing IL17A, while Treg cells were defined as CD4+ T-cells that were FoxP3+CD25+CD127−. Data analysis was performed using the CXP software (Beckman Coulter). The complete methodology is detailed in the Supplementary Methods. 2.5. Microbiota Composition Faecal DNA extraction: Faecal samples from the study participants were collected using the SOP.03.V2 protocol from the International Human Microbiome Standards (IHMS). The handbook included in the QIAamp DNA Stool Mini Kit was used with some modifica- tions (see the Supplementary Methods). Samples were stored at −20 ◦ C until analysis. 2.6. Bioinformatics and Statistical Analysis In order to study the effect of the intervention, we used two different approaches. First, we focused on the analysis comparing the different time points (basal vs. week 12) from each randomisation group (SMD and controls). Next, the analysis was focused on the Nutrients 2021, 13, 1141 4 of 18 mathematical change using the delta (∆) of each parameter by randomisation group (∆SMD vs. ∆controls). ∆ was calculated from each marker as follows: ∆ = (value at week 12) − (value at baseline). In order to study the effect of the diet supplementation, we used the ∆MEDAS between baseline and week 12, (end of the study). Both ∆ of the quantified markers (metabolic, microbial translocation, inflammatory, nutritional, and immunological markers) and ∆ of the gut microbiota composition were analysed. Due to the different number of patients included in the high- and low-adherence groups at baseline and at the end of the study, and with the aim of avoid bias induced by the inclusion of the same subject in two different groups, we established the adherence groups as fixed by the MEDAS score at the end of the study (week 12). In order to study the effect of the nutritional behaviour in the gut microbiota composition, we used the MEDAS score at week 12, using both time points (baseline and week 12) from each participant; in this regard, the two time-point samples from each patient were considered as replicates, and each replicate was considered as a dependent variable in the statistical analysis to avoid bias due to subject effect. The statistical analysis for the different parameters (lipid, metabolic, nutritional pro- file, inflammation, bacterial translocation, immune system activation, Treg, and Th17 T-lymphocyte subsets) between the different groups and time points was performed using the R software. Differences between groups were assessed with multiple Mann–Whitney– Wilcoxon tests or the Kruskal–Wallis test with Bonferroni correction, as required. The gut microbiota composition was assessed using the QIIME2 software [18]. The 16S rRNA sequence analysis is detailed in the Supplementary Methods. Microbiome samples were clustered according to their genera composition using a non-metric multidimensional scaling (NMDS) approach based on ecological distance matrices calculated by Bray–Curtis dissimilarities, implemented in R packages (Vegan, metaMDS, and ggplot2 packages). NMDS ellipses were drawn based on a confidence interval (CI) of 0.95. For the determination of the alpha diversity, we used the following diversity indices (Shannon index, 1/Simpson, and Fisher index) and richness parameters (observed). For the determination of the beta diversity, we used the principal coordinate analysis (PCoA) with the NMDS obtained, as well as the gut microbiota composition (relative abundances). The differences in gut microbiota composition between groups were inspected using the linear discriminant analysis (LDA) effect size (LEfSe). Sample dissimilarity between groups was evaluated using the Adonis test (PERMANOVA). The association between variables (metabolic, microbial translocation, inflammatory, nutritional, and immunological markers) and the different groups (randomisation groups: control or SMD; adherence groups: low or high adherence; time points: baseline or week 12) was evaluated using the two-tailed Wilcoxon rank sum test, when two groups were com- pared (paired: basal vs. week 12; unpaired: low-adherence vs. high-adherence). When three or more groups were compared, it was assessed with the Kruskal–Wallis test with Bon- ferroni correction. Correlations between the markers and the gut microbiota composition were obtained using the Spearman’s rank correlation coefficient with Holm’s correction for multiple comparisons. Data were considered statistically significant at p ≤ 0.05. In the post hoc analysis, individuals in the group men who have sex with men (MSM) (n = 60) were selected to evaluate the similarities between bacterial communities. Balances between subgroups were obtained using the gneiss plugin from QIIME2, next steps were executed in R software. The cross-validation in balances was conducted in the selbal analysis as described by Rivera-Pinto et al. [19]. 3. Results 3.1. Demographic Data In this study, 102 participants living with HIV were randomised. Twenty participants only attended the visit at baseline and were thus excluded from the analysis. Therefore, data from 82 participants who completed the assessment in week 12 are shown (Supplementary Nutrients 2021, 13, 1141 5 of 18 Figure S1). No differences were detected at baseline between patients who were lost to follow-up and those who completed the evaluation in week 12 (data not shown). The median age of the participants was 47 years, 69 (84%) were men, and 60 (73%) were men who have sex with men (MSM). The median (interquartile range (IQR)) CD4+ T-cell count at baseline and at the nadir was 820 (663, 1028) and 378 (312, 468) cells/µL, respectively. Supplementary Table S1 shows the characteristics of the subjects by study group. 3.2. Adherence to the SMD Stratified by Randomisation Group As shown in Table 1, the distribution of patients in the different adherence groups was similar at baseline. Individuals in the SMD group (n = 37) significantly improved their nutritional habits from baseline to week 12 (from a median MEDAS score of 6 to 12 points, p < 0.005; see Supplementary Table S2). At baseline, only 8% (n = 3) of the individuals in the SMD group (n = 37) presented a high adherence to the MD (MEDAS ≥ 10 points), with this proportion increasing to 84% (n = 31) at the end of the study (week 12). Conversely, individuals in the control group (n = 37) maintained their baseline MEDAS scores at the end of the study. The SMD group significantly increased their consumption of EVOO, nuts, walnuts, fruits, vegetables, legumes, and fish (p < 0.05). In addition, they also reduced their intake of refined cereals, red meat, and meat products, as well as pastries, cakes, and sweets (p < 0.05). No differences were found in the key food items analysed in the individuals of the control group (data not shown). Table 1. Scores at baseline and at the 12-week follow-up from the 14-item MEDAS questionnaire validated by the PREDIMED guidelines. The percentages of total individuals in each study group (the SMD or control group) are presented in the brackets. The data presented includes all individuals randomised by study group (n = 74); men who have sex with men (MSM) randomised by study group (n = 60); and a description of the improvement in the MEDAS scores at week 12. The adherence scores of two individuals from the SMD group were not registered at week 12. These two participants were considered as showing no improvements in their MEDAS scores. SMD, supplemented Mediterranean diet; MSM, men who have sex with men; MEDAS, MD Adherence Screener. * Increase. ** Decrease. Subject Selection MEDAS Group Basal (Week 0) End of Study (Week 12) All Individuals (n = 74) Control group High-Adherence 6 (16%) 6 (16%) (n = 37) (MEDAS ≥ 10) Medium-Adherence 20 (54%) 20 (54%) (7 ≤ MEDAS < 10) Low-Adherence 11 (30%) 11 (30%) (MEDAS < 7) SMD group High-Adherence 3 (8%) 31 (89%) * (n = 37) (MEDAS ≥ 10) Medium-Adherence 17 (46%) 4 (11%) ** (7 ≤ MEDAS < 10) Low-Adherence 17 (46%) 0 ** (MEDAS < 7) MSM (n = 60) Control group High-Adherence 6 (19%) 6 (19%) (n = 32) (MEDAS ≥ 10) Medium-Adherence 18 (56%) 18 (56%) (7 ≤ MEDAS < 10) Low-Adherence 8 (25%) 8 (25%) (MEDAS < 7) SMD group High-Adherence 3 (11%) 24 (92%) * (n = 28) (MEDAS ≥10) Medium-Adherence 14 (50%) 2 (8%) ** (7 ≤ MEDAS < 10) Low-Adherence 11 (39%) 0 ** (MEDAS < 7) Nutrients 2021, 13, 1141 6 of 18 Table 1. Cont. Delta (∆) MEDAS group Number of subjects MSM (n = 60) Control group Best improvement, ∆ ≥ 4 0 (n = 32) ∆ = 1–3 1 (3%) No improvement, ∆ = 0 31 (97%) SMD group Best improvement, ∆ ≥ 4 17 (61%) (n = 28) ∆ = 1–3 9 (32%) No improvement, ∆ = 0 2 (7%) 3.3. Metabolic, Microbial Translocation, Inflammatory, and Immunological Parameters An improvement in the lipid profile was observed in the SMD group compared to that in the control group ((mean (standard error, SE) delta total cholesterol −3.36 (3.29) vs. +9.43 (4.51) mg/dL, respectively, p = 0.02) (mean (SE) delta B-lipoprotein −2.11 (3.34) vs. +7.75 (3.58) mg/dL, respectively, p = 0.05)) A trend was observed in the increase of the CD4+ T-cells in the SMD at the end of the study (CD4+ (%), p = 0.07). IFN-γ-producing T-cells significantly decreased at week 12 with respect to baseline in the SMD group (median (IQR) CD8+IFNγ+: 61.51 (49.51, 69.35) and 50.49 (40.93, 68.1) for week 0 and 12, respectively, p = 0.002). No significant differences were observed between the SMD and control groups in the markers of inflammation, microbial translocation, and immune activation examined (Supplementary Table S2). 3.4. Gut Microbiota Diversity and Richness No differences in alpha and beta diversity were found between the study groups at the end of the study. By contrast, we found important differences in alpha diversity (observed, p = 0.002; Fisher, p < 0.005) and beta diversity between the men and women participants (Figure 1; Adonis test (PERMANOVA): p = 0.001, R2 = 0.18) at baseline, indicating that the gut microbiota of the studied cohort was highly influenced by the sex. 4. Sub-Study with MSM Individuals Stratified by the MEDAS Score Although we did not find differences in the gut microbiota between the study groups, we hypothesised that patients with a higher adherence to the MD could have a better profile. To assess this hypothesis, we performed a sub-study, classifying the participants according to their MEDAS score (MEDAS ≥ 10 points indicated high adherence, 7 points ≤ MEDAS < 10 points indicated medium adherence, and MEDAS < 7 points indicated low adherence). The groups were fixed using the MEDAS score obtained at the end of the study (week 12), this was done in order to avoid bias induced by the inclusion of the same subject in two different groups. In order to study the effect of the diet supplementation we used the ∆MEDAS between baseline and week 12, (end of the study). We classified the subjects by the increase in their MEDAS scores from baseline to the end of the study (∆MEDAS < 2 points or ∆MEDAS ≥ 4 points). We excluded the women participants and focused on MSM individuals (n = 60), given the significant differences observed in the gut microbiota between men and women and also the previous results about the impact of sexual preference on the microbiome [10]. As shown in Table 1, MSM individuals presented the same adherence behaviour according to the randomisation arm as the whole cohort. The key food and dietary nutrient intake among the MSM individuals stratified by their MEDAS scores at week 12 are shown in Supplementary Table S3. 4.1. Metabolic, Microbial Translocation, Inflammatory, and Immunological Parameters Stratified by the MEDAS Scores We divided participants at baseline according to Table 1, to see whether the adherence to MD at the basal time point also affected the inflammatory, bacterial translocation, and immunological markers. The data showed no statistically significant differences between Nutrients 2021, 13, 1141 7 of 18 the low-adherence and the high-adherence groups (Supplementary Table S4). The analysis of the entire cohort by the adherence groups (n = 74) indicated that B-lipoprotein levels increased significantly between week 0 (baseline) and week 12 (end of the study) in the low- adherence group (mean (SE) delta B-lipoprotein +9.70 mg/dL (3.55), p = 0.02). Additionally, there was a significant reduction of immune activation in the high-adherence group (mean (SE) delta CD4+HLADR+CD38+ −0.16% (0.67), p = 0.02; delta CD8+HLADR+CD38+ −0.26% (1.46), p = 0.01), in contrast to the low-adherence group, which showed an in- crease (mean (SE) delta CD4+HLADR+CD38+ +1.00% (1.91); delta CD8+HLADR+CD38+ +0.38% (2.41)). Observed Shannon index women women men women men men Fisher alpha Inverse Simpson index women men women men (a) Alpha diversity by sex Figure 1. Cont. Nutrients 2021, 13, x. https://doi.org/10.3390/xxxxx www.mdpi.com/journal/nutrients Nutrients 2021, 13, 1141 8 of 18 Nutrients 2021, 13, x FOR PEER REVIEW 2 of 23 (b) Beta diversity by sex FigureFigure 1. Microbiome diversity 1. Microbiome and richness diversity in accordance and richness with the in accordance sex.the with (a)sex. Alpha(a) diversity according Alpha diversity to the sex. according Grey to the boxes sex. Greycorrespond to w boxes boxes correspond to men individuals. All subjects from the cohort were selected at the basal time point. Left correspond to women individuals and blue boxes correspond to men individuals. All subjects from the cohort were top: number of observed operatio right top: Shannon index; left bottom: Fisher alpha index; right bottom: 1/Simpson index. For every parameter, the p-value for every compariso selected at the basal time point. Left top: number of observed operational taxonomic units (OTUs); right top: Shannon index; is presented. Signification code: p < 0.005: ***, p < 0.01: **, p < 0.05: *, p > 0.05: ns. (b) Principal coordinate analysis (PCoA) plot clustered by the s left bottom: Fisher alpha index; right bottom: 1/Simpson index. For every parameter, the p-value for every comparison in the cohort were selected and classified by the sex at the basal time point. Non-metric multidimensional scaling (NMDS) used: Bray-Curti between women were calculated andabundances using the men is presented. Signification of the bacterial genus’ code: p < 0.005:at***, composition thep basal < 0.01: **, ppoint. time < 0.05: *, p > 0.05:vegan. R package: ns. (b) Principal coordinate analysis (PCoA) plot clustered by the sex. All individuals included in the cohort were selected and classified by the sex at the basal time point. Non-metric multidimensional scaling (NMDS) used: Bray-Curtis distances. These distances were calculated using the abundances of the bacterial genus’ composition at the basal time point. R package: vegan. 4.2. Metabolic, Microbial Translocation, Inflammatory, and Immunological Parameters in MSM Stratified by Their MEDAS Scores No important differences were observed in the metabolic, inflammatory, and translo- cation markers in the MSM individuals. Regarding immune activation, individuals in the high-adherence group presented a significant reduction in their CD4+HLADR+CD38+ (p = 0.003) and CD8+HLADR+CD38+ (p = 0.007) cells compared to the low-adherence group (see Supplementary Table S5). In this case, there were no significant changes in the CD8+IFNγ+ cells. Even so, the CD8+IFNγ+ cells presented a direct correlation with CD4+HLADR+CD38+ (p = 0.01, R = 0.46) and CD8+HLADR+CD38+ (p = 0.003, R = 0.23) cells in the MSM subjects in the high-adherence group (not shown). 4.3. Gut Microbial Diversity and Richness After stratifying the MSM individuals by their MEDAS scores from week 12, the gut microbiota from individuals in the high-adherence group presented significantly higher species counts and richness (Figure 2a). Beta diversity was examined using the principal coordinates analysis (PCoA, Figure 2b). All obtained PCoAs both for the entire cohort and the MSM individuals at baseline and week 12 are shown in Supplementary Figure S2. To inspect beta diversity, different statistical approaches were undertaken using the obtained distances. The PERMANOVA analysis showed important differences between the groups: high-adherence group vs. low-adherence group (p < 0.005, Q < 0.05) and the medium- adherence group vs. the low-adherence group (p < 0.05, Q < 0.05). These results were confirmed by the Adonis test (p < 0.05, R = 0.022) and the multivariate linear regression modelling (p = 0.05; adjusted R-squared: 0.03; t-statistic: medium adherence < 0.05, high adherence < 0.05). Nutrients 2021, 13, 1141 9 of 18 Observed Shannon index Low Medium High Low Medium High Adherence Adherence Fisher alpha Inverse Simpson index Low Medium High Low Medium High Adherence Adherence (a) Alpha diversity by the adherence to MD Figure 2. Cont. Nutrients Nutrients 2021, FOR13, 13, x2021, 1141 PEER REVIEW 3 of 23 10 of 18 (b) Beta diversity by the adherence to the MD Figure 2.Figure Microbiome diversitydiversity 2. Microbiome and richness in the different and richness adherence in the different groups. adherence (a) After groups. classifying (a) After the the classifying subjects according subjects to to according their MEDAS sc determined at the end of the study. MSM subjects were selected (n = 60). Top left: number of observed OTUs; top their MEDAS scores, alpha diversity was determined at the end of the study. MSM subjects were selected (n = 60). Top left:right: the Shannon index; b index; and bottom right: Simpson’s diversity index. For each parameter, the global Kruskal–Wallis p-value and the p-values for every compariso number of observed OTUs; top right: the Shannon index; bottom left: Fisher’s alpha index; and bottom right: Simpson’s groups at week 12 are presented. *** p < 0.005, ** p < 0.01, * p ≤ 0.05. ns: p < 0.05. (b) PCoA plot clustered by the MEDAS scores from week 12. MSM i diversity index. For each parameter, the global Kruskal–Wallis p-value and the p-values for every comparison between the Non-metric multidimensional scaling (NMDS) used: Bray–Curtis distances. R package: vegan. adherence groups at week 12 are presented. *** p < 0.005, ** p < 0.01, * p ≤ 0.05. ns: p < 0.05. (b) PCoA plot clustered by the MEDAS scores from week 12. MSM individuals were selected. Non-metric multidimensional scaling (NMDS) used: Bray–Curtis distances. R package: vegan. 4.4. Gut Microbiota Composition No differences were found in the gut microbiota composition between the study groups (the SMD and control groups, Supplementary Figure S3). The composition of the gut microbiota was assessed in the subgroup of MSM individuals living with HIV stratified by their MEDAS scores from week 12. The abundance of Bacteroides was lower in the high-adherence group than in the low-adherence group (p = 0.0001, Supplementary Figure S4). The linear discriminant analysis (LDA) effect size (LEfSe) of the basal differences between low- and high-adherence groups are shown in Figure 3a. When both time points were considered, LEfSe analysis showed that the individuals in the high-adherence group presented significantly increased levels of: Burkholderiales, Butyrivibrio, Catenibacterium, and Succinivibrio. Conversely, individuals in the low-adherence group presented high levels of: Bacteroides, Parabacteroides, Desulfovibrio, Paraprevotella, and Bilophila (Figure 3b). When the participants were studied according to the improvement in their MEDAS scores (∆MEDAS) using the LEfSe analysis, the gut microbiota of the individuals with ∆MEDAS ≥ 4 points were enriched exclusively with the Bifidobacterium genus at week 12 compared to those who did not improve their MEDAS scores at week 12 (Figure 3c). Nutrients 2021, 13, x FOR PEER REVIEW 12 of 20 that best explained the differences between the high-adherence and low-adherence Nutrients 2021, 13, 1141 groups (receiver operating characteristic (ROC) curve, area under the curve (AUC)11=of 18 0.842). (a) Gut microbiota composition at baseline according to the MD adherence (b) Gut microbiota composition to track the effect of the MD adherence Figure 3. Cont. Nutrients 2021, 13, 1141 12 of 18 Nutrients 2021, 13, x FOR PEER REVIEW 13 of 20 Nutrients 2021, 13, x FOR PEER REVIEW 13 of 20 (c) Gut microbiota composition to track the effect of the diet supplementation Figure Figure 3. 3. Linear Linear discriminant discriminant analysis analysis (LDA) (LDA) effect effect size size (LEfSe) (LEfSe) inin the group of the group of MSM MSM individuals. individuals. (a) (a) Influence Influence of of the the adherence adherence groups, at baseline (the high-adherence group (n = 9) is shown in red, while the low-adherence group (n == 19) groups, at baseline (the high-adherence group (n = 9) is shown in red, while the low-adherence group (n 19) is shown in green), on the gut microbiota composition. (b) Influence of the adherence groups, fixed at week 12 (the high- is shown in green), on the gut microbiota composition. (b) Influence of the adherence groups, fixed at week 12 (the adherence group (n = 30) is shown in red, while the low-adherence group (n = 8) is shown in green), on the gut microbiota high-adherence group (n = 30) is shown in red, while the low-adherence group (n = 8) is shown in green), on the gut composition. (c) Influence of the increase in the MEDAS score between baseline and week 12 (ΔMEDAS) on the gut mi- microbiota crobiota composition. composition (c) Influence (ΔMEDAS of the increase ≥ 4 points (n = 17):ingreen; the MEDAS ΔMEDAS score