Modulatory role of Faecalibacterium on insulin resistance and coagulation in patients with post-viral long haulers depending on adiposity.

Patients with Post-viral long hauler encompass lasting symptoms and comorbid complexities, often exacerbated in individuals with excessive body weight. The aim was to study gut microbiota in 130 patients with post-viral long hauler stratified by body mass index (BMI) and the relationship between inflammation and microbiota. Significant higher values were found for anthropometric variables and markers of glucose and dyslipidemia in individuals with higher BMI, as well as elevated levels of C-reactive protein, fibrinogen, IL-6, uric acid, and D-dimer. An interactive association showed an interplay between Faecalibacterium, D-dimer levels, and insulin resistance. This investigation showed that anthropometric, biochemical, and inflammatory variables were impaired in patients with post-viral long haulers with higher BMI. In addition, gut microbiota differences were found between groups and a modification effect on Faecalibacterium abundance regarding insulin resistance and D-dimer. These findings suggest that considering adiposity and gut microbiota structure and composition may improve personalized clinical interventions in patients with chronic inflammation.

Reciprocal and Differential Influences of Mediterranean Diet and Physical Activity on Adiposity in a Cohort of Young and Older than 40 Years Adults.

Translational research has documented the conjoint beneficial relationships between dietary and physical activity habits concerning weight maintenance. However, the precise interplay between diet and exercise impacting body composition remains unclear, challenging personalized interventions. This study aimed to explore potential interactions and effect modifications of these factors affecting the body mass index (BMI) within an online adult cohort. Data from 11,883 NUTRiMDEA cohort participants were analyzed in this cross-sectional study, categorizing individuals by age, sex, and BMI using linear regression models to assess the interactions between lifestyle factors and adiposity. Significant differences emerged in anthropometry, lifestyle, and health-related quality of life (HRQoL) across categories. The combined effect of diet and physical activity had a greater impact on BMI than physical activity or Mediterranean diet adherence alone, with lower BMI as physical activity levels increased (ß: -0.5) and adherence to the Mediterranean diet decreased, where a modification effect between them was identified (ß: -0.28). Participants with lower Mediterranean diet adherence displayed superior BMI when physical activity was low, but when activity levels were higher, their BMI aligned with those with healthier dietary habits. An interaction link between lifestyle factors and BMI was found, showing the differential effects of the Mediterranean diet and physical activity combination concerning adiposity.

Biological Rhythms, Chrono-Nutrition, and Gut Microbiota: Epigenomics Insights for Precision Nutrition and Metabolic Health.

Circadian rhythms integrate a finely tuned network of biological processes recurring every 24 h, intricately coordinating the machinery of all cells. This self-regulating system plays a pivotal role in synchronizing physiological and behavioral responses, ensuring an adaptive metabolism within the environmental milieu, including dietary and physical activity habits. The systemic integration of circadian homeostasis involves a balance of biological rhythms, each synchronically linked to the central circadian clock. Central to this orchestration is the temporal dimension of nutrient and food intake, an aspect closely interwoven with the neuroendocrine circuit, gut physiology, and resident microbiota. Indeed, the timing of meals exerts a profound influence on cell cycle regulation through genomic and epigenetic processes, particularly those involving gene expression, DNA methylation and repair, and non-coding RNA activity. These (epi)genomic interactions involve a dynamic interface between circadian rhythms, nutrition, and the gut microbiota, shaping the metabolic and immune landscape of the host. This research endeavors to illustrate the intricate (epi)genetic interplay that modulates the synchronization of circadian rhythms, nutritional signaling, and the gut microbiota, unravelling the repercussions on metabolic health while suggesting the potential benefits of feed circadian realignment as a non-invasive therapeutic strategy for systemic metabolic modulation via gut microbiota. This exploration delves into the interconnections that underscore the significance of temporal eating patterns, offering insights regarding circadian rhythms, gut microbiota, and chrono-nutrition interactions with (epi)genomic phenomena, thereby influencing diverse aspects of metabolic, well-being, and quality of life outcomes.

Fecal Microbiota Composition as a Metagenomic Biomarker of Dietary Intake.

Gut microbiota encompasses the set of microorganisms that colonize the gastrointestinal tract with mutual relationships that are key for host homeostasis. Increasing evidence supports cross intercommunication between the intestinal microbiome and the eubiosis-dysbiosis binomial, indicating a networking role of gut bacteria as potential metabolic health surrogate markers. The abundance and diversity of the fecal microbial community are already recognized to be associated with several disorders, such as obesity, cardiometabolic events, gastrointestinal alterations, and mental diseases, which suggests that intestinal microbes may be a valuable tool as causal or as consequence biomarkers. In this context, the fecal microbiota could also be used as an adequate and informative proxy of the nutritional composition of the food intake and about the adherence to dietary patterns, such as the Mediterranean or Western diets, by displaying specific fecal microbiome signatures. The aim of this review was to discuss the potential use of gut microbial composition as a putative biomarker of food intake and to screen the sensitivity value of fecal microbiota in the evaluation of dietary interventions as a reliable and precise alternative to subjective questionnaires.

An Interplay between Oxidative Stress (Lactate Dehydrogenase) and Inflammation (Anisocytosis) Mediates COVID-19 Severity Defined by Routine Clinical Markers.

Viral infections activate the innate immune response and the secretion of inflammatory cytokines. They also alter oxidative stress markers, which potentially can have an involvement in the pathogenesis of the disease. The aim of this research was to study the role of the oxidative stress process assessed through lactate dehydrogenase (LDH) on the severity of COVID-19 measured by oxygen saturation (SaO2) and the putative interaction with inflammation. The investigation enrolled 1808 patients (mean age of 68 and 60% male) with COVID-19 from the HM Hospitals database. To explore interactions, a regression model and mediation analyses were performed. The patients with lower SaO2 presented lymphopenia and higher values of neutrophils-to-lymphocytes ratio and on the anisocytosis coefficient. The regression model showed an interaction between LDH and anisocytosis, suggesting that high levels of LDH (>544 U/L) and an anisocytosis coefficient higher than 10% can impact SaO2 in COVID-19 patients. Moreover, analysis revealed that LDH mediated 41% (p value = 0.001) of the effect of anisocytosis on SaO2 in this cohort. This investigation revealed that the oxidative stress marker LDH and the interaction with anisocytosis have an important role in the severity of COVID-19 infection and should be considered for the management and treatment of the oxidative phenomena concerning this within a precision medicine strategy.

Targeted suppression of human IBD-associated gut microbiota commensals by phage consortia for treatment of intestinal inflammation.

Human gut commensals are increasingly suggested to impact non-communicable diseases, such as inflammatory bowel diseases (IBD), yet their targeted suppression remains a daunting unmet challenge. In four geographically distinct IBD cohorts (n = 537), we identify a clade of Klebsiella pneumoniae (Kp) strains, featuring a unique antibiotics resistance and mobilome signature, to be strongly associated with disease exacerbation and severity. Transfer of clinical IBD-associated Kp strains into colitis-prone, germ-free, and colonized mice enhances intestinal inflammation. Stepwise generation of a lytic five-phage combination, targeting sensitive and resistant IBD-associated Kp clade members through distinct mechanisms, enables effective Kp suppression in colitis-prone mice, driving an attenuated inflammation and disease severity. Proof-of-concept assessment of Kp-targeting phages in an artificial human gut and in healthy volunteers demonstrates gastric acid-dependent phage resilience, safety, and viability in the lower gut. Collectively, we demonstrate the feasibility of orally administered combination phage therapy in avoiding resistance, while effectively inhibiting non-communicable disease-contributing pathobionts.

Effects of Resveratrol Administration in Liver Injury Prevention as Induced by an Obesogenic Diet: Role of Ruminococcaceae.

Gut microbiota dysbiosis has been described in several metabolic disruptions, such as non-alcoholic fatty liver disease (NAFLD). Administration of resveratrol has been claimed to elicit benefits against NAFLD along with modulating gut microbiota composition. This investigation aims to study the putative mediating role of gut microbiota in the potential hepato-protective effects of resveratrol in a diet-induced NAFLD rat model. The involvement of bacteria from the Ruminococcaceae family in such effects was also addressed. Resveratrol administration resulted in lowered liver weight and serum total and non-HDL cholesterol concentrations, as well as in increased serum HDL cholesterol levels. The administration of this polyphenol also prevented obesogenic diet-induced serum transaminase increases. In addition, histopathological analysis revealed that resveratrol administration ameliorated the dietary-induced liver steatosis and hepatic inflammation. Gut microbiota sequencing showed an inverse relationship between some bacteria from the Ruminococcaceae family and the screened hepatic markers, whereas in other cases the opposite relationship was also found. Interestingly, an interaction was found between UBA-1819 abundance and resveratrol induced liver weight decrease, suggesting that for this marker resveratrol induced effects were greater when the abundance of this bacteria was high, while no actions were found when UBA-1819 abundance was low.

Hematological- and Immunological-Related Biomarkers to Characterize Patients with COVID-19 from Other Viral Respiratory Diseases.

COVID-19 has overloaded health system worldwide; thus, it demanded a triage method for an efficient and early discrimination of patients with COVID-19. The objective of this research was to perform a model based on commonly requested hematological variables for an early featuring of patients with COVID-19 form other viral pneumonia. This investigation enrolled 951 patients (mean of age 68 and 56% of male) who underwent a PCR test for respiratory viruses between January 2019 and January 2020, and those who underwent a PCR test for detection of SARS-CoV-2 between February 2020 and October 2020. A comparative analysis of the population according to PCR tests and logistic regression model was performed. A total of 10 variables were found for the characterization of COVID-19: age, sex, anemia, immunosuppression, C-reactive protein, chronic obstructive pulmonary disease, cardiorespiratory disease, metastasis, leukocytes and monocytes. The ROC curve revealed a sensitivity and specificity of 75%. A deep analysis showed low levels of leukocytes in COVID-19-positive patients, which could be used as a primary outcome of COVID-19 detection. In conclusion, this investigation found that commonly requested laboratory variables are able to help physicians to distinguish COVID-19 and perform a quick stratification of patients into different prognostic categories.

A weight-loss model based on baseline microbiota and genetic scores for selection of dietary treatments in overweight and obese population.

BACKGROUND & AIMS: The response to weight loss depends on the interindividual variability of determinants such as gut microbiota and genetics. The aim of this investigation was to develop an integrative model using microbiota and genetic information to prescribe the most suitable diet for a successful weight loss in individuals with excess of body weight. METHODS: A total of 190 Spanish overweight and obese participants were randomly assigned to two hypocaloric diets for 4 months: 61 women and 29 men followed a moderately high protein (MHP) diet, and 72 women and 28 men followed a low fat (LF) diet. Baseline fecal DNA was sequenced and used for the construction of four microbiota subscores associated with the percentage of BMI loss for each diet (MHP and LF) and for each sex. Bootstrapping techniques and multiple linear regression models were used for the selection of families, genera and species included in the subscores. Finally, two total microbiota scores were generated for each sex. Two genetic subscores previously reported to weight loss were used to generate a total genetic score. In an attempt to personalize the weight loss prescription, several linear mixed models that included interaction with diet between microbiota scores and genetic scores for both, men and women, were studied. RESULTS: The microbiota subscore for the women who followed the MHP-diet included Coprococcus, Dorea, Flavonifractor, Ruminococcus albus and Clostridium bolteaea. For LF-diet women, Cytophagaceae, Catabacteriaceae, Flammeovirgaceae, Rhodobacteriaceae, Clostridium-x1vb, Bacteriodes nordiiay, Alistipes senegalensis, Blautia wexlerae and Psedoflavonifractor phocaeensis. For MHP-diet men, Cytophagaceae, Acidaminococcaceae, Marinilabiliaceae, Bacteroidaceae, Fusicatenibacter, Odoribacter and Ruminococcus faecis; and for LF-men, Porphyromanadaceae, Intestinimonas, Bacteroides finegoldii and Clostridium bartlettii. The mixed models with microbiota scores facilitated the selection of diet in 72% of women and in 84% of men. The model including genetic information allows to select the type of diet in 84% and 73%, respectively. CONCLUSIONS: Decision algorithm models can help to select the most adequate type of weight loss diet according to microbiota and genetic information. CLINICAL TRIAL REGISTRY NUMBER: This trial was registered at www. CLINICALTRIALS: gov as NCT02737267 (https://clinicaltrials.gov/ct2/show/NCT02737267?term=NCT02737267&cond=obekit&draw=2&rank=1).

Lifestyle and Health-Related Quality of Life Relationships Concerning Metabolic Disease Phenotypes on the Nutrimdea Online Cohort.

Obesity, diabetes and cardiovascular events are non-communicable diseases (NCDs) directly related to lifestyle and life quality. Rises on NCDs rates are leading to increases in early deaths concerning metabolic morbidities. Health-related quality of life (HRQoL) has been described as a subjective perception about the influence of health and personal features on human well-being. This study aimed to characterize phenotypic and lifestyle roles on the occurrence of metabolic diseases and determine the potential mutual interactions and with HRQoL. Data from an online adult population (NUTRiMDEA study, n = 17,332) were used to estimate an adapted Obesogenic Score (ObS), while logistic regression analyses were fitted in order to examine relevant factors related to the prevalence of different metabolic diseases including HRQoL. Sex and age showed significant differences depending on lifestyle and metabolic health (p < 0.05). Adherence to the Mediterranean diet and physical activity showed a mutual interaction concerning ObS (p < 0.001), as well with metabolic health (p = 0.044). Furthermore, metabolic diseases showed own features related to sociodemographic and lifestyle characteristics in this population. Metabolic syndrome components may be differently influenced by diverse lifestyle or socioeconomic factors which in turn affect the perceived HRQoL. These outcomes should be taken into account individually for a precision medicine and public health purposes.

Differentially methylated regions (DMRs) in PON3 gene between responders and non-responders to a weight loss dietary intervention: a new tool for precision management of obesity.

Differentially methylated regions (DMR) are genomic regions with different methylation status. The aim of this research was to identify DMRs in subjects with obesity that predict the response to a weight-loss dietary intervention and its association with metabolic variables. Based on the change in body mass index (BMI), 201 subjects with overweight and obesity were categorized in tertiles according to their response to a hypocaloric diet: Responders (R; n = 64) and Non-Responders (NR; n = 63). The R group lost 4.55 ± 0.91 BMI units (kg/m2) and the NR group lost 1.95 ± 0.73 kg/m2 (p < 0.001). DNA methylation was analysed in buffy coat through a methylation array at baseline. DMRs were analysed using a function of ChAMP (Chip Analysis Methylation Pipeline) in R software. Baseline DNA methylation analysis between R and NR exhibited a DMR located at paraoxonase 3 gene (PON3) consisting of 13 CpG sites, eleven of them significantly hypermethylated in R. To analyse the implication of these 11 CpGs on weight loss, a z-score was performed as a measure of DMR methylation. This analysis showed a correlation between PON3 DNA methylation and BMI loss. This z-score negatively correlated with PON3 protein serum levels. Total paraoxonase activity in serum was not different between groups, but PON enzymatic activity positively correlated with oxidized LDL levels. The present study identified a DMR within PON3 gene that is related to PON3 protein levels in serum, and that could be used as a potential biomarker to predict the response to weight-loss dietary interventions.

Gut Microbiota Differences According to Ultra-Processed Food Consumption in a Spanish Population.

Ultra-processed foods (UPFs) consumption could affect gut microbiota diversity and profile. We aimed to evaluate the effects of UPFs on microbiota, considering the role of sex. The consumption of UPFs (using NOVA criteria) was assessed with a validated 137-item food-frequency questionnaire. Participants (n = 359) were classified into less than three servings per day (n = 96) of UPFs and more than five (n = 90). Women and men were subclassified following the same criteria. 16S rRNA sequencing was performed from DNA fecal samples, and differences in microbiota were analyzed using EdgeR. The relationship between UPFs and bacteria was assessed by Spearman correlation and comparison of tertiles of consumption. Women who consumed more than five servings/day of UPFs presented an increase in Acidaminococcus, Butyrivibrio, Gemmiger, Shigella, Anaerofilum, Parabacteroides, Bifidobacterium, Enterobacteriales, Bifidobacteriales and Actinobacteria and a decrease in Melainabacter and Lachnospira. Bifidobacterium, Bifidobacteriales and Actinobacteria was positively associated with pizza and Actinobacteria with industrially processed dairy in women. Men who consumed more than five servings/day presented an increase of Granulicatella, Blautia, Carnobacteriaceae, Bacteroidaceae, Peptostreptococcaceae, Bacteroidia and Bacteroidetes and a decrease of Anaerostipes and Clostridiaceae. Bacteroidia and Bacteroidetes correlated positively with industrially processed meat. This study suggests that UPFs may affect microbiota composition differently in women and men.

A predictive regression model of the obesity-related inflammatory status based on gut microbiota composition.

BACKGROUND AND AIM: Fecal microbiome disturbances are linked to different human diseases. In the case of obesity, gut microbiota seems to play a role in the development of low-grade inflammation. The purpose of the present study was to identify specific bacterial families and genera associated with an increased obesity-related inflammatory status, which would allow to build a regression model for the prediction of the inflammatory status of obese and overweight subjects based on fecal microorganisms. METHODS: A total of 361 volunteers from the Obekit trial (65 normal-weight, 110 overweight, and 186 obese) were classified according to four variables: waist/hip ratio (≥0.86 for women and ≥1.00 for men), leptin/adiponectin ratio (LAR, ≥3.0 for women and ≥1.4 for men), and plasma C-reactive protein (≥2 mg/L) and TNF levels (≥0.85 pg/mL). An inflammation score was designed to classify individuals in low (those subjects who did exceed the threshold value in 0 or 1 variable) or high inflammatory index (those subjects who did exceed the threshold value in 2 or more variables). Fecal 16 S rRNA sequencing was performed for all participants, and differential abundance analyses for family and genera were performed using the MicrobiomeAnalyst web-based platform. RESULTS: Methanobacteriaceae, Christensenellaceae, Coriobacteriaceae, Bifidobacteriaceae, Catabacteriaceae, and Dehalobacteriaceae families, and Methanobrevibacter, Eggerthella, Gemmiger, Anaerostipes, and Collinsella genera were significantly overrepresented in subjects with low inflammatory index. Conversely, Carnobacteriaceae, Veillonellaceae, Pasteurellaceae, Prevotellaceae and Enterobacteriaceae families, and Granulicatella, Veillonella, Haemophilus, Dialister Parabacteroides, Prevotella, Shigella, and Allisonella genera were more abundant in subjects with a high inflammatory index. A regression model adjusted by BMI, sex, and age and including the families Coriobacteriaceae and Prevotellaceae and the genus Veillonella was developed. CONCLUSION: A microbiota-based regression model was able to predict the obesity-related inflammatory status (area under the ROC curve = 0.8570 ± 0.0092 Harrell's optimism-correction) and could be useful in the precision management of inflammobesity.

Gut Microbiota Bacterial Species Associated with Mediterranean Diet-Related Food Groups in a Northern Spanish Population.

The MD (Mediterranean diet) is recognized as one of the healthiest diets worldwide and is associated with the prevention of cardiovascular and metabolic diseases. Dietary habits are considered one of the strongest modulators of gut microbiota, which seem to play a significant role in health status of the host. The purpose of the present study was to evaluate interactive associations between gut microbiota composition and habitual dietary intake in 360 Spanish adults from the Obekit cohort (normal weight, overweight, and obese participants). Dietary intake and adherence to the MD tests were administered and fecal samples were collected from each participant. Fecal 16S rRNA (ribosomal Ribonucleic Acid) gene sequencing was performed and checked against the dietary habits. MetagenomeSeq was the statistical tool applied to analyze data at the species taxonomic level. Results from this study identified several beneficial bacteria that were more abundant in the individuals with higher adherence to the MD. Bifidobacterium animalis was the species with the strongest association with the MD. Some SCFA (Short Chain Fatty Acids) -producing bacteria were also associated with MD. In conclusion, this study showed that MD, fiber, legumes, vegetable, fruit, and nut intake are associated with an increase in butyrate-producing taxa such as Roseburia faecis, Ruminococcus bromii, and Oscillospira (Flavonifractor) plautii.

Diet- and sex-related changes of gut microbiota composition and functional profiles after 4 months of weight loss intervention.

PURPOSE: Obesity has been related to intestinal dysbiosis and the modification of gut microbiota composition by dietary strategies becomes a promising strategy to help manage obesity. The aim of the current study was to evaluate the effect of two weight-loss diets on the composition and functional profile of gut microbiota. METHODS: 55 men and 124 women with BMI > 25 kg/m2 were randomly assigned to moderately high-protein (MHP) or low-fat (LF) diet. Differences in fecal bacteria abundance (based on 16 s rRNA sequencing) between before and after 4 months of calorie restriction was analyzed using EdgeR tool in MicrobiomeAnalyst platform. Bacterial functional profile was predicted using Tax4Fun and metagenomeSeq analysis. Significant KEGG Orthology (KO) terms were selected for the metabolomic study using chromatography. RESULTS: After the intervention, MHP-men showed a significant decrease in Negativicutes, Selenomonadales, Dielma and Dielma fastidiosa. LF-men showed a significant increase in Bacilli, Lactobacillales, Christensenellaceae, Peptococcaceae, and Streptococcaceae, Peptococcus, Streptococcus and Christensenella, Duncaniella dubosii_CP039396_93.49%, Roseburia sp_AB744234_98.96% and Alistipes inops_KJ572413_99.57%. MHP-women increased Pasteurellales, Phascolarctobacterium succinatutens, Ruthenibacterium lactatiformans_LR215981_99.55% and decreased in Phascolarctobacterium succinatutens_NR112902_99.56%. Finally, LF-women presented a significant decrease in Bacteroides clarus and Erysipelothrix inopinata_CP060715_84.4%. Surprisingly, no matching bacterial changes were found between these four groups. A total of 42 KO, 10 metabolic pathways and 107 related metabolites related were found implicated in these bacterial changes. Seven metabolites were confirmed in plasma. CONCLUSION: Weight-loss-related-changes in gut microbiome composition and the functional profile occur in a sex- and diet-related manner, showing that women and men could differentially benefit from the consumption of MHP and LF diets. TRIAL REGISTRATION: NCT02737267, 10th March 2016 retrospectively registered.

Comprehensive Analysis Reveals Novel Interactions between Circulating MicroRNAs and Gut Microbiota Composition in Human Obesity.

BACKGROUND: The determinants that mediate the interactions between microRNAs and the gut microbiome impacting on obesity are scarcely understood. Thus, the aim of this study was to investigate possible interactions between circulating microRNAs and gut microbiota composition in obesity. METHOD: The sample comprised 78 subjects with obesity (cases, body mass index (BMI): 30-40 kg/m2) and 25 eutrophic individuals (controls, BMI ≤ 25 kg/m2). The expression of 96 microRNAs was investigated in plasma of all individuals using miRCURY LNA miRNA Custom PCR Panels. Bacterial DNA sequencing was performed following the Illumina 16S protocol. The FDR correction was used for multiple comparison analyses. RESULTS: A total of 26 circulating microRNAs and 12 bacterial species were found differentially expressed between cases and controls. Interestingly, an interaction among three miRNAs (miR-130b-3p, miR-185-5p and miR-21-5p) with Bacteroides eggerthi and BMI levels was evidenced (r2 = 0.148, p = 0.004). Moreover, these microRNAs regulate genes that participate in metabolism-related pathways, including fatty acid degradation, insulin signaling and glycerolipid metabolism. CONCLUSIONS: This study characterized an interaction between the abundance of 4 bacterial species and 14 circulating microRNAs in relation to obesity. Moreover, the current study also suggests that miRNAs may serve as a communication mechanism between the gut microbiome and human hosts.

Crosstalk between circulating microRNAs and chronotypical features in subjects with metabolic syndrome.

Circulating microRNAs (miRNAs) are valuable biomarkers that may provide important insight into the pathogenesis of metabolic syndrome (MetS). Moreover, there is an association between chronotypical characteristics and MetS predisposition. Considering that expression of some miRNAs is circadian-rhythm-dependent, the aim of this study was to investigate the circulating miRNA profile in subjects with and without MetS in association with chronotype. The expression of 86 metabolic syndrome-related miRNAs was investigated in the plasma of 21 subjects with MetS and in 82 subjects without MetS using miRCURY LNA miRNA PCR System technology. Chronotype was assessed using the Horne and Östberg Morningness-Eveningness Questionnaire. Bioinformatic analyses were performed to explore the target genes and biological pathways regulated by the selected miRNAs. Subjects with MetS were more often evening chronotype compared to non-MetS controls. Additionally, four miRNAs (miR-140-3p, miR-150-5p, miR-375, and miR-29 c-3p) demonstrated interaction with MetS and chronotype. Interestingly, the target genes of these four miRNAs participate in pathways related to the circadian clock. In conclusion, we identified four circulating miRNAs whose circulating levels could interact with MetS and chronotype.

Sex-Specific Associations between Gut Prevotellaceae and Host Genetics on Adiposity.

The gut microbiome has been recognized as a tool for understanding adiposity accumulation and for providing personalized nutrition advice for the management of obesity and accompanying metabolic complications. The genetic background is also involved in human energy homeostasis. In order to increase the value of nutrigenetic dietary advice, the interplay between genetics and microbiota must be investigated. The purpose of the present study was to evaluate interactive associations between gut microbiota composition and 95 obesity-related single nucleotide polymorphisms (SNPs) searched in the literature. Oral mucosa and fecal samples from 360 normal weight, overweight and obese subjects were collected. Next generation genotyping of these 95 SNPs and fecal 16S rRNA sequencing were performed. A genetic risk score (GRS) was constructed with 10 SNPs statistically or marginally associated with body mass index (BMI). Several microbiome statistical analyses at family taxonomic level were applied (LEfSe, Canonical Correspondence Analysis, MetagenomeSeq and Random Forest), and Prevotellaceae family was found in all of them as one of the most important bacterial families associated with BMI and GRS. Thus, in this family it was further analyzed the interactive association between BMI and GRS with linear regression models. Interestingly, women with higher abundance of Prevotellaceae and higher GRS were more obese, compared to women with higher GRS and lower abundance of Prevotellaceae. These findings suggest relevant interrelationships between Prevotellaceae and the genetic background that may determine interindividual BMI differences in women, which opens the way to new precision nutrition-based treatments for obesity.

Changes in Anxiety and Depression Traits Induced by Energy Restriction: Predictive Value of the Baseline Status.

Current evidence proposes diet quality as a modifiable risk factor for mental or emotional impairments. However, additional studies are required to investigate the effect of dietary patterns and weight loss on improving psychological symptoms. The aim of this investigation was to evaluate the effect of energy-restriction, prescribed to overweight and obese participants, on anxiety and depression symptoms, as well as the potential predictive value of some baseline psychological features on weight loss. Overweight and obese participants (n = 305) were randomly assigned for 16 weeks to two hypocaloric diets with different macronutrient distribution: a moderately high-protein (MHP) diet and a low-fat (LF) diet. Anthropometrical, clinical, psychological, and lifestyle characteristics were assessed at baseline and at the end of the intervention. The nutritional intervention evidenced that weight loss has a beneficial effect on trait anxiety score in women (ß = 0.24, p = 0.03), depression score in all population (ß = 0.15, p = 0.02), particularly in women (ß = 0.22, p = 0.03) and in subjects who followed the LF diet (ß = 0.22, p = 0.04). Moreover, weight loss could be predicted by anxiety status at baseline, mainly in women and in those who were prescribed a LF diet. This trial suggests that weight loss triggers an improvement in psychological traits, and that anxiety symptoms could predict those volunteers that benefit most from a balanced calorie-restricted intervention, which will contribute to individualized precision nutrition.

Diet, Gut Microbiota, and Obesity: Links with Host Genetics and Epigenetics and Potential Applications.

Diverse evidence suggests that the gut microbiota is involved in the development of obesity and associated comorbidities. It has been reported that the composition of the gut microbiota differs in obese and lean subjects, suggesting that microbiota dysbiosis can contribute to changes in body weight. However, the mechanisms by which the gut microbiota participates in energy homeostasis are unclear. Gut microbiota can be modulated positively or negatively by different lifestyle and dietary factors. Interestingly, complex interactions between genetic background, gut microbiota, and diet have also been reported concerning the risk of developing obesity and metabolic syndrome features. Moreover, microbial metabolites can induce epigenetic modifications (i.e., changes in DNA methylation and micro-RNA expression), with potential implications for health status and susceptibility to obesity. Also, microbial products, such as short-chain fatty acids or membrane proteins, may affect host metabolism by regulating appetite, lipogenesis, gluconeogenesis, inflammation, and other functions. Metabolomic approaches are being used to identify new postbiotics with biological activity in the host, allowing discovery of new targets and tools for incorporation into personalized therapies. This review summarizes the current understanding of the relations between the human gut microbiota and the onset and development of obesity. These scientific insights are paving the way to understanding the complex relation between obesity and microbiota. Among novel approaches, prebiotics, probiotics, postbiotics, and fecal microbiome transplantation could be useful to restore gut dysbiosis.