Lifestyle Genomics最新文献

{"title":"A Pilot Study to Evaluate the Role of Obesity and Genetic Variants in Serum C-Reactive Protein Response to an Acute Fructose Load.","authors":"Sai Sravani Vennam, Valentina Talevi, Geethika Venkataraman, Rayyan Ahmed Syed, Xinruo Zhang, Baba B Mass, Venkata Saroja Voruganti","doi":"10.1159/000544832","DOIUrl":"https://doi.org/10.1159/000544832","url":null,"abstract":"<p><p>33 Introduction: Excess fructose intake has been linked to increased risk for dyslipidemia, insulin, 34 resistance, hyperuricemia, inflammation, and obesity. In this human study, we investigated if serum 35 CRP concentrations change after fructose consumption, and whether genetic variants and 36 obesity status influences this change.</p><p><strong>Methods: </strong>Blood was drawn before and at four time points 37 after administration of a fructose load (n=57). Serum concentrations of CRP were measured, 38 and 11 single nucleotides polymorphisms (SNPs) (rs1205, rs1417938, rs1470515, rs3093068, 39 rs6588158, rs16842568, rs2259820, rs157581, rs2794521, rs3093062, rs17700633), 40 previously associated with serum CRP were genotyped and assessed for their association with 41 CRP levels.</p><p><strong>Results: </strong>Participants identifying as White (n = 37) had higher mean CRP levels across 42 all time points compared to those identifying as Black (n = 20). Participants with obesity (BMI ≥ 30 43 kg/m2) (n = 25) were younger and had higher mean CRP levels throughout the study period 44 compared to those without (n = 32). All SNPs were in Hardy-Weinberg Equilibrium and their 45 effect allele frequencies ranged between 11and 96%. Baseline CRP was associated with CRP 46 SNPs rs1417938 and rs2794521 (p <0.005), with rs2794521 also associated with CRP response to 47 fructose challenge (p < 0.005). The variability in responses to fructose and genetic associations 48 were mainly observed in individuals without obesity. Obesity status was associated with early 49 changes in CRP (0-30 min and 30-60min) whereas CRP SNPs were associated with later changes 50 (60-120min and 120-180 min).</p><p><strong>Conclusion: </strong>Changes in serum CRP were associated with obesity 51 status or SNPs based on the time elapsed since fructose ingestion. Larger studies are needed to 52 confirm and validate these associations. 53 54.</p>","PeriodicalId":18030,"journal":{"name":"Lifestyle Genomics","volume":" ","pages":"1-27"},"PeriodicalIF":2.0,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143523862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital twins - the future of Personalized nutrition and health?","authors":"Mariëtte Abrahams","doi":"10.1159/000543483","DOIUrl":"https://doi.org/10.1159/000543483","url":null,"abstract":"","PeriodicalId":18030,"journal":{"name":"Lifestyle Genomics","volume":" ","pages":"1-7"},"PeriodicalIF":2.0,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143414558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring Differentially Methylated Genes amongst Preterm birth and Full-term birth.","authors":"Aleem Razzaq, Razan ElKahlout, Gheyath K Nasrallah, Faisal E Ibrahim, Muthanna Samara, Hatem Zayed, Palli Valapila Abdulrouf, Rana Al-Jurf, Ahmed Najjar, Thomas Farrell, M Walid Qoronfleh, Hilal Al Rifai, Nader Al-Dewik","doi":"10.1159/000543372","DOIUrl":"https://doi.org/10.1159/000543372","url":null,"abstract":"<p><strong>Introduction: </strong>Preterm birth (PTB) is associated with newborn morbidity and mortality. DNA methylation plays an important role in the development of fetus, thus can also serve as an epigenetic biomarker. Limited epigenetic studies were conducted in regard to PTB. Thus, this study aims to determine whether there are any epigenetic changes amongst PTB vs. term birth (TB).</p><p><strong>Methods: </strong>In the current study, a total 218 cord blood samples from three different PTB studies have been carried out to explore differentially methylated sites (DMS) and regions (DMRs) associated with PTB. The differential methylation analysis was done after controlling for multiple covariates like age, gender, and disease status. The DMRs (genes and promoters) and DMS (CpG) were investigated in PTB compared to TB infants.</p><p><strong>Results: </strong>In PTB infants, genes like RNASE3, HGF, CLEC5A, LIPN, NXF1, and CCDC12 showed hypermethylation (p < 0.05) while the MUC20 and IFNL4 genes showed hypomethylation (p < 0.05) along with other significantly identified genes in this analysis. The eForge analysis of hypermethylated (p < 0.05) CpG sites exhibited enrichment in different fetal tissues like small and large intestine, adrenal gland, fetal heart, lungs, and kidney while hypomethylated CpGs showed no significant enrichment. The GO enrichment analysis of these genes revealed pathways associated with the regulation of immune response. Interestingly, the analysis also observed S100A9 and S100A8 genes, along with their associated CpG sites exhibited hypermethylation (p < 0.05) in PTB infants which plays a crucial role in developing neonatal sepsis.</p><p><strong>Conclusion: </strong>Overall, this study revealed differential methylation in immune-related genes related to PTB that could be used as potential epigenetics biomarkers. These findings not only enhance our understanding of PTB pathogenesis but also pave the way for developing innovative diagnostic and therapeutic strategies.</p>","PeriodicalId":18030,"journal":{"name":"Lifestyle Genomics","volume":" ","pages":"1-23"},"PeriodicalIF":2.0,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142922039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nicotine Metabolism-Related Genetic Polymorphisms Associated with Smoking Cessation in Korean Men: A Candidate Gene Association Study in a Korean Cohort.","authors":"Jae-Min Park, Ja-Eun Choi, Ji-Won Lee, Kyung-Won Hong","doi":"10.1159/000543543","DOIUrl":"10.1159/000543543","url":null,"abstract":"<p><strong>Introduction: </strong>Smoking cessation is influenced by genetic and environmental factors, particularly genetic polymorphisms influencing nicotine metabolism. This study investigated the association between specific nicotine metabolism-related genetic variants and smoking cessation among Korean men.</p><p><strong>Methods: </strong>A candidate gene association study was performed targeting single nucleotide polymorphisms (SNPs) within nicotine metabolism-related genes. Participants were categorized as never, former, or current smokers. A Genetic Risk Score (GRS) was computed using significant SNPs to evaluate cumulative genetic influence.</p><p><strong>Results: </strong>Six SNPs showed significant association with smoking cessation in a Korean cohort. A higher GRS was associated with increased odds of current smoking compared to former smoking (OR = 1.18, 95% CI: 1.12-1.25, p < 0.001).</p><p><strong>Conclusion: </strong>This study indicates a substantial genetic component in smoking cessation, highlighting the importance of population-specific approaches, and may aid personalized smoking cessation strategies based on genetic predisposition among Koreans.</p>","PeriodicalId":18030,"journal":{"name":"Lifestyle Genomics","volume":" ","pages":"20-26"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11844709/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142979027","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncoupling Proteins Variants Are Linked to Hypercholesterolemia and Abdominal Obesity in Metabolically Unhealthy Women.","authors":"Erika Sierra-Ruelas, Nathaly Torres-Castillo, Barbara Vizmanos, Wendy Campos Pérez, Erika Martínez-López","doi":"10.1159/000543484","DOIUrl":"10.1159/000543484","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Introduction: &lt;/strong&gt;It has been reported that even with the same body mass index (BMI); there are subjects with metabolically healthy (MH) or unhealthy (MUH) phenotype. The main determinants of the unhealthy phenotype are the type and distribution of fat, ectopic fat accumulation, genetics, and lifestyle factors. Uncoupling proteins (UCPs) disengage mitochondrial respiration from ATP synthesis and result in heat production, which in turn is related to energy expenditure and, thus, to fat mass accumulation. The association of the UCP1 3826A/G (rs1800592), UCP2 Ala55Val (rs660339), and UCP3 55C/T (rs1800849) variants with metabolic variables was evaluated according to metabolic phenotype in Mexican women.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Women aged 18-65 years classified as normal weight (NW) or excessive weight (EW) according to their BMI (from 18.5 to &lt;25 kg/m2 for NW, and from 25 to &lt;40 kg/m2 for EW), were included. Participants were classified into two metabolic phenotypes: MH or MUH, respectively, based on ATP-III criteria and the homeostasis model assessment of insulin resistance (HOMA-IR). The genetic variants were determined by allelic discrimination using TaqMan® probes.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In participants with the UCP1 3826A/G variant, an increased risk of hypercholesterolemia was observed in those with the NW-MUH phenotype (OR = 5.09, 95% CI = 1.03-25.12, p = 0.017). The UCP2 Ala55Val variant in EW-MUH subjects was associated with higher abdominal obesity risk (OR = 3.23, 95% CI = 1.21-8.60, p = 0.019), while no associations were found with the UCP3 55C/T variant.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;UCP1 and UCP2 variants are related with hypercholesterolemia and visceral fat accumulation in women with MUH phenotype.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Introduction: &lt;/strong&gt;It has been reported that even with the same body mass index (BMI); there are subjects with metabolically healthy (MH) or unhealthy (MUH) phenotype. The main determinants of the unhealthy phenotype are the type and distribution of fat, ectopic fat accumulation, genetics, and lifestyle factors. Uncoupling proteins (UCPs) disengage mitochondrial respiration from ATP synthesis and result in heat production, which in turn is related to energy expenditure and, thus, to fat mass accumulation. The association of the UCP1 3826A/G (rs1800592), UCP2 Ala55Val (rs660339), and UCP3 55C/T (rs1800849) variants with metabolic variables was evaluated according to metabolic phenotype in Mexican women.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Women aged 18-65 years classified as normal weight (NW) or excessive weight (EW) according to their BMI (from 18.5 to &lt;25 kg/m2 for NW, and from 25 to &lt;40 kg/m2 for EW), were included. Participants were classified into two metabolic phenotypes: MH or MUH, respectively, based on ATP-III criteria and the homeostasis model assessment of insulin resistance (HOMA-IR). The genetic variants were determined by allelic discrimination using TaqMan® probes.&lt;/p&gt;&lt;p&gt;&lt;","PeriodicalId":18030,"journal":{"name":"Lifestyle Genomics","volume":" ","pages":"27-35"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11838145/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143007863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomics and Recurrence of Atrial Fibrillation: A Pilot Study Nested in the PREDIMAR Trial.","authors":"Cristina Razquin, Joaquín Fernandez-Irigoyen, María Teresa Barrio-López, Begoña López, Susana Ravassa, Pablo Ramos, Rosa Macías-Ruíz, Alicia Ibañez Criado, Enrique Santamaría, Leticia Goni, Eduardo Castellanos, Jose Luis Ibañez Criado, Luis Tercedor, Ignacio García-Bolao, Miguel A Martínez-González, Jesús Almendral, Miguel Ruiz-Canela","doi":"10.1159/000543639","DOIUrl":"10.1159/000543639","url":null,"abstract":"<p><strong>Introduction: </strong>Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia worldwide. Although catheter ablation is the most efficacious therapy, relapses occur frequently (30%) in the first year after ablation. Novel biomarkers of recurrence are needed for a better prediction of recurrence and management of AF. In this pilot study, we aimed to analyze the baseline proteome of subjects included in a case-control study to find differential proteins associated with AF recurrence.</p><p><strong>Methods: </strong>Baseline serum proteomics (354 proteins) data from 16 cases (recurrent AF) and 17 controls (non-recurrent) were obtained using MS/MS analysis. A false discovery rate was performed using a nonlinear fitting method for the selection of proteins. Logistic regression models were used to further analyze the association between differentially expressed proteins and AF recurrence.</p><p><strong>Results: </strong>Ten proteins were differentially represented in cases vs. controls. Two were upregulated in the cases compared to the controls: keratin type I cytoskeletal 17 (Fold-change [FC] = 2.14; p = 0.017) and endoplasmic bifunctional protein (FC = 1.65; p = 0.032). Eight were downregulated in the cases compared to the controls: C4bpA (FC = 0.64; p = 0.006), coagulation factor XI (FC = 0.83; p = 0.011), CLIC1 (FC = 0.62; p = 0.017), haptoglobin (FC = 0.37; p = 0.021), Ig alpha-2 chain C region (FC = 0.49; p = 0.022), C4bpB (FC = 0.73; p = 0.028), N-acetylglucosamine-1-phosphotransferase subunit gamma (FC = 0.61; p = 0.033), and platelet glycoprotein Ib alpha chain (FC = 0.84; p = 0.038).</p><p><strong>Conclusion: </strong>This pilot study identifies ten differentially expressed serum proteins associated with AF recurrence, offering potential biomarkers for improved prediction and management.</p>","PeriodicalId":18030,"journal":{"name":"Lifestyle Genomics","volume":" ","pages":"52-58"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143047143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CC Genotype at TCF7L2 Diabetes Risk Locus rs7903146 Directs a Coordinated Fatty Acid Response to a Mediterranean Diet Intervention: A Randomized Controlled Trial.","authors":"Laurence D Parnell, Chao-Qiang Lai, Christina Holzapfel, Jacob J Christensen, José M Ordovás","doi":"10.1159/000542468","DOIUrl":"10.1159/000542468","url":null,"abstract":"<p><strong>Introduction: </strong>Previous studies identified genetic links between the TCF7L2 C/T variant rs7903146, type 2 diabetes (T2D), and obesity. We wished to deepen our understanding of how specific diets interact with this variant to affect blood metabolites, an aspect not previously investigated. Hence, we conducted a controlled study where individuals with different genotypes followed a Mediterranean (Med) or low-fat (LF) diet for 1 week.</p><p><strong>Methods: </strong>Participants were recruited from the Boston, MA (USA) area. Anthropometric and clinical measures were taken. Genotypes at rs7903146 were ascertained, with homozygous carriers of the more common and protective CC or risk TT genotype invited to participate. Participants followed both diets (LF or Med) for 1 week with ∼10 days' washout between diets. Blood samples taken at the beginning and end of each diet period underwent metabolomics analysis using nuclear magnetic resonance spectroscopy. We evaluated how the diet affected different metabolites based on genetic profile.</p><p><strong>Results: </strong>The cohort of 35 persons was 43% female, aged 18-70 y, with BMI between 26.4 and 33.9 kg/m2. Focusing on fatty acids (FAs) and other lipid metabolic factors (n = 23), we observed a greater number and stronger correlations among these factors in the CC genotype-Med diet group than in the other three genotype-diet combinations. An aggregate of 11 factors, each negatively correlating with delta-saturated fatty acids (SFA), showed a significant genotype-Med diet interaction on delta-SFA in CC individuals on the Med diet (p = 0.0046). A similar genotype-Med diet interaction was observed for delta-monounsaturated fatty acids (p = 0.0078). These interactions were not statistically significant at the end of the LF intervention.</p><p><strong>Conclusion: </strong>Our findings suggest that the Med diet has a stronger influence on regulating lipid factors in individuals with the CC genotype at the TCF7L2 variant rs7903146. This diet-genotype interaction may have significant implications for understanding the inter-individual variation of metabolic response on specific dietary regimens.</p>","PeriodicalId":18030,"journal":{"name":"Lifestyle Genomics","volume":" ","pages":"36-51"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143059822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guidance and Position of RINN22 regarding Precision Nutrition and Nutriomics.","authors":"Omar Ramos-Lopez, Taís Silveira Assmann, Elcy Yaned Astudillo Muñoz, Luis Baquerizo-Sedano, Elisa Barrón-Cabrera, Claudio Adrián Bernal, Josefina Bressan, Amanda Cuevas-Sierra, Alberto Dávalos, Ulises De la Cruz-Mosso, Ana Laura De la Garza, Daniel A De Luis, Rocío I Díaz de la Garza, Karina Dos Santos, Roxana Carla Fernández-Condori, Alfredo Fernández-Quintela, Diego F Garcia Diaz, Karina Gonzalez-Becerra, Eliane Lopes Rosado, María-Carmen López de Las Hazas, Bertha Araceli Marín Alejandre, Alberto Angel Martin, Erika Martinez-Lopez, Diego Martínez-Urbistondo, Fermin I Milagro, Helen Hermana M Hermsdorff, Begoña Muguerza, Carolina F Nicoletti, Ana Maria Obregón Rivas, Isela Parra-Rojas, Maria Puy Portillo, José L Santos, Thais Steemburgo, Maria Elizabeth Tejero, Anny Cristina Terán, Victor Treviño, Bárbara Vizmanos, J Alfredo Martinez","doi":"10.1159/000542789","DOIUrl":"10.1159/000542789","url":null,"abstract":"<p><strong>Background: </strong>Precision nutrition is based on the integration of individual's phenotypical and biological characteristics including genetic variants, epigenetic marks, gut microbiota profiles, and metabolite fingerprints as well as medical history, lifestyle practices, and environmental and cultural factors. Thus, nutriomics areas including nutrigenomics, nutrigenetics, nutriepigenetics, nutrimetabolomics, and nutrimetagenomics have emerged to comprehensively understand the complex interactions between nutrients, diet, and the human body's molecular processes through precision nutrition.</p><p><strong>Summary: </strong>This document from the Ibero-American Network of Nutriomics and Precision Nutrition (RINN22; <ext-link ext-link-type=\"uri\" xlink:href=\"https://rinn22.com/\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://rinn22.com/</ext-link>) provides a comprehensive overview of the concepts of precision nutrition approaches to guide their application in clinical and public health as well as establish the position of RINN22 regarding the current and future state of precision nutrition.</p><p><strong>Key messages: </strong>The progress and participation of nutriomics to precision nutrition is an essential pillar for addressing diet-related diseases and developing innovative managing strategies, which will be promoted by advances in bioinformatics, machine learning, and integrative software, as well as the description of specific novel biomarkers. In this context, synthesizing and critically evaluating the latest developments, potential applications, and future needs in the field of nutrition is necessary with a holistic perspective, incorporating progress in omics technologies aimed at precision nutrition interventions. This approach must address and confront healthy, social, food security, physically active lifestyle, sanitation, and sustainability challenges with preventive, participatory, and predictive strategies of personalized, population, and planetary nutrition for a precision tailored health.</p>","PeriodicalId":18030,"journal":{"name":"Lifestyle Genomics","volume":" ","pages":"1-19"},"PeriodicalIF":2.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11844698/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142770311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum.","authors":"","doi":"10.1159/000539272","DOIUrl":"10.1159/000539272","url":null,"abstract":"","PeriodicalId":18030,"journal":{"name":"Lifestyle Genomics","volume":"17 1","pages":"41"},"PeriodicalIF":2.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141065843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of gut bacterial profiling information in precision nutrition for obesity and weight loss management","authors":"O. Ramos-López, P. Aranaz, J. Riezu-Boj, F. Milagro","doi":"10.1159/000536156","DOIUrl":"https://doi.org/10.1159/000536156","url":null,"abstract":"Background: It has been suggested that the dysfunction of the gut microbiome can have deleterious effects on the regulation of body weight and adiposity by affecting energy metabolism. In this context, gut bacterial profiling studies have contributed to characterize specific bacteria associated with obesity. This review covers the information driven by gut bacterial profiling analyses and emphasizes the potential application of this knowledge in precision nutrition strategies for obesity understanding and weight loss management.\u0000Summary: Gut bacterial profiling studies have identified bacterial families that are more abundant in obese than in non-obese individuals (i.e. Prevotellaeae, Ruminococcaceae, and Veillonellaceae) as well as other families that have been repeatedly found more abundant in non-obese people (i.e. Christensenellaceae and Coriobacteriaceae), suggesting that an increase in their relative amount could be an interesting target in weight-loss treatments. Also, some gut-derived metabolites have been related to the regulation of body weight, including short chain fatty acids (SCFA), trimethylamine-N-oxide (TMAO), and branched-chain and aromatic amino acids. Moreover, gut microbiota profiles may play a role in determining weight loss responses to specific nutritional treatments for the precise management of obesity. Thus, incorporating gut microbiota features may improve the performance of integrative models to predict weight loss outcomes.\u0000Key Messages: The application of gut bacterial profiling information is of great value for precision nutrition in metabolic diseases, since it contributes to the understanding of the role of the gut microbiota in obesity onset and progression, facilitates the identification of potential microorganism targets, and allows the personalization of tailored weight loss diets as well as the prediction of adiposity outcomes based on the gut bacterial profiling of each individual. Integrating microbiota information with other omics knowledge (genetics, epigenetics, transcriptomics, proteomics, and metabolomics) may provide a more comprehensive understanding of the molecular and physiological events underlying obesity and adiposity outcomes for precision nutrition. \u0000","PeriodicalId":18030,"journal":{"name":"Lifestyle Genomics","volume":"1 12","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139437913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}