Mediation effect and metabolic pathways of gut microbiota in the associations between lifestyles and dyslipidemia
Pirillo, A., Casula, M., Olmastroni, E., Norata, G. D. & Catapano, A. L. Global epidemiology of dyslipidaemias. Nat. Rev. Cardiol. 18, 689–700 (2021).
Google Scholar
Joint Committee on the Chinese Guidelines for Lipid M. [Chinese guidelines for lipid management (2023)]. Zhonghua Xin Xue Guan Bing Za Zhi. 51, 221–255 (2023).
Hasheminasabgorji, E. & Jha J. C. Dyslipidemia, diabetes and atherosclerosis: role of inflammation and ROS-redox-sensitive factors. Biomedicines. 9, 1602 (2021).
Collaboration NCDRF Repositioning of the global epicentre of non-optimal cholesterol. Nature 582, 73–77 (2020).
Google Scholar
Baik, I. Dietary and modifiable factors contributing to hyper-LDL-cholesterolemia prevalence in nationwide time series data and the implications for primary prevention strategies. Nutr. Res. Pract. 14, 62–69 (2020).
Google Scholar
Jain, R. B. & Ducatman, A. Associations between smoking and lipid/lipoprotein concentrations among US adults aged >/=20 years. J Circ Biomark. 7, 1849454418779310 (2018).
Ye, X. F., Miao, C. Y., Zhang, W., Ji, L. N. & Wang, J. G. investigators A. Alcohol intake and dyslipidemia in male patients with hypertension and diabetes enrolled in a China multicenter registry. J. Clin. Hypertens.25, 183–190 (2023).
Google Scholar
Zou, Q. et al. Longitudinal Association between physical activity, blood lipids, and risk of dyslipidemia among chinese adults: findings from the China Health and Nutrition Surveys in 2009 and 2015. Nutrients. 15, 341 (2023).
Norris, G. H. & Blesso, C. N. Dietary sphingolipids: potential for management of dyslipidemia and nonalcoholic fatty liver disease. Nutr. Rev. 75, 274–285 (2017).
Google Scholar
Antinozzi, M. et al. Cigarette smoking and human gut microbiota in healthy adults: a systematic review. Biomedicines. 10, 510 (2022).
Torquati, L. et al. Effects of exercise intensity on gut microbiome composition and function in people with type 2 diabetes. Eur. J. Sport Sci. 23, 530–541 (2023).
Google Scholar
Bjorkhaug, S. T. et al. Characterization of gut microbiota composition and functions in patients with chronic alcohol overconsumption. Gut Microbes 10, 663–675 (2019).
Google Scholar
Morrison, D. J. & Preston, T. Formation of short chain fatty acids by the gut microbiota and their impact on human metabolism. Gut Microbes 7, 189–200 (2016).
Google Scholar
Kasubuchi, M., Hasegawa, S., Hiramatsu, T., Ichimura, A. & Kimura, I. Dietary gut microbial metabolites, short-chain fatty acids, and host metabolic regulation. Nutrients 7, 2839–2849 (2015).
Google Scholar
Ross, F. C. et al. The interplay between diet and the gut microbiome: implications for health and disease. Nat. Rev. Microbiol. 22, 671–686 (2024).
Google Scholar
Zhang, X. et al. Multi-trajectories of body mass index, waist circumference, gut microbiota, and incident dyslipidemia: a 27-year prospective study. Res. Sq. rs.3, 4251069 (2024).
Thomas, M. S. et al. Dietary influences on gut microbiota with a focus on metabolic syndrome. Metab. Syndr. Relat. Disord. 20, 429–439 (2022).
Google Scholar
Lv, J. et al. Adherence to healthy lifestyle and cardiovascular diseases in the Chinese population. J. Am. Coll. Cardiol. 69, 1116–1125 (2017).
Google Scholar
Nudelman, G., Kalish, Y. & Shiloh, S. The centrality of health behaviours: a network analytic approach. Br. J. Health Psychol. 24, 215–236 (2019).
Google Scholar
Zhao, X. et al. China multi-ethnic cohort collaborative g. Cohort Profile: the China multi-ethnic cohort (CMEC) study. Int. J. Epidemiol. 50, 721–721l (2021).
Google Scholar
Yang, S. et al. Development and validation of an age-sex-ethnicity-specific metabolic syndrome score in the Chinese adults. Nat. Commun. 14, 6988 (2023).
Google Scholar
Ma, H. et al. Associations of residential physical activity development trajectory with carotid plaque. Prev. Med. 50, 4497–4502 (2023).
Guerra, R. M. & Pagliarini, D. J. Coenzyme Q biochemistry and biosynthesis. Trends Biochem. Sci. 48, 463–476 (2023).
Google Scholar
Pietrocola, F., Galluzzi, L., Bravo-San Pedro, J. M., Madeo, F. & Kroemer, G. Acetyl coenzyme A: a central metabolite and second messenger. Cell Metab. 21, 805–821 (2015).
Google Scholar
Liu, Y. et al. Machine learning framework for gut microbiome biomarkers discovery and modulation analysis in large-scale obese population. BMC Genomics 23, 850 (2022).
Google Scholar
Chiu, C. M. et al. Systematic analysis of the association between gut flora and obesity through high-throughput sequencing and bioinformatics approaches. Biomed. Res. Int. 2014, 906168 (2014).
Google Scholar
Liu, R. et al. Gut microbiome and serum metabolome alterations in obesity and after weight-loss intervention. Nat. Med. 23, 859–868 (2017).
Google Scholar
Michels, N. et al. Human microbiome and metabolic health: an overview of systematic reviews. Obes. Rev. 23, e13409 (2022).
Google Scholar
Li, C. et al. Gut microbiome and metabolome profiling in Framingham heart study reveals cholesterol-metabolizing bacteria. Cell 187, 1834–1852 e1819 (2024).
Google Scholar
Folcik, V. A. & Cathcart, M. K. Predominance of esterified hydroperoxy-linoleic acid in human monocyte-oxidized LDL. J. Lipid Res. 35, 1570–1582 (1994).
Google Scholar
Das, U. N. Arachidonic acid in health and disease with focus on hypertension and diabetes mellitus: a review. J. Adv. Res 11, 43–55 (2018).
Google Scholar
Roman, R. J. P. -450 metabolites of arachidonic acid in the control of cardiovascular function. Physiol. Rev. 82, 131–185 (2002).
Google Scholar
Horrillo, R. et al. 5-lipoxygenase activating protein signals adipose tissue inflammation and lipid dysfunction in experimental obesity. J. Immunol. 184, 3978–3987 (2010).
Google Scholar
Sacerdoti, D., Gatta, A. & McGiff, J. C. Role of cytochrome P450-dependent arachidonic acid metabolites in liver physiology and pathophysiology. Prostaglandins Other Lipid Mediat. 72, 51–71 (2003).
Google Scholar
Li, S., Su, W., Zhang, X. Y. & Guan, Y. F. [Arachidonic acid metabolism in liver glucose and lipid homeostasis]. Sheng Li Xue Bao 73, 657–664 (2021).
Google Scholar
Bennett, B. J. et al. Trimethylamine-N-oxide, a metabolite associated with atherosclerosis, exhibits complex genetic and dietary regulation. Cell Metab. 17, 49–60 (2013).
Google Scholar
Koeth, R. A. et al. Intestinal microbiota metabolism of L-carnitine, a nutrient in red meat, promotes atherosclerosis. Nat. Med. 19, 576–585 (2013).
Google Scholar
Seldin, M. M. et al Trimethylamine N-oxide promotes vascular inflammation through signaling of mitogen-activated protein kinase and nuclear factor-κB. J. Am. Heart Assoc. 5, e002767 (2016).
Li, X. et al. Effect of Lactobacillus plantarum HT121 on serum lipid profile, gut microbiota, and liver transcriptome and metabolomics in a high-cholesterol diet-induced hypercholesterolemia rat model. Nutrition 79-80, 110966 (2020).
Google Scholar
Li, T. et al. Eight weeks of bifidobacterium lactis BL-99 supplementation improves lipid metabolism and sports performance through short-chain fatty acids in cross-country skiers: a preliminary study. Nutrients. 15, 4554 (2023).
Hibberd, A. A. et al. Probiotic or synbiotic alters the gut microbiota and metabolism in a randomised controlled trial of weight management in overweight adults. Benef. Microbes 10, 121–135 (2019).
Google Scholar
Cai, J., Rimal, B., Jiang, C., Chiang, J. Y. L. & Patterson, A. D. Bile acid metabolism and signaling, the microbiota, and metabolic disease. Pharm. Ther. 237, 108238 (2022).
Google Scholar
Xu, W., Kong, Y., Zhang, T., Gong, Z. & Xiao, W. L-Theanine regulates lipid metabolism by modulating gut microbiota and bile acid metabolism. J. Sci. Food Agric. 103, 1283–1293 (2023).
Google Scholar
Jie, L. et al. The mechanism of palmatine-mediated intestinal flora and host metabolism intervention in OA-OP comorbidity rats. Front. Med.10, 1153360 (2023).
Google Scholar
Deng, K. et al. Comparison of fecal and blood metabolome reveals inconsistent associations of the gut microbiota with cardiometabolic diseases. Nat. Commun. 14, 571 (2023).
Google Scholar
Bugajska, J., Berska, J., Wójcik, M. & Sztefko, K. Amino acid profile in overweight and obese prepubertal children – can simple biochemical tests help in the early prevention of associated comorbidities?. Front. Endocrinol.14, 1274011 (2023).
Google Scholar
Kim, M. J., Sim, D. Y., Lee, H. M., Lee, H. J. & Kim S. H. Hypolipogenic Effect of Shikimic Acid Via Inhibition of MID1IP1 and Phosphorylation of AMPK/ACC. Int. J. Mol. Sci. 20, 582 (2019).
Askari, A. A. et al. Basal and inducible anti-inflammatory epoxygenase activity in endothelial cells. Biochem. Biophys. Res. Commun. 446, 633–637 (2014).
Google Scholar
Crost, E. H., Coletto, E., Bell, A. & Juge, N. Ruminococcus gnavus: friend or foe for human health. FEMS Microbiol. Rev. 47, fuad014 (2023).
Google Scholar
van Soest, A. P. M. et al. Associations between pro- and anti-inflammatory gastro-intestinal microbiota, diet, and cognitive functioning in dutch healthy older adults: the NU-AGE Study. Nutrients. 12, 3471 (2020).
Ma, E. et al. Long-term association between diet quality and characteristics of the gut microbiome in the multiethnic cohort study. Br. J. Nutr. 1–10 (2021).
Roager, H. M. & Licht, T. R. Microbial tryptophan catabolites in health and disease. Nat. Commun. 9, 3294 (2018).
Google Scholar
Chatterjee, B., Echchgadda I. & Seog Song C. Vitamin D receptor regulation of the steroid/bile acid sulfotransferase SULT2A1. In: Methods Enzymol. Academic Press, 165–191 (2005).
Chaudhari, S. N. et al. A microbial metabolite remodels the gut-liver axis following bariatric surgery. Cell Host Microbe 29, 408–424.e407 (2021).
Google Scholar
Robben, J., Janssen, G., Merckx, R. & Eyssen, H. Formation of delta 2- and delta 3-cholenoic acids from bile acid 3-sulfates by a human intestinal Fusobacterium strain. Appl. Environ. Microbiol. 55, 2954–2959 (1989).
Google Scholar
Antharam, V. C. et al. An integrated metabolomic and microbiome analysis identified specific gut microbiota associated with fecal cholesterol and coprostanol in clostridium difficile infection. PLoS ONE11, e0148824 (2016).
Google Scholar
Louis, P., Young, P., Holtrop, G. & Flint, H. J. Diversity of human colonic butyrate-producing bacteria revealed by analysis of the butyryl-CoA:acetate CoA-transferase gene. Environ. Microbiol. 12, 304–314 (2010).
Google Scholar
Gophna, U., Konikoff, T. & Nielsen, H. B. Oscillospira and related bacteria – from metagenomic species to metabolic features. Environ. Microbiol. 19, 835–841 (2017).
Google Scholar
Parker, B. J., Wearsch, P. A., Veloo, A. C. M. & Rodriguez-Palacios, A. The genus alistipes: gut bacteria with emerging implications to inflammation, cancer, and mental health. Front. Immunol. 11, 906 (2020).
Google Scholar
Franzosa, E. A. et al. Gut microbiome structure and metabolic activity in inflammatory bowel disease. Nat. Microbiol. 4, 293–305 (2019).
Google Scholar
Jie, Z. et al. The gut microbiome in atherosclerotic cardiovascular disease. Nat. Commun. 8, 845 (2017).
Google Scholar
DePhillips, C., Parikh, P. B. & Stevens, G. A. Dyslipidemia: current therapies and strategies to overcome barriers for use. J. Nurse Pract.17, 1167–1173 (2021).
Google Scholar
Wang, L., Zhang, L., Zhang, Y. & Li, J. P. Impact of allogenic fecal microbiota transplantation (FMT) on lipid parameters in patients with metabolic syndrome (MetS): a meta-analysis. Eur. Heart J. 45, ehae666.3361 (2024).
Google Scholar
Mederle, A. L. et al. Impact of gut microbiome interventions on glucose and lipid metabolism in metabolic diseases: a systematic review and meta-analysis. Life 14, 1485 (2024).
Google Scholar
Qu, Q. et al. Population-level gut microbiome and its associations with environmental factors and metabolic disorders in Southwest China. NPJ Biofilms Microbiomes 11, 24 (2025).
Google Scholar
Zhu, N. et al. Prevalence of ‘healthy lifestyle’ in Chinese adults. Chin. J. Epidemiol. 40, 136–141 (2019).
Google Scholar
World Health Organization. Global Action Plan on Physical Activity 2018–2030: More Active People for a Healthier World. (2018).
Du, H. et al. Physical activity and sedentary leisure time and their associations with BMI, waist circumference, and percentage body fat in 0.5 million adults: the China Kadoorie Biobank study. Am. J. Clin. Nutr. 97, 487–496 (2013).
Google Scholar
Yu, W. et al. Rural-urban disparities in the associations of residential greenness with diabetes and prediabetes among adults in southeastern China. Sci. Total Environ. 860, 160492 (2023).
Google Scholar
Ainsworth, B. E. et al. 2011 Compendium of Physical Activities: a second update of codes and MET values. Med. Sci. Sports Exerc. 43, 1575–1581 (2011).
Google Scholar
Craig, C. L. et al. International physical activity questionnaire: 12-country reliability and validity. Med. Sci. Sports Exerc. 35, 1381–1395 (2003).
Google Scholar
Eckel, R. H. et al. 2013 AHA/ACC guideline on lifestyle management to reduce cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J. Am. Coll. Cardiol. 63, 2960–2984 (2014).
Google Scholar
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
Google Scholar
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–U354 (2012).
Google Scholar
Wood, D. E., Lu, J. & Langmead, B. Improved metagenomic analysis with Kraken 2. Genome Biol. 20, 257 (2019).
Google Scholar
Li, D. H., Liu, C. M., Luo, R. B., Sadakane, K. & Lam, T. W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31, 1674–1676 (2015).
Google Scholar
Want, E. J. et al. Global metabolic profiling of animal and human tissues via UPLC-MS. Nat. Protoc. 8, 17–32 (2013).
Google Scholar
Smith, C. A., Want, E. J., O’Maille, G., Abagyan, R. & Siuzdak, G. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal. Chem. 78, 779–787 (2006).
Google Scholar
Navarro-Reig, M., Jaumot, J., García-Reiriz, A. & Tauler, R. Evaluation of changes induced in rice metabolome by Cd and Cu exposure using LC-MS with XCMS and MCR-ALS data analysis strategies. Anal. Bioanal. Chem. 407, 8835–8847 (2015).
Google Scholar
Wishart, D. S. et al. HMDB: the human metabolome database. Nucleic Acids Res. 35, D521–D526 (2007).
Google Scholar
Sud, M. et al. LMSD: LIPID MAPS structure database. Nucleic Acids Res. 35, D527–D532 (2007).
Google Scholar
Ogata, H. et al. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 27, 29–34 (1999).
Google Scholar
Garralda-Del-Villar, M. et al Healthy lifestyle and incidence of metabolic syndrome in the SUN cohort. Nutrients. 11, 65 (2018).
Sun, Q. et al. Healthy lifestyle and life expectancy at age 30 years in the Chinese population: an observational study. Lancet Public Health 7, e994–e1004 (2022).
Google Scholar
Nearing, J. T. et al. Microbiome differential abundance methods produce different results across 38 datasets. Nat. Commun. 13, 342 (2022).
Google Scholar
Lu, J. et al. Chinese gut microbiota and its associations with staple food type, ethnicity, and urbanization. NPJ Biofilms Microbiomes 7, 71 (2021).
Google Scholar
Mallick, H. et al. Multivariable association discovery in population-scale meta-omics studies. PLoS Comput. Biol. 17, e1009442 (2021).
Google Scholar
Jeong, S. et al. Cognitive function associated with gut microbial abundance in sucrose and s-adenosyl-l-methionine (SAMe) metabolic pathways. J. Alzheimers Dis. 87, 1115–1130 (2022).
Google Scholar
Lloyd-Price, J. et al. Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases. Nature 569, 655–662 (2019).
Google Scholar
Friedman, J. & Alm, E. J. Inferring correlation networks from genomic survey data. PLoS Comput. Biol. 8, e1002687 (2012).
Google Scholar
Ren, Y. et al. Lifestyle patterns influence the composition of the gut microbiome in a healthy Chinese population. Sci. Rep. 13, 14425 (2023).
Google Scholar
link
:max_bytes(150000):strip_icc()/Scientists-Just-Discovered-a-Huge-Health-Benefit-of-Mango-44fbf60c4af84e57854580c44613cb46.jpg "Eating Mango Supports Heart Health, Blood Sugar")
