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Depressive Disorder (Depression) https://www.who.int/news-room/fact-sheets/detail/depression.
Kunasegaran, T., Balasubramaniam, V. R. M. T., Arasoo, V. J. T., Palanisamy, U. D. & Ramadas, A. The modulation of gut microbiota composition in the pathophysiology of gestational diabetes mellitus: a systematic review. Biology (Basel) 10, (2021).
Li, J. et al. Microbial and metabolic profiles unveil mutualistic microbe-microbe interaction in obesity-related colorectal cancer. Cell Rep. Med. 101429 https://doi.org/10.1016/J.XCRM.2024.101429 (2024).
Garcia-Fernandez, H. et al. Sex-specific differences in intestinal microbiota associated with cardiovascular diseases. Biol. Sex Differ. 15, (2024).
Shimizu, K. et al. Dysbiosis of gut microbiota in patients with severe COVID-19. Acute Med. Surg. 11, (2024).
Nikolova, V. L. et al. Perturbations in gut microbiota composition in psychiatric disorders: a review and meta-analysis. JAMA Psychiatry 78, 1 (2021) .
Montagnani, M. et al. The crosstalk between gut microbiota and nervous system: a bidirectional interaction between microorganisms and metabolome. Int. J. Mol. Sci. 24, (2023).
Cryan, J. F. et al. The microbiota–gut–brain axis. Physiol. Rev. 99, 1877–2013 (2019).
Wang, F. B. & Powley, T. L. Vagal innervation of intestines: afferent pathways mapped with new en bloc horseradish peroxidase adaptation. Cell Tissue Res. 329, 221–230 (2007) .
Zhu, F., Tu, H. & Chen, T. The microbiota–gut–brain axis in depression: the potential pathophysiological mechanisms and microbiota combined antidepression effect. Nutrients 14, (2022).
Miller, A. H. & Raison, C. L. The role of inflammation in depression: from evolutionary imperative to modern treatment target. Nat. Rev. Immunol.16, 22–34 (2015).
Dalile, B., Van Oudenhove, L., Vervliet, B. & Verbeke, K. The role of short-chain fatty acids in microbiota–gut–brain communication. Nat. Rev. Gastroenterol. Hepatol. 16, 461–478 (2019).
Braniste, V. et al. The gut microbiota influences blood-brain barrier permeability in mice. Sci. Transl. Med. 6, (2014).
O’Mahony, S. M., Clarke, G., Borre, Y. E., Dinan, T. G. & Cryan, J. F. Serotonin, tryptophan metabolism and the brain–gut–microbiome axis. Behav. Brain Res. 277, 32–48 (2015).
Zierer, J. et al. The fecal metabolome as a functional readout of the gut microbiome. Nat. Genet. 50, 790–795 (2018).
Gao, M. et al. Gut microbiota composition in depressive disorder: a systematic review, meta-analysis, and meta-regression. Transl. Psychiatry 13, 1–18 (2023).
Liu, X. et al. Comparative analysis of gut microbiota and fecal metabolome features among multiple depressive animal models. J. Affect. Disord. 314, 103–111 (2022).
Chen, Y. et al. Gut microbiota dysbiosis in depressed women: the association of symptom severity and microbiota function. J. Affect. Disord. 282, 391–400 (2021).
Lai, W. T. et al. Shotgun metagenomics reveals both taxonomic and tryptophan pathway differences of gut microbiota in major depressive disorder patients. Psychol. Med. 51, 90–101 (2021).
Madan, A. et al. The gut microbiota is associated with psychiatric symptom severity and treatment outcome among individuals with serious mental illness. J. Affect. Disord. 264, 98–106 (2020).
Simpson, C. A., Mu, A., Haslam, N., Schwartz, O. S. & Simmons, J. G. Feeling down? A systematic review of the gut microbiota in anxiety/depression and irritable bowel syndrome. J. Affect. Disord. 266, 429–446 (2020).
Naseribafrouei, A. et al. Correlation between the human fecal microbiota and depression. Neurogastroenterol. Motil. 26, 1155–1162 (2014).
Zheng, P. et al. Gut microbiome remodeling induces depressive-like behaviors through a pathway mediated by the host’s metabolism. Mol. Psychiatry 21, 786–796 (2016).
Mansuy-Aubert, V. & Ravussin, Y. Short chain fatty acids: the messengers from down below. Front. Neurosci. 17 (2023).
Faugere, M. et al. Quality of life is associated with chronic inflammation in depression: a cross-sectional study. J. Affect. Disord. 227, 494–497 (2018).
Oki, K. et al. Comprehensive analysis of the fecal microbiota of healthy Japanese adults reveals a new bacterial lineage associated with a phenotype characterized by a high frequency of bowel movements and a lean body type. BMC Microbiol. 16, 1–13 (2016).
Luo, H., Jiang, Z. L. & Ren, Y. Therapy management of metabolic disorder comorbidity with depression. Front. Psychol. 12, 683320 (2021).
Ang, W. S. et al. A keystone gut bacterium christensenella minuta—a potential biotherapeutic agent for obesity and associated metabolic diseases. Foods 12, 2485 (2023).
Boiangiu, C. D. et al. Sodium ion pumps and hydrogen production in glutamate fermenting anaerobic bacteria. J. Mol. Microbiol. Biotechnol. 10, 105–119 (2005).
Serafini, G., Rihmer, Z. & Amore, M. The role of glutamate excitotoxicity and neuroinflammation in depression and suicidal behavior: focus on microglia cells. Neuroscience 2, 127–130 (2015).
Sanacora, G. & Banasr, M. From pathophysiology to novel antidepressant drugs: glial contributions to the pathology and treatment of mood disorders. Biol. Psychiatry 73, 1172–1179 (2013).
Neis, E. P. J. G., Dejong, C. H. C. & Rensen, S. S. The role of microbial amino acid metabolism in host metabolism. Nutrients 7, 2930–2946 (2015).
Escobar-Arregocés, F. et al. Characterization of the oral microbiota and the relationship of the oral microbiota with the dental and periodontal status in children and adolescents with nonsyndromic cleft lip and palate. Systematic literature review and meta-analysis. Clin. Oral Investig. 28, (2024).
Liu, Z. et al. Regulation of serotonin production by specific microbes from piglet gut. J. Anim. Sci. Biotechnol. 14, (2023).
Moreira, L. B. et al. Presence of Streptococcus mutans and interleukin-6 and -10 in amniotic fluid. J. Matern. Fetal Neonatal Med. 35, 9463–9469 (2022).
Shan, C., Zhang, C. & Zhang, C. The role of IL-6 in neurodegenerative disorders. Neurochem. Res. 49, 834–846 (2024).
Louis, P. & Flint, H. J. Formation of propionate and butyrate by the human colonic microbiota. Environ. Microbiol. 19, 29–41 (2017).
Tong, L. C. et al. Propionate ameliorates dextran sodium sulfate-induced colitis by improving intestinal barrier function and reducing inflammation and oxidative stress. Front. Pharmacol. 7, 202262 (2016).
Regulska, M., Szuster-Głuszczak, M., Trojan, E., Leśkiewicz, M. & Basta-Kaim, A. The emerging role of the double-edged impact of arachidonic acid- derived eicosanoids in the neuroinflammatory background of depression. Curr. Neuropharmacol. 19, 278–293 (2020).
Chaudhary, S., Sahu, U., Kar, S. & Parvez, S. Phytanic acid-induced neurotoxicological manifestations and apoptosis ameliorated by mitochondria-mediated actions of melatonin. Mol. Neurobiol. 54, 6960–6969 (2017).
Chen, M., Wang, L., Lou, Y. & Huang, Z. Effects of chronic unpredictable mild stress on gut microbiota and fecal amino acid and short-chain fatty acid pathways in mice. Behav. Brain Res. 464, 114930 (2024).
Xie, Z. et al. Integrated multi-omics analysis reveals gut microbiota dysbiosis and systemic disturbance in major depressive disorder. Psychiatry Res. 334, 115804 (2024).
Wheelan, P. & Murphy, R. C. Metabolism of 6-trans-Isomers of leukotriene B4 in cultured hepatoma cells and in human polymorphonuclear leukocytes. J. Biol. Chem. 270, 19845–19852 (1995).
Guzior, D. V. & Quinn, R. A. Review: microbial transformations of human bile acids. Microbiome 9, 1–13 (2021).
Strasser, B., Sperner-Unterweger, B., Fuchs, D. & Gostner, J. M. Mechanisms of inflammation-associated depression: immune influences on tryptophan and phenylalanine metabolisms. Curr. Top. Behav. Neurosci. 31, (2017).
Bremm, K. D. et al. Generation of leukotrienes from human granulocytes by alveolysin from Bacillus alvei. Infect. Immun. 44, 188–193 (1984).
Shetty, N., Wren, M. W. D. & Coen, P. G. The role of glutamate dehydrogenase for the detection of Clostridium difficile in faecal samples: a meta-analysis. J. Hosp. Infect. 77, 1–6 (2011).
Coleman, J. P. & Hudson, L. L. Cloning and characterization of a conjugated bile acid hydrolase gene from Clostridium perfringens. Appl. Environ. Microbiol. 61, 2514 (1995).
Nikolova, V. L., Cleare, A. J., Young, A. H. & Stone, J. M. Acceptability, tolerability, and estimates of putative treatment effects of probiotics as adjunctive treatment in patients with depression: a randomized clinical trial. JAMA Psychiatry 80, 842–847 (2023).
Tian, P. et al. Bifidobacterium breve CCFM1025 attenuates major depression disorder via regulating gut microbiome and tryptophan metabolism: a randomized clinical trial. Brain Behav. Immun. 100, 233–241 (2022).
Kim, C. S. et al. Probiotic supplementation improves cognitive function and mood with changes in gut microbiota in community-dwelling older adults: a randomized, double-blind, placebo-controlled, multicenter trial. J. Gerontol. A Biol. Sci. Med. Sci. 76, 32–40 (2021).
Salas-Salvadó, J. et al. Effect of a lifestyle intervention program with energy-restricted mediterranean diet and exercise on weight loss and cardiovascular risk factors: one-year results of the PREDIMED-Plus Trial. Diabetes Care 42, 777–788 (2019).
Alberti, K. G. M. M. et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 120, 1640–1645 (2009).
Martínez-González, M. A. et al. Cohort Profile: design and methods of the PREDIMED-Plus randomized trial. Int. J. Epidemiol. 48, 387–388o (2019).
Molina, L. et al. Validation of the regicor short physical activity questionnaire for the adult population. PLoS ONE 12, e0168148 (2017).
Fernández-Ballart, J. D. et al. Relative validity of a semi-quantitative food-frequency questionnaire in an elderly Mediterranean population of Spain. Br. J. Nutr. 103, 1808–1816 (2010).
Beck, A., Steer, R. & Brown, G. W. Beck Depression Inventory–II (BDI-II). APA PsycTests https://doi.org/10.1037/T00742-000 (1996).
Maksimovskiy, A. L., Okine, C., Cataldo, A. M. & Dillon, D. G. Sluggish retrieval of positive memories in depressed adults. Cogn. Affect. Behav. Neurosci. 22, 1172–1182 (2022).
Gehrman, P. R., Bartky, E. J., Travers, C. & Lapidus, K. A Fully remote randomized trial of transcranial alternating current stimulation for the acute treatment of major depressive disorder. J. Clin. Psychiatry 85, (2024).
Callahan, B. J. et al. DADA2: high resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581 (2016).
Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590 (2013).
Kostic, A. D. et al. The dynamics of the human infant gut microbiome in development and in progression towards type 1 diabetes. Cell Host Microbe 17, 260 (2015).
Chao, A. Estimating the population size for capture-recapture data with unequal catchability. Biometrics 43, 783 (1987).
Shannon, C. E. A mathematical theory of communication. Bell Syst. Tech. J. 27, 623–656.
Simpson, E. H. Measurement of diversity [16]. Nature 163, 688 (1949).
Wilcoxon, F. Individual comparisons by ranking methods. Biometr. Bull. 1, 80 (1945).
Aitchison, J., Barceló-Vidal, C., Martín-Fernández, J. A. & Pawlowsky-Glahn, V. Logratio analysis and compositional distance. Math. Geol. 32, 271–275 (2000).
Anderson, M. J. A new method for non-parametric multivariate analysis of variance. Austral Ecol. 26, 32–46 (2001).
Mallick, H. et al. Multivariable association discovery in population-scale meta-omics studies. PLoS Comput. Biol. 17, e1009442 (2021).
Lin, H. & Peddada, S.D. Analysis of compositions of microbiomes with bias correction. Nat. Commun. 11, 1–11 (2020).
Wallen, Z. D. et al. Metagenomics of Parkinson’s disease implicates the gut microbiome in multiple disease mechanisms. Nat. Commun. 13, (2022).
Faggiani, L. D. et al. Effect of ultra-processed food consumption on the gut microbiota in the first year of life: findings from the MINA-Brazil birth cohort study. Clin. Nutr. 46, 181–190 (2025).
Douglas, G. M. et al. PICRUSt2 for prediction of metagenome functions. Nat. Biotechnol. 38, 685 (2020).
Kanehisa, M. & Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27 (2000).
McCaw, Z. R., Lane, J. M., Saxena, R., Redline, S. & Lin, X. Operating characteristics of the rank-based inverse normal transformation for quantitative trait analysis in genome-wide association studies. Biometrics 76, 1262–1272 (2020).
García-Gavilán, J. F. et al. Olive oil consumption, plasma metabolites, and risk of type 2 diabetes and cardiovascular disease. Cardiovasc. Diabetol. 22, 340 (2023).
Bishara, A. J. & Hittner, J. B. Testing the significance of a correlation with nonnormal data: comparison of Pearson, Spearman, transformation, and resampling approaches. Psychol. Methods 17, 399–417 (2012).
Zou, H. & Hastie, T. Regularization and variable selection via the elastic net. J. R. Stat. Soc. Ser. B Stat. Methodol. 67, 301–320 (2005).
Zhang, Y. et al. Metabolomic profiles of sleep-disordered breathing are associated with hypertension and diabetes mellitus development. Nat. Commun. 15, (2024).
Li, J. et al. The Mediterranean diet, plasma metabolome, and cardiovascular disease risk. Eur. Heart J. 41, 2645–2656 (2020).
Bever, A. M. et al. Metabolomic signatures of inflammation and metabolic dysregulation in relation to colorectal cancer risk. J. Natl Cancer Inst. 116, 1126–1136 (2024).
Schröder, H. et al. Validity of the energy-restricted Mediterranean Diet Adherence Screener. Clin. Nutr. 40, 4971–4979 (2021).
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