SpringerLink
Log in

Stress-resilience impacts psychological wellbeing as evidenced by brain–gut microbiome interactions

  • Article
  • Published:

From Nature Mental Health

View current issue Submit your manuscript

Abstract

The brain–gut microbiome (BGM) system plays an influential role on mental health. We characterized BGM patterns related to resilience using fecal samples and multimodal magnetic resonance imaging. Data integration analysis using latent components showed that the high-resilience phenotype was associated with lower depression and anxiety symptoms, higher frequency of bacterial transcriptomes (related to environmental adaptation, genetic propagation, energy metabolism and anti-inflammation), increased metabolites (N-acetylglutamate, dimethylglycine) and cortical signatures (increased resting-state functional connectivity between reward circuits and sensorimotor networks; decreased gray-matter volume and white-matter tracts within the emotion regulation network). Our findings support a multi-omic signature involving the BGM system, suggesting that resilience impacts psychological symptoms, emotion regulation and cognitive function, as reflected by unique neural correlates and microbiome function supporting eubiosis and gut-barrier integrity. Bacterial transcriptomes provided the highest classification accuracy, suggesting that the microbiome is critical in sha** resilience, and highlighting that microbiome modifications can optimize mental health.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1: Graphical summary.
Fig. 2: Boxplots of DIABLO-selected variables of importance.
Fig. 3: Loading plots from the DIABLO-selected variables of importance.
Fig. 4: Connectogram depicting the correlations within the variables of importance from all the datasets.

Similar content being viewed by others

Data availability

De-identified individual participant data (brain) can be shared upon request and will be made available through the Center’s pain repository portal (https://www.painrepository.org/). To access the data, participants will fill out a user agreement, after which access to the data will be made available through a secure password-protected portal. Raw microbiome sequences can be accessed via the NIH NCBI BioProject (BioProject ID PRJNA946906).

Code availability

All data analyses used readily available programs (for example, open-source R code). No custom code was used.

References

  1. Workplace stress. American Institute of Stress http://www.stress.org/workplace-stress/ (2013).

  2. Vella, S.-L. C. & Pai, N. B. A theoretical review of psychological resilience: defining resilience and resilience research over the decades. Arch. Med. Health Sci. 7, 233–239 (2019).

    Article  Google Scholar 

  3. Hill, Y., Den Hartigh, R. J. R., Meijer, R. R., De Jonge, P. & Van Yperen, N. W. The temporal process of resilience. Sport Exerc. Perform. Psychol. 7, 363–370 (2018).

    Google Scholar 

  4. Connor, K. M. & Davidson, J. R. Development of a new resilience scale: the Connor-Davidson Resilience Scale (CD-RISC). Depress. Anxiety 18, 76–82 (2003).

    Article  PubMed  Google Scholar 

  5. Ahmed, Z. & Julius, S. H. Academic performance, resilience, depression, anxiety and stress among women college students. Ind. J. Positive Psychol. 6, 367–370 (2015).

    Google Scholar 

  6. Poudel-Tandukar, K. et al. Resilience and anxiety or depression among resettled Bhutanese adults in the United States. Int. J. Soc. Psychiatry 65, 496–506 (2019).

    Article  PubMed  Google Scholar 

  7. Harker, R., Pidgeon, A. M., Klaassen, F. & King, S. Exploring resilience and mindfulness as preventative factors for psychological distress burnout and secondary traumatic stress among human service professionals. Work 54, 631–637 (2016).

    Article  PubMed  Google Scholar 

  8. Eisen, S. V. et al. Postdeployment resilience as a predictor of mental health in operation enduring freedom/operation Iraqi freedom returnees. Am. J. Prev. Med. 47, 754–761 (2014).

    Article  PubMed  Google Scholar 

  9. Uliaszek, A. A. et al. The role of neuroticism and extraversion in the stress-anxiety and stress-depression relationships. Anxiety Stress Co** 23, 363–381 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Polizzi, C. P. & Lynn, S. J. Regulating emotionality to manage adversity: a systematic review of the relation between emotion regulation and psychological resilience. Cognitive Ther. Res. 45, 577–597 (2021).

    Article  Google Scholar 

  11. Allott, K. A. et al. The impact of neuropsychological functioning and co** style on perceived stress in individuals with first-episode psychosis and healthy controls. Psychiatry Res. 226, 128–135 (2015).

    Article  PubMed  Google Scholar 

  12. Sippel, L. M., Pietrzak, R. H., Charney, D. S., Mayes, L. C. & Southwick, S. M. How does social support enhance resilience in the trauma-exposed individual? Ecol. Soc. 20, art10 (2015).

    Article  Google Scholar 

  13. Carney, R. M. et al. Change in heart rate and heart rate variability during treatment for depression in patients with coronary heart disease. Psychosom. Med. 62, 639–647 (2000).

    Article  PubMed  Google Scholar 

  14. Sydnor, V. J. et al. Neurodevelopment of the association cortices: patterns, mechanisms and implications for psychopathology. Neuron 109, 2820–2846 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Turnbaugh, P. J. et al. The human microbiome project. Nature 449, 804–810 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Jiang, H. et al. Altered fecal microbiota composition in patients with major depressive disorder. Brain Behav. Immun. 48, 186–194 (2015).

    Article  PubMed  Google Scholar 

  17. Jiang, H. Y. et al. Altered gut microbiota profile in patients with generalized anxiety disorder. J. Psychiatr. Res. 104, 130–136 (2018).

    Article  PubMed  Google Scholar 

  18. He, Y. et al. Gut microbiome and magnetic resonance spectroscopy study of subjects at ultra-high risk for psychosis may support the membrane hypothesis. Eur. Psychiatry 53, 37–45 (2018).

    Article  PubMed  Google Scholar 

  19. Butler, M. I. et al. The gut microbiome in social anxiety disorder: evidence of altered composition and function. Transl. Psychiatry 13, 95 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Evans, S. J. et al. The gut microbiome composition associates with bipolar disorder and illness severity. J. Psychiatr. Res. 87, 23–29 (2017).

    Article  PubMed  Google Scholar 

  21. Kang, D. W. et al. Reduced incidence of Prevotella and other fermenters in intestinal microflora of autistic children. PLoS ONE 8, e68322 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Foster, J. A. & McVey Neufeld, K. A. Gut–brain axis: how the microbiome influences anxiety and depression. Trends Neurosci. 36, 305–312 (2013).

    Article  PubMed  Google Scholar 

  23. Mayer, E. A. The neurobiology of stress and gastrointestinal disease. Gut 47, 861–869 (2000).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Bear, T. et al. The microbiome–gut–brain axis and resilience to develo** anxiety or depression under stress. Microorganisms 9, 723 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Cryan, J. F. & Dinan, T. G. Mind-altering microorganisms: the impact of the gut microbiota on brain and behaviour. Nat. Rev. Neurosci. 13, 701–712 (2012).

    Article  PubMed  Google Scholar 

  26. Parashar, A. & Udayabanu, M. Gut microbiota regulates key modulators of social behavior. Eur. Neuropsychopharmacol. 26, 78–91 (2016).

    Article  PubMed  Google Scholar 

  27. Yang, C. et al. Bifidobacterium in the gut microbiota confer resilience to chronic social defeat stress in mice. Sci. Rep. 7, 45942 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Li, L. F. et al. Increased Lactobacillus abundance contributes to stress resilience in mice exposed to chronic social defeat stress. Neuroendocrinology 113, 563–576 (2023).

    Article  PubMed  Google Scholar 

  29. Wang, X. et al. Abnormal compositions of gut microbiota and metabolites are associated with susceptibility versus resilience in rats to inescapable electric stress. J. Affect. Disord. 331, 369–379 (2023).

    Article  PubMed  Google Scholar 

  30. Zhang, K. et al. Abnormal composition of gut microbiota is associated with resilience versus susceptibility to inescapable electric stress. Transl. Psychiatry 9, 231 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y. & Morishima, K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 45, D353–D361 (2017).

    Article  PubMed  Google Scholar 

  32. Barrett, E., Ross, R. P., O’Toole, P. W., Fitzgerald, G. F. & Stanton, C. γ-Aminobutyric acid production by culturable bacteria from the human intestine. J. Appl. Microbiol. 113, 411–417 (2012).

    Article  PubMed  Google Scholar 

  33. Baj, A. et al. Glutamatergic signaling along the microbiota-gut-brain axis. Int. J. Mol. Sci. 20, 1482 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  34. 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).

    Article  PubMed  Google Scholar 

  35. Cryan, J. F. et al. The microbiota–gut–brain axis. Physiol. Rev. 99, 1877–2013 (2019).

    Article  PubMed  Google Scholar 

  36. Rosso, I. M. et al. Insula and anterior cingulate GABA levels in posttraumatic stress disorder: preliminary findings using magnetic resonance spectroscopy. Depress. Anxiety 31, 115–123 (2014).

    Article  PubMed  Google Scholar 

  37. Murrough, J. W. et al. Reduced amygdala serotonin transporter binding in posttraumatic stress disorder. Biol. Psychiatry 70, 1033–1038 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Bonaz, B., Bazin, T. & Pellissier, S. The vagus nerve at the interface of the microbiota-gut-brain axis. Front. Neurosci. 12, 49 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Miller, T. L. & Wolin, M. J. Pathways of acetate, propionate and butyrate formation by the human fecal microbial flora. Appl. Environ. Microbiol. 62, 1589–1592 (1996).

    Article  PubMed  PubMed Central  Google Scholar 

  40. Stilling, R. M. et al. The neuropharmacology of butyrate: the bread and butter of the microbiota-gut-brain axis? Neurochem. Int. 99, 110–132 (2016).

    Article  PubMed  Google Scholar 

  41. Bharwani, A. et al. Structural and functional consequences of chronic psychosocial stress on the microbiome and host. Psychoneuroendocrinology 63, 217–227 (2016).

    Article  PubMed  Google Scholar 

  42. Tanelian, A., Nankova, B., Miari, M., Nahvi, R. J. & Sabban, E. L. Resilience or susceptibility to traumatic stress: potential influence of the microbiome. Neurobiol. Stress 19, 100461 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Sampson, T. R. & Mazmanian, S. K. Control of brain development, function and behavior by the microbiome. Cell Host Microbe 17, 565–576 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Tillisch, K. et al. Brain structure and response to emotional stimuli as related to gut microbial profiles in healthy women. Psychosom. Med. 79, 905–913 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Kohn, N. et al. Multivariate associative patterns between the gut microbiota and large-scale brain network connectivity. Gut Microbes 13, 2006586 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Tillisch, K. et al. Consumption of fermented milk product with probiotic modulates brain activity. Gastroenterology 144, 1394–1401 (2013).

    Article  PubMed  Google Scholar 

  47. Tabibnia, G. An affective neuroscience model of boosting resilience in adults. Neurosci. Biobehav. Rev. 115, 321–350 (2020).

    Article  PubMed  Google Scholar 

  48. Christoff, K., Irving, Z. C., Fox, K. C., Spreng, R. N. & Andrews-Hanna, J. R. Mind-wandering as spontaneous thought: a dynamic framework. Nat. Rev. Neurosci. 17, 718–731 (2016).

    Article  PubMed  Google Scholar 

  49. Hamilton, J. P. et al. Default-mode and task-positive network activity in major depressive disorder: implications for adaptive and maladaptive rumination. Biol. Psychiatry 70, 327–333 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Shaurya Prakash, R., De Leon, A. A., Klatt, M., Malarkey, W. & Patterson, B. Mindfulness disposition and default-mode network connectivity in older adults. Soc. Cogn. Affect. Neurosci. 8, 112–117 (2013).

    Article  PubMed  Google Scholar 

  51. Gupta, A. et al. Morphological brain measures of cortico-limbic inhibition related to resilience. J. Neurosci. Res. 95, 1760–1775 (2017).

    Article  PubMed  Google Scholar 

  52. Helpman, L. et al. PTSD remission after prolonged exposure treatment is associated with anterior cingulate cortex thinning and volume reduction. Depress. Anxiety 33, 384–391 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Kong, F., Wang, X., Hu, S. & Liu, J. Neural correlates of psychological resilience and their relation to life satisfaction in a sample of healthy young adults. Neuroimage 123, 165–172 (2015).

    Article  PubMed  Google Scholar 

  54. Doucet, G. E., Bassett, D. S., Yao, N., Glahn, D. C. & Frangou, S. The role of intrinsic brain functional connectivity in vulnerability and resilience to bipolar disorder. Am. J. Psychiatry 174, 1214–1222 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  55. Ke, J. et al. A longitudinal fMRI investigation in acute post-traumatic stress disorder (PTSD). Acta Radiol. 57, 1387–1395 (2016).

    Article  PubMed  Google Scholar 

  56. Admon, R. et al. Imbalanced neural responsivity to risk and reward indicates stress vulnerability in humans. Cereb. Cortex 23, 28–35 (2013).

    Article  PubMed  Google Scholar 

  57. Schmidt, A. T. et al. Diffusion tensor imaging correlates of resilience following adolescent traumatic brain injury. Cogn. Behav. Neurol. 34, 259–274 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  58. Goldberg, L. R. et al. The international personality item pool and the future of public-domain personality measures. J. Res. Pers. 40, 84–96 (2006).

    Article  Google Scholar 

  59. Baer, R. A., Smith, G. T., Hopkins, J., Krietemeyer, J. & Toney, L. Using self-report assessment methods to explore facets of mindfulness. Assessment 13, 27–45 (2006).

    Article  PubMed  Google Scholar 

  60. Zigmond, A. S. & Snaith, R. P. The hospital anxiety and depression scale. Acta Psychiatr. Scand. 67, 361–370 (1983).

    Article  PubMed  Google Scholar 

  61. Julian, L. J. Measures of anxiety: State-Trait Anxiety Inventory (STAI), Beck Anxiety Inventory (BAI) and Hospital Anxiety and Depression Scale-Anxiety (HADS-A). Arthritis Care Res. (Hoboken) 63, S467–S472 (2011).

    Article  Google Scholar 

  62. Seidenberg, M., Haltiner, A., Taylor, M. A., Hermann, B. B. & Wyler, A. Development and validation of a Multiple Ability Self-Report Questionnaire. J. Clin. Exp. Neuropsychol. 16, 93–104 (1994).

    Article  PubMed  Google Scholar 

  63. Gonzalez, I., Cao, K. A., Davis, M. J. & Dejean, S. Visualising associations between paired ‘omics’ data sets. Biodata Min. 5, 19 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Garcia-Martinez, P. et al. Perceived stress in relation to quality of life and resilience in patients with advanced chronic kidney disease undergoing hemodialysis. Int. J. Environ. Res. Public Health 18, 536 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  65. Creswell, J. D. Mindfulness interventions. Annu. Rev. Psychol. 68, 491–516 (2017).

    Article  PubMed  Google Scholar 

  66. Hildebrandt, L. K., McCall, C., Engen, H. G. & Singer, T. Cognitive flexibility, heart rate variability and resilience predict fine-grained regulation of arousal during prolonged threat. Psychophysiology 53, 880–890 (2016).

    Article  PubMed  Google Scholar 

  67. Martindale, S. L. et al. Neuropsychological functioning, co** and quality of life among returning war veterans. Rehabil. Psychol. 61, 231–239 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  68. Rutherford, S. T. & Bassler, B. L. Bacterial quorum sensing: its role in virulence and possibilities for its control. Cold Spring Harb. Perspect. Med. 2, a012427 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Caldovic, L. & Tuchman, M. N-Acetylglutamate and its changing role through evolution. Biochem. J. 372, 279–290 (2003).

    Article  PubMed  PubMed Central  Google Scholar 

  70. Bowerman, K. L. et al. Disease-associated gut microbiome and metabolome changes in patients with chronic obstructive pulmonary disease. Nat. Commun. 11, 5886 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  71. Li, J. Y. et al. Arginine metabolism regulates the pathogenesis of inflammatory bowel disease. Nutr. Rev. 81, 578–586 (2023).

    Article  PubMed  Google Scholar 

  72. Graber, C. D., Goust, J. M., Glassman, A. D., Kendall, R. & Loadholt, C. B. Immunomodulating properties of dimethylglycine in humans. J. Infect. Dis. 143, 101–105 (1981).

    Article  PubMed  Google Scholar 

  73. Wang, Z., Shao, D., Wu, S., Song, Z. & Shi, S. Heat stress-induced intestinal barrier damage and dimethylglycine alleviates via improving the metabolism function of microbiota gut brain axis. Ecotoxicol. Environ. Saf. 244, 114053 (2022).

    Article  PubMed  Google Scholar 

  74. Hamani, C. et al. The subcallosal cingulate gyrus in the context of major depression. Biol. Psychiatry 69, 301–308 (2011).

    Article  PubMed  Google Scholar 

  75. Etkin, A., Egner, T. & Kalisch, R. Emotional processing in anterior cingulate and medial prefrontal cortex. Trends Cogn. Sci. 15, 85–93 (2011).

    Article  PubMed  Google Scholar 

  76. Rode, J. et al. Probiotic mixture containing Lactobacillus helveticus, Bifidobacterium longum and Lactiplantibacillus plantarum affects brain responses toward an emotional task in healthy subjects: a randomized clinical trial. Front. Nutr. 9, 827182 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  77. Rode, J. et al. Multi-strain probiotic mixture affects brain morphology and resting state brain function in healthy subjects: an RCT. Cells 11, 2922 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  78. Uhr, L., Tsolaki, E. & Pouratian, N. Diffusion tensor imaging correlates of depressive symptoms in Parkinson disease. J. Comp. Neurol. 530, 1729–1738 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  79. Montag, C., Reuter, M., Weber, B., Markett, S. & Schoene-Bake, J. C. Individual differences in trait anxiety are associated with white matter tract integrity in the left temporal lobe in healthy males but not females. Neuroscience 217, 77–83 (2012).

    Article  PubMed  Google Scholar 

  80. Amico, F. et al. Structural MRI correlates for vulnerability and resilience to major depressive disorder. J. Psychiatry Neurosci. 36, 15–22 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  81. Williams, L. M. et al. Arousal dissociates amygdala and hippocampal fear responses: evidence from simultaneous fMRI and skin conductance recording. Neuroimage 14, 1070–1079 (2001).

    Article  PubMed  Google Scholar 

  82. Butler, T. et al. Human fear-related motor neurocircuitry. Neuroscience 150, 1–7 (2007).

    Article  PubMed  Google Scholar 

  83. Feeny, N. C., Zoellner, L. A., Fitzgibbons, L. A. & Foa, E. B. Exploring the roles of emotional numbing, depression and dissociation in PTSD. J. Trauma Stress 13, 489–498 (2000).

    Article  PubMed  Google Scholar 

  84. Roeckner, A. R., Oliver, K. I., Lebois, L. A. M., van Rooij, S. J. H. & Stevens, J. S. Neural contributors to trauma resilience: a review of longitudinal neuroimaging studies. Transl. Psychiatry 11, 508 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  85. Patel, R., Spreng, R. N., Shin, L. M. & Girard, T. A. Neurocircuitry models of posttraumatic stress disorder and beyond: a meta-analysis of functional neuroimaging studies. Neurosci. Biobehav. Rev. 36, 2130–2142 (2012).

    Article  PubMed  Google Scholar 

  86. Peng, L., Li, Z. R., Green, R. S., Holzman, I. R. & Lin, J. Butyrate enhances the intestinal barrier by facilitating tight junction assembly via activation of AMP-activated protein kinase in Caco-2 cell monolayers. J. Nutr. 139, 1619–1625 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  87. Lewis, K. et al. Enhanced translocation of bacteria across metabolically stressed epithelia is reduced by butyrate. Inflamm. Bowel Dis. 16, 1138–1148 (2010).

    Article  PubMed  Google Scholar 

  88. Maes, M., Kubera, M. & Leunis, J. C. The gut–brain barrier in major depression: intestinal mucosal dysfunction with an increased translocation of LPS from gram negative enterobacteria (leaky gut) plays a role in the inflammatory pathophysiology of depression. Neuro Endocrinol. Lett. 29, 117–124 (2008).

    PubMed  Google Scholar 

  89. Forsythe, P., Bienenstock, J. & Kunze, W. A. Vagal pathways for microbiome-brain-gut axis communication. Adv. Exp. Med. Biol. 817, 115–133 (2014).

    Article  PubMed  Google Scholar 

  90. Jacobs, J. P. et al. Cognitive behavioral therapy for irritable bowel syndrome induces bidirectional alterations in the brain–gut–microbiome axis associated with gastrointestinal symptom improvement. Microbiome 9, 236 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  91. Jacobs, J. P. et al. Multi-omics profiles of the intestinal microbiome in irritable bowel syndrome and its bowel habit subtypes. Microbiome 11, 5 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  92. Dong, T. S. et al. A distinct brain–gut–microbiome profile exists for females with obesity and food addiction. Obesity (Silver Spring) 28, 1477–1486 (2020).

    Article  PubMed  Google Scholar 

  93. Dong, T. S. et al. Obesity is associated with a distinct brain–gut microbiome signature that connects Prevotella and Bacteroides to the brain’s reward center. Gut Microbes 14, 2051999 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  94. Dong, T. S. et al. How discrimination gets under the skin: biological determinants of discrimination associated with dysregulation of the brain-gut microbiome system and psychological symptoms. Biol. Psychiatry 94, 203–214 (2023).

    Article  PubMed  Google Scholar 

  95. Sarnoff, R. P. et al. A multi-omic brain gut microbiome signature differs between IBS subjects with different bowel habits. Neuropharmacology 225, 109381 (2023).

    Article  PubMed  Google Scholar 

  96. Steinhardt, M. A., Mamerow, M. M., Brown, S. A. & Jolly, C. A. A resilience intervention in African American adults with type 2 diabetes: a pilot study of efficacy. Diabetes Educ. 35, 274–284 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  97. Bremner, J. D., Vermetten, E. & Mazure, C. M. Development and preliminary psychometric properties of an instrument for the measurement of childhood trauma: the Early Trauma Inventory. Depress. Anxiety 12, 1–12 (2000).

    Article  PubMed  Google Scholar 

  98. Felitti, V. J. et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. The Adverse Childhood Experiences (ACE) Study. Am. J. Prev. Med. 14, 245–258 (1998).

    Article  PubMed  Google Scholar 

  99. Rosenstiel, A. K. & Keefe, F. J. The use of co** strategies in chronic low back pain patients: relationship to patient characteristics and current adjustment. Pain 17, 33–44 (1983).

    Article  PubMed  Google Scholar 

  100. Cohen, S., Kamarck, T. & Mermelstein, R. A global measure of perceived stress. J. Health Soc. Behav. 24, 385–396 (1983).

    Article  PubMed  Google Scholar 

  101. Watson, D., Clark, L. A. & Tellegen, A. Development and validation of brief measures of positive and negative affect: the PANAS scales. J. Pers. Soc. Psychol. 54, 1063–1070 (1988).

    Article  PubMed  Google Scholar 

  102. Ware, J. Jr., Kosinski, M. & Keller, S. D. A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Med. Care 34, 220–233 (1996).

    Article  PubMed  Google Scholar 

  103. Craig, C. L., Brownson, R. C., Cragg, S. E. & Dunn, A. L. Exploring the effect of the environment on physical activity: a study examining walking to work. Am. J. Prev. Med. 23, 36–43 (2002).

    Article  PubMed  Google Scholar 

  104. Craig, J., Russell, C., Patterson, V. & Wootton, R. User satisfaction with realtime teleneurology. J. Telemed. Telecare 5, 237–241 (1999).

    Article  PubMed  Google Scholar 

  105. Carver, C. S. & White, T. L. Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: the BIS/BAS Scales. J. Pers. Soc. Psychol. 67, 319–333 (1994).

    Article  Google Scholar 

  106. Paradies, Y. A systematic review of empirical research on self-reported racism and health. Int. J. Epidemiol. 35, 888–901 (2006).

    Article  PubMed  Google Scholar 

  107. Williams, D. R., Yan, Y., Jackson, J. S. & Anderson, N. B. Racial differences in physical and mental health: socio-economic status, stress and discrimination. J. Health Psychol. 2, 335–351 (1997).

    Article  PubMed  Google Scholar 

  108. Carver, C. S. You want to measure co** but your protocol’s too long: consider the brief COPE. Int. J. Behav. Med. 4, 92–100 (1997).

    Article  PubMed  Google Scholar 

  109. Kroenke, K., Spitzer, R. L. & Williams, J. B. The PHQ-15: validity of a new measure for evaluating the severity of somatic symptoms. Psychosom. Med. 64, 258–266 (2002).

    Article  PubMed  Google Scholar 

  110. Carlson, L. E. & Brown, K. W. Validation of the Mindful Attention Awareness Scale in a cancer population. J. Psychosom. Res. 58, 29–33 (2005).

    Article  PubMed  Google Scholar 

  111. Buysse, D. J. et al. Development and validation of patient-reported outcome measures for sleep disturbance and sleep-related impairments. Sleep 33, 781–792 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  112. Labus, J. S. et al. The Visceral Sensitivity Index: development and validation of a gastrointestinal symptom-specific anxiety scale. Aliment. Pharmacol. Ther. 20, 89–97 (2004).

    Article  PubMed  Google Scholar 

  113. Pletikosic Toncic, S. & Tkalcic, M. A measure of suffering in relation to anxiety and quality of life in IBS patients: preliminary results. BioMed Res. Int. 2017, 2387681 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  114. Roelofs, J., Peters, M. L., McCracken, L. & Vlaeyen, J. W. S. The Pain Vigilance and Awareness Questionnaire (PVAQ): further psychometric evaluation in fibromyalgia and other chronic pain syndromes. Pain 101, 299–306 (2003).

    Article  PubMed  Google Scholar 

  115. Sullivan, M. J. L., Bishop, S. R. & Pivik, J. The Pain Catastrophizing Scale: development and validation. Psychol. Assess. 7, 524–532 (1995).

    Article  Google Scholar 

  116. Osman, A. et al. Factor structure, reliability and validity of the Pain Catastrophizing Scale. J. Behav. Med. 20, 589–605 (1997).

    Article  PubMed  Google Scholar 

  117. Costa, P. T. & McCrae, R. R. The five-factor model of personality and its relevance to personality disorders. J. Pers. Disord. 6, 343–359 (1992).

    Article  Google Scholar 

  118. Costa, P. T. & McCrae, R. R. Multiple uses for longitudinal personality data. Eur. J. Personality 6, 85–102 (2020).

    Article  Google Scholar 

  119. Dong, T. S. et al. Improvement in uncontrolled eating behavior after laparoscopic sleeve gastrectomy is associated with alterations in the brain-gut-microbiome axis in obese women. Nutrients 12, 2924 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  120. Osadchiy, V. et al. Analysis of brain networks and fecal metabolites reveals brain-gut alterations in premenopausal females with irritable bowel syndrome. Transl. Psychiatry 10, 367 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  121. Tong, M., Jacobs, J. P., McHardy, I. H. & Braun, J. Sampling of intestinal microbiota and targeted amplification of bacterial 16S rRNA genes for microbial ecologic analysis. Curr. Protoc. Immunol. 107, 7.41.1–7.41.11 (2014).

    Article  PubMed  Google Scholar 

  122. Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  123. Yilmaz, P. et al. The SILVA and ‘All-species Living Tree Project (LTP)’ taxonomic frameworks. Nucleic Acids Res. 42, D643–D648 (2014).

    Article  PubMed  Google Scholar 

  124. Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).

    Article  PubMed  Google Scholar 

  125. Glockner, F. O. et al. 25 years of serving the community with ribosomal RNA gene reference databases and tools. J. Biotechnol. 261, 169–176 (2017).

    Article  PubMed  Google Scholar 

  126. Evans, A. M., DeHaven, C. D., Barrett, T., Mitchell, M. & Milgram, E. Integrated, nontargeted ultrahigh performance liquid chromatography/electrospray ionization tandem mass spectrometry platform for the identification and relative quantification of the small-molecule complement of biological systems. Anal. Chem. 81, 6656–6667 (2009).

    Article  PubMed  Google Scholar 

  127. Hatch, A. et al. A robust metatranscriptomic technology for population-scale studies of diet, gut microbiome and human health. Int. J. Genomics 2019, 1718741 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  128. Li, J. et al. An integrated catalog of reference genes in the human gut microbiome. Nat. Biotechnol. 32, 834–841 (2014).

    Article  PubMed  Google Scholar 

  129. Chudler, E. H. & Dong, W. K. The role of the basal ganglia in nociception and pain. Pain 60, 3–38 (1995).

    Article  PubMed  Google Scholar 

  130. Fischl, B. FreeSurfer. Neuroimage 62, 774–781 (2012).

    Article  PubMed  Google Scholar 

  131. Destrieux, C., Fischl, B., Dale, A. & Halgren, E. Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature. Neuroimage 53, 1–15 (2010).

    Article  PubMed  Google Scholar 

  132. Edlow, B. L. et al. Neuroanatomic connectivity of the human ascending arousal system critical to consciousness and its disorders. J. Neuropathol. Exp. Neurol. 71, 531–546 (2012).

    Article  PubMed  Google Scholar 

  133. Bhatt, R. R. et al. Integrated multi-modal brain signatures predict sex-specific obesity status. Brain Commun. 5, fcad098 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  134. Guan, M. et al. Improved psychosocial measures associated with physical activity may be explained by alterations in brain–gut microbiome signatures. Sci. Rep. 13, 10332 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  135. Labus, J. S. et al. Sex-specific brain microstructural reorganization in irritable bowel syndrome. Pain 164, 292–304 (2023).

    Article  PubMed  Google Scholar 

  136. Nieto-Castanon, A. Handbook of Functional Connectivity Magnetic Resonance Imaging Methods in CONN (Hilbert Press, 2020).

  137. Ashburner, J. & Friston, K. J. Unified segmentation. Neuroimage 26, 839–851 (2005).

    Article  PubMed  Google Scholar 

  138. Behzadi, Y., Restom, K., Liau, J. & Liu, T. T. A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage 37, 90–101 (2007).

    Article  PubMed  Google Scholar 

  139. Friston, K. J., Williams, S., Howard, R., Frackowiak, R. S. & Turner, R. Movement-related effects in fMRI time-series. Magn. Reson. Med. 35, 346–355 (1996).

    Article  PubMed  Google Scholar 

  140. Power, J. D. et al. Methods to detect, characterize and remove motion artifact in resting state fMRI. Neuroimage 84, 320–341 (2014).

    Article  PubMed  Google Scholar 

  141. Whitfield-Gabrieli, S. & Nieto-Castanon, A. Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connect. 2, 125–141 (2012).

    Article  PubMed  Google Scholar 

  142. Hallquist, M. N., Hwang, K. & Luna, B. The nuisance of nuisance regression: spectral misspecification in a common approach to resting-state fMRI preprocessing reintroduces noise and obscures functional connectivity. Neuroimage 82, 208–225 (2013).

    Article  PubMed  Google Scholar 

  143. Andersson, J. L. R. & Sotiropoulos, S. N. An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage 125, 1063–1078 (2016).

    Article  PubMed  Google Scholar 

  144. Cook, P. A. et al. Camino: open-source diffusion-MRI reconstruction and processing. Proc. Intl. Soc. Magn. Reson. Med. 14, 2759 (2006).

    Google Scholar 

  145. Sarwar, T., Ramamohanarao, K. & Zalesky, A. Map** connectomes with diffusion MRI: deterministic or probabilistic tractography? Magn. Reson. Med. 81, 1368–1384 (2019).

    Article  PubMed  Google Scholar 

  146. Singh, A. et al. DIABLO: an integrative approach for identifying key molecular drivers from multi-omics assays. Bioinformatics 35, 3055–3062 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  147. Tenenhaus, A. et al. Variable selection for generalized canonical correlation analysis. Biostatistics 15, 569–583 (2014).

    Article  PubMed  Google Scholar 

  148. Desikan, R. S. et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31, 968–980 (2006).

    Article  PubMed  Google Scholar 

  149. Frazier, J. A. et al. Structural brain magnetic resonance imaging of limbic and thalamic volumes in pediatric bipolar disorder. Am. J. Psychiatry 162, 1256–1265 (2005).

    Article  PubMed  Google Scholar 

  150. Goldstein, J. M. et al. Hypothalamic abnormalities in schizophrenia: sex effects and genetic vulnerability. Biol. Psychiatry 61, 935–945 (2007).

    Article  PubMed  Google Scholar 

  151. Makris, N. et al. Decreased volume of left and total anterior insular lobule in schizophrenia. Schizophr. Res. 83, 155–171 (2006).

    Article  PubMed  Google Scholar 

  152. Backhausen, L. L., Herting, M. M., Tamnes, C. K. & Vetter, N. C. Best practices in structural neuroimaging of neurodevelopmental disorders. Neuropsychol. Rev. 32, 400–418 (2022).

    Article  PubMed  Google Scholar 

  153. Barnes, J. et al. Head size, age and gender adjustment in MRI studies: a necessary nuisance? Neuroimage 53, 1244–1255 (2010).

    Article  PubMed  Google Scholar 

  154. Voevodskaya, O. et al. The effects of intracranial volume adjustment approaches on multiple regional MRI volumes in healthy aging and Alzheimer’s disease. Front. Aging Neurosci. 6, 264 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  155. Farber, O. & Kadmon, R. Assessment of alternative approaches for bioclimatic modeling with special emphasis on the Mahalanobis distance. Ecol. Model. 160, 115–130 (2003).

    Article  Google Scholar 

  156. Weisberg, S. Applied Linear Regression 4th edn (Wiley, 2013).

Download references

Acknowledgements

This research was supported by grants from the National Institutes of Health, including R01 MD015904 (A.G.), K23 DK106528 (A.G.), R03 DK121025 (A.G.), the ULTR001881/DK041301 UCLA CURE/CTSI Pilot and Feasibility Study (A.G.), and pilot funds provided for brain scanning by the Ahmanson-Lovelace Brain Map** Center. These funders played no role in study design or the collection, analysis and interpretation of data. We acknowledge the analytical and data curation efforts provided by the Neuroimaging Core, the Integrative Biostatistics and Bioinformatics Core and the Database and Clinical Core of the Goodman-Luskin Microbiome Center at UCLA. Figure 1 was created with BioRender.com.

Author information

Author notes

  1. These authors contributed equally: Eric An, Desiree R. Delgadillo.

  2. These authors jointly supervised this work: Tien S. Dong, Arpana Gupta.

Authors and Affiliations

  1. David Geffen School of Medicine, UCLA, Los Angeles, CA, USA

    Eric An, Desiree R. Delgadillo, Jennifer Yang, Jennifer S. Labus, Lisa A. Kilpatrick, Priten Vora, Allison Vaughan, Tien S. Dong & Arpana Gupta

  2. University of California, Los Angeles, CA, USA

    Eric An, Desiree R. Delgadillo, Jennifer Yang, Rishabh Agarwal, Jennifer S. Labus, Shrey Pawar, Madelaine Leitman, Lisa A. Kilpatrick, Priten Vora, Allison Vaughan, Tien S. Dong & Arpana Gupta

  3. G. Oppenheimer Center for Neurobiology of Stress & Resilience, UCLA, Los Angeles, CA, USA

    Desiree R. Delgadillo, Jennifer Yang, Rishabh Agarwal, Jennifer S. Labus, Shrey Pawar, Madelaine Leitman, Lisa A. Kilpatrick, Priten Vora, Allison Vaughan, Tien S. Dong & Arpana Gupta

  4. Vatche and Tamar Manoukian Division of Digestive Diseases, UCLA, Los Angeles, CA, USA

    Desiree R. Delgadillo, Jennifer Yang, Jennifer S. Labus, Lisa A. Kilpatrick, Priten Vora, Allison Vaughan, Tien S. Dong & Arpana Gupta

  5. Goodman Luskin Microbiome Center, UCLA, Los Angeles, CA, USA

    Desiree R. Delgadillo, Jennifer S. Labus, Tien S. Dong & Arpana Gupta

  6. Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Marina del Rey, CA, USA

    Ravi R. Bhatt

Authors
  1. Eric An
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Desiree R. Delgadillo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jennifer Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rishabh Agarwal
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jennifer S. Labus
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Shrey Pawar
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Madelaine Leitman
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Lisa A. Kilpatrick
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ravi R. Bhatt
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Priten Vora
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Allison Vaughan
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Tien S. Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Arpana Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

E.A. and D.R.D. carried out statistical analysis, drafting of the manuscript and critical revision of the manuscript for important intellectual content. J.Y., R.A., S.P., M.L. and P.V. carried out statistical analysis, data interpretation and visualization. J.S.L. interpreted data. A.V. collected data. L.A.K. and R.R.B. interpreted data and performed critical revision of the manuscript for important intellectual content. A.G. and T.S.D. acquired funding, provided the study concept and design, performed statistical analysis and interpretation of data as well as critical revision of the manuscript for important intellectual content, and provided technical support and study supervision.

Corresponding authors

Correspondence to Tien S. Dong or Arpana Gupta.

Ethics declarations

Competing interests

A.G. is a scientific advisor to Yamaha on studies related to aging and currently has a stress study being funded by them. However, Yamaha had no input or involvement in the current study. The other authors declare no competing interests.

Peer review

Peer review information

Nature Mental Health thanks Kenji Hashimoto, Quentin Leyrolle and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Table 1 and Figs. 1–4.

Reporting Summary

Supplementary Data 1

Statistical source data for Supplementary Table 1.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

An, E., Delgadillo, D.R., Yang, J. et al. Stress-resilience impacts psychological wellbeing as evidenced by brain–gut microbiome interactions. Nat. Mental Health (2024). https://doi.org/10.1038/s44220-024-00266-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s44220-024-00266-6

  • Springer Nature America, Inc.

Search

Navigation