Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Nutrition in acute and chronic diseases

Food groups associated with immune-mediated inflammatory diseases: a Mendelian randomization and disease severity study



Immune-mediated inflammatory diseases (IMIDs) are prevalent diseases. There is, however, a lack of understanding of the link between diet and IMIDs, how much dietary patterns vary between them and if there are food groups associated with a worsening of the disease.


To answer these questions we analyzed a nation-wide cohort of n = 11,308 patients from six prevalent IMIDs and 2050 healthy controls. We compared their weekly intake of the major food categories, and used a Mendelian randomization approach to determine which dietary changes are caused by disease. Within each IMID, we analyzed the association between food frequency and disease severity.


After quality control, n = 11,230 recruited individuals were used in this study. We found that diet is profoundly altered in all IMIDs: at least three food categories are significantly altered in each disease (P < 0.05). Inflammatory bowel diseases showed the largest differences compared to controls (n ≥ 8 categories, P < 0.05). Mendelian randomization analysis supported that some of these dietary changes, like vegetable reduction in Crohn’s Disease (P = 2.5 × 10−10, OR(95% CI) = 0.73(0.65, 0.80)), are caused by the disease. Except for Psoriatic Arthritis and Systemic Lupus Erythematosus, we have found ≥2 food groups significantly associated with disease severity in the other IMIDs (P < 0.05).


This cross-disease study demonstrates that prevalent IMIDs are associated to a significant change in the normal dietary patterns. This variation is highly disease-specific and, in some cases, it is caused by the disease itself. Severity in IMIDs is also associated with specific food groups. The results of this study underscore the importance of studying diet in IMIDs.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.


  1. 1.

    Bayry J, Radstake TR. Immune-mediated inflammatory diseases: progress in molecular pathogenesis and therapeutic strategies. Expert Rev Clin Immunol. 2013;9:297–299.

    CAS  Article  Google Scholar 

  2. 2.

    Davidson A, Diamond B. Autoimmune diseases. N. Engl J Med. 2001;345:340–50.

    CAS  Article  Google Scholar 

  3. 3.

    Gutierrez-Arcelus M, Rich SS, Raychaudhuri S. Autoimmune diseases: connecting risk alleles with molecular traits of the immune system. Nat Rev Genet. 2016;17:160–74.

    Article  Google Scholar 

  4. 4.

    Ellinghaus D, Jostins L, Spain SL, Cortes A, Bethune J, Han B, et al. Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci. Nat Genet. 2016;48:510.

    CAS  Article  Google Scholar 

  5. 5.

    Thorburn AN, Macia L, Mackay CR. Diet, metabolites, and “western-lifestyle” inflammatory diseases. Immunity. 2014;40:833–42.

    CAS  Article  Google Scholar 

  6. 6.

    Kleinewietfeld M, Manzel A, Titze J, Kvakan H, Yosef N, Linker RA, et al. Sodium chloride drives autoimmune disease by the induction of pathogenic T H 17 cells. Nature. 2013;496:518–22.

    CAS  Article  Google Scholar 

  7. 7.

    Maslowski KM, Mackay CR. Diet, gut microbiota and immune responses. Nat Immunol. 2011;12:5–9.

    CAS  Article  Google Scholar 

  8. 8.

    Marino E, Richards JL, McLeod KH, Stanley D, Yap YA, Knight J, et al. Gut microbial metabolites limit the frequency of autoimmune T cells and protect against type 1 diabetes. Nat Immunol. 2017;18:552.

    CAS  Article  Google Scholar 

  9. 9.

    Davey Smith G, Ebrahim S. ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003;32:1–22.

    Article  Google Scholar 

  10. 10.

    Haycock PC, Burgess S, Wade KH, Bowden J, Relton C, Davey Smith G. Best (but oft-forgotten) practices: the design, analysis, and interpretation of Mendelian randomization studies. Am J Clin Nutr. 2016;103:965–78.

    CAS  Article  Google Scholar 

  11. 11.

    Maxwell JR, Gowers IR, Moore DJ, Wilson AG. Alcohol consumption is inversely associated with risk and severity of rheumatoid arthritis. Rheumatology. 2010;49:2140–2146.

    CAS  Article  Google Scholar 

  12. 12.

    Limdi JK, Aggarwal D, McLaughlin JT. Dietary practices and beliefs in patients with inflammatory bowel disease. Inflamm Bowel Dis 2016;22:164–70.

    Article  Google Scholar 

  13. 13.

    Hardy CJ, Palmer BP, Muir KR, Sutton AJ, Powell RJ. Smoking history, alcohol consumption, and systemic lupus erythematosus: a case-control study. Ann Rheum Dis 1998;57:451–455.

    CAS  Article  Google Scholar 

  14. 14.

    Azizov V, Dietel K, Steffen F, Dürholz K, Meidenbauer J, Lucas S, et al. Ethanol consumption inhibits T FH cell responses and the development of autoimmune arthritis. Nat Commun. 2020;11:1–14.

    Article  Google Scholar 

  15. 15.

    Kirwan J, REEBACK JS. Stanford Health Assessment Questionnaire modified to assess disability in British patients with rheumatoid arthritis. Rheumatology. 1986;25:206–209.

    CAS  Article  Google Scholar 

  16. 16.

    MedlinePlus. Crohn Disease, (2020).

  17. 17.

    Brown AC, Rampertab SD, Mullin GE. Existing dietary guidelines for Crohn’s disease and ulcerative colitis. Expert Rev Gastroenterol Hepatol. 2011;5:411–25.

    Article  Google Scholar 

  18. 18.

    De Vries J, Birkett A, Hulshof T, Verbeke K, Gibes K. Effects of cereal, fruit and vegetable fibers on human fecal weight and transit time: a comprehensive review of intervention trials. Nutrients. 2016;8:130.

    Article  Google Scholar 

  19. 19.

    Tragnone A, Valpiani D, Miglio F, Elmi G, Bazzocchi G, Pipitone E, et al. Dietary habits as risk factors for inflammatory bowel disease. Eur J Gastroenterol Hepatol. 1995;7:47–51.

    CAS  PubMed  Google Scholar 

  20. 20.

    Kang S, Denman SE, Morrison M, Yu Z, Dore J, Leclerc M, et al. Dysbiosis of fecal microbiota in Crohn’s disease patients as revealed by a custom phylogenetic microarray. Inflamm Bowel Dis. 2010;16:2034–42.

    Article  Google Scholar 

  21. 21.

    Kolchak NA, Tetarnikova MK, Theodoropoulou MS, Michalopoulou AP, Theodoropoulos DS. Prevalence of antigliadin IgA antibodies in psoriasis vulgaris and response of seropositive patients to a gluten-free diet. J Multidiscip Healthc. 2018;11:13.

    Article  Google Scholar 

  22. 22.

    Nagui N, El Nabarawy E, Mahgoub D, Mashaly H, Saad N, El‐Deeb D. Estimation of (IgA) anti‐gliadin, anti‐endomysium and tissue transglutaminase in the serum of patients with psoriasis. Clin Exp Dermatol: Exp Dermatol. 2011;36:302–304.

    CAS  Article  Google Scholar 

  23. 23.

    Ludvigsson JF, Card TR, Kaukinen K, Bai J, Zingone F, Sanders DS, et al. Screening for celiac disease in the general population and in high-risk groups. U Eur Gastroenterol J. 2015;3:106–20.

    Article  Google Scholar 

  24. 24.

    Lundin KE, Wijmenga C. Coeliac disease and autoimmune disease—genetic overlap and screening. Nat Rev Gastroenterol Hepatol. 2015;12:507.

    CAS  Article  Google Scholar 

  25. 25.

    Reano A, Faure M, Jacques Y, Reichert U, Schaefer H, Thivolet J. Lectins as markers of human epidermal cell differentiation. Differentiation. 1982;22:205–10.

    CAS  Article  Google Scholar 

  26. 26.

    Schuler G, Romani N, Linert J, Shevach EM, Stingl G. Subsets of epidermal Langerhans cells as defined by lectin binding profiles. J Invest Dermatol. 1983;81:397–402.

    CAS  Article  Google Scholar 

  27. 27.

    Freed DL. Lectins in food: their importance in health and disease. J Nutritional Med. 1991;2:45–64.

    Article  Google Scholar 

  28. 28.

    Neuhouser ML. Red and processed meat: more with less? Am J Clin Nutr. 2020;111:252–255.

    Article  Google Scholar 

  29. 29.

    Prentice RL, Huang Y. Nutritional epidemiology methods and related statistical challenges and opportunities. Stat theory Relat Fields. 2018;2:2–10.

    Article  Google Scholar 

  30. 30.

    Alonso A, Julià A, Vinaixa M, Domènech E, Fernández-Nebro A, Cañete JD, et al. Urine metabolome profiling of immune-mediated inflammatory diseases. BMC Med. 2016;14:133.

    Article  Google Scholar 

  31. 31.

    Prevoo M, Van’t Hof M, Kuper H, Van Leeuwen M, Van de Putte L, Van Riel P. Modified disease activity scores that include twenty‐eight‐joint counts development and validation in a prospective longitudinal study of patients with rheumatoid arthritis. Arthritis Rheum. 1995;38:44–48.

    CAS  Article  Google Scholar 

  32. 32.

    Mattei P, Corey K, Kimball A. Psoriasis Area Severity Index (PASI) and the Dermatology Life Quality Index (DLQI): the correlation between disease severity and psychological burden in patients treated with biological therapies. J Eur Acad Dermatol Venereol. 2014;28:333–337.

    CAS  Article  Google Scholar 

  33. 33.

    Hay E, Bacon P, Gordon C, Isenberg D, Maddison P, Snaith M, et al. The BILAG index: a reliable and valid instrument for measuring clinical disease activity in systemic lupus erythematosus. QJM: Int J Med. 1993;86:447–58.

    CAS  Google Scholar 

  34. 34.

    Harvey R, Bradshaw J. A simple index of Crohn’s-disease activity. Lancet. 1980;315:514.

    Article  Google Scholar 

  35. 35.

    Lichtiger S, Present DH, Kornbluth A, Gelernt I, Bauer J, Galler G, et al. Cyclosporine in severe ulcerative colitis refractory to steroid therapy. N Engl J Med. 1994;330:1841–1845.

    CAS  Article  Google Scholar 

  36. 36.

    Hutchinson D, Shepstone L, Moots R, Lear J, Lynch M. Heavy cigarette smoking is strongly associated with rheumatoid arthritis (RA), particularly in patients without a family history of RA. Ann Rheum Dis. 2001;60:223–227.

    CAS  Article  Google Scholar 

  37. 37.

    Organization WH. The use and interpretation of anthropometry: report of a WHO expert committee. World Health Organ Tech Rep. Ser. 1995;854:312–409.

    Google Scholar 

  38. 38.

    R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.

  39. 39.

    Torkamani A, Wineinger NE, Topol EJ. The personal and clinical utility of polygenic risk scores. Nat Rev Genet. 2018;19:581.

    CAS  Article  Google Scholar 

  40. 40.

    Burgess S, Small DS, Thompson SG. A review of instrumental variable estimators for Mendelian randomization. Stat Methods Med Res. 2017;26:2333–55.

    Article  Google Scholar 

  41. 41.

    Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38:904–909.

    CAS  Article  Google Scholar 

Download references


The IMID Consortium includes the following: Eduardo Fonseca, Jesús Rodríguez, Patricia Carreira, Valle García, José A. Pinto-Tasende, Lluís Puig, Elena Ricart, Francisco Blanco, Jordi Gratacós, Ricardo Blanco, Víctor Martínez Taboada, Emilia Fernández, Isidoro González, Fernando Gomollón García, Raimon Sanmartí, Ana Gutiérrez, Àlex Olivé, José Luís López Estebaranz, Esther García-Planella, Juan Carlos Torre-Alonso, José Luis Andreu, David Moreno Ramírez, Benjamín Fernández, Mª Ángeles Aguirre Zamorano, Pablo de la Cueva, Pilar Nos Mateu, Paloma Vela, Francisco Vanaclocha, Héctor Corominas, Santiago Muñoz, Joan Miquel Nolla, Enrique Herrera, Carlos González, José Luis Marenco de la Fuente, Maribel Vera, Alba Erra, Daniel Roig, Antonio Zea, María Esteve, Carlos Tomás, Pedro Zarco, José María Pego, Cristina Saro, Antonio González, Mercedes Freire, Alicia García, Elvira Díez, Georgina Salvador, César Díaz-Torne, Simón Sánchez, Alfredo Willisch Domínguez, José Antonio Mosquera, Julio Ramírez, Esther Rodríguez Almaraz, Núria Palau, Raül Tortosa, Mireia López, Andrea Pluma, Adrià Aterido. We would like to thank Dr Eduard Cabré for stimulating discussions.

IMID Consortium

Eduardo Fonseca17, Jesús Rodríguez18, Patricia Carreira19, Valle García20, José A. Pinto-Tasende21, Lluís Puig22, Elena Ricart23, Francisco Blanco24, Jordi Gratacós25, Ricardo Blanco26, Víctor Martínez Taboada26, Emilia Fernández27, Pablo Unamuno27, Isidoro González28, Fernando Gomollón García29, Raimon Sanmartí30, Ana Gutiérrez31, Àlex Olivé32, José Luís López Estebaranz33, Esther García-Planella34, Juan Carlos Torre-Alonso35, José Luis Andreu36, David Moreno Ramírez37, Benjamín Fernández38, Mª Ángeles Aguirre Zamorano39, Pablo de la Cueva40, Pilar Nos Mateu41, Paloma Vela42, Francisco Vanaclocha43, Héctor Coromines44, Santiago Muñoz45, Joan Miquel Nolla46, Enrique Herrera47, Carlos González48, José Luis Marenco de la Fuente49, Maribel Vera50, Alba Erra51, Daniel Roig52, Antonio Zea53, María Esteve Comas54, Carles Tomàs55, Pedro Zarco56, José María Pego57, Cristina Saro58, Antonio González59, Mercedes Freire60, Alicia García61, Elvira Díez62, Georgina Salvador63, César Díaz64, Simón Sánchez65, Alfredo Willisch Dominguez66, José Antonio Mosquera67, Julio Ramírez68, Esther Rodríguez Almaraz69, Núria Palau51, Raül Tortosa51, Mireia López51, Andrea Pluma51, Adrià Aterido51


This work was supported by the Spanish Ministry of Economy and Competitiveness grants (IPT-010000-2010-36, PSE-010000-2006-6, and PI12/01362).

Author information





AJ designed the study, conceived, designed and analyzed data and wrote the manuscript; SH performed data curation and statistical analysis; ED, JDC, CF, JT, JPG, AFN, ED, MBA, CP, RQ, FJLL, JLSC, JLM, MA, CM, JJPV, FM, SC and MLL contributed to patient recruitment, clinical data collection and analysis and manuscript revision; AA contributed to genetic data analysis; SM designed the study, coordinated clinical data collection and analysis, and co-wrote the manuscript.

Corresponding authors

Correspondence to Antonio Julià or Sara Marsal.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

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

Members of the IMID Consortium are listed below Acknowledgements.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Julià, A., Martínez-Mateu, S.H., Domènech, E. et al. Food groups associated with immune-mediated inflammatory diseases: a Mendelian randomization and disease severity study. Eur J Clin Nutr (2021).

Download citation


Quick links