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Body mass, neuro-hormonal stress processing, and disease activity in lean to obese people with multiple sclerosis

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Abstract

Overweight and obesity can worsen disease activity in multiple sclerosis (MS). Although psychobiological stress processing is increasingly recognized as important obesity factor that is tightly connected to proinflammatory metabolic hormones and cytokines, its role for MS obesity remains unexplored. Consequently, we investigated the interplay between body mass index (BMI), neural stress processing (functional connectivity, FC), and immuno-hormonal stress parameters (salivary cortisol and T cell glucocorticoid [GC] sensitivity) in 57 people with MS (six obese, 19 over-, 28 normal-, and four underweight; 37 females, 46.4 ± 10.6 years) using an Arterial-Spin-Labeling MRI task comprising a rest and stress stage, along with quantitative PCR. Our findings revealed significant positive connections between BMI and MS disease activity (i.e., higher BMI was accompanied by higher relapse rate). BMI was positively linked to right supramarginal gyrus and anterior insula FC during rest and negatively to right superior parietal lobule and cerebellum FC during stress. BMI showed associations with GC functioning, with higher BMI associated with lower CD8+ FKBP4 expression and higher CD8+ FKBP5 expression on T cells. Finally, the expression of CD8+ FKBP4 positively correlated with the FC of right supramarginal gyrus and left superior parietal lobule during rest. Overall, our study provides evidence that body mass is tied to neuro-hormonal stress processing in people with MS. The observed pattern of associations between BMI, neural networks, and GC functioning suggests partial overlap between neuro-hormonal and neural-body mass networks. Ultimately, the study underscores the clinical importance of understanding multi-system crosstalk in MS obesity.

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Data availability

Access to the data will be granted by the corresponding author on request depending on the approval by the ethics committee and under a formal Data Sharing Agreement.

References

  1. Gianfrancesco MA, Barcellos LF (2016) Obesity and multiple sclerosis susceptibility: a review. Neurol Neuromedicine 1(7):1–5

    Article  Google Scholar 

  2. Bassi MS, Iezzi E, Buttari F, Gilio L, Simonelli I, Carbone F, et al. (2019) Obesity worsens central inflammation and disability in multiple sclerosis. Multiple Sclerosis Journal.

  3. Escobar JM, Cortese M, Edan G, Freedman MS, Hartung H-P, Montalban X, Sandbrink R, Radü E-W, Barkhof F, Wicklein E-M, Kappos L, Ascherio A, Munger KL (2022) Body mass index as a predictior of MS activity and progression among participants in BENEFIT. Mult Scler 28(8):1277–1285

    Article  PubMed Central  Google Scholar 

  4. Vreeken D, Seidel F, de La Roij G, Vening W, den Hengst WA, Verschuren L, Özsezen S, Kessels RPC, Duering M, Mutsaerts HJMM, Kleemann R, Wiesmann M, Hazebroek EJ, Kiliaan AJ (2023) Impact of white adipose tissue on brain structure, perfusion, and cognitive function in patients with severe obesity: the BARICO study. Neurology 100(7):e703–e718

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Schreiner TG, Genes TM (2021) Obesity and multiple sclerosis—A multifaceted association. J Clin Med 10:2689

    Article  PubMed  PubMed Central  Google Scholar 

  6. Guerrero-Garcia JJ, Carrera-Quintanar L, Lopez-Roa RI, Marquez-Aguirre AL, Rojas-Mayorquin AE, Ortuno-Sahagun D (2016) Multiple sclerosis and obesity: possible roles of adipokines. Mediators Inflamm 2016:4036232

    Article  PubMed  PubMed Central  Google Scholar 

  7. Marrodan M, Farez MF, Balbuena Aguirre ME, Correale J (2021) Obesity and the risk of multiple sclerosis. the role of Leptin. Ann Clin Transl Neurol 8:406–424

    Article  CAS  PubMed  Google Scholar 

  8. Matarese G, Biagio Carrieri P, La Cava A, Perna F, Sanna V, De Rosa V (2005) Leptin increase in multiple sclerosis associates with reduced number of CD4(+)CD25+ regulatory T cells. Proc Natl Acad Sci USA 102:5150–5155

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Fahmi RM, Kamel AE, Elsayed DA, Zidan AA, Sarhan NT (2021) Serum levels of leptin and adiponectin in patients with multiple sclerosis. Egypt J Neurol Psychiatry Neurosurg 57:114

    Article  Google Scholar 

  10. Asghar A, Sheikh N (2017) Role of immune cells in obesity induced low grade inflammation and insulin resistance. Cell Immunol 315:18–26

    Article  CAS  PubMed  Google Scholar 

  11. Balasa R, Maier S, Barcutean L, Stoian A, Motataianu A. (2020) The direct deleterious effect of Th17 cells in the nervous system compartment in multiple sclerosis and experimental autoimmune encephalomyelitis: one possible link between neuroinflammation and neurodegeneration. Rev Romana Med Laborator, 28.

  12. Volkow ND, Wise RA, Baler R (2017) The dopamine motive system: implications for drug and food addiction. Nat Rev Neurosci 18(12):741–752

    Article  CAS  PubMed  Google Scholar 

  13. Kozarzewski K, Maurer MA, Spranger J, Weygandt M (2022) Computational approaches to predicting treatment response to obesity using neuroimaging. Rev Endocrine Metabolic Disord 23:773–805

    Article  Google Scholar 

  14. Egecioglu E, Skibicka KP, Hansson C, Alvarez-Crespo M, Friberg PA, Jerlhag E, Engel JA, Dickson SL (2011) Hedonic and incentive signals for body weight control. Rev Endocr Metab Disord 12(3):141–151

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Robbins TW, Ersche KD, Everitt BJ (2008) Drug addiction and the memory systems of the brain. Ann N Y Acad Sci 1141:1–21. https://doi.org/10.1196/annals.1441.020

    Article  CAS  PubMed  Google Scholar 

  16. Weygandt M, Spranger J, Leupelt V, Maurer L, Bobbert T, Mai K (2019) Interactions between neural decision-making circuits predict long-term dietary treatment success in obesity. Neuroimage 84:520–534

    Article  Google Scholar 

  17. Rangel A (2013) Regulation of dietary choice by the decision-making circuitry. Nat Neurosci 16:1717–1724

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Van der Valk ES, Savas M, van Rossum EFC (2018) Stress and obesity: are there more susceptible individuals? Curr Obes Rep 7:193–203

    Article  PubMed  PubMed Central  Google Scholar 

  19. Maier SU, Makwana AB, Hare TA (2015) Acute stress impairs self-control in goal-directed choice by altering multiple functional connections within the brain’s decision circuits. Neuron 87:621–631

    Article  CAS  PubMed  Google Scholar 

  20. Guerrero-Hreins E, Goldstone AP, Brown RM, Sumithran P (2021) The therapeutic potential of GLP-1 analogues for stress-related eating and role of GLP-1 in stress, emotion and mood: a review. Prog Neuropsychopharmacol Biol Psychiatry 110:110303

    Article  CAS  PubMed  Google Scholar 

  21. Block JP, He Y, Zaslavsky AM, Ding L, Ayanian JZ (2009) Psychosocial stress and change in weight among US adults. Am J Epidemiol 170:181–192

    Article  PubMed  PubMed Central  Google Scholar 

  22. Thom G, Dombrowski SU, Brosnahan N, Algindan YY (2020) The role of appetite-related hormones, adaptive thermogenesis, perceived hunger and stress in long-term weight-loss maintenance: a mixed-methods study. Eur J Clin Nutr 74(4):622–632

    Article  CAS  PubMed  Google Scholar 

  23. Wester VL, Staufenbiel SM, Veldhorst MAB, Visser JA, Manenschijn L, Koper JW (2014) Long-term cortisol levels measured in scalp hair of obese patients. Obesity (Silver Spring) 22(9):1956–1958

    Article  CAS  PubMed  Google Scholar 

  24. Rosmond R, Chagnon YC, Holm G, Chagnon M, Perusse L, Lindell K et al (2000) A glucocorticoid receptor gene marker is associated with abdominal obesity, leptin, and dysregulation of the hypothalamic- pituitary-adrenal axis. Obes Res 8:211–218

    Article  CAS  PubMed  Google Scholar 

  25. Menke A, Kloiber S, Best J, Rex-Haffner M, Uhr M, Holsboer F, Binder EB (2013) GR-mediated FKBP5 RNA induction differentially influenced by weight in major depression and healthy controls. Pharmacopsychiatry. https://doi.org/10.1055/s-0033-1353276

    Article  Google Scholar 

  26. Maes M, Song C, Lin A, De Jongh R, Van Gastel A, Kenis G, Bosmans E, De Meester I, Benoy I, Neels H, Demedts P, Janca A, Scharpé S, Smith RS (1998) The effects of psychological stress on humans: increased production of pro-inflammatory cytokines and a Th1-like response in stress-induced anxiety. Cytokine 10(4):313–318

    Article  CAS  PubMed  Google Scholar 

  27. Bouillon-Minois J-B, Trousselard M, Thivel D, Benson AC, Schmidt J, Moustafa F, Bouvier D, Dutheil F (2021) Leptin as a biomarker of stress: a systematic review and meta-analysis. Nutrients 13(10):3350

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Ambrée O, Ruland C, Zwanzger P, Klotz L, Baune BT, Arolt V, Scheu S, Alferink J (2019) Social defeat modulates T helper cell percentages in stress susceptible and resilient mice. Int J Mol Sci 20(14):3512

    Article  PubMed  PubMed Central  Google Scholar 

  29. Brasanac J, Hetzer S, Asseyer S, Kuchling J, Bellmann-Strobl J, Ritter K, Gamradt S, Scheel M, Haynes JD, Brandt AU, Paul F, Gold SM, Weygandt M. (2022) Central stress processing, T cell responsivity to stress hormones, and disease severity in multiple sclerosis. Brain Commun 4: fcac086.

  30. Wang J, Rao H, Wetmore GS, Furlan PM, Korczykowski M, Dinges DF, Detre JA (2005) Perfusion functional MRI reveals cerebral blood flow pattern under psychological stress. Proc Natl Acad Sci U S A 102:17804–17809

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Meyer-Arndt L, Schmitz-Hübsch T, Bellmann-Strobl J, Brandt AU, Haynes JD, Gold SM, Paul F, Weygandt M (2021) Neural processes of psychological stress and relaxation predict the future evolution of quality of life in multiple sclerosis. Front Neurol 12:753107

    Article  PubMed  PubMed Central  Google Scholar 

  32. Meyer-Arndt L, Hetzer S, Asseyer S, Bellmann-Strobl J, Scheel M, Stellmann J-P, Heesen C, Engel AK, Brandt AU, Haynes J-D, Paul F, Gold SM, Weygandt M (2020) Blunted neural and psychological stress processing predicts future grey matter atrophy in multiple sclerosis. Neurobiol Stress 13:100244

    Article  PubMed  PubMed Central  Google Scholar 

  33. Weygandt M, Meyer-Arndt L, Behrens J, Wakonig K, Bellmann-Strobl J, Ritter K, Scheel M, Brandt AU, Labadie C, Hetzer S, Gold SM, Paul F, Haynes JD (2016) Stress-induced brain activity, brain atrophy, and clinical disability in multiple sclerosis. Proc Natl Acad Sci U S A 113:13444–13449

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Wang JJ, Korczykowski M, Rao H, Fan Y, Pluta J, Gur RC, McEwen BS, Detre JA (2007) Gender difference in neural response to psychological stress. Soc Cogn Aff Neurosci 2:227–239

    Article  Google Scholar 

  35. Schulz MA, Hetzer S, Eitel F, Asseyer S, Meyer-Arndt L, Schmitz-Hübsch T, Bellmann-Strobl J, Cole JH, Gold SM, Paul F, Ritter K, Weygandt M (2023) Similar neural pathways link psychological stress and brain-age in health and multiple sclerosis. iScience. https://doi.org/10.1016/j.isci.2023.107679

    Article  PubMed  PubMed Central  Google Scholar 

  36. Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M (2011) Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol 69(2):292–302

    Article  PubMed  PubMed Central  Google Scholar 

  37. Sheehan DV, Lecrubier C, Sheehan KH, Amorim P, Janavs J, Weiller E, Hergueta T, Baker R, Dunbar GC (1998) Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry 59(20):22–30

    PubMed  Google Scholar 

  38. Kurtzke JF (1983) Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS). Neurology 33:1444–1452

    Article  CAS  PubMed  Google Scholar 

  39. Hautzinger M, Keller F and Kuhner C. (2009) BDI-II: Beck-depressions-inventar (Revision. 2nd Edition). Frankfurt: pearson assessment.

  40. Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J (1961) An inventory for measuring depression. Arch Gen Psychiatry 4:561–571

    Article  CAS  PubMed  Google Scholar 

  41. Wahl I, Löwe B, Bjorner JB, Fischer F, Langs G, Voderholzerg U, (2014) Standardization of depression measurement: a common metric was developed for 11 self-report depression measures. J Clin Epidemiol 67, 73e86.

  42. Weygandt M, Wakonig K, Behrens J, Meyer-Arndt L, Söder E, Brandt AU, Bellmann-Strobl J, Ruprecht R, Gold SM, Haynes J-D, Paul F (2018) Brain activity, regional grey matter loss, and decision-making in Multiple Sclerosis. Mult Scler 24:1163–1173

    Article  PubMed  Google Scholar 

  43. Zannas AS, Wiechmann T, Gassen NC, Binder EB (2016) Gene-Stress-Epigenetic regulation of FKBP5: clinical and translational implications. Neuropsychopharmacology 41:261–274

    Article  CAS  PubMed  Google Scholar 

  44. Cannarile L, Delfino DV, Adorisio S, Riccardi C, Ayroldi E (2019) Implicating the role of GILZ in glucocorticoid modulation of T-cell activation. Front Immunol 10:1823

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N (2002) Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15(1):273–289

    Article  CAS  PubMed  Google Scholar 

  46. Paolini BM, Laurienti PJ, Simpson SL, Burdette JH, Lyday RG, Rejeski WJ (2015) Global integration of the hot-state brain network of appetite predicts short term weight loss in older adult. Front Aging Neurosci 7:70

    Article  PubMed  PubMed Central  Google Scholar 

  47. García-García I, Jurado MÁ, Garolera M, Segura B, Sala-Llonch R, Marqués-Iturria I (2013) Alterations of the salience network in obesity: A resting-state fMRI study. Hum Brain Mapp 34:2786–2797

    Article  PubMed  Google Scholar 

  48. Chen JJ, Jann K, Wang DJJ (2015) Characterizing resting-state brain function using arterial spin labeling. Brain connectivity 5:527–542

    Article  PubMed  PubMed Central  Google Scholar 

  49. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 1988; 2nd ed., Lawrence Erlbaum Associates: Hillsdale.

  50. Voskuhl RR, Patel K, Paul F, Gold SM, Scheel M, Kuchling J, Cooper G, Asseyer S, Chien C, Brandt AU, Meyer CE, MacKenzie-Graham A (2020) Sex differences in brain atrophy in multiple sclerosis. Biol Sex Differ 11(1):49. https://doi.org/10.1186/s13293-020-00326-3

    Article  PubMed  PubMed Central  Google Scholar 

  51. Naqvi NH, Gaznick N, Tranel D, Bechara A (2014) The insula: a critical neural substrate for craving and drug seeking under conflict and risk. Ann N Y Acad Sci 1316:53–70

    Article  PubMed  PubMed Central  Google Scholar 

  52. Jastreboff AM, Sinha R, Lacadie C, Small DM, Sherwin RS, Potenza MS (2013) Neural correlates of stress- and food Cue-induced food craving in obesity. Association Insulin levels Diabetes Care 36:394–402

    Article  PubMed  Google Scholar 

  53. Rothemund Y, Preuschhof C, Bohner G, Bauknecht HC, Klingebiel R, Flor H, Klapp BF (2007) Differential activation of the dorsal striatum by high-calorie visual food stimuli in obese individuals. Neuroimage 37:410–421. https://doi.org/10.1016/j.neuroimage.2007.05.008

    Article  PubMed  Google Scholar 

  54. Menon V, Uddin LQ (2010) Saliency, switching, attention and control: a network model of insula function. Brain Struct Funct 214(5–6):655–667

    Article  PubMed  PubMed Central  Google Scholar 

  55. Van der Laan LN, de Ridder DTD, Viergever MA, Smeets PAM (2014) Activation in inhibitory brain regions during food choice correlates with temptation strength and self-regulatory success in weight-concerned women. Front Neurosci 8:308

    PubMed  PubMed Central  Google Scholar 

  56. Steward T, Picó-Pérez M, Mata F, Martínez-Zalacaín I, Cano M, Contreras-Rodríguez O et al (2016) Emotion regulation and excess weight: impaired affective processing characterized by dysfunctional insula activation and connectivity. PLoS ONE 11:e0152150. https://doi.org/10.1371/journal.pone.0152150

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Moreno-Rius J (2019) The cerebellum under stress. Front Neuroendocrinol 54:100774. https://doi.org/10.1016/j.yfrne.2019.100774

    Article  CAS  PubMed  Google Scholar 

  58. Koh KB, Sohn SH, Kang JI, Lee YJ, Lee JD (2012) Relationship between neural activity and immunity in patients with undifferentiated somatoform disorder. Psychiatry Res 202(3):252–256

    Article  PubMed  Google Scholar 

  59. Fermin ASR, Friston K, Yamasaki S (2022) An insula hierarchical network architecture for active interoceptive inference. R Soc Open Sci 9(6):220226

    Article  PubMed  PubMed Central  Google Scholar 

  60. Koren T, Yifa R, Amer M, Krot M, Boshnak N et al (2021) Insular cortex neurons encode and retrieve specific immune responses. Cell 184(24):5902-5915.e17

    Article  CAS  PubMed  Google Scholar 

  61. Lazic SE (2008) Why we should use simpler models if the data allow this: relevance for ANOVA designs in experimental biology. BMC Physiol 8:16

    Article  PubMed  PubMed Central  Google Scholar 

  62. Galazzo IB, Storti SF, Barnes A, De Blasi B, De Vita E, Koepp M (2019) Arterial spin labeling reveals disrupted brain networks and functional connectivity in drug-resistant temporal epilepsy. Front Neuroinform 12:101

    Article  Google Scholar 

  63. Boissoneault J, Letzen J, Lai S, O’Shea A, Craggs J, Robinson M, Staud R (2016) Abnormal resting state functional connectivity in patients with chronic fatigue syndrome: an arterial spin-labeling fMRI study. Magn Reson Imaging 34(4):603–608

    Article  PubMed  Google Scholar 

  64. Liu Y, Li B, Feng N, Pu H, Zhang X, Lu H, Yin H (2016) Perfusion deficits and functional connectivity alterations in memory-related regions of patients with post-traumatic stress disorder. PLoS ONE 11(5):e0156016

    Article  PubMed  PubMed Central  Google Scholar 

  65. Fernandez-Seara MA, Mengual E, Vidorreta M, Castellanos G, Irigoyen J, Erro W, Pastor MA (2015) Resting state functional connectivity of the subthalamic nucleus in Parkinson’s disease assessed using arterial spin-labeled perfusion fMRI. Hum Brain Mapp 36:1937–1950

    Article  PubMed  PubMed Central  Google Scholar 

  66. Vallée C, Maurel P, Corouge I, Barillot C, (2020) Acquisition duration in resting-state arterial spin labeling. How long is enough? Front Neurosci 14:598.

  67. Kirschbaum C, Pirke KM, Hellhammer DH (1993) The ‘Trier Social Stress Test’-a tool for investigating psychobiological stress responses in a laboratory setting. Neuropsychobiology 28:76–81

    Article  CAS  PubMed  Google Scholar 

  68. Rocca AM, Schoonheim MM, Valsassina, Geurts JJG, Filippi M. (2022) Task- and resting state fMRi studies in multiple sclerosis: from regions to systems and time-varying analysis. Current status and future perspective. Neuroimage Clin 35: 103076.

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Acknowledgements

This work was supported by the German Research Foundation (WE 5967/2-1 and WE 5967/2-2 to MW, GO 1357/5-1 and GO 1357/5-2 to SMG, Exc 257 to FP). Our funding sources did not influence the study design, the collection, analysis and interpretation of data, the writing of the report or the decision to submit the article for publication.

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Author notes

  1. Friedemann Paul, Stefan M. Gold, and Martin Weygandt have contributed equally to this work.

Authors and Affiliations

  1. Experimental and Clinical Research Center, a cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité Universitätsmedizin, Berlin, Germany

    Lil Meyer-Arndt, Jelena Brasanac, Judith Bellmann-Strobl, Tanja Schmitz-Hübsch, Friedemann Paul & Martin Weygandt

  2. Experimental and Clinical Research Center, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 13125, Berlin, Germany

    Lil Meyer-Arndt, Jelena Brasanac, Judith Bellmann-Strobl, Tanja Schmitz-Hübsch, Friedemann Paul & Martin Weygandt

  3. Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125, Berlin, Germany

    Lil Meyer-Arndt, Jelena Brasanac, Judith Bellmann-Strobl, Tanja Schmitz-Hübsch, Friedemann Paul & Martin Weygandt

  4. Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, NeuroCure Clinical Research Center, 10117, Berlin, Germany

    Lil Meyer-Arndt, Jelena Brasanac, Tanja Schmitz-Hübsch, Friedemann Paul & Martin Weygandt

  5. Department of Neurology and Experimental Neurology, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, 10117, Berlin, Germany

    Lil Meyer-Arndt, Judith Bellmann-Strobl & Friedemann Paul

  6. Department of Psychiatry and Psychotherapy, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, 12203, Berlin, Germany

    Jelena Brasanac, Stefanie Gamradt & Stefan M. Gold

  7. Department of Endocrinology and Metabolism, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, 10117, Berlin, Germany

    Lukas Maurer, Knut Mai & Joachim Spranger

  8. Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Max Rubner Center for Cardiovascular-Metabolic-Renal Research, 10117, Berlin, Germany

    Lukas Maurer & Joachim Spranger

  9. Berlin Institute of Health, 10117, Berlin, Germany

    Lukas Maurer

  10. Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, 13347, Berlin, Germany

    Lukas Maurer, Knut Mai & Joachim Spranger

  11. Melbourne School of Psychological Sciences, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Redmond Barry Building #817, Parkville, VIC, 3010, Australia

    Trevor Steward

  12. Department of Psychosomatic Medicine, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, 10117, Berlin, Germany

    Stefan M. Gold

  13. Institute of Neuroimmunology and Multiple Sclerosis (INIMS), Center for Molecular Neurobiology Hamburg, Universitätsklinikum Hamburg-Eppendorf, 20251, Hamburg, Germany

    Stefan M. Gold

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  1. Lil Meyer-Arndt
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Contributions

LMA: data analysis, investigation, writing, reviewing, editing, JB: data analysis, data curation, reviewing, editing, SG: data analysis, reviewing, editing, JBS: project administration, reviewing, LM: data curation, reviewing, KM: resources, reviewing, TS: reviewing, editing, JS: resources, reviewing, TSH: project administration, reviewing. FP: Resources, project administration, reviewing, editing, SG: reviewing, editing, MW: resources, conceptualization, data curation, data analysis, visualization, writing, reviewing, editing.

Corresponding author

Correspondence to Martin Weygandt.

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The authors declare no conflicts of interest.

Ethical approval

The projects were conducted in accordance with the Helsinki Declaration of 1975 and approved by the ethics committee of Charité – Universitätsmedizin Berlin (first project: EA1/182/10, amendment V; second: EA1/208/16). Written informed consent was obtained from all participants.

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Meyer-Arndt, L., Brasanac, J., Gamradt, S. et al. Body mass, neuro-hormonal stress processing, and disease activity in lean to obese people with multiple sclerosis. J Neurol 271, 1584–1598 (2024). https://doi.org/10.1007/s00415-023-12100-7

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