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Association of life course adiposity with risk of incident dementia: a prospective cohort study of 322,336 participants

Molecular Psychiatry volume 27, pages 3385–3395 (2022)Cite this article

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Abstract

Cohort studies report inconsistent associations between body mass index (BMI) and all-cause incident dementia. Furthermore, evidence on fat distribution and body composition measures are scarce and few studies estimated the association between early life adiposity and dementia risk. Here, we included 322,336 participants from UK biobank to investigate the longitudinal association between life course adiposity and risk of all-cause incident dementia and to explore the underlying mechanisms driven by metabolites, inflammatory cells and brain structures. Among the 322,336 individuals (mean (SD) age, 62.24 (5.41) years; 53.9% women) in the study, during a median 8.74 years of follow-up, 5083 all-cause incident dementia events occurred. The risk of dementia was 22% higher with plumper childhood body size (p < 0.001). A strong U-shaped association was observed between adult BMI and dementia. More fat and less fat-free mass distribution on arms were associated with a higher risk of dementia. Interestingly, similar U-shaped associations were found between BMI and four metabolites (i.e., 3-hydroxybutrate, acetone, citrate and polyunsaturated fatty acids), four inflammatory cells (i.e., neutrophil, lymphocyte, monocyte and leukocyte) and abnormalities in brain structure that were also related to dementia. The findings that adiposity is associated with metabolites, inflammatory cells and abnormalities in brain structure that were related to dementia risk might provide clues to underlying biological mechanisms. Interventions to prevent dementia should begin early in life and include not only BMI control but fat distribution and body composition.

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Fig. 1: Associations between life course adiposity and all-cause incident dementia.
Fig. 2: Sex-specific estimated cutoffs in the adiposity-dementia association, and associations with dementia below and above cutoffs.
Fig. 3: The relationship between adiposity, metabolites, inflammatory cells and dementia.
Fig. 4: Associations between adiposity and brain structure.

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Data availability

The data that support the findings of this study are available from 343 UK Biobank project site, subject to registration and application process. Further details can be found at https://www.ukbiobank.ac.uk.

References

  1. Livingston G, Huntley J, Sommerlad A, Ames D, Ballard C, Banerjee S, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet. 2020;396:413–46.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Gustafson D. Adiposity indices and dementia. Lancet Neurol. 2006;5:713–20.

    Article  PubMed  Google Scholar 

  3. Kivimäki M, Luukkonen R, Batty GD, Ferrie JE, Pentti J, Nyberg ST, et al. Body mass index and risk of dementia: analysis of individual-level data from 1.3 million individuals. Alzheimers Dement. 2018;14:601–9.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Singh-Manoux A, Dugravot A, Shipley M, Brunner EJ, Elbaz A, Sabia S, et al. Obesity trajectories and risk of dementia: 28 years of follow-up in the Whitehall II Study. Alzheimers Dement. 2018;14:178–86.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Chooi YC, Ding C, Magkos F. The epidemiology of obesity. Metabolism. 2019;92:6–10.

    Article  CAS  PubMed  Google Scholar 

  6. Rodríguez-Fernández JM, Danies E, Martínez-Ortega J, Chen WC. Cognitive decline, body mass index, and waist circumference in community-dwelling elderly participants. J Geriatr Psychiatry Neurol. 2017;30:67–76.

    Article  PubMed  Google Scholar 

  7. Srikanthan P, Horwich TB, Tseng CH. Relation of muscle mass and fat mass to cardiovascular disease mortality. Am J Cardiol. 2016;117:1355–60.

    Article  PubMed  Google Scholar 

  8. Winkler TW, Günther F, Höllerer S, Zimmermann M, Loos RJ, Kutalik Z, et al. A joint view on genetic variants for adiposity differentiates subtypes with distinct metabolic implications. Nat Commun. 2018;9:1946.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Mulugeta A, Lumsden A, Hyppönen E. Unlocking the causal link of metabolically different adiposity subtypes with brain volumes and the risks of dementia and stroke: a Mendelian randomization study. Neurobiol Aging. 2021;102:161–9.

    Article  PubMed  Google Scholar 

  10. Xu XH, Huang Y, Wang G, Chen SD. Metabolomics: a novel approach to identify potential diagnostic biomarkers and pathogenesis in Alzheimer’s disease. Neurosci Bull. 2012;28:641–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kaddurah-Daouk R, Kristal BS, Weinshilboum RM. Metabolomics: a global biochemical approach to drug response and disease. Annu Rev Pharm Toxicol. 2008;48:653–83.

    Article  CAS  Google Scholar 

  12. Trushina E, Mielke MM. Recent advances in the application of metabolomics to Alzheimer’s disease. Biochim Biophys Acta. 2014;1842:1232–9.

    Article  CAS  PubMed  Google Scholar 

  13. Würtz P, Wang Q, Kangas AJ, Richmond RC, Skarp J, Tiainen M, et al. Metabolic signatures of adiposity in young adults: Mendelian randomization analysis and effects of weight change. PLoS Med. 2014;11:e1001765.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Xu K, Shi L, Zhang B, Mi B, Yang J, Sun X, et al. Distinct metabolite profiles of adiposity indices and their relationships with habitual diet in young adults. Nutr Metab Cardiovasc Dis. 2021;31:2122–30.

    Article  CAS  PubMed  Google Scholar 

  15. Bahceci M, Gokalp D, Bahceci S, Tuzcu A, Atmaca S, Arikan S. The correlation between adiposity and adiponectin, tumor necrosis factor alpha, interleukin-6 and high sensitivity C-reactive protein levels. Is adipocyte size associated with inflammation in adults? J Endocrinol Invest. 2007;30:210–4.

    Article  CAS  PubMed  Google Scholar 

  16. Windham BG, Simpson BN, Lirette S, Bridges J, Bielak L, Peyser PA, et al. Associations between inflammation and cognitive function in African Americans and European Americans. J Am Geriatr Soc. 2014;62:2303–10.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Bharath LP, Ip BC, Nikolajczyk BS. Adaptive immunity and metabolic health: harmony becomes dissonant in obesity and aging. Compr Physiol. 2017;7:1307–37.

    Article  PubMed  Google Scholar 

  18. Wu KM, Zhang YR, Huang YY, Dong Q, Tan L, Yu JT. The role of the immune system in Alzheimer’s disease. Ageing Res Rev. 2021;70:101409.

    Article  CAS  PubMed  Google Scholar 

  19. Zhang YR, Wang JJ, Chen SF, Wang HF, Li YZ, Ou YN, et al. Peripheral immunity is associated with the risk of incident dementia. Mol Psychiatry. 2022:1–7. https://doi.org/10.1038/s41380-022-01446-5. Online ahead of print.

  20. Kolaczkowska E, Kubes P. Neutrophil recruitment and function in health and inflammation. Nat Rev Immunol. 2013;13:159–75.

    Article  CAS  PubMed  Google Scholar 

  21. Shi C, Pamer EG. Monocyte recruitment during infection and inflammation. Nat Rev Immunol. 2011;11:762–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Ley K, Laudanna C, Cybulsky MI, Nourshargh S. Getting to the site of inflammation: the leukocyte adhesion cascade updated. Nat Rev Immunol. 2007;7:678–89.

    Article  CAS  PubMed  Google Scholar 

  23. Sproston NR, Ashworth JJ. Role of C-reactive protein at sites of inflammation and infection. Front Immunol. 2018;9:754.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Windham BG, Lirette ST, Fornage M, Benjamin EJ, Parker KG, Turner ST, et al. Associations of brain structure with adiposity and changes in adiposity in a middle-aged and older biracial population. J Gerontol A Biol Sci Med Sci. 2017;72:825–31.

    PubMed  Google Scholar 

  25. Isaac V, Sim S, Zheng H, Zagorodnov V, Tai ES, Chee M. Adverse associations between visceral adiposity, brain structure, and cognitive performance in healthy elderly. Front Aging Neurosci. 2011;3:12.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Gudmundsson P, Olesen PJ, Simoni M, Pantoni L, Östling S, Kern S, et al. White matter lesions and temporal lobe atrophy related to incidence of both dementia and major depression in 70-year-olds followed over 10 years. Eur J Neurol. 2015;22:781–8.

    Article  CAS  PubMed  Google Scholar 

  27. Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562:203–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Palmer LJ. UK Biobank: bank on it. Lancet. 2007;369:1980–2.

    Article  PubMed  Google Scholar 

  29. Mally K, Trentmann J, Heller M, Dittmar M. Reliability and accuracy of segmental bioelectrical impedance analysis for assessing muscle and fat mass in older Europeans: a comparison with dual-energy X-ray absorptiometry. Eur J Appl Physiol. 2011;111:1879–87.

    Article  PubMed  Google Scholar 

  30. Rask-Andersen M, Karlsson T, Ek WE, Johansson Å. Genome-wide association study of body fat distribution identifies adiposity loci and sex-specific genetic effects. Nat Commun. 2019;10:339.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Szewczyk P, Zimny A, Trypka E, Wojtyńska R, Leszek J, Sąsiadek M. Assessment of degradation of the selected projectile, commissural and association brain fibers in patients with Alzheimer’s disease on diffusion tensor MR imaging. Pol J Radio. 2010;75:7–14.

    Google Scholar 

  32. Kantarci K, Avula R, Senjem ML, Samikoglu AR, Zhang B, Weigand SD, et al. Dementia with Lewy bodies and Alzheimer disease: neurodegenerative patterns characterized by DTI. Neurology. 2010;74:1814–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Zeki Al Hazzouri A, Vittinghoff E, Hoang T, Golden SH, Fitzpatrick AL, Zhang A, et al. Body mass index in early adulthood and dementia in late life: findings from a pooled cohort. Alzheimers Dement. 2021;17:1798–807.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Richardson TG, Sanderson E, Elsworth B, Tilling K, Davey Smith G. Use of genetic variation to separate the effects of early and later life adiposity on disease risk: mendelian randomisation study. BMJ. 2020;369:m1203.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Pedditzi E, Peters R, Beckett N. The risk of overweight/obesity in mid-life and late life for the development of dementia: a systematic review and meta-analysis of longitudinal studies. Age Ageing. 2016;45:14–21.

    Article  PubMed  Google Scholar 

  36. Qizilbash N, Gregson J, Johnson ME, Pearce N, Douglas I, Wing K, et al. BMI and risk of dementia in two million people over two decades: a retrospective cohort study. Lancet Diabetes Endocrinol. 2015;3:431–6.

    Article  PubMed  Google Scholar 

  37. Suemoto CK, Gilsanz P, Mayeda ER, Glymour MM. Body mass index and cognitive function: the potential for reverse causation. Int J Obes. 2015;39:1383–9.

    Article  CAS  Google Scholar 

  38. Kerwin DR, Gaussoin SA, Chlebowski RT, Kuller LH, Vitolins M, Coker LH, et al. Interaction between body mass index and central adiposity and risk of incident cognitive impairment and dementia: results from the Women’s Health Initiative Memory Study. J Am Geriatr Soc. 2011;59:107–12.

    Article  PubMed  Google Scholar 

  39. Ma Y, Ajnakina O, Steptoe A, Cadar D. Higher risk of dementia in English older individuals who are overweight or obese. Int J Epidemiol. 2020;49:1353–65.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Abellan van Kan G, Rolland Y, Gillette-Guyonnet S, Gardette V, Annweiler C, Beauchet O, et al. Gait speed, body composition, and dementia. The EPIDOS-Toulouse cohort. J Gerontol A Biol Sci Med Sci. 2012;67:425–32.

    Article  PubMed  Google Scholar 

  41. van Kan GA, Cesari M, Gillette-Guyonnet S, Dupuy C, Vellas B, Rolland Y. Association of a 7-year percent change in fat mass and muscle mass with subsequent cognitive dysfunction: the EPIDOS-Toulouse cohort. J Cachexia Sarcopenia Muscle. 2013;4:225–9.

    Article  PubMed  Google Scholar 

  42. Cui C, Mackey RH, Shaaban CE, Kuller LH, Lopez OL, Sekikawa A. Associations of body composition with incident dementia in older adults: Cardiovascular Health Study-Cognition Study. Alzheimers Dement. 2020;16:1402–11.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Letra L, Santana I, Seiça R. Obesity as a risk factor for Alzheimer’s disease: the role of adipocytokines. Metab Brain Dis. 2014;29:563–8.

    Article  CAS  PubMed  Google Scholar 

  44. Park HS, Park JY, Yu R. Relationship of obesity and visceral adiposity with serum concentrations of CRP, TNF-alpha and IL-6. Diabetes Res Clin Pr. 2005;69:29–35.

    Article  CAS  Google Scholar 

  45. Yaghootkar H, Lotta LA, Tyrrell J, Smit RA, Jones SE, Donnelly L, et al. Genetic evidence for a link between favorable adiposity and lower risk of type 2 diabetes, hypertension, and heart disease. Diabetes. 2016;65:2448–60.

    Article  CAS  PubMed  Google Scholar 

  46. Sotelo-Orozco J, Abbeduto L, Hertz-Picciotto I, Slupsky CM. Association between plasma metabolites and psychometric scores among children with developmental disabilities: investigating sex-differences. Front Psychiatry. 2020;11:579538.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Yang H, Shan W, Zhu F, Wu J, Wang Q. Ketone bodies in neurological diseases: focus on neuroprotection and underlying mechanisms. Front Neurol. 2019;10:585.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Mujica-Parodi LR, Amgalan A, Sultan SF, Antal B, Sun X, Skiena S, et al. Diet modulates brain network stability, a biomarker for brain aging, in young adults. Proc Natl Acad Sci USA. 2020;117:6170–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Batetta B, Griinari M, Carta G, Murru E, Ligresti A, Cordeddu L, et al. Endocannabinoids may mediate the ability of (n-3) fatty acids to reduce ectopic fat and inflammatory mediators in obese Zucker rats. J Nutr. 2009;139:1495–501.

    Article  CAS  PubMed  Google Scholar 

  50. Kim J, Carlson ME, Kuchel GA, Newman JW, Watkins BA. Dietary DHA reduces downstream endocannabinoid and inflammatory gene expression and epididymal fat mass while improving aspects of glucose use in muscle in C57BL/6J mice. Int J Obes. 2016;40:129–37.

    Article  CAS  Google Scholar 

  51. An P, Zhou X, Du Y, Zhao J, Song A, Liu H, et al. Association of neutrophil-lymphocyte ratio with mild cognitive impairment in elderly Chinese adults: a case-control study. Curr Alzheimer Res. 2019;16:1309–15.

    Article  CAS  PubMed  Google Scholar 

  52. Rembach A, Watt AD, Wilson WJ, Rainey-Smith S, Ellis KA, Rowe CC, et al. An increased neutrophil-lymphocyte ratio in Alzheimer’s disease is a function of age and is weakly correlated with neocortical amyloid accumulation. J Neuroimmunol. 2014;273:65–71.

    Article  CAS  PubMed  Google Scholar 

  53. Zhang Y, Schuff N, Jahng GH, Bayne W, Mori S, Schad L, et al. Diffusion tensor imaging of cingulum fibers in mild cognitive impairment and Alzheimer disease. Neurology. 2007;68:13–19.

    Article  CAS  PubMed  Google Scholar 

  54. Salat DH, Tuch DS, van der Kouwe AJ, Greve DN, Pappu V, Lee SY, et al. White matter pathology isolates the hippocampal formation in Alzheimer’s disease. Neurobiol Aging. 2010;31:244–56.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Squire LR, Stark CE, Clark RE. The medial temporal lobe. Annu Rev Neurosci. 2004;27:279–306.

    Article  CAS  PubMed  Google Scholar 

  56. Hickok G, Poeppel D. The cortical organization of speech processing. Nat Rev Neurosci. 2007;8:393–402.

    Article  CAS  PubMed  Google Scholar 

  57. Beauchamp MS. The social mysteries of the superior temporal sulcus. Trends Cogn Sci. 2015;19:489–90.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Lisman J, Buzsáki G, Eichenbaum H, Nadel L, Ranganath C, Redish AD. Viewpoints: how the hippocampus contributes to memory, navigation and cognition. Nat Neurosci. 2017;20:1434–47.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Lazarov O, Hollands C. Hippocampal neurogenesis: learning to remember. Prog Neurobiol. 2016;138-140:1–18.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Catani M, Dell’acqua F, Thiebaut, de Schotten M. A revised limbic system model for memory, emotion and behaviour. Neurosci Biobehav Rev. 2013;37:1724–37.

    Article  PubMed  Google Scholar 

  61. Cárdenas D, Madinabeitia I, Vera J, de Teresa C, Alarcón F, Jiménez R, et al. Better brain connectivity is associated with higher total fat mass and lower visceral adipose tissue in military pilots. Sci Rep. 2020;10:610.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Elmquist JK, Flier JS. Neuroscience. The fat-brain axis enters a new dimension. Science. 2004;304:63–4.

    Article  CAS  PubMed  Google Scholar 

  63. Arnoldussen IA, Kiliaan AJ, Gustafson DR. Obesity and dementia: adipokines interact with the brain. Eur Neuropsychopharmacol. 2014;24:1982–99.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Harvey J, Shanley LJ, O’Malley D, Irving AJ. Leptin: a potential cognitive enhancer? Biochem Soc Trans. 2005;33:1029–32.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This study was supported by grants from the National Natural Science Foundation of China (82071201, 81971032), Shanghai Municipal Science and Technology Major Project (No. 2018SHZDZX01), Research Start-up Fund of Huashan Hospital (2022QD002), Excellence 2025 Talent Cultivation Program at Fudan University (3030277001), and ZHANGJIANG LAB, Tianqiao and Chrissy Chen Institute, and the State Key Laboratory of Neurobiology and Frontiers Center for Brain Science of Ministry of Education, Fudan University. WC was supported by grants from the National Natural Sciences Foundation of China (No. 82071997) and the Shanghai Rising-Star Program (No. 21QA1408700). The authors gratefully thank all the participants and professionals contributing to the UK Biobank.

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Authors and Affiliations

  1. Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China

    Yue-Ting Deng, Shu-Yi Huang, Shi-Dong Chen, Ya-Ru Zhang, Liu Yang, Qiang Dong & Jin-Tai Yu

  2. Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China

    Yu-Zhu Li, Wei Zhang, Jian-Feng Feng & Wei Cheng

  3. Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China

    Yu-Zhu Li, Wei Zhang, Jian-Feng Feng & Wei Cheng

  4. Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China

    Ya-Nan Ou

  5. Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK

    Jian-Feng Feng

  6. Department of Psychiatry, University of Cambridge, Cambridge, UK

    John Suckling

  7. Department of Pharmacology, University of Oxford, Oxford, UK

    A. David Smith

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  1. Yue-Ting Deng
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Contributions

JTY generated the hypothesis and designed the study. JTY and WC had full access to all of the data in the study. JFF and WC were responsible for the cohort data. YTD performed the association analysis between life course adiposity and incident dementia. YZL and WC conducted the brain imaging analysis. YTD and YRZ performed the metabolite and inflammatory cell analyses. YTD, YZL, ADS, JS, and JTY wrote the first draft of the report and SYH, YNO, SDC, LY, JFF, WC, ADS, JS, WC, and JTY helped in revising the text. QD, JFF, WC, and JTY provide administrative, technical and material support. All authors read and approved the final manuscript. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

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Correspondence to Wei Cheng or Jin-Tai Yu.

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Deng, YT., Li, YZ., Huang, SY. et al. Association of life course adiposity with risk of incident dementia: a prospective cohort study of 322,336 participants. Mol Psychiatry 27, 3385–3395 (2022). https://doi.org/10.1038/s41380-022-01604-9

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