Skip to main content

Thank you for visiting nature.com. 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.

  • Article
  • Published:

Epidemiology and Population Health

Causality of abdominal obesity on cognition: a trans-ethnic Mendelian randomization study

International Journal of Obesity volume 46, pages 1487–1492 (2022)Cite this article

Subjects

Abstract

Background

Obesity has been associated with cognition in observational studies; however, whether its effect is confounding or a reverse causality remains inconclusive. This study aimed to investigate the causal relationships of overall obesity, measured by body mass index (BMI), and abdominal adiposity, measured by waist–hip ratio adjusted for BMI (WHRadjBMI), and cognition across European and Asian populations using Mendelian randomization (MR) analysis.

Methods

We used publicly available genome-wide association study (GWAS) summary data of European ancestry, including BMI (n = 322,154) and WHRadjBMI (n = 210,088) from the GIANT consortium, and cognition performance (n = 257,828) from the UK Biobank and COGENT consortium. Data for individuals of Asian ancestry were retrieved from Taiwan Biobank to perform GWAS for BMI (n = 65,689), WHRadjBMI (n = 65,683), and Mini-Mental State Examination (MMSE, n = 21,273). MR analysis was carried out using the inverse-variance weighted method for the main results. Further, we examined the overall pleiotropy by MR-Egger intercept, and detected and adjusted for possible outliers using MR PRESSO.

Results

No causal effect of BMI on cognition performance (beta [95% CI] = 0.00 [−0.07, 0.07], p value = 0.91) was found for Europeans; however, a 1-SD increase in WHRadjBMI was associated with a 0.07 standardized score decrease in cognition performance (beta [95% CI] = −0.07 [−0.12, −0.02], p value = 0.006). Further, no causal effect of BMI on MMSE (beta [95% CI] = 0.01 [−0.08, 0.10], p = 0.91) was found for Asians; however, a 1-SD increase in WHRadjBMI was associated with a 0.17 standardized score decrease in MMSE (beta [95% CI] = −0.17 [−0.30, −0.03], p = 0.02). In both populations, overall pleiotropy was not detected, and outliers did not affect the robustness of the main findings.

Conclusions

This trans-ethnic MR study reveals that abdominal adiposity, as measured by WHR adjusted for BMI, impairs cognition, whereas weak evidence suggests that BMI impairs cognition.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: The Mendelian randomization (MR) association between obesity-related traits and cognitive performance in the European population.
Fig. 2: The Mendelian randomization (MR) association between obesity-related traits and MMSE in the Asian population.
Fig. 3: The Mendelian randomization (MR) association between cognitive performance and obesity-related traits in the European population.

Similar content being viewed by others

Data availability

This study used publicly available GWAS summary statistics from the GIANT consortium, the UK Biobank, and COGENT consortium. In terms of individual data from the Taiwan Biobank, interested researchers can apply the Taiwan Biobank through formal application biobank@gate.sinica.edu.tw.

References

  1. Abarca-Gómez L, Abdeen ZA, Hamid ZA, Abu-Rmeileh NM, Acosta-Cazares B, Acuin C, et al. Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128· 9 million children, adolescents, and adults. Lancet. 2017;390:2627–42.

    Article  Google Scholar 

  2. GBD Obesity Collaborators. Health effects of overweight and obesity in 195 countries over 25 years. N Engl J Med. 2017;377:13–27.

    Article  Google Scholar 

  3. Milaneschi Y, Simmons WK, van Rossum EF, Penninx BW. Depression and obesity: evidence of shared biological mechanisms. Mol Psychiatry. 2019;24:18–33.

    Article  CAS  PubMed  Google Scholar 

  4. Pedditizi 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  Google Scholar 

  5. Cournot M, Marquie J, Ansiau D, Martinaud C, Fonds H, Ferrieres J, et al. Relation between body mass index and cognitive function in healthy middle-aged men and women. Neurology. 2006;67:1208–14.

    Article  CAS  PubMed  Google Scholar 

  6. Boeka AG, Lokken KL. Neuropsychological performance of a clinical sample of extremely obese individuals. Arch Clin Neuropsychol. 2008;23:467–74.

    Article  PubMed  Google Scholar 

  7. Fergenbaum JH, Bruce S, Lou W, Hanley AJ, Greenwood C, Young TK. Obesity and lowered cognitive performance in a Canadian First Nations population. Obesity. 2009;17:1957–63.

    Article  PubMed  Google Scholar 

  8. Ariza M, Garolera M, Jurado MA, Garcia-Garcia I, Hernan I, Sanchez-Garre C, et al. Dopamine genes (DRD2/ANKK1-TaqA1 and DRD4-7R) and executive function: their interaction with obesity. PLoS ONE. 2012;7:e41482.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Halkjær J, Holst C, Sørensen TI. Intelligence test score and educational level in relation to BMI changes and obesity. Obes Res. 2003;11:1238–45.

    Article  PubMed  Google Scholar 

  10. Rosenblad A, Nilsson G, Leppert J. Intelligence level in late adolescence is inversely associated with BMI change during 22 years of follow-up: results from the WICTORY study. Eur J Epidemiol. 2012;27:647–55.

    Article  PubMed  Google Scholar 

  11. Kanazawa S. Childhood intelligence and adult obesity. Obesity. 2013;21:434–40.

    Article  PubMed  Google Scholar 

  12. Prickett C, Brennan L, Stolwyk R. Examining the relationship between obesity and cognitive function: a systematic literature review. Obes Res Clin Pract. 2015;9:93–113.

    Article  PubMed  Google Scholar 

  13. Smith E, Hay P, Campbell L, Trollor JN. A review of the association between obesity and cognitive function across the lifespan: implications for novel approaches to prevention and treatment. Obes Rev. 2011;12:740–55.

    Article  CAS  PubMed  Google Scholar 

  14. 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 

  15. Marini S, Merino J, Montgomery BE, Malik R, Sudlow CL, Dichgans M, et al. Mendelian randomization study of obesity and cerebrovascular disease. Ann Neurol. 2020;87:516–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Riaz H, Khan MS, Siddiqi TJ, Usman MS, Shah N, Goyal A, et al. Association between obesity and cardiovascular outcomes: a systematic review and meta-analysis of mendelian randomization studies. JAMA Netw Open. 2018;1:e183788.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Thrift AP, Shaheen NJ, Gammon MD, Bernstein L, Reid BJ, Onstad L, et al. Obesity and risk of esophageal adenocarcinoma and Barrett’s esophagus: a Mendelian randomization study. JNCI. 2014;106:dju252.

  18. Mokry LE, Ross S, Timpson NJ, Sawcer S, Davey Smith G, Richards JB. Obesity and multiple sclerosis: a mendelian randomization study. PLoS Med. 2016;13:e1002053.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Debette S, Wolf C, Lambert J-C, Crivello F, Soumaré A, Zhu Y-C, et al. Abdominal obesity and lower gray matter volume: a Mendelian randomization study. Neurobiol Aging. 2014;35:378–86.

    Article  PubMed  Google Scholar 

  20. 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 

  21. Li YR, Keating BJ. Trans-ethnic genome-wide association studies: advantages and challenges of mapping in diverse populations. Genome Med. 2014;6:1–14.

    Article  CAS  Google Scholar 

  22. Seidell J, Björntorp P, Sjöström L, Sannerstedt R, Krotkiewski M, Kvist H. Regional distribution of muscle and fat mass in men–new insight into the risk of abdominal obesity using computed tomography. Int J Obes. 1989;13:289–303.

    CAS  PubMed  Google Scholar 

  23. Emdin CA, Khera AV, Natarajan P, Klarin D, Zekavat SM, Hsiao AJ, et al. Genetic association of waist-to-hip ratio with cardiometabolic traits, type 2 diabetes, and coronary heart disease. Jama. 2017;317:626–34.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Cheng C-H, Ho C-C, Yang C-F, Huang Y-C, Lai C-H, Liaw Y-P. Waist-to-hip ratio is a better anthropometric index than body mass index for predicting the risk of type 2 diabetes in Taiwanese population. Nutr Res. 2010;30:585–93.

    Article  CAS  PubMed  Google Scholar 

  25. Locke A, Kahali B, Berndt S, Justice A, Pers T, Day F, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518:197–206.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Shungin D, Winkler T, Croteau-Chonka D, Ferreira T, Locke A, Mägi R, et al. New genetic loci link adipose and insulin biology to body fat distribution. Nature. 2015;518:187–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Lee J, Wedow R, Okbay A, Kong E, Maghzian O, Zacher M, et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat Genet. 2018;50:1112–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Chen C-H, Yang J-H, Chiang CW, Hsiung C-N, Wu P-E, Chang L-C, et al. Population structure of Han Chinese in the modern Taiwanese population based on 10,000 participants in the Taiwan Biobank project. Hum Mol Genet. 2016;25:5321–31.

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Genomes Project Consortium. A global reference for human genetic variation. Nature. 2015;526:68.

    Article  CAS  Google Scholar 

  30. Akiyama M, Okada Y, Kanai M, Takahashi A, Momozawa Y, Ikeda M, et al. Genome-wide association study identifies 112 new loci for body mass index in the Japanese population. Nat Genet. 2017;49:1458–67.

    Article  CAS  PubMed  Google Scholar 

  31. Pulit S, Stoneman C, Morris A, Wood A, Glastonbury C, Tyrrell J, et al. Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. Hum Mol Genet. 2019;28:166–74.

    Article  CAS  PubMed  Google Scholar 

  32. Shyu Y-IL, Yip P-K. Factor structure and explanatory variables of the Mini-Mental State Examination (MMSE) for elderly persons in Taiwan. J Formos Med Assoc. 2001;100:676–83.

    CAS  PubMed  Google Scholar 

  33. Klimentidis Y, Raichlen D, Bea J, Garcia D, Wineinger N, Mandarino L, et al. Genome-wide association study of habitual physical activity in over 377,000 UK Biobank participants identifies multiple variants including CADM2 and APOE. Int J Obes. 2018;42:1161–76.

    Article  CAS  Google Scholar 

  34. Howard D, Adams M, Clarke T, Hafferty J, Gibson J, Shirali M, et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci. 2019;22:343–52.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Karlsson Linnér R, Biroli P, Kong E, Meddens S, Wedow R, Fontana M, et al. Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences. Nat Genet. 2019;51:245–57.

    Article  PubMed  CAS  Google Scholar 

  36. Lane J, Jones S, Dashti H, Wood A, Aragam K, van Hees V, et al. Biological and clinical insights from genetics of insomnia symptoms. Nat Genet. 2019;51:387–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol. 2013;37:658–65.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44:512–25.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Bowden J, Davey, Smith G, Haycock PC, Burgess S. Consistent estimation in mendelian randomization with some invalid instruments using a weighted Median estimator. Genet Epidemiol. 2016;40:304–14.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Hartwig F, Davey Smith G, Bowden J. Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption. Int J Epidemiol. 2017;46:1985–98.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Verbanck M, Chen C, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018;50:693–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Bowden J, Del Greco MF, Minelli C, Davey Smith G, Sheehan N, Thompson J. A framework for the investigation of pleiotropy in two-sample summary data Mendelian randomization. Stat Med. 2017;36:1783–802.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Del Greco MF, Minelli C, Sheehan NA, Thompson JR. Detecting pleiotropy in Mendelian randomisation studies with summary data and a continuous outcome. Stat Med. 2015;34:2926–40.

    Article  Google Scholar 

  44. Liu Z, Yang H, Chen S, Cai J, Huang Z. The association between body mass index, waist circumference, waist–hip ratio and cognitive disorder in older adults. J Public Health. 2019;41:305–12.

    Article  CAS  Google Scholar 

  45. Wolf PA, Beiser A, Elias MF, Au R, Vasan RS, Seshadri S. Relation of obesity to cognitive function: importance of central obesity and synergistic influence of concomitant hypertension. The Framingham Heart Study. Curr Alzheimer Res. 2007;4:111–6.

    Article  CAS  PubMed  Google Scholar 

  46. 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 

  47. Zhang T, Yan R, Chen Q, Ying X, Zhai Y, Li F, et al. Body mass index, waist-to-hip ratio and cognitive function among Chinese elderly: a cross-sectional study. BMJ Open. 2018;8:e022055.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Dalton M, Cameron AJ, Zimmet PZ, Shaw JE, Jolley D, Dunstan DW, et al. Waist circumference, waist–hip ratio and body mass index and their correlation with cardiovascular disease risk factors in Australian adults. J Intern Med. 2003;254:555–63.

    Article  CAS  PubMed  Google Scholar 

  49. Czernichow S, Kengne A-P, Huxley RR, Batty GD, De Galan B, Grobbee D, et al. Comparison of waist-to-hip ratio and other obesity indices as predictors of cardiovascular disease risk in people with type-2 diabetes: a prospective cohort study from ADVANCE. Eur J Prev Cardiol. 2011;18:312–9.

    Article  Google Scholar 

  50. Elias MF, Elias PK, Sullivan LM, Wolf PA, D’Agostino RB. Obesity, diabetes and cognitive deficit: the Framingham Heart Study. Neurobiol Aging. 2005;26:11–6.

    Article  PubMed  CAS  Google Scholar 

  51. Gunstad J, Lhotsky A, Wendell CR, Ferrucci L, Zonderman AB. Longitudinal examination of obesity and cognitive function: results from the Baltimore longitudinal study of aging. Neuroepidemiology. 2010;34:222–9.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Shah NR, Braverman ER. Measuring adiposity in patients: the utility of body mass index (BMI), percent body fat, and leptin. PloS ONE. 2012;7:e33308.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Mukherjee S, Walter S, Kauwe JS, Saykin AJ, Bennett DA, Larson EB, et al. Genetically predicted body mass index and Alzheimer’s disease–related phenotypes in three large samples: Mendelian randomization analyses. Alzheimers Dement. 2015;11:1439–51.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Nordestgaard LT, Tybjærg-Hansen A, Nordestgaard BG, Frikke-Schmidt R. Body mass index and risk of Alzheimer’s disease: a mendelian randomization study of 399,536 individuals. J Clin Endocrinol Metab. 2017;102:2310–20.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Zhou Y, Sun X, Zhou M. Body shape and Alzheimer’s disease: a Mendelian randomization analysis. Front Neurosci. 2019;13:1084.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Wenk GL. Neuropathologic changes in Alzheimer’s disease. J Clin Psychiatry. 2003;64:7–10.

    PubMed  Google Scholar 

  57. Anjum I, Fayyaz M, Wajid A, Sohail W, Ali A. Does obesity increase the risk of dementia: a literature review. Cureus. 2018;10:e2660.

    PubMed  PubMed Central  Google Scholar 

  58. Siervo M, Arnold R, Wells J, Tagliabue A, Colantuoni A, Albanese E, et al. Intentional weight loss in overweight and obese individuals and cognitive function: a systematic review and meta‐analysis. Obes Rev. 2011;12:968–83.

    Article  CAS  PubMed  Google Scholar 

  59. Deng L, Zhang H, Yu K. Power calculation for the general two-sample Mendelian randomization analysis. Genet Epidemiol. 2020;44:290–9.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was supported by National Health Research Institutes, Taiwan (NHRI-EX109-10931PI, NHRI-EX110-10931PI, NHRI-EX111-10931PI) and China Medical University, Taiwan (CMU110-MF-24). This study was posted without peer review on the preprint server medRxiv.

Author information

Authors and Affiliations

  1. Department of Occupational Safety and Health, College of Public Health, China Medical University, Taichung, Taiwan

    Shi-Heng Wang & Mei-Hsin Su

  2. Department of Public Health, College of Public Health, China Medical University, Taichung, Taiwan

    Shi-Heng Wang

  3. Biogen, Cambridge, MA, USA

    Chia-Yen Chen

  4. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Chia-Yen Chen

  5. Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan

    Yen-Feng Lin

  6. Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan

    Yen-Chen A. Feng & Po-Chang Hsiao

  7. School of Medicine, College of Medicine, China Medical University, Taichung, Taiwan

    Yi-Jiun Pan

  8. National Center for Geriatrics and Welfare Research, National Health Research Institutes, Miaoli, Taiwan

    Chi-Shin Wu

  9. Department of Psychiatry, National Taiwan University Hospital, Yunlin Branch, Yunlin, Taiwan

    Chi-Shin Wu

Authors
  1. Shi-Heng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mei-Hsin Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chia-Yen Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yen-Feng Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yen-Chen A. Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Po-Chang Hsiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yi-Jiun Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Chi-Shin Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualized the study: SHW, CSW. Performed the analysis: SHW, MHS, and PCH. Wrote the paper: SHW, CSW. Critically revised the paper: MHS, CYC, YFL, YAF, PCH, and YJP. All authors reviewed and approved the final version of the paper.

Corresponding author

Correspondence to Chi-Shin Wu.

Ethics declarations

Competing interests

CYC is an employee of Biogen. The remaining 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.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, SH., Su, MH., Chen, CY. et al. Causality of abdominal obesity on cognition: a trans-ethnic Mendelian randomization study. Int J Obes 46, 1487–1492 (2022). https://doi.org/10.1038/s41366-022-01138-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41366-022-01138-8

Search

Advanced search

Quick links