Letter | Published:

Learning one’s genetic risk changes physiology independent of actual genetic risk

Nature Human Behaviourvolume 3pages4856 (2019) | Download Citation


Millions of people now access personal genetic risk estimates for diseases such as Alzheimer’s, cancer and obesity1. While this information can be informative2,3,4, research on placebo and nocebo effects5,6,7,8 suggests that learning of one’s genetic risk may evoke physiological changes consistent with the expected risk profile. Here we tested whether merely learning of one’s genetic risk for disease alters one’s actual risk by making people more likely to exhibit the expected changes in gene-related physiology, behaviour and subjective experience. Individuals were genotyped for actual genetic risk and then randomly assigned to receive either a ‘high-risk’ or ‘protected’ genetic test result for obesity via cardiorespiratory exercise capacity (experiment 1, N = 116) or physiological satiety (experiment 2, N = 107) before engaging in a task in which genetic risk was salient. Merely receiving genetic risk information changed individuals’ cardiorespiratory physiology, perceived exertion and running endurance during exercise, and changed satiety physiology and perceived fullness after food consumption in a self-fulfilling manner. Effects of perceived genetic risk on outcomes were sometimes greater than the effects associated with actual genetic risk. If simply conveying genetic risk information can alter actual risk, clinicians and ethicists should wrestle with appropriate thresholds for when revealing genetic risk is warranted.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Data availability

Data is available on the Open Science Framework at the following link: https://osf.io/gz57m/?view_only=71292e851b754bacbd89dc07c8113829.

Additional information

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


  1. 1.

    Regalado, A. 2017 was the year consumer DNA testing blew up. MIT Technology Review https://www.technologyreview.com/s/610233/2017-was-the-year-consumer-dna-testing-blew-up/ (12 February 2018).

  2. 2.

    McBride, C. M., Koehly, L. M., Sanderson, S. C. & Kaphingst, K. A. The behavioral response to personalized genetic information: will genetic risk profiles motivate individuals and families to choose more healthful behaviors? Annu. Rev. Public Health 31, 89–103 (2010).

  3. 3.

    Dancey, J. E., Bedard, P. L., Onetto, N. & Hudson, T. J. The genetic basis for cancer treatment decisions. Cell 148, 409–420 (2012).

  4. 4.

    Rieder, M. J. et al. Effect of VKORC1 haplotypes on transcriptional regulation and warfarin dose. N. Engl. J. Med. 352, 2285–2293 (2005).

  5. 5.

    Kaptchuk, T. J. & Miller, F. G. Placebo effects in medicine. N. Engl. J. Med. 373, 8–9 (2015).

  6. 6.

    Finniss, D. G., Kaptchuk, T. J., Miller, F. & Benedetti, F. Biological, clinical, and ethical advances of placebo effects. Lancet 375, 686–695 (2010).

  7. 7.

    Colloca, L. & Finniss, D. Nocebo effects, patient-clinician communication, and therapeutic outcomes. JAMA 307, 567–568 (2012).

  8. 8.

    Crum, A. J., Leibowitz, K. A. & Verghese, A. Making mindset matter. BMJ 356, j674 (2017).

  9. 9.

    Rubinstein, W. S. et al. The NIH genetic testing registry: a new, centralized database of genetic tests to enable access to comprehensive information and improve transparency. Nucleic Acids Res. 41, D925–D935 (2012).

  10. 10.

    Hollands, G. J. et al. The impact of communicating genetic risks of disease on risk-reducing health behaviour: systematic review with meta-analysis. BMJ 352, i1102 (2016).

  11. 11.

    Dar-Nimrod, I. & Heine, S. J. Genetic essentialism: on the deceptive determinism of DNA. Psychol. Bull. 137, 800–818 (2011).

  12. 12.

    Dar-Nimrod, I., Cheung, B. Y., Ruby, M. B. & Heine, S. J. Can merely learning about obesity genes affect eating behavior? Appetite 81, 269–276 (2014).

  13. 13.

    Dar-Nimrod, I. & Heine, S. J. Exposure to scientific theories affects women‘s math performance. Science 314, 435 (2006).

  14. 14.

    Dar‐Nimrod, I., Heine, S. J., Cheung, B. Y. & Schaller, M. Do scientific theories affect men‘s evaluations of sex crimes? Aggress. Behav. 37, 440–449 (2011).

  15. 15.

    Persky, S., Bouhlal, S., Goldring, M. R. & McBride, C. M. Beliefs about genetic influences on eating behaviors: characteristics and associations with weight management confidence. Eat. Behav. 26, 93–98 (2017).

  16. 16.

    Beauchamp, M. R., Rhodes, R. E., Kreutzer, C. & Rupert, J. L. Experiential versus genetic accounts of inactivity: implications for inactive individuals’ self-efficacy beliefs and intentions to exercise. Behav. Med. 37, 8–14 (2011).

  17. 17.

    Wang, C. & Coups, E. J. Causal beliefs about obesity and associated health behaviors: results from a population-based survey. Int. J. Behav. Nutr. Phys. Act. 7, 19 (2010).

  18. 18.

    Dweck, C. S. Can personality be changed? The role of beliefs in personality and change. Curr. Dir. Psychol. Sci. 17, 391–394 (2008).

  19. 19.

    Crum, A. J., Salovey, P. & Achor, S. Rethinking stress: the role of mindsets in determining the stress response. J. Pers. Soc. Psychol. 104, 716–733 (2013).

  20. 20.

    Levy, B. R., Slade, M. D., Kunkel, S. R. & Kasl, S. V. Longevity increased by positive self-perceptions of aging. J. Pers. Soc. Psychol. 83, 261–270 (2002).

  21. 21.

    Levy, B. R., Hausdorff, J. M., Hencke, R. & Wei, J. Y. Reducing cardiovascular stress with positive self-stereotypes of aging. J. Gerontol. B Psychol. Sci. Soc. Sci. 55, 205–213 (2000).

  22. 22.

    Crum, A. J., Akinola, M., Martin, A. & Fath, S. The role of stress mindset in shaping cognitive, emotional, and physiological responses to challenging and threatening stress. Anxiety Stress Coping 30, 379–395 (2017).

  23. 23.

    Benedetti, F., Amanzio, M., Vighetti, S. & Asteggiano, G. The biochemical and neuroendocrine bases of the hyperalgesic nocebo effect. J. Neurosci. 26, 12014–12022 (2006).

  24. 24.

    Crum, A. J. & Langer, E. J. Mind-set matters exercise and the placebo effect. Psychol. Sci. 18, 165–171 (2007).

  25. 25.

    Crum, A. J., Corbin, W. R., Brownell, K. D. & Salovey, P. Mind over milkshakes: mindsets, not just nutrients, determine ghrelin response. Health Psychol. 30, 424–429 (2011).

  26. 26.

    Barsky, A. J. The iatrogenic potential of the physician’s words. JAMA 318, 2425–2426 (2017).

  27. 27.

    Silvestri, A. et al. Report of erectile dysfunction after therapy with beta-blockers is related to patient knowledge of side effects and is reversed by placebo. Eur. Heart J. 24, 1928–1932 (2003).

  28. 28.

    Myers, M. G., Cairns, J. A. & Singer, J. The consent form as a possible cause of side effects. Clin. Pharmacol. Ther. 42, 250–253 (1987).

  29. 29.

    Green, R. C. et al. Disclosure of APOE genotype for risk of Alzheimer‘s disease. N. Engl. J. Med. 361, 245–254 (2009).

  30. 30.

    Lineweaver, T. T., Bondi, M. W., Galasko, D. & Salmon, D. P. Effect of knowledge of APOE genotype on subjective and objective memory performance in healthy older adults. Am. J. Psychiatry 171, 201–208 (2014).

  31. 31.

    Dar-Nimrod, I., Zuckerman, M. & Duberstein, P. R. The effects of learning about one‘s own genetic susceptibility to alcoholism: a randomized experiment. Genet. Med. 15, 132–138 (2012).

  32. 32.

    de Viron, S. et al. Impact of genetic notification on smoking cessation: systematic review and pooled-analysis. PLoS ONE 7, e40230 (2012).

  33. 33.

    Bloss, C. S., Schork, N. J. & Topol, E. J. Effect of direct-to-consumer genomewide profiling to assess disease risk. N. Engl. J. Med. 364, 524–534 (2011).

  34. 34.

    Boeldt, D., Schork, N., Topol, E. & Bloss, C. Influence of individual differences in disease perception on consumer response to direct‐to‐consumer genomic testing. Clin. Genet. 87, 225–232 (2015).

  35. 35.

    Frosch, D. L., Mello, P. & Lerman, C. Behavioral consequences of testing for obesity risk. Cancer Epidemiol. Biomark. Prev. 14, 1485–1489 (2005).

  36. 36.

    Meisel, S. F., Walker, C. & Wardle, J. Psychological responses to genetic testing for weight gain: a vignette study. Obesity 20, 540–546 (2012).

  37. 37.

    Sanderson, S., Persky, S. & Michie, S. Psychological and behavioral responses to genetic test results indicating increased risk of obesity: does the causal pathway from gene to obesity matter? Public Health Genomics 13, 34–47 (2010).

  38. 38.

    Harvey-Berino, J., Gold, E. C., West, D. S. & Shuldiner, A. R. Does genetic testing for obesity influence confidence in the ability to lose weight? A pilot investigation. J. Acad. Nutr. Diet. 101, 1351–1353 (2001).

  39. 39.

    Meisel, S. F., Beeken, R. J., van Jaarsveld, C. H. & Wardle, J. Genetic susceptibility testing and readiness to control weight: results from a randomized controlled trial. Obesity 23, 305–312 (2015).

  40. 40.

    Wang, C. et al. A randomized trial examining the impact of communicating genetic and lifestyle risks for obesity. Obesity 24, 2481–2490 (2016).

  41. 41.

    Ahn, W.-K. & Lebowitz, M. S. An experiment assessing effects of personalized feedback about genetic susceptibility to obesity on attitudes towards diet and exercise. Appetite 120, 23–31 (2018).

  42. 42.

    Karoly, H. C. et al. Genetic influences on physiological and subjective responses to an aerobic exercise session among sedentary adults. J. Cancer Epidemiol. 2012, 1–12 (2012).

  43. 43.

    Rankinen, T., Argyropoulos, G., Rice, T., Rao, D. C. & Bouchard, C. CREB1 is a strong genetic predictor of the variation in exercise heart rate response to regular exercise: the HERITAGE Family Study. Circ. Cardiovasc. Genet. 3, 294–299 (2010).

  44. 44.

    Rankinen, T. et al. Heritability of submaximal exercise heart rate response to exercise training is accounted for by nine SNPs. J. Appl. Physiol. 112, 892–897 (2011).

  45. 45.

    Frayling, T. M. et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 316, 889–894 (2007).

  46. 46.

    den Hoed, M., Westerterp-Plantenga, M. S., Bouwman, F. G., Mariman, E. C. & Westerterp, K. R. Postprandial responses in hunger and satiety are associated with the rs9939609 single nucleotide polymorphism in FTO. Am. J. Clin. Nutr. 90, 1426–1432 (2009).

  47. 47.

    Karra, E. et al. A link between FTO, ghrelin, and impaired brain food-cue responsivity. J. Clin. Investig. 123, 3539–3551 (2013).

  48. 48.

    Wardle, J. et al. Obesity associated genetic variation in FTO is associated with diminished satiety. J. Clin. Endocrinol. Metab. 93, 3640–3643 (2008).

  49. 49.

    Rapuano, K. M. et al. Genetic risk for obesity predicts nucleus accumbens size and responsivity to real-world food cues. Proc. Natl Acad. Sci. USA 114, 160–165 (2017).

  50. 50.

    Velders, F. P. et al. FTO atrs9939609, food responsiveness, emotional control and symptoms of ADHD in preschool children. PLoS ONE 7, e49131 (2012).

  51. 51.

    Lovallo, W. R. Stress and Health: Biological and Psychological Interactions (Sage Publications, Thousand Oaks, 2015).

  52. 52.

    Crum, A. & Zuckerman, B. Changing mindsets to enhance treatment effectiveness. JAMA 317, 2063–2064 (2017).

  53. 53.

    LaRusse, S. et al. Genetic susceptibility testing versus family history-based risk assessment: impact on perceived risk of Alzheimer disease. Genet. Med. 7, 48–53 (2005).

  54. 54.

    Lerman, C. et al. Incorporating biomarkers of exposure and genetic susceptibility into smoking cessation treatment: effects on smoking-related cognitions, emotions, and behavior change. Health Psychol. 16, 87–99 (1997).

  55. 55.

    Voils, C. I. et al. Does type 2 diabetes genetic testing and counseling reduce modifiable risk factors? A randomized controlled trial of veterans. J. Gen. Intern. Med. 30, 1591–1598 (2015).

  56. 56.

    Flint, A., Raben, A., Astrup, A. & Holst, J. J. Glucagon-like peptide 1 promotes satiety and suppresses energy intake in humans. J. Clin. Investig. 101, 515–520 (1998).

  57. 57.

    De Silva, A. et al. The gut hormones PYY 3-36 and GLP-1 7-36 amide reduce food intake and modulate brain activity in appetite centers in humans. Cell Metab. 14, 700–706 (2011).

  58. 58.

    Holst, J. J. The physiology of glucagon-like peptide 1. Physiol. Rev. 87, 1409–1439 (2007).

  59. 59.

    Dossat, A. M., Lilly, N., Kay, K. & Williams, D. L. Glucagon-like peptide 1 receptors in nucleus accumbens affect food intake. J. Neurosci. 31, 14453–14457 (2011).

  60. 60.

    Turton, M., Shea, D., Gunn, I. & Beak, S. A role for glucagon-like peptide-1 in the central regulation of feeding. Nature 379, 69–72 (1996).

  61. 61.

    Wren, A. et al. Ghrelin enhances appetite and increases food intake in humans. J. Clin. Endocrinol. Metab. 86, 5992 (2001).

  62. 62.

    Malik, S., McGlone, F., Bedrossian, D. & Dagher, A. Ghrelin modulates brain activity in areas that control appetitive behavior. Cell Metab. 7, 400–409 (2008).

Download references


This research is supported by the Foundation for the Science of the Therapeutic Encounter, the National Science Foundation GRFP Grant No. DGE-11474 and the National Institutes of Health DP2 AT009511 and U54EB020405. The funders had no role in the conceptualization, design, data collection, analysis, decision to publish or preparation of the manuscript. We thank Y. Rosenberg-Hasson, the Clinical Translational Research Unit, Human Immune Monitoring Center, Human Performance Lab and Protein and Nucleic Acid Facility at Stanford University for assistance in the collection and processing of biological samples. We thank colleagues C. Dweck, H. Markus, K. Hall and G. Walton for comments on versions of this manuscript.

Author information


  1. Department of Psychology, Stanford University, Stanford, CA, USA

    • Bradley P. Turnwald
    • , J. Parker Goyer
    • , Danielle Z. Boles
    •  & Alia J. Crum
  2. Department of Bioengineering, Stanford University, Stanford, CA, USA

    • Amy Silder
    •  & Scott L. Delp


  1. Search for Bradley P. Turnwald in:

  2. Search for J. Parker Goyer in:

  3. Search for Danielle Z. Boles in:

  4. Search for Amy Silder in:

  5. Search for Scott L. Delp in:

  6. Search for Alia J. Crum in:


B.P.T. and A.J.C. conceived and designed the study. B.P.T., A.S., S.L.D. and A.J.C. designed protocol details. B.P.T. and D.Z.B. were responsible for consenting participants, running participants through the protocol and debriefing participants. A.S. was responsible for processing physiological data, B.P.T. and D.Z.B. were in charge of data management and J.P.G. was in charge of data analysis. B.P.T. wrote the first draft, and all authors contributed critical revisions of the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Bradley P. Turnwald.

Supplementary information

  1. Supplementary Information

    Supplementary Methods, Supplementary Notes, Supplementary Figures 1–3, Supplementary Tables 1–11, Supplementary References

  2. Reporting Summary

About this article

Publication history