Adult survivors of childhood cancer have high rates of obesity, which, in combination with the cardiotoxic effects of specific cancer therapies, places them at high risk for cardiovascular morbidity. Here we show the contribution of genetic risk scores (GRSs) to increase prediction of those survivors of childhood cancer who are at risk for severe obesity (body mass index ≥40 kg m−2) as an adult. Among 2,548 individuals of European ancestry from the St. Jude Lifetime Cohort Study who were 5-year survivors of childhood cancer, the GRS was found to be associated with 53-fold-higher odds of severe obesity. Addition of GRSs to risk prediction models based on cancer treatment exposures and lifestyle factors significantly improved model prediction (area under the curve increased from 0.68 to 0.75, resulting in the identification of 4.3-times more high-risk survivors), which was independently validated in 6,064 individuals from the Childhood Cancer Survivor Study. Genetic predictors improve identification of patients who could benefit from heightened surveillance and interventions to mitigate the risk of severe obesity and associated cardio-metabolic complications.
This is a preview of subscription content, access via your institution
Open Access articles citing this article.
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Rent or buy this article
Prices vary by article type
Prices may be subject to local taxes which are calculated during checkout
Aligned binary files for all the SJLIFE survivors and a subset of CCSS survivors whose childhood cancer was diagnosed between 1987 and 1999 and the joint genotype calls are accessible through the St. Jude Cloud (https://stjude.cloud). For CCSS survivors diagnosed between 1970 and 1986, genome-wide genotype data are available through the database of Genotypes and Phenotypes (accession number phs001327.v2.p1). Relevant phenotype data are available through the St. Jude Cloud for SJLIFE survivors and through https://ccss.stjude.org/ for CCSS survivors. Variant-level information used to calculate various GRSs examined in this study are available from previously published studies, including Turcot et al.16 (GRSrare), Khera et al.18 (GRScommon), Monda et al.61 (GRSAFR_8 and GRSAFR_179), Ng et al.62 (GRSAFR_genomewide), Vogelezang et al.22 (GRSchildhood_bmi), Bradfield et al.23 (GRSchildhood_obesity), Pulit et al.21 (GRSwhradjBMI) and Yengo et al.24 (GRS941). All data generated or analyzed during the study are included in the published article (and its supplementary files).
In-house scripts used to calculate AUC values and their CIs using 1,000 bootstrap iterations are available to download from https://github.com/sapkotagrp/NatMed2022_SevereObesity.
Robison, L. L. & Hudson, M. M. Survivors of childhood and adolescent cancer: life-long risks and responsibilities. Nat. Rev. Cancer 14, 61–70 (2014).
Garmey, E. G. et al. Longitudinal changes in obesity and body mass index among adult survivors of childhood acute lymphoblastic leukemia: a report from the Childhood Cancer Survivor Study. J. Clin. Oncol. 26, 4639–4645 (2008).
Janiszewski, P. M. et al. Abdominal obesity, liver fat, and muscle composition in survivors of childhood acute lymphoblastic leukemia. J. Clin. Endocr. Metab. 92, 3816–3821 (2007).
Oeffinger, K. C. et al. Obesity in adult survivors of childhood acute lymphoblastic leukemia: a report from the childhood cancer survivor study. J. Clin. Oncol. 21, 1359–1365 (2003).
Razzouk, B. I. et al. Obesity in survivors of childhood acute lymphoblastic leukemia and lymphoma. J. Clin. Oncol. 25, 1183–1189 (2007).
Wilson, C. L. et al. Genetic and clinical factors associated with obesity among adult survivors of childhood cancer: a report from the St. Jude Lifetime Cohort. Cancer 121, 2262–2270 (2015).
Armstrong, G. T. et al. Modifiable risk factors and major cardiac events among adult survivors of childhood cancer. J. Clin. Oncol. 31, 3673–3680 (2013).
Armstrong, G. T. et al. Reduction in late mortality among 5-year survivors of childhood cancer. N. Engl. J. Med. 374, 833–842 (2016).
Chow, E. J., Pihoker, C., Hunt, K., Wilkinson, K. & Friedman, D. L. Obesity and hypertension among children after treatment for acute lymphoblastic leukemia. Cancer 110, 2313–2320 (2007).
Reilly, J. J., Blacklock, C. J., Dale, E., Donaldson, M. & Gibson, B. E. S. Resting metabolic rate and obesity in childhood acute lymphoblastic leukaemia. Int. J. Obesity 20, 1130–1132 (1996).
Warner, J. T., Bell, W., Webb, D. K. H. & Gregory, J. W. Daily energy expenditure and physical activity in survivors of childhood malignancy. Pediatr. Res. 43, 607–613 (1998).
Poirier, P. et al. Obesity and cardiovascular disease: pathophysiology, evaluation, and effect of weight loss—an update of the 1997 American Heart Association Scientific Statement on obesity and heart disease from the Obesity Committee of the Council on Nutrition, Physical Activity, and Metabolism. Circulation 113, 898–918 (2006).
Ndumele, C. E. et al. Obesity and subtypes of incident cardiovascular disease. J. Am. Heart Assoc. 5, e003921 (2016).
Flegal, K. M., Kit, B. K., Orpana, H. & Graubard, B. I. Association of all-cause mortality with overweight and obesity using standard body mass index categories a systematic review and meta-analysis. JAMA 309, 71–82 (2013).
Locke, A. E. et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197–206 (2015).
Turcot, V. et al. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat. Genet. 50, 26–41 (2018).
Inouye, M. et al. Genomic risk prediction of coronary artery disease in 480,000 adults: implications for primary prevention. J. Am. Coll. Cardiol. 72, 1883–1893 (2018).
Khera, A. V. et al. Polygenic prediction of weight and obesity trajectories from birth to adulthood. Cell 177, 587–596 (2019).
Green, D. M. et al. Risk factors for obesity in adult survivors of childhood cancer: a report from the Childhood Cancer Survivor Study. J. Clin. Oncol. 30, 246–255 (2012).
Meacham, L. R. et al. Body mass index in long-term adult survivors of childhood cancer—a report of the Childhood Cancer Survivor Study. Cancer 103, 1730–1739 (2005).
Pulit, S. L. et al. Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. Hum. Mol. Genet. 28, 166–174 (2019).
Vogelezang, S. et al. Novel loci for childhood body mass index and shared heritability with adult cardiometabolic traits. PLoS Genet. 16, e1008718 (2020).
Bradfield, J. P. et al. A trans-ancestral meta-analysis of genome-wide association studies reveals loci associated with childhood obesity. Hum. Mol. Genet. 28, 3327–3338 (2019).
Yengo, L. et al. Meta-analysis of genome-wide association studies for height and body mass index in similar to 700 000 individuals of European ancestry. Hum. Mol. Genet. 27, 3641–3649 (2018).
Chow, E. J. et al. Prediction of ischemic heart disease and stroke in survivors of childhood cancer. J. Clin. Oncol. 36, 44–52 (2018).
Chow, E. J. et al. Individual prediction of heart failure among childhood cancer survivors. J. Clin. Oncol. 33, 394–U326 (2015).
Sapkota, Y. et al. Whole-genome sequencing of childhood cancer survivors treated with cranial radiation therapy identifies 5p15.33 locus for stroke: a report from the St. Jude Lifetime Cohort Study. Clin. Cancer Res. 25, 6700–6708 (2019).
Sapkota, Y. et al. Genetic variants associated with therapy-related cardiomyopathy among childhood cancer survivors of African ancestry. Cancer Res. 81, 2556–2565 (2021).
Sapkota, Y. et al. Genome-wide association study in irradiated childhood cancer survivors identifies HTR2A for subsequent basal cell carcinoma. J. Invest. Dermatol. 139, 2042–2045 (2019).
Sapkota, Y. et al. A novel locus predicts spermatogenic recovery among childhood cancer survivors exposed to alkylating agents. Cancer Res. 80, 3755–3764 (2020).
Wang, Z. et al. Genetic risk for subsequent neoplasms among long-term survivors of childhood cancer. J. Clin. Oncol. 36, 2078–2087 (2018).
Sapkota, Y. et al. Contribution of polygenic risk to hypertension among long-term survivors of childhood cancer. JACC CardioOncol. 3, 76–84 (2021).
Qi, Q.B. et al. Fried food consumption, genetic risk, and body mass index: gene-diet interaction analysis in three US cohort studies. BMJ 348, g1610 (2014).
Qi, Q. B. et al. Sugar-sweetened beverages and genetic risk of obesity. N. Engl. J. Med. 367, 1387–1396 (2012).
Tyrrell, J. et al. Gene–obesogenic environment interactions in the UK Biobank study. Int. J. Epidemiol. 46, 559–575 (2017).
Krul, A. J., Daanen, H. A. M. & Choi, H. Self-reported and measured weight, height and body mass index (BMI) in Italy, the Netherlands and North America. Eur. J. Public Health 21, 414–419 (2011).
Wang, Y., Rimm, E. B., Stampfer, M. J., Willett, W. C. & Hu, F. B. Comparison of abdominal adiposity and overall obesity in predicting risk of type 2 diabetes among men. Am. J. Clin. Nutr. 81, 555–563 (2005).
Collaborators, G. B. D. O. et al. Health effects of overweight and obesity in 195 countries over 25 years. N. Engl. J. Med. 377, 13–27 (2017).
Natarajan, P. et al. Polygenic risk score identifies subgroup with higher burden of atherosclerosis and greater relative benefit from statin therapy in the primary prevention setting. Circulation 135, 2091–2101 (2017).
Khera, A. V. et al. Genetic risk, adherence to a healthy lifestyle, and coronary disease. N. Engl. J. Med. 375, 2349–2358 (2016).
Mega, J. L. et al. Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: an analysis of primary and secondary prevention trials. Lancet 385, 2264–2271 (2015).
Pharoah, P. D. P., Antoniou, A. C., Easton, D. F. & Ponder, B. A. J. Polygenes, risk prediction, and targeted prevention of breast cancer. N. Engl. J. Med. 358, 2796–2803 (2008).
Marston, N. A. et al. Predicting benefit from evolocumab therapy in patients with atherosclerotic disease using a genetic risk score: results from the FOURIER trial. Circulation 141, 616–623 (2020).
Damask, A. et al. Patients with high genome-wide polygenic risk scores for coronary artery disease may receive greater clinical benefit from alirocumab treatment in the ODYSSEY OUTCOMES trial. Circulation 141, 624–636 (2020).
Yanovski, S. Z. & Yanovski, J. A. Long-term drug treatment for obesity: a systematic and clinical review. JAMA 311, 74–86 (2014).
Wadden, T. A., Webb, V. L., Moran, C. H. & Bailer, B. A. Lifestyle modification for obesity: new developments in diet, physical activity, and behavior therapy. Circulation 125, 1157–1170 (2012).
Martin, A. R. et al. Clinical use of current polygenic risk scores may exacerbate health disparities. Nat. Genet. 51, 584–591 (2019).
Howell, C. R. et al. Cohort profile: the St. Jude Lifetime Cohort Study (SJLIFE) for paediatric cancer survivors. Int. J. Epidemiol. 50, 39–49 (2021).
Hudson, M. M. et al. Prospective medical assessment of adults surviving childhood cancer: study design, cohort characteristics, and feasibility of the St. Jude Lifetime Cohort study. Pediatr. Blood Cancer 56, 825–836 (2011).
Bhakta, N. et al. The cumulative burden of surviving childhood cancer: an initial report from the St Jude Lifetime Cohort Study (SJLIFE). Lancet 390, 2569–2582 (2017).
Leisenring, W. M. et al. Pediatric cancer survivorship research: experience of the Childhood Cancer Survivor Study. J. Clin. Oncol. 27, 2319–2327 (2009).
Robison, L. L. et al. Study design and cohort characteristics of the childhood cancer survivor study: a multi-institutional collaborative project. Med. Pediatr. Oncol. 38, 229–239 (2002).
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).
McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).
Chang, C. C. et al. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 7 (2015).
Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).
Morton, L. M. et al. Genome-wide association study to identify susceptibility loci that modify radiation-related risk for breast cancer after childhood cancer. J. Natl Cancer Inst. 109, djx058 (2017).
Das, S. et al. Next-generation genotype imputation service and methods. Nat. Genet. 48, 1284–1287 (2016).
The 1000 Genomes Project Consortium. A global reference for human genetic variation. Nature 526, 68–74 (2015).
Monda, K. L. et al. A meta-analysis identifies new loci associated with body mass index in individuals of African ancestry. Nat. Genet. 45, 690–696 (2013).
Ng, M. C. Y. et al. Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium. PLoS Genet. 13, e1006719 (2017).
Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults—the evidence report. National Institutes of Health. Obes. Res. 6, 51S–209S (1998).
Petersen, R., Pan, L. P. & Blanck, H. M. Racial and ethnic disparities in adult obesity in the United States: CDC’s tracking to inform state and local action. Prev. Chronic Dis. 16, E46 (2019).
Price, A. L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).
Price, A. L., Zaitlen, N. A., Reich, D. & Patterson, N. New approaches to population stratification in genome-wide association studies. Nat. Rev. Genet. 11, 459–463 (2010).
Ogden, C. L. et al. Prevalence of overweight and obesity in the United States, 1999–2004. JAMA 295, 1549–1555 (2006).
The St. Jude Lifetime Cohort (U01 CA195547: M.M.H. and K.K.N.) and the Childhood Cancer Survivor Study (U24 CA55727; G.T.A.) are supported by the National Cancer Institute at the National Institutes of Health and the Cancer Center Support CORE grant (CA21765: C. Roberts). The CCSS original cohort genotyping was supported by the Intramural Research Program of the National Cancer Institute, National Institutes of Health. This work is also supported by R01 CA261898 (Y.S.) and R01 CA216354 (Y.Y. and J.Z.) from the National Cancer Institute at the National Institutes of Health and the American Lebanese Syrian Associated Charities in Memphis, Tennessee.
The authors declare no competing interests.
Peer review information
Nature Medicine thanks Struan Grant and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary handling editor: Anna Maria Ranzoni, in collaboration with the Nature Medicine team.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Sapkota, Y., Qiu, W., Dixon, S.B. et al. Genetic risk score enhances the risk prediction of severe obesity in adult survivors of childhood cancer. Nat Med 28, 1590–1598 (2022). https://doi.org/10.1038/s41591-022-01902-3
This article is cited by
Surveillance cardiopulmonary exercise testing can risk-stratify childhood cancer survivors: underlying pathophysiology of poor exercise performance and possible room for improvement
Nature Reviews Endocrinology (2022)
Nature Medicine (2022)