Muktar Ahmed1,2,3, Anwar Mulugeta1,3,4, S Hong Lee1,3, Ville-Petteri Mäkinen1,5, Terry Boyle1,3, Elina Hyppönen6,7. 1. Australian Centre for Precision Health, Unit of Clinical and Health Sciences and Unit of Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia. 2. Department of Epidemiology, Faculty of Public Health, Jimma University Institute of Health, Jimma, Ethiopia. 3. South Australian Health and Medical Research Institute, Adelaide, SA, Australia. 4. Department of Pharmacology and Clinical Pharmacy, College of Health Sciences, Addis Ababa, Ethiopia. 5. Computational Systems Biology Program, Precision Medicine Theme, South Australian Health and Medical Research Institute, Adelaide, Australia. 6. Australian Centre for Precision Health, Unit of Clinical and Health Sciences and Unit of Allied Health and Human Performance, University of South Australia, Adelaide, SA, Australia. Elina.Hypponen@unisa.edu.au. 7. South Australian Health and Medical Research Institute, Adelaide, SA, Australia. Elina.Hypponen@unisa.edu.au.
Abstract
BACKGROUND: Observational and Mendelian randomization (MR) studies link obesity and cancer, but it remains unclear whether these depend upon related metabolic abnormalities. METHODS: We used information from 321,472 participants in the UK biobank, including 30,561 cases of obesity-related cancer. We constructed three genetic instruments reflecting higher adiposity together with either "unfavourable" (82 SNPs), "favourable" (24 SNPs) or "neutral" metabolic profile (25 SNPs). We looked at associations with 14 types of cancer, previously suggested to be associated with obesity. RESULTS: All genetic instruments had a strong association with BMI (p < 1 × 10-300 for all). The instrument reflecting unfavourable adiposity was also associated with higher CRP, HbA1c and adverse lipid profile, while instrument reflecting metabolically favourable adiposity was associated with lower HbA1c and a favourable lipid profile. In MR-inverse-variance weighted analysis unfavourable adiposity was associated with an increased risk of non-hormonal cancers (OR = 1.22, 95% confidence interval [CI]:1.08, 1.38), but a lower risk of hormonal cancers (OR = 0.80, 95%CI: 0.72, 0.89). From individual cancers, MR analyses suggested causal increases in the risk of multiple myeloma (OR = 1.36, 95%CI: 1.09, 1.70) and endometrial cancer (OR = 1.77, 95%CI: 1.16, 2.68) by greater genetically instrumented unfavourable adiposity but lower risks of breast and prostate cancer (OR = 0.72, 95%CI: 0.61, 0.83 and OR = 0.81, 95%CI: 0.68, 0.97, respectively). Favourable or neutral adiposity were not associated with the odds of any individual cancer. CONCLUSIONS: Higher adiposity associated with a higher risk of non-hormonal cancer but a lower risk of some hormone related cancers. Presence of metabolic abnormalities might aggravate the adverse effects of higher adiposity on cancer. Further studies are warranted to investigate whether interventions on adverse metabolic health may help to alleviate obesity-related cancer risk.
BACKGROUND: Observational and Mendelian randomization (MR) studies link obesity and cancer, but it remains unclear whether these depend upon related metabolic abnormalities. METHODS: We used information from 321,472 participants in the UK biobank, including 30,561 cases of obesity-related cancer. We constructed three genetic instruments reflecting higher adiposity together with either "unfavourable" (82 SNPs), "favourable" (24 SNPs) or "neutral" metabolic profile (25 SNPs). We looked at associations with 14 types of cancer, previously suggested to be associated with obesity. RESULTS: All genetic instruments had a strong association with BMI (p < 1 × 10-300 for all). The instrument reflecting unfavourable adiposity was also associated with higher CRP, HbA1c and adverse lipid profile, while instrument reflecting metabolically favourable adiposity was associated with lower HbA1c and a favourable lipid profile. In MR-inverse-variance weighted analysis unfavourable adiposity was associated with an increased risk of non-hormonal cancers (OR = 1.22, 95% confidence interval [CI]:1.08, 1.38), but a lower risk of hormonal cancers (OR = 0.80, 95%CI: 0.72, 0.89). From individual cancers, MR analyses suggested causal increases in the risk of multiple myeloma (OR = 1.36, 95%CI: 1.09, 1.70) and endometrial cancer (OR = 1.77, 95%CI: 1.16, 2.68) by greater genetically instrumented unfavourable adiposity but lower risks of breast and prostate cancer (OR = 0.72, 95%CI: 0.61, 0.83 and OR = 0.81, 95%CI: 0.68, 0.97, respectively). Favourable or neutral adiposity were not associated with the odds of any individual cancer. CONCLUSIONS: Higher adiposity associated with a higher risk of non-hormonal cancer but a lower risk of some hormone related cancers. Presence of metabolic abnormalities might aggravate the adverse effects of higher adiposity on cancer. Further studies are warranted to investigate whether interventions on adverse metabolic health may help to alleviate obesity-related cancer risk.
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