HFHeinz Freisling
Papers(2)
Adiposity distributio…Metabolically Defined…
Collaborators(10)
Marc J GunterInge HuybrechtsJames YarmolinskyLaure DossusLi LiLucy J GoudswaardLudmila VodickovaMaria-Jose SánchezMatthew A LeeM. Playdon
Institutions(7)
Centre International …Imperial College Lond…Qilu Hospital of Shan…The University of Bri…Univerzita KarlovaCentro De Investigaci…University of Utah

Papers

Adiposity distribution and risks of 12 obesity-related cancers: a Mendelian randomization analysis

Abstract Introduction There is convincing evidence that overall adiposity increases the risks of several cancers. Whether the distribution of adiposity plays a similar role is unclear. Methods We used 2-sample Mendelian randomization (MR) to examine causal relationships of 5 adiposity distribution traits (abdominal subcutaneous adipose tissue (ASAT); visceral adipose tissue (VAT); gluteofemoral adipose tissue (GFAT); liver fat; and pancreas fat) with the risks of 12 obesity-related cancers (endometrial, ovarian, breast, colorectal, pancreas, multiple myeloma, liver, kidney (renal cell), thyroid, gallbladder, esophageal adenocarcinoma, and meningioma). Results Sample size across all genome-wide association studies (GWAS) ranged from 8407 to 728 896 (median: 57 249). We found evidence that higher genetically predicted ASAT increased the risks of endometrial cancer, liver cancer, and esophageal adenocarcinoma (odds ratios (OR) and 95% confidence intervals (CI) per standard deviation (SD) higher ASAT = 1.79 (1.18 to 2.71), 3.83 (1.39 to 10.53), and 2.34 (1.15 to 4.78), respectively). Conversely, we found evidence that higher genetically predicted GFAT decreased the risks of breast cancer and meningioma (ORs and 95% CIs per SD higher genetically predicted GFAT = 0.77 (0.62 to 0.97) and 0.53 (0.32 to 0.90), respectively). We also found evidence for an effect of higher genetically predicted VAT and liver fat on increased liver cancer risk (ORs and 95% CIs per SD higher genetically predicted adiposity trait = 4.29 (1.41 to 13.07) and 4.09 (2.29 to 7.28), respectively). Discussion Our analyses provide novel insights into the relationship between adiposity distribution and cancer risk. These insights highlight the potential importance of adipose tissue distribution alongside maintaining a healthy weight for cancer prevention.

Metabolically Defined Body Size Phenotypes and Risk of Endometrial Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC)

Abstract Background: Obesity is a risk factor for endometrial cancer but whether metabolic dysfunction is associated with endometrial cancer independent of body size is not known. Methods: The association of metabolically defined body size phenotypes with endometrial cancer risk was investigated in a nested case–control study (817 cases/ 817 controls) within the European Prospective Investigation into Cancer and Nutrition (EPIC). Concentrations of C-peptide were used to define metabolically healthy (MH; <1st tertile) and metabolically unhealthy (MU; ≥1st tertile) status among the control participants. These metabolic health definitions were combined with normal weight (NW); body mass index (BMI)<25 kg/m2 or waist circumference (WC)<80 cm or waist-to-hip ratio (WHR)<0.8) and overweight (OW; BMI≥25 kg/m2 or WC≥80 cm or WHR≥0.8) status, generating four phenotype groups for each anthropometric measure: (i) MH/NW, (ii) MH/OW, (iii) MU/NW, and (iv) MU/OW. Results: In a multivariable-adjusted conditional logistic regression model, compared with MH/NW individuals, endometrial cancer risk was higher among those classified as MU/NW [ORWC, 1.48; 95% confidence interval (CI), 1.05–2.10 and ORWHR, 1.68; 95% CI, 1.21–2.35] and MU/OW (ORBMI, 2.38; 95% CI, 1.73–3.27; ORWC, 2.69; 95% CI, 1.92–3.77 and ORWHR, 1.83; 95% CI, 1.32–2.54). MH/OW individuals were also at increased endometrial cancer risk compared with MH/NW individuals (ORWC, 1.94; 95% CI, 1.24–3.04). Conclusions: Women with metabolic dysfunction appear to have higher risk of endometrial cancer regardless of their body size. However, OW status raises endometrial cancer risk even among women with lower insulin levels, suggesting that obesity-related pathways are relevant for the development of this cancer beyond insulin. Impact: Classifying women by metabolic health may be of greater utility in identifying those at higher risk for endometrial cancer than anthropometry per se.

286Works
2Papers
33Collaborators
Colorectal NeoplasmsNeoplasmsCardiovascular DiseasesBreast NeoplasmsProstatic NeoplasmsGenetic Predisposition to DiseaseLiver NeoplasmsEndometrial Neoplasms
Keywords
Dietary exposure assessmentObesityNutrition epidemiologyCancer