scholarly journals Variation in body fat distribution and breast cancer risk in the families of patients with breast cancer and control families

Cancer ◽  
1993 ◽  
Vol 71 (9) ◽  
pp. 2764-2768 ◽  
Author(s):  
David V. Schapira ◽  
Nagi B. Kumar ◽  
Gary H. Lyman
2012 ◽  
Vol 23 (4) ◽  
pp. 565-574 ◽  
Author(s):  
Temidayo O. Ogundiran ◽  
Dezheng Huo ◽  
Adeniyi Adenipekun ◽  
Oladapo Campbell ◽  
Rasaaq Oyesegun ◽  
...  

Cancers ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 5053
Author(s):  
Dennis Freuer ◽  
Jakob Linseisen ◽  
Tracy A. O’Mara ◽  
Michael Leitzmann ◽  
Hansjörg Baurecht ◽  
...  

Background: Mounting evidence shows that adiposity increases female-specific cancer risk, but the role of body fat distribution is less clear. We used a two-sample Mendelian randomization (MR) approach to elucidate causal relations of body fat distribution to the risks of breast, endometrial and ovarian cancers and their subtypes. Methods: Body composition was assessed using segmental bioelectrical impedance analysis, yielding trunk, arm, and leg fat ratios (TFR, AFR, LFR) and BMI including 195,043 and 434,794 European women, respectively. The sample sizes for the outcomes ranged between 58,396 and 228,951. Causal effects were estimated per one standard deviation increment in the respective exposure within the radial regression framework. Robust sensitivity analyses were performed to verify MR assumptions. In a multivariable MR setting, the proportion of risk attributable to overall and abdominal fat content was assessed. Results: TFR, which represents abdominal fat content, was associated with ovarian cancer and its clear cell and endometrioid histotypes independent of overall fat content. BMI was inversely associated with breast cancer and its ER− and ER+ subtypes, but positively with endometrial cancer and ovarian cancer, including its endometrioid histotype. These estimates were confirmed using AFR as proxy for overall body fat. Conclusions: Visceral adiposity seems to be a driver of elevated ovarian cancer risk, particularly of the endometrioid and clear cell ovarian cancer histotypes. General adiposity decreases the risk of breast cancer but increases the risk of endometrial and ovarian cancer.


1990 ◽  
Vol 82 (4) ◽  
pp. 286-290 ◽  
Author(s):  
R. Ballard-Barbash ◽  
A. Schatzkin ◽  
C. L. Carter ◽  
W. B. Kannel ◽  
B. E. Kreger ◽  
...  

Author(s):  
Thanh Thi Ngoc Nguyen ◽  
Giau Thi Ngoc Mai ◽  
Hue Thi Nguyen

Breast cancer is the most common cancer for women around the world. The presence of single nucleotide polymorphisms (SNP) on or near the coding region of breast cancer susceptibility genes can affect the regulation of gene expression, which may increase or decrease the risk of breast cancer. BARX2 was showed to stimulate the expression of ERS1, which involved in the development of breast cancer. SNP rs7107217 on 152kb downstream of the BARX2 could affect the level of protein BARX2 and had been proved to associate with the breast cancer risk in populations similar to Vietnamese, including Chinese and Korean. In this study, rs7107217 was genotyped and initially detemined the association with the breast cancer risk in Vietnamese. Real-time PCR HRM was optimized and used to genotype rs7107217 in 117 breast cancer cases and 105 healthy controls. Thereafter, the correlation of this SNP with the risk of breast cancer was initially determined by analyzing the differences in allelic and genotypic frequencies between cases and control groups. The results showed the optimal rs7107217 genotyping condition was successfully developed with the high sensitivity, specificity, and consistency. SNP rs7107217 had high polymorphism with the frequency of minor allele C of 29.9% and 35.3% in case and control, respectively. SNP rs7107217 had been found no association with the breast cancer risk (C vs A: P = 0.23, OR (95% CI) = 0.79 (0.53 – 1.17)). However with the low reliability of the analysis (11.71%) and the high potential related to the formation of breast cancer, the association between rs7107217 and breast cancer risk in Vietnamese population should be further conducted on a larger sample size to get higher accuracy.


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