Discussion
Main Findings
The meta-analysis suggested that higher BW was relative to the risk of
many cancers including breast cancer, testicular cancer, colorectal
cancer, prostate cancer, ovarian cancer while higher BW was the
protective factor of endometrial cancer. But only breast cancer and
testicular cancer had a non-linear relationship with BW. With the
increase of BW, the slope of the dose‐response curve of breast cancer
increased. For testicular cancer, the slope increased before 3000g and
decreased above 3000g. Our results were consistent with the conclusions
of most previous articles. Current meta-analyses of BW and breast cancer
reported that higher BW was relative to breast cancer53-55. Some found that the relationship was linear53, 55 but some indicated that it was nonlinear54. One meta-analysis also found a U-shaped
distribution between BW and subsequent risk for testicular cancer, but
the risk of corresponding BW group was not specifically reported56. While another meta-analysis showed that there was
no significant correlation in high BW 57.
Strengths
Our study has several advantages. Firstly, it’s the first study to
systematically elucidated the relationship between BW and the risk of
multiple cancers by combining dose-response meta-analysis and mendelian
randomization analysis. In dose-response meta-analysis, we synthesized
several articles to calculate the pooled RR and the changing trend of
cancer risk with the increase of dose. In Mendelian randomization
analysis, it could avoid the interference of confounding factors to
calculate the effect value from the causal level. Secondly, when we
collected studies in dose-response meta-analysis, we calculated the
missing data of some studies instead of excluding them which made more
articles were included in our study. Thirdly, we used three models for
dose-response curve fitting to explore the optimal dose-response
relationship. We changed the percentage of three nodes in the restricted
cubic spline model according to different cancers data to ensure the
accuracy of the fitting effect. Fourthly, we chose the newest GWAS
studies of BW and cancers based on a large consortium which provided
enough sample size to perform statistical calculations. And according to
the power value and F statistic, we ensured that under the current
sample size and genetic variation interpretation our MR result was
statistically persuasive.
Limitations
Yet there are still some limitations in our study. Firstly, when we
gathered data on BW with the risk of breast cancer, we found moderate
heterogeneity among articles (I2=48%). But in the
sensitivity analyses by removing one study at a time, we did not observe
obvious fluctuation of the result, with a range from 1.08 (95% CI,
1.02-1.15) to 1.13 (95% CI, 1.06-1.19). In addition, except for breast
cancer and testicular cancer, studies included in other cancers were
fewer so it may increase publication bias. But all of them passed the
Egger’s test (Povarian=0.41,
Pcolorectal=0.31, Pendometrial=0.68,
Pprostate=0.59). Secondly, most of our research articles
came from high-income countries especially for the Mendelian
randomization analysis which the population was all from Europe. It may
limit the generalization of the results. Therefore, it should be
considered carefully when applied the results.
Interpretation
Several studies had shown that high BW was related to the increase of
intrauterine estrogen 58, 59. Significantly, excessive
intrauterine estrogen exposure was often considered as the pathogenesis
of both breast cancer and testicular cancer 60, 61. In
the process of individual growth, the development of the mammary gland
and testis was regulated by estrogen. Trichopoulos et al. early reported
that breast cancer may originate from the uterus in 199062. The study suggested that prenatal exposure to
estrogen is the highest at any other time in a woman’s life. After 4
weeks of pregnancy, most estrogens in the maternal body were produced by
the placenta that was significantly higher than before pregnancy which
estrogen was produced by the ovary 63. One study also
found that the occurrence of breast cancer may be due to the imbalance
of the self-renewal function of normal stem cells. Estrogen could
promote cell proliferation, which also made it a cancer promoter, thus
affecting cell growth and mutation 64, 65. During the
fetal period, excessive estrogen can inhibit the secretion of Miller
inhibitory substance (MIS) and the development of Leydig cells which
produced testosterone, thereby affecting the development of testicles
and then promoting the incidence rate of testicular cancer61. On the other hand, intrauterine growth retardation
(IUGR) may lead to a lower BW which is associated with cryptorchidism
and maldescended testis 66, 67. Both of them were
considered to be risk factors for testicular cancer68. Therefore, low BW also increases the risk of
testicular cancer.
However, in our two-sample MR, we provided no evidence to support the
association between BW and cancer which meant that BW may not affect
tumorigenesis as an independent factor. We only found that BW had a
casual effect of invasive mucinous ovarian cancer. But the incidence
rate of this subtype of ovarian cancer was very low69, and most of them were metastatic cancer. These
positive results did not affect the total conclusion of the irrelevant
relationship between BW and ovarian cancer. Due to the lack of
corresponding GWAS articles, we did not analyze the causal relationship
between testicular cancer and BW.
Our MR analysis contradicted the traditional observational results. The
MR analysis used single nucleotide polymorphisms (SNPs) relative to the
exposure to infer a causal relationship between the exposure and the
outcome. Compared with an observational study, it could avoid potential
confounding and reverse causality. In addition, our MR results showed
consistency when using different MR methods and the sensitivity analysis
under sufficient statistical power. Therefore, we were sure that our MR
results can better illustrate the relationship between BW and cancer.
There were some reasons to explain the contradiction between
meta-analysis and MR analysis. Firstly, BW was correlated with other
characteristics such as birth length, body mass index, menarche age and
so on which would also affect the risk of cancers. One newest
meta-analysis of BW and cancer risk found that after adjusting the
potential confounding factors the relationship was null or weak52. Silva et al. reassessed the relationship between
birth size and breast cancer risk from 32 studies and found that birth
length is the strongest independent indicator of breast cancer risk.
After adjusting for birth length, the association with BW disappeared70. Meanwhile, as mentioned above, low BW may be
caused by fetal intrauterine dysplasia which was also the risk factor of
cryptorchidism 66, 67. All suggested that BW may not
be a direct factor in the occurrence of testicular cancer. Secondly,
compared with genetic factors, BW is more affected by maternal nutrition
and hormones. The growth of the fetus depends on the nutrition provided
by the mother through the placenta. As the report of Horikoshi M et al.45, the genes they identified associated with BW could
only explained 15% of the weight variation. Therefore, the increase of
BW may be related to the risk of cancer through other non genetic
factors. But so far, It is difficult to distinguish the role of genetic
and non genetic factors in the relationship between BW and the
developing of cancers. What’s more, Horikoshi M et al. excluded
individuals with extreme BW when collecting the data which we thought to
be relative to cancer risk. To some extent, we lacked genetic variation
for extreme BW that may affect the results.