Introduction
Cancer is one of the leading causes of death worldwide and the number of
cancer cases is increasing. There were an estimated 19.3 million cancer
cases and almost 10.0 million cancer deaths around the world in 20201. With this growing global burden, the prevention of
cancer is one of the most significant public health challenges of the
21st century. Therefore, it is urgent to find out cancer risk factors.
Birth weight (BW) is considered a marker of the intrauterine environment
and has been widely studied in epidemiological researches. A mass of
evidence implicates the essential role of early life factors in the
occurrence of adult-onset diseases, including cancers2. According to the Developmental Origins of Health
and Disease hypothesis, fetal adaptive strategies to the adverse
intrauterine environment produce long-term consequences for poor health3. Over the
decades, a number studies reported associations between BW and
increased- or decreased- cancer risks, especially breast4-23 and testicular cancers 24-33.
The World Cancer Research Fund have concluded that the heavier people
weighed at birth, the higher risk of some cancers they got. From their
viewpoints, there is strong evidence that BW is causally associated with
increased risk of breast cancer and so on34.
However, after summarizing the most relating studies, it turns out that
evidence to reliably establish a causal role of BW on cancer is
obviously discrepant. One observational cohort study of BW and overall
cancer found that BW was positively correlated with the risk of lung
cancer and colon cancer. Yet, no significant trend was observed in
breast cancer risk 35. But another cohort study
reported that breast cancer were positively correlated with BW36.
Observational epidemiological studies are prone to confounding, reverse
causation, and various biases and have generated findings that proved to
be unreliable indicators of the causal effects of modifiable exposures
on disease outcomes 37. To avoid these disadvantages,
Mendelian randomization (MR) analysis came into existence. It is
analogous to a randomized clinical trial where randomization to genotype
takes place at conception which is less likely to be affected by
confounding. The approach is being widely applied in many
studies38.
Thus, this analysis aims to explore the effect of BW on cancer by a
dose-response meta-analysis and MR analysis. The genetic data for BW
were used as an instrumental variable to perform an MR analysis and
observational studies were selected to establish a dose-response
meta-analysis.