Page 110 - EJMO-9-3

Eurasian Journal of
Medicine and Oncology Vitamin D and breast cancer

age, body mass index, hormone levels, and lifestyle factors information was obtained through GWAS techniques.
(such as smoking, alcohol consumption, and exercise Relevant datasets were retrieved and downloaded by
habits). Subsequently, statistical methods (such as multiple visiting the GWAS Data Aggregation Website (https://
regression analysis) were used to evaluate whether the gwas.mrcieu.ac.uk/), operated by the University of
association between genetic variants and exposure factors Bristol’s Epidemiological Research Unit. The website
remained significant after adjusting for these confounding integrated data from multiple GWAS consortia and
factors (34). By reviewing relevant literature and databases, provided the main source of data for this study. The
we ensured that the selected genetic variants had not been genetic variants associated with Vitamin D levels in
reported to be associated with these confounding factors in this study were derived from the ebi-a-GCST90000618
previous studies. In addition, when conducting MR analysis, database, which documented a large-scale GWAS
the MR-Egger intercept method and the MR-Pleiotropy involving 496,946 participants of European ancestry.
RESidual Sum and Outlier (PRESSO) method were employed Data for breast cancer were derived from the R11 version
to detect horizontal pleiotropy. These two methods can, of the FinnGen study’s finngen_R11_C3_BREAST_
to some extent, reflect whether genetic variants affect the EXALLC dataset, which covered 20,586 breast cancer
outcome through other pathways, thus indirectly assessing patients and 201,494 control individuals. As of June 24,
the independence of genetic variants from confounding 2024, the latest data freeze R11 reveals a total sample size
factors. Figure 1 illustrates the flowchart of the MR analysis. of 453,733 (including 254,618 women and 199,115 men).
A total of 21,311,942 genetic variants were analyzed and
2.2. Data source 2,447 disease phenotypes were available for research,
The data for this study were obtained from publicly available details of which can be found on the project’s official
database resources on the internet. Genetic variation website (https://r11.finngen.fi/).

Figure 1. Flow chart of the two-sample Mendelian randomization (MR) study
Abbreviations: IV: Instrumental variable; PRESSO: Pleiotropy RESidual Sum and Outlier; SNP: Single nucleotide polymorphism.

Volume 9 Issue 3 (2025) 102 doi: 10.36922/EJMO025130064