Case-control study finds vitamin D deficiency and receptor polymorphisms linked to breast cancer risk in Bangladeshi women, suggesting clinicogenetic utility for early risk screening.
Breast cancer is increasing in Bangladesh with high rate of aggressive subtypes such as Triple-Negative Breast Cancer (TNBC). But population-specific genetic evidence remains limited. This study evaluated the association of Vitamin D Receptor ( VDR ) polymorphisms and serum 25-hydroxyvitamin D [25(OH)D] levels with breast cancer risk among Bangladeshi women. This case-control study was conducted involving 300 breast cancer patients and 204 healthy controls. Serum 25(OH)D concentrations were measured using high-performance liquid chromatography (HPLC) and VDR polymorphisms ( FokI , BsmI , ApaI , and TaqI ) were genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Associations were assessed using multimodal logistic regression and receiver operating characteristic (ROC) curve analyses. Breast cancer patients exhibited significantly lower serum 25(OH)D levels than controls ( p = 0.002). Under a recessive inheritance model, the FokI C/C genotype found to be a major risk factor for breast cancer (OR = 3.53, p < 0.001). Subtype-stratified analysis revealed notable enrichment of the TaqI T/T genotype among TNBC patients ( p = 0.007). An integrated clinicogenetic model combining FokI C/C, TaqI T/T, and BsmI G/G genotypes with age, body mass index (BMI), and menopausal status demonstrated strong discriminatory performance (AUC = 0.776). The model outperforms a genotype-only model (AUC = 0.670; p < 0.001). These findings indicate that FokI C/C and TaqI T/T polymorphisms are important genetic markers of breast cancer susceptibility in Bangladeshi women. The TaqI T/T showed subtype-specific enrichment in TNBC. The observed association between vitamin D deficiency and breast cancer risk highlights the potential contribution of vitamin D signaling pathways to disease development. The proposed clinicogenetic model may support early risk stratification and personalized screening approaches, although validation in independent South Asian populations is required.
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Mowla et al. (2026) studied this question.
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