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Nuclear magnetic resonance-determined lipoprotein profile and risk of breast cancer: a Mendelian randomization study

  • Epidemiology
  • Published:
Breast Cancer Research and Treatment Aims and scope Submit manuscript

Abstract

Purpose

While crudely quantified lipoproteins have been reported to affect the risk of breast cancer, the effects of subclass lipoproteins characterized by particle size, particle number, and lipidomes remain unknown.

Methods

Utilizing nuclear magnetic resonance-based GWAS of 85 lipoprotein traits, we performed two-sample univariable Mendelian randomization (MR) to evaluate the causal relationship between each trait with breast cancer (Ncase/control = 133,384/113,789) and with its estrogen receptor (ER) subtypes. Then, we applied multivariable MR to investigate the independent effects considering both general and central obesity.

Results

In univariable MR, a heterogeneous effect of subclass high-density lipoproteins (HDL) was observed, in which small HDL traits (ORs ranged from 0.89 to 0.94) were associated with a decreased risk of breast cancer while non-small HDLs traits (OR ranged from 1.04 to 1.08) were associated with an increased risk of breast cancer. Very-low-density lipoproteins (VLDL) traits and serum total triglycerides (TG) were associated with a decreased risk of breast cancer (ORs ranged from 0.88 to 0.94). Similar association patterns were found for ER + subtype. In multivariable MR, only the protective effects of small HDL, VLDL and TG on ER + subtype remained significant.

Conclusion

We identified a heterogeneous effect of subclass HDLs and a consistent protective effect of VLDL on breast cancer. Only the effects of small HDL and VLDL on ER + subtype remained robust after controlling for obesity. These findings provide new insight into the causal pathway underlying lipoproteins and breast cancer.

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Data availability

All data used in this study are publicly available summary-level data, with the relevant studies cited.

Abbreviations

BC:

Breast cancer

BMI:

Body mass index

CI:

Confidence interval

ER:

Estrogen-receptor

FDR:

False discovery rate

GWAS:

Genome-wide association study

HDL:

High-density lipoproteins

HR:

Hazard ratio

IDL:

Intermediate-density lipoproteins

IVs:

Instrumental variables

IVW:

Inverse-variance-weighted

LD:

Linkage disequilibrium

LDL:

Low-density lipoproteins

MR:

Mendelian randomization

MVMR:

Multivariable Mendelian randomization

NMR:

Nuclear magnetic resonance

OR:

Odds ratio

SNP:

Single nucleotide polymorphisms

TG:

Serum total triglycerides

VLDL:

Very-low-density lipoproteins

WHRadjBMI:

BMI-adjusted waist-to-hip ratio

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Funding

This study was supported by funds from the National Natural Science Foundation of China (81874282, U22A20359, 81874283, 81673255), the National Key R&D Program of China (2020YFC2006505, 2022YFC3600600, 2022YFC3600604), the Health Commission of Sichuan Province (20PJ093), the Key R&D Program of Sichuan, China (2022YFS0055), the Recruitment Program for Young Professionals of China, the Promotion Plan for Basic Medical Sciences, the Development Plan for Cutting-Edge Disciplines, Sichuan University, and other Projects from West China School of Public Health and West China Fourth Hospital, Sichuan University. The sponsors of this study had no role in study design, data collection, analysis, interpretation, writing of the report, or the decision for submission.

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BZ, XJ, and JL conceived and supervised the study. JX did the analyses. JX and XJ drafted the manuscript with significant contributions from, YH, XW, XZ, CX, ZW, LZ, HX, CY, PY, MT, YW, LC, YL, YZ, CY and YY. All authors contributed to the interpretations of the findings, critically revised the paper, and had final responsibility for the decision to submit for publication.

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Correspondence to Jiayuan Li, Xia Jiang or Ben Zhang.

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Correspondence to: Ben Zhang, Xia Jiang or Jiayuan Li

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Xiao, J., Hao, Y., Wu, X. et al. Nuclear magnetic resonance-determined lipoprotein profile and risk of breast cancer: a Mendelian randomization study. Breast Cancer Res Treat 200, 115–126 (2023). https://doi.org/10.1007/s10549-023-06930-2

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