Plasma metabolomics profiles and breast cancer risk.

IF 7.4 1区 医学 Q1 Medicine
Hui-Chen Wu, Yunjia Lai, Yuyan Liao, Maya Deyssenroth, Gary W Miller, Regina M Santella, Mary Beth Terry
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引用次数: 0

Abstract

Background: Breast cancer (BC) is the most common cancer in women and incidence rates are increasing; metabolomics may be a promising approach for identifying the drivers of the increasing trends that cannot be explained by changes in known BC risk factors.

Methods: We conducted a nested case-control study (median followup 6.3 years) within the New York site of the Breast Cancer Family Registry (BCFR) (n = 40 cases and 70 age-matched controls). We conducted a metabolome-wide association study using untargeted metabolomics coupling hydrophilic interaction liquid chromatography (HILIC) and C18 chromatography with high-resolution mass spectrometry (LC-HRMS) to identify BC-related metabolic features.

Results: We found eight metabolic features associated with BC risk. For the four metabolites negatively associated with risk, the adjusted odds ratios (ORs) ranged from 0.31 (95% confidence interval (CI): 0.14, 0.66) (L-Histidine) to 0.65 (95% CI: 0.43, 0.98) (N-Acetylgalactosamine), and for the four metabolites positively associated with risk, ORs ranged from 1.61 (95% CI: 1.04, 2.51, (m/z: 101.5813, RT: 90.4, 1,3-dibutyl-1-nitrosourea, a potential carcinogen)) to 2.20 (95% CI: 1.15, 4.23) (11-cis-Eicosenic acid). These results were no longer statistically significant after adjusting for multiple comparisons. Adding the BC-related metabolic features to a model, including age, the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk score improved the accuracy of BC prediction from an area under the curve (AUC) of 66% to 83%.

Conclusions: If replicated in larger prospective cohorts, these findings offer promising new ways to identify exposures related to BC and improve BC risk prediction.

血浆代谢组学特征与乳腺癌风险。
背景:乳腺癌(BC)是女性最常见的癌症,其发病率正在上升;代谢组学可能是一种很有前途的方法,可用于确定BC发病率上升趋势的驱动因素,而这些驱动因素无法用已知的BC风险因素的变化来解释:我们在纽约乳腺癌家族登记处(BCFR)进行了一项巢式病例对照研究(中位数随访 6.3 年)(n = 40 例病例和 70 例年龄匹配的对照)。我们采用亲水相互作用液相色谱(HILIC)和C18色谱与高分辨质谱(LC-HRMS)联用的非靶向代谢组学方法进行了一项全代谢组关联研究,以确定与BC相关的代谢特征:结果:我们发现了八种与乳腺癌风险相关的代谢特征。对于与风险呈负相关的四种代谢物,调整后的几率比(ORs)从 0.31(95% 置信区间 (CI):0.14, 0.66)(L-组氨酸)到 0.65(95% CI:0.43, 0.对于与风险呈正相关的四种代谢物,ORs 从 1.61(95% CI:1.04,2.51,(m/z:101.5813,RT:90.4,1,3-二丁基-1-亚硝基脲,一种潜在的致癌物质))到 2.20(95% CI:1.15,4.23)(11-顺式-二十烯酸)不等。经多重比较调整后,这些结果不再具有统计学意义。在包括年龄在内的模型中加入与BC相关的代谢特征、乳腺和卵巢疾病发病率分析及载体估计算法(BOADICEA)风险评分,可将BC预测的准确率从曲线下面积(AUC)的66%提高到83%:如果在更大规模的前瞻性队列中得到推广,这些发现将为识别与乳腺癌相关的暴露并改善乳腺癌风险预测提供新的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
12.00
自引率
0.00%
发文量
76
审稿时长
12 weeks
期刊介绍: Breast Cancer Research, an international, peer-reviewed online journal, publishes original research, reviews, editorials, and reports. It features open-access research articles of exceptional interest across all areas of biology and medicine relevant to breast cancer. This includes normal mammary gland biology, with a special emphasis on the genetic, biochemical, and cellular basis of breast cancer. In addition to basic research, the journal covers preclinical, translational, and clinical studies with a biological basis, including Phase I and Phase II trials.
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