Stephanie Alimena, Briana Joy K Stephenson, James W Webber, Laura Wollborn, Chad B Sussman, Daniel George Packard, Marta Williams, Cameron Elizabeth Comrie, Joyce Y Wang, Tahireh Markert, Julia Spiegel, Carmen B Rodriguez, Maya Lightfoot, Amia Graye, Sean O'Connor, Kevin M Elias
{"title":"不同种族、族裔和社会经济地位的血清 miRNA 图谱差异:开发公平的卵巢癌筛查测试的意义。","authors":"Stephanie Alimena, Briana Joy K Stephenson, James W Webber, Laura Wollborn, Chad B Sussman, Daniel George Packard, Marta Williams, Cameron Elizabeth Comrie, Joyce Y Wang, Tahireh Markert, Julia Spiegel, Carmen B Rodriguez, Maya Lightfoot, Amia Graye, Sean O'Connor, Kevin M Elias","doi":"10.1158/1940-6207.CAPR-23-0156","DOIUrl":null,"url":null,"abstract":"<p><p>Serum miRNAs are promising biomarkers for several clinical conditions, including ovarian cancer. To inform equitable implementation of these tests, we investigated the effects of race, ethnicity, and socioeconomic status on serum miRNA profiles. Serum samples from a large institutional biobank were analyzed using a custom panel of 179 miRNA species highly expressed in human serum, measured using the Abcam Fireplex assay via flow cytometry. Data were log-transformed prior to analysis. Differences in miRNA by race and ethnicity were assessed using logistic regression. Pairwise t tests analyzed racial and ethnic differences among eight miRNAs previously associated with ovarian cancer risk. Pearson correlations determined the relationship between mean miRNA expression and the social deprivation index (SDI) for Massachusetts residents. Of 1,586 patients (76.9% white, non-Hispanic), compared with white, non-Hispanic patients, those from other racial and ethnic groups were younger (41.9 years ± 13.2 vs. 51.3 ± 15.1, P < 0.01) and had fewer comorbidities (3.5 comorbidities ± 2.7 vs. 4.6 ± 2.8, P < 0.01). On logistic regression, miRNAs predicted race and ethnicity at an AUC of 0.69 (95% confidence interval, 0.66-0.72), which remained consistent when stratified by most comorbidities. Among eight miRNAs previously associated with ovarian cancer risk, seven significantly varied by race and ethnicity (all P < 0.01). There were no significant differences in SDI for any of these eight miRNAs. miRNA expression is significantly influenced by race and ethnicity, which remained consistent after controlling for confounders. Understanding baseline differences in biomarker test characteristics prior to clinical implementation is essential to ensure instruments perform comparably across diverse populations.</p><p><strong>Prevention relevance: </strong>This study aimed to understand factors affecting miRNA expression, to ensure we create equitable screening tests for ovarian cancer that perform well in diverse populations. The goal is to ensure that we are detecting ovarian cancer cases earlier (secondary prevention) in women of all races, ethnic backgrounds, and socioeconomic means.</p>","PeriodicalId":72514,"journal":{"name":"Cancer prevention research (Philadelphia, Pa.)","volume":" ","pages":"177-185"},"PeriodicalIF":0.0000,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11070176/pdf/","citationCount":"0","resultStr":"{\"title\":\"Differences in Serum miRNA Profiles by Race, Ethnicity, and Socioeconomic Status: Implications for Developing an Equitable Ovarian Cancer Screening Test.\",\"authors\":\"Stephanie Alimena, Briana Joy K Stephenson, James W Webber, Laura Wollborn, Chad B Sussman, Daniel George Packard, Marta Williams, Cameron Elizabeth Comrie, Joyce Y Wang, Tahireh Markert, Julia Spiegel, Carmen B Rodriguez, Maya Lightfoot, Amia Graye, Sean O'Connor, Kevin M Elias\",\"doi\":\"10.1158/1940-6207.CAPR-23-0156\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Serum miRNAs are promising biomarkers for several clinical conditions, including ovarian cancer. 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Of 1,586 patients (76.9% white, non-Hispanic), compared with white, non-Hispanic patients, those from other racial and ethnic groups were younger (41.9 years ± 13.2 vs. 51.3 ± 15.1, P < 0.01) and had fewer comorbidities (3.5 comorbidities ± 2.7 vs. 4.6 ± 2.8, P < 0.01). On logistic regression, miRNAs predicted race and ethnicity at an AUC of 0.69 (95% confidence interval, 0.66-0.72), which remained consistent when stratified by most comorbidities. Among eight miRNAs previously associated with ovarian cancer risk, seven significantly varied by race and ethnicity (all P < 0.01). There were no significant differences in SDI for any of these eight miRNAs. miRNA expression is significantly influenced by race and ethnicity, which remained consistent after controlling for confounders. 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引用次数: 0
摘要
血清 miRNA 是包括卵巢癌在内的多种临床疾病的有希望的生物标记物。为了为公平实施这些检测提供信息,我们研究了种族、民族和社会经济地位对血清 miRNA 图谱的影响。我们使用定制的 179 种在人类血清中高度表达的 miRNA 进行了分析。数据在分析前进行了对数转换。使用逻辑回归评估了不同种族和族裔的 miRNA 差异。配对 t 检验分析了以前与卵巢癌风险相关的八种 miRNA 的种族和民族差异。皮尔逊相关性确定了 miRNA 平均表达与马萨诸塞州居民社会贫困指数(SDI)之间的关系。在 1586 名患者(76.9% 为白人、非西班牙裔)中,与白人、非西班牙裔患者相比,来自其他种族和民族群体的患者更年轻(41.9 岁 ± 13.2 vs 51.3 ± 15.1, p
Differences in Serum miRNA Profiles by Race, Ethnicity, and Socioeconomic Status: Implications for Developing an Equitable Ovarian Cancer Screening Test.
Serum miRNAs are promising biomarkers for several clinical conditions, including ovarian cancer. To inform equitable implementation of these tests, we investigated the effects of race, ethnicity, and socioeconomic status on serum miRNA profiles. Serum samples from a large institutional biobank were analyzed using a custom panel of 179 miRNA species highly expressed in human serum, measured using the Abcam Fireplex assay via flow cytometry. Data were log-transformed prior to analysis. Differences in miRNA by race and ethnicity were assessed using logistic regression. Pairwise t tests analyzed racial and ethnic differences among eight miRNAs previously associated with ovarian cancer risk. Pearson correlations determined the relationship between mean miRNA expression and the social deprivation index (SDI) for Massachusetts residents. Of 1,586 patients (76.9% white, non-Hispanic), compared with white, non-Hispanic patients, those from other racial and ethnic groups were younger (41.9 years ± 13.2 vs. 51.3 ± 15.1, P < 0.01) and had fewer comorbidities (3.5 comorbidities ± 2.7 vs. 4.6 ± 2.8, P < 0.01). On logistic regression, miRNAs predicted race and ethnicity at an AUC of 0.69 (95% confidence interval, 0.66-0.72), which remained consistent when stratified by most comorbidities. Among eight miRNAs previously associated with ovarian cancer risk, seven significantly varied by race and ethnicity (all P < 0.01). There were no significant differences in SDI for any of these eight miRNAs. miRNA expression is significantly influenced by race and ethnicity, which remained consistent after controlling for confounders. Understanding baseline differences in biomarker test characteristics prior to clinical implementation is essential to ensure instruments perform comparably across diverse populations.
Prevention relevance: This study aimed to understand factors affecting miRNA expression, to ensure we create equitable screening tests for ovarian cancer that perform well in diverse populations. The goal is to ensure that we are detecting ovarian cancer cases earlier (secondary prevention) in women of all races, ethnic backgrounds, and socioeconomic means.