Yingmiao Liu, Jiatong Li, Jing Lyu, Lauren E Howard, Alexander B Sibley, Mark D Starr, John C Brady, Christy Arrowood, Elise C Kohn, S Percy Ivy, Herbert I Hurwitz, James L Abbruzzese, Kouros Owzar, Andrew B Nixon
{"title":"健康受试者血管组生物标志物随时间变化的生物学特性。","authors":"Yingmiao Liu, Jiatong Li, Jing Lyu, Lauren E Howard, Alexander B Sibley, Mark D Starr, John C Brady, Christy Arrowood, Elise C Kohn, S Percy Ivy, Herbert I Hurwitz, James L Abbruzzese, Kouros Owzar, Andrew B Nixon","doi":"10.1158/1055-9965.EPI-24-0644","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Biomarker analyses are an integral part of cancer research. Despite the intense efforts to identify and characterize biomarkers in cancer patients, little is known regarding the natural variation of biomarkers in healthy populations. Here we conducted a clinical study to evaluate the natural variability of biomarkers over time in healthy participants.</p><p><strong>Methods: </strong>The angiome multiplex array, a panel of 25 circulating protein biomarkers, was assessed in 28 healthy participants across 8 timepoints over the span of 60 days. We utilized the intraclass correlation coefficient (ICC) to quantify the reliability of the biomarkers. Adjusted ICC values were calculated under the framework of a linear mixed-effects model, taking into consideration age, sex, body mass index (BMI), fasting status, and sampling factors.</p><p><strong>Results: </strong>ICC was calculated to determine the reliability of each biomarker. HGF was the most stable marker (ICC=0.973), while PDGF-BB was the most variable marker (ICC=0.167). In total, ICC analyses revealed that 22 out of 25 measured biomarkers display good (≥0.4) to excellent (>0.75) ICC values. Three markers (PDGF-BB, TGF-1, PDGF-AA) had ICC values <0.4. Greater age was associated with higher IL-6 (p=0.0114). Higher BMI was associated with higher levels of IL-6 (p=0.0003) and VEGF-R3 (p=0.0045).</p><p><strong>Conclusions: </strong>Of the 25 protein biomarkers measured over this short time period, 22 markers were found to have good or excellent ICC values, providing additional validation for this biomarker assay.</p><p><strong>Impact: </strong>This data further supports the validation of the angiome biomarker assay and its application as an integrated biomarker in clinical trial testing.</p>","PeriodicalId":9458,"journal":{"name":"Cancer Epidemiology Biomarkers & Prevention","volume":" ","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Characterization of the Biological Variability of the Angiome Biomarkers over Time in Healthy Subjects.\",\"authors\":\"Yingmiao Liu, Jiatong Li, Jing Lyu, Lauren E Howard, Alexander B Sibley, Mark D Starr, John C Brady, Christy Arrowood, Elise C Kohn, S Percy Ivy, Herbert I Hurwitz, James L Abbruzzese, Kouros Owzar, Andrew B Nixon\",\"doi\":\"10.1158/1055-9965.EPI-24-0644\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Biomarker analyses are an integral part of cancer research. Despite the intense efforts to identify and characterize biomarkers in cancer patients, little is known regarding the natural variation of biomarkers in healthy populations. Here we conducted a clinical study to evaluate the natural variability of biomarkers over time in healthy participants.</p><p><strong>Methods: </strong>The angiome multiplex array, a panel of 25 circulating protein biomarkers, was assessed in 28 healthy participants across 8 timepoints over the span of 60 days. We utilized the intraclass correlation coefficient (ICC) to quantify the reliability of the biomarkers. Adjusted ICC values were calculated under the framework of a linear mixed-effects model, taking into consideration age, sex, body mass index (BMI), fasting status, and sampling factors.</p><p><strong>Results: </strong>ICC was calculated to determine the reliability of each biomarker. HGF was the most stable marker (ICC=0.973), while PDGF-BB was the most variable marker (ICC=0.167). In total, ICC analyses revealed that 22 out of 25 measured biomarkers display good (≥0.4) to excellent (>0.75) ICC values. Three markers (PDGF-BB, TGF-1, PDGF-AA) had ICC values <0.4. Greater age was associated with higher IL-6 (p=0.0114). Higher BMI was associated with higher levels of IL-6 (p=0.0003) and VEGF-R3 (p=0.0045).</p><p><strong>Conclusions: </strong>Of the 25 protein biomarkers measured over this short time period, 22 markers were found to have good or excellent ICC values, providing additional validation for this biomarker assay.</p><p><strong>Impact: </strong>This data further supports the validation of the angiome biomarker assay and its application as an integrated biomarker in clinical trial testing.</p>\",\"PeriodicalId\":9458,\"journal\":{\"name\":\"Cancer Epidemiology Biomarkers & Prevention\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Epidemiology Biomarkers & Prevention\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1158/1055-9965.EPI-24-0644\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Epidemiology Biomarkers & Prevention","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1158/1055-9965.EPI-24-0644","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
Characterization of the Biological Variability of the Angiome Biomarkers over Time in Healthy Subjects.
Background: Biomarker analyses are an integral part of cancer research. Despite the intense efforts to identify and characterize biomarkers in cancer patients, little is known regarding the natural variation of biomarkers in healthy populations. Here we conducted a clinical study to evaluate the natural variability of biomarkers over time in healthy participants.
Methods: The angiome multiplex array, a panel of 25 circulating protein biomarkers, was assessed in 28 healthy participants across 8 timepoints over the span of 60 days. We utilized the intraclass correlation coefficient (ICC) to quantify the reliability of the biomarkers. Adjusted ICC values were calculated under the framework of a linear mixed-effects model, taking into consideration age, sex, body mass index (BMI), fasting status, and sampling factors.
Results: ICC was calculated to determine the reliability of each biomarker. HGF was the most stable marker (ICC=0.973), while PDGF-BB was the most variable marker (ICC=0.167). In total, ICC analyses revealed that 22 out of 25 measured biomarkers display good (≥0.4) to excellent (>0.75) ICC values. Three markers (PDGF-BB, TGF-1, PDGF-AA) had ICC values <0.4. Greater age was associated with higher IL-6 (p=0.0114). Higher BMI was associated with higher levels of IL-6 (p=0.0003) and VEGF-R3 (p=0.0045).
Conclusions: Of the 25 protein biomarkers measured over this short time period, 22 markers were found to have good or excellent ICC values, providing additional validation for this biomarker assay.
Impact: This data further supports the validation of the angiome biomarker assay and its application as an integrated biomarker in clinical trial testing.
期刊介绍:
Cancer Epidemiology, Biomarkers & Prevention publishes original peer-reviewed, population-based research on cancer etiology, prevention, surveillance, and survivorship. The following topics are of special interest: descriptive, analytical, and molecular epidemiology; biomarkers including assay development, validation, and application; chemoprevention and other types of prevention research in the context of descriptive and observational studies; the role of behavioral factors in cancer etiology and prevention; survivorship studies; risk factors; implementation science and cancer care delivery; and the science of cancer health disparities. Besides welcoming manuscripts that address individual subjects in any of the relevant disciplines, CEBP editors encourage the submission of manuscripts with a transdisciplinary approach.