BACKGROUND: Understanding spontaneous preterm birth ([PTB] < 37 weeks) is difficult due to heterogeneities associated with multitudes of risk factors and pathophysiological pathways. Several biomarkers are routinely used clinically for predicting preterm labor; however, these factors are either nonspecific or detected too late. OBJECTIVE: Systematic review of literature on PTB biomarkers in the last 40 years to map out the existing knowledge and gaps in understanding PTB biomarkers. SEARCH STRATEGIES: Five electronic databases were searched for human studies on PTB biomarkers published in any language between 1965 and 2008. SELECTION CRITERIA: The phenotype of interest for final data extraction was exclusively spontaneous PTB with no rupture of membranes. Data extraction included (a) general characteristics of the study (clinical setting, period, and study design), (b) study/participant characteristics (inclusion and exclusion criteria, race/ethnicity, number of participants, gestational age at sampling, (c) characteristics of the biomarker (type, rationale for its selection, type of biological sample, and assay used, and (d) concentration of biomarkers in cases and controls. DATA COLLECTION AND ANALYSIS: The search yielded 7255 citations and data were extracted from 217 articles which met our inclusion and exclusion criteria. MAIN RESULTS: A total of 116 different biomarkers were reported and these were assayed 578 times in the 217 included studies. Over two thirds of the 217 studies were performed on North American or European populations. No reliable biomarkers emerged as a risk predictor of PTB. CONCLUSIONS: Identifying similar studies on biomarkers for the prediction of PTB was a very challenging task due heterogeneities in study design, sampling issues (types, timing and processing), assay methods, and analyses. Major areas of concern identified in this review include poor phenotype definition, nonideal study designs and poor rationale for biomarker selection and assays and population stratification issues.
BACKGROUND: Understanding spontaneous preterm birth ([PTB] < 37 weeks) is difficult due to heterogeneities associated with multitudes of risk factors and pathophysiological pathways. Several biomarkers are routinely used clinically for predicting preterm labor; however, these factors are either nonspecific or detected too late. OBJECTIVE: Systematic review of literature on PTB biomarkers in the last 40 years to map out the existing knowledge and gaps in understanding PTB biomarkers. SEARCH STRATEGIES: Five electronic databases were searched for human studies on PTB biomarkers published in any language between 1965 and 2008. SELECTION CRITERIA: The phenotype of interest for final data extraction was exclusively spontaneous PTB with no rupture of membranes. Data extraction included (a) general characteristics of the study (clinical setting, period, and study design), (b) study/participant characteristics (inclusion and exclusion criteria, race/ethnicity, number of participants, gestational age at sampling, (c) characteristics of the biomarker (type, rationale for its selection, type of biological sample, and assay used, and (d) concentration of biomarkers in cases and controls. DATA COLLECTION AND ANALYSIS: The search yielded 7255 citations and data were extracted from 217 articles which met our inclusion and exclusion criteria. MAIN RESULTS: A total of 116 different biomarkers were reported and these were assayed 578 times in the 217 included studies. Over two thirds of the 217 studies were performed on North American or European populations. No reliable biomarkers emerged as a risk predictor of PTB. CONCLUSIONS: Identifying similar studies on biomarkers for the prediction of PTB was a very challenging task due heterogeneities in study design, sampling issues (types, timing and processing), assay methods, and analyses. Major areas of concern identified in this review include poor phenotype definition, nonideal study designs and poor rationale for biomarker selection and assays and population stratification issues.
Authors: Lasha S Clarke; Elizabeth J Corwin; Anne L Dunlop; Allison Hankus; Joshua M Bradner; Sudeshna Paul; Yunshen Jiao; Alicia K Smith; Nikolay Patrushev; Jennifer G Mulle; Timothy D Read; Carol J R Hogue; Bradley D Pearce Journal: Am J Reprod Immunol Date: 2020-05-23 Impact factor: 3.886
Authors: Nadia Falah; Jude McElroy; Victoria Snegovskikh; Charles J Lockwood; Errol Norwitz; Jeffey C Murray; Edward Kuczynski; Ramkumar Menon; Kari Teramo; Louis J Muglia; Thomas Morgan Journal: Hum Genet Date: 2012-09-13 Impact factor: 4.132
Authors: William A Grobman; Yinglei Lai; Jay D Iams; Uma M Reddy; Brian M Mercer; George Saade; Alan T Tita; Dwight J Rouse; Yoram Sorokin; Ronald J Wapner; Kenneth J Leveno; Sean C Blackwell; M Sean Esplin; Jorge E Tolosa; John M Thorp; Steve N Caritis Journal: J Ultrasound Med Date: 2016-05-05 Impact factor: 2.153
Authors: Bingqian Zhu; Ulf G Bronas; David W Carley; Kathryn Lee; Alana Steffen; Mary C Kapella; Bilgay Izci-Balserak Journal: Ann N Y Acad Sci Date: 2020-05-28 Impact factor: 5.691