Proteomic Profiling of Maternal Serum for Early Risk Analysis of Preterm Birth

IF 0.5 4区 生物学 Q4 BIOCHEMICAL RESEARCH METHODS Current Proteomics Pub Date : 2022-04-12 DOI:10.2174/1570164619666220412122959
Javeria Malik, Shaaf Ahmad, Humaira Aziz, N. Roohi, M. A. Iqbal
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Abstract

The absence of absolute clinical indicators and suitable biomarkers hinders the timely diagnosis of women at risk of preterm birth. It influences roughly 12% of births. At delivery and clinical presentation, preterm births are generally inspected based on the gestational period. Different disturbed pathways are associated with the signs of at-risk pregnancies. The main purpose of this study is to analyze and explore the serum proteome of early deliveries and help health care professionals to improve the understanding of the progression of preterm birth. In the present study, 200 pregnant females of 20-30 years of age were selected. We collected samples of second and third-trimester pregnant females, out of which 40 females delivered preterm. We further divided them into three groups, i.e., extremely preterm group, very preterm, and controls. Overall comparison of serum profiles of all the three groups expressing fourteen proteins ranging between 200-10kDa was made. Serum proteins were isolated by one-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis and photographed by totalLab quant software. Groups were evaluated using the ANOVA Tukey’s Post Hoc analysis. Proteins of 69kDa and 15kDa expressed a significant decrease when compared with control subjects. In contrast, the proteins of 23kDa expressed a significant increase, while the proteins of 77kDa, 45kDa, and 25kDa demonstrated no considerable variation. The serum proteins showing significant difference as compared to the control group will serve as predictive biomarkers for at-risk pregnancies. The present study is expected to considerably improve the understanding of the disease pathogenesis along with improved diagnostic and therapeutic approaches leading to better management of pregnancy and reducing the risk of preterm birth.

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早产儿早期风险分析的母体血清蛋白质组学分析
缺乏绝对的临床指标和合适的生物标志物阻碍了对有早产风险的妇女的及时诊断。它影响了大约12%的新生儿。在分娩和临床表现中,早产儿通常根据妊娠期进行检查。不同的干扰途径与高危妊娠的迹象有关。本研究的主要目的是分析和探讨早期分娩的血清蛋白质组学,帮助医护人员提高对早产进展的认识。本研究选取20 ~ 30岁的孕妇200例。我们收集了怀孕中期和晚期的女性样本,其中40名女性早产。我们进一步将他们分为三组,即极度早产儿组,非常早产儿组和对照组。对表达200-10kDa范围内的14种蛋白的三组血清谱进行总体比较。采用一维十二烷基硫酸钠-聚丙烯酰胺凝胶电泳分离血清蛋白,并用totalLab定量软件拍照。采用方差分析(ANOVA)对各组进行事后分析。与对照组相比,69kDa和15kDa蛋白表达显著降低。相比之下,23kDa蛋白表达显著增加,而77kDa、45kDa和25kDa蛋白表达无明显变化。与对照组相比,血清蛋白显示出显著差异,将作为高危妊娠的预测性生物标志物。本研究有望大大提高对该病发病机制的认识,同时改进诊断和治疗方法,从而更好地管理妊娠并降低早产风险。
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来源期刊
Current Proteomics
Current Proteomics BIOCHEMICAL RESEARCH METHODS-BIOCHEMISTRY & MOLECULAR BIOLOGY
CiteScore
1.60
自引率
0.00%
发文量
25
审稿时长
>0 weeks
期刊介绍: Research in the emerging field of proteomics is growing at an extremely rapid rate. The principal aim of Current Proteomics is to publish well-timed in-depth/mini review articles in this fast-expanding area on topics relevant and significant to the development of proteomics. Current Proteomics is an essential journal for everyone involved in proteomics and related fields in both academia and industry. Current Proteomics publishes in-depth/mini review articles in all aspects of the fast-expanding field of proteomics. All areas of proteomics are covered together with the methodology, software, databases, technological advances and applications of proteomics, including functional proteomics. Diverse technologies covered include but are not limited to: Protein separation and characterization techniques 2-D gel electrophoresis and image analysis Techniques for protein expression profiling including mass spectrometry-based methods and algorithms for correlative database searching Determination of co-translational and post- translational modification of proteins Protein/peptide microarrays Biomolecular interaction analysis Analysis of protein complexes Yeast two-hybrid projects Protein-protein interaction (protein interactome) pathways and cell signaling networks Systems biology Proteome informatics (bioinformatics) Knowledge integration and management tools High-throughput protein structural studies (using mass spectrometry, nuclear magnetic resonance and X-ray crystallography) High-throughput computational methods for protein 3-D structure as well as function determination Robotics, nanotechnology, and microfluidics.
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