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Unique motif Sequences for early diagnosis of preeclampsia
Farizky Martriano Humardani1, Agustina Tri Endharti1, Ratih Asmana Ningrum2
1Doctoral Program in Medical Science, Faculty of Medicine Universitas Brawijaya, Malang, Indonesia.
Insights
This study explores FRAGmentomics-based Methylation Analysis (FRAGMA) for early preeclampsia (PE) detection. Six genes show potential as biomarkers for this pregnancy complication, requiring further validation.
Area of Science:
- Biomarkers
- Genomics
- Obstetrics
Background:
- Preeclampsia (PE) significantly affects maternal and infant health, with current diagnostics identifying it late in gestation.
- There is a critical need for early screening and diagnostic biomarkers for PE.
- Bioinformatics approaches offer a novel strategy for identifying these early biomarkers.
Purpose of the Study:
- To review bioinformatics methods for early preeclampsia biomarker discovery.
- To investigate the potential of FRAGmentomics-based Methylation Analysis (FRAGMA) for PE screening.
- To identify specific genes as potential early diagnostic markers for PE.
Main Methods:
- Utilized bioinformatics approaches, specifically FRAGmentomics-based Methylation Analysis (FRAGMA).
- Targeted the CGCGCGG sequence motif in cell-free DNA (cfDNA) for methylation analysis.
- Analyzed cfDNA methylation patterns, as cfDNA is largely derived from the placenta, the primary site of PE pathophysiology.
Main Results:
- Identified 66 genes containing the target motif implicated in PE pathophysiology.
- Six genes (FN1, ITGA2, ITGA5, ITGB1, ITGB3, and VWF) were highlighted as potential early detection biomarkers for PE.
- These candidate genes require further investigation for biomarker utility.
Conclusions:
- FRAGMA is a promising approach for identifying early preeclampsia biomarkers using cfDNA methylation.
- Specific genes like FN1 and VWF show potential for early PE detection.
- Further research is essential to validate these identified genes as reliable biomarkers for preeclampsia.
Abstract:
Preeclampsia (PE) is a disease that significantly impacts both maternal and infant health with its prevalence varying across different ethnicities. Current diagnostic methods for PE typically identify the condition after 20 weeks of gestation, often when the disease has already manifested and reached an advanced stage. The situation underscores the urgent need for early biomarkers capable of effective screening and diagnosis. Our review addresses this challenge by utilizing bioinformatics approaches as an alternative method prior to preclinical and clinical studies. Specifically, we focus on FRAGmentomics-based Methylation Analysis (FRAGMA), targeting the CGCGCGG sequence motif for methylation studies in cell-free DNA (cfDNA). Since cfDNA is largely derived from the placenta, the FRAGMA approach is particularly promising, given that the primary pathophysiology of PE originates in the placenta, and methylation patterns are unique to specific tissues. In the previous research, we identified 66 genes containing this sequence motif that are implicated in the pathophysiology of PE, and only six genes - FN1, ITGA2, ITGA5, ITGB1, ITGB3, and VWF - show potential as early detection biomarkers for PE. These genes still require further investigation to confirm their utility as biomarkers for PE in the future studies.
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