Datasets for published work

The maternal inflammatory proteome during pregnancy and its role in predicting the risk of spontaneous preterm birth<br>1. Dataset Overview-------------------This dataset contains cell-free RNA (cfRNA) transcriptomic and Olink inflammation-related proteomic data from maternal blood plasma samples collected during the second trimester of pregnancy from the INSIGHT cohort. The data were generated to support the development of predictive models for spontaneous preterm birth (sPTB) risk &lt; 35 weeks.<br>2. Study Design---------------- Cohort: INSIGHT- Sample type: Maternal blood plasma- Collection window: 16–24 weeks' gestation- Sample size: Total = 138 (sPTB = 46, Term = 92)- Outcomes: Spontaneous preterm birth (&lt;35 weeks gestation) vs. term birth (≥37 weeks gestation)<br>3. Data Files Included----------------------- `FinalcfRNA.csv`: Log2 Counts Per Million (log2CPM) expression values for 25 selected cfRNA transcripts previously identified as predictive of sPTB (&lt;35 weeks), as published in: Camunas-Soler J et al. *Predictive RNA profiles for early and very early spontaneous preterm birth*. Am J Obstet Gynecol. 2022 Jul;227(1):72.e1–72.e16.<br>- `FinalRawOlink.csv`: Raw NPX values of inflammation-related proteins measured using the Olink Explore 384 Inflammation panel.<br>- `FinalSampleInfo.csv`: Sample-level metadata including gestational age at sampling, delivery outcome, maternal age, and more.<br>4. Variable Definitions in `FinalSampleInfo.csv`------------------------------------------------- `SampleID`: Sample identifier - `GA_del_w`: Gestational age at delivery (week) - `GA_del_d`: Gestational age at delivery (day) - `GA_visit_w`: Gestational age at sample collection (week) - `GA_visit_d`: Gestational age at sample collection (days) - `group`: Indicates whether the sample is an sPTB case, term control (high risk), or term control (low risk)<br>5. Citation-----------If you use this dataset, please cite:[Insert your paper citation once available] DOI: [Insert DOI once dataset is published on Figshare]<br>6. Contact----------For questions or further information, please contact:<br>Fewa Laleye [e-mail] King's College London<br>