Integration of proteomics with prospective birth cohort to elucidate early life origins of cardiometabolic diseases: Rationale, study design, lab assay, and quality control

Background: Longitudinal plasma proteome profiling over time within individuals provides valuable insights into an individual health and disease dynamics at molecular level. To date, proteome study is very limited in pediatric population, especially, using prospective birth cohort. We launched a longitudinal proteomics study in the Boston Birth Cohort (BBC, referred as "BBC proteomics study"), which aimed to profile proteome at two time points (birth and early childhood) to investigate the biological pathways underlying the link between preterm birth and child long-term cardiometabolic health. This paper describes the rationale, study design, proteomic assay, and quality control (QC) steps for the BBC proteomics study. Methods: The BBC proteomics study includes 990 children from the BBC, a US predominantly urban, low-income, multi-ethnic prospective birth cohort. Using the OLINK^® Explore 3072 platform, we performed proteomic profiling in cord plasma collected at birth and in postnatal plasma collected during early childhood. QC steps included calculation of coefficient of variation (CV), missingness rates per sample or per protein, principal component analyses to identify clustering and outliers, and correlation analyses among the duplicates to indicate reproducibility. Results: Here we report the findings from the first batch of proteome assay, consisting of 349 children with both cord plasma samples and early childhood plasma samples. A total of 2941 proteins from eight OLINK panels were successfully measured at both time points. Almost 100% of samples passed lab-prespecified QC, and four samples with high missingness (>50% of proteins with values lower than limit of detection in each sample) were removed from subsequent analyses. Approximately 89% of proteins were detected in >50% samples. Across the eight panels, 79.6% had intra-CV ≤15% and 79.9% had inter-CV ≤30%. Conclusions: Our data suggests that this high-throughput proteomic profiling is feasible and reproducible in archived pediatric plasma samples, including cord blood. We anticipate that successful completion of this proteomics study will help identify early life novel predictive biomarkers for cardiometabolic risk, so that high-risk newborns can be identified, and effective interventions can be initiated during the earliest developmental window when they may have the greatest life-long benefit.