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Related Concept Videos

Proteomics01:33

Proteomics

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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis
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Inflammation proteomics datasets in the ALSPAC cohort.

Neil Goulding1, Lucy J Goudswaard1,2, David A Hughes1,2

  • 1Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.

Wellcome Open Research
|September 13, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a new proteomic dataset from the Avon Longitudinal Study of Parents and Children, analyzing 92 inflammatory proteins in thousands of mother and offspring blood samples. The data enables further research into inflammation

Keywords:
ALSPACOlinkProteomicsbirth cohortinflammationinter-generational

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Area of Science:

  • Biochemistry
  • Genetics
  • Epidemiology

Background:

  • Proteomics enables the study of protein expression within biological systems.
  • High-throughput proteomic technologies facilitate large-scale epidemiological investigations.
  • The Avon Longitudinal Study of Parents and Children (ALSPAC) provides a unique cohort for longitudinal health research.

Purpose of the Study:

  • To describe a newly released proteomic dataset from the ALSPAC cohort.
  • To present proteomic data on 92 circulating inflammatory proteins.
  • To facilitate future research on the role of inflammation in health and disease.

Main Methods:

  • Utilized Olink Proteomic Proximity Extension Assay (PEA) technology.
  • Analyzed 92 inflammatory proteins in 8983 blood plasma samples from mothers and offspring.
  • Applied a standardized data processing workflow (metaboprep) for quality control and filtering.

Main Results:

  • Generated a high-quality, filtered proteomic dataset for 8983 samples.
  • Demonstrated high correlation between Olink-measured IL-6 and clinical chemistry IL-6 (r=0.77).
  • Reproduced the established positive association between body mass index (BMI) and IL-6 levels.

Conclusions:

  • The ALSPAC cohort now offers a rich proteomic resource for studying inflammation.
  • The validated dataset supports further characterization of inflammatory protein roles in health and disease.
  • This data facilitates deeper understanding of longitudinal inflammatory profiles.