Olink Target 96 Cardiometabolic Panel

What is the Olink Target 96 Cardiometabolic Panel

Customized panel for human

The Olink Target 96 Cardiometabolic Panel is designed to quantify proteins, with comprehensive biomarker details accessible on the Our company website. Leveraging Biomarker technology, the panel analyzes 92 proteins through a three-step process: incubation, extension/amplification, and detection. During incubation, DNA-labeled antibody pairs are added to the sample and incubated overnight to bind specific target proteins. The next day, extension and amplification steps create unique DNA reporter sequences for each protein, followed by preamplification using standard PCR. Detection is performed using high-throughput real-time qPCR on the Olink Signature Q100 System to quantify the DNA reporter sequences. Samples were randomly allocated across plates to ensure unbiased analysis. Data quality control and normalization were conducted using internal extension and interplate controls, addressing both intra- and inter-batch variability. Protein levels are expressed as normalized protein expression (NPX) values, calculated on a log2 scale for accurate interpretation.

Features of the pane

• Species: Primarily validated for human proteins; cross-reactivity with other species is not guaranteed.
• Proteins : Simultaneously analyze 92 protein biomarkers.
• Sample: Requires only 1µL of plasma, serum or other biofluids.
• Readout: Data are delivered in normalized protein expression (NPX) units, providing accurate insights into relative protein levels.
• Platform: The panel is optimized for use on the Olink Signature Q100 platform.

List of 92 human derived biomarkers

Protein category

The Olink Target 96 Cardiometabolic Panel includes 92 proteins categorized into ten main groups: the enzymes (20), Immune-related (17), Cell Adhesion Molecules (9), Receptors (13), Extracellular Matrix Proteins (11), Chemokines (3), Growth Factor Binding Proteins (3), Transport Proteins (5), Enzyme Inhibitors (6), and other functional proteins (5). These protein biomarkers were selected taking into account both the dynamic range in the sample and the closeness of cardiometabolic processes. The proteins contained in the myocardial metabolism panel were classified and summarized by Uniprot, Human Protein Atlas, Gene Ontology and DisGeNET, including cell metabolic process, cell adhesion, immune response and complement activation.

Table. List of Target 96 Cardiometabolic Panel.

Protein Functions

Biological process

Primarily associated with metabolic, cardiovascular, cancer, immune, and neurological conditions.

Disease area

Primarily associated with immune systerm diseases, innate immune system, and extracellular matrix organization.

Workflow of Olink Proteomics

Demo Results of Olink Data

(Figures come from Ding, R., et al. 2024)

The bar chart displayed the number of proteins.

Volcano plots of differentially expressed proteins.

Heatmap of differentially expressed proteins.

Case Study

Circulating Factors as Potential Biomarkers of Cardiovascular Damage Progression Associated with Type 2 Diabetes

Journal: Proteomes
Year: 2024

• Background
• Results

Diabetes, especially type 2 diabetes (T2D), is associated with an increased risk of developing coronary heart disease (CHD). This study aims to evaluate potential circulating biomarkers of coronary heart disease using a targeted proteomics approach based on proximity extension assays (PEAs).

Differences in protein profiles between patient groups were assessed using one-way ANOVA and 6 proteins with significant differences were found. Post-hoc analyses of pairwise comparisons confirmed differences between groups. In particular, lysosomal precursor x carboxypeptidase (PRCP), hepatic carboxylatease 1 (CES1), complement C2 (C2), and intercellular adhesion molecule 3 (ICAM3) were lower in the DC and NC groups compared to the DN group. The levels of calculite stone-1 α (REG1A) and immunoglobulin lambda constant 2 (IGLC2) were higher in the DC group compared to the DN and NC groups (Figure 1).

Figure 1. The box plot shows the distribution of normalized protein expression (NPX) units of proteins with significant differences between groups. (Giovanni Sartore, et al. 2024)

FAQs

Why Creative Proteomics

Advanced Bioinformatics Solutions

Advanced bioinformatics is provided for Olink data, uncovering metabolic insights tailored to research goals.

Diverse Scientific Applications

Disease modeling, translational research, and biomarker discovery are supported across diverse scientific fields.

Efficient Workflow with High Precision

Olink Q100 is utilized for rapid, precise sample analysis, ensuring reliable and reproducible results.

Comprehensive Research Support

End-to-end support is offered, from design to analysis, ensuring seamless research and transformative discoveries.

Sample Requirements

References

1. Sartore, G., Piarulli, F., Ragazzi, E., et al. (2024). Circulating Factors as Potential Biomarkers of Cardiovascular Damage Progression Associated with Type 2 Diabetes. Proteomes, 12(4), 29. https://doi.org/10.3390/proteomes12040029 
2. Kraaijenhof, J. M., Nurmohamed, N. S., Bom, M. J., et al. (2025). Plasma proteomics improves prediction of coronary plaque progression. European heart journal. Cardiovascular Imaging, 26(3), 489–499. https://doi.org/10.1093/ehjci/jeae313 
3. Ding, R., Wu, L., Wei, S., et al. (2024). Multi-targeted olink proteomics analyses of cerebrospinal fluid from patients with aneurysmal subarachnoid hemorrhage. Proteome science, 22(1), 11. https://doi.org/10.1186/s12953-024-00236-x