Olink Explore 1536 (4 Panel Combinations)

What is the Olink Explore 1536 (4 Panel Combinations)

Customized panel for human

The Olink Explore 1536 (4 Panel Combinations) utilizes Proximity Extension Assay (PEA) technology to simultaneously quantify 1536 protein biomarkers, spanning established and exploratory targets. With a sample requirement of only 1–4 µL plasma/serum and a throughput of 88 samples per run, the platform achieves exceptional sensitivity (<1 pg/mL detection) and reproducibility (<5% CV) through Normalized Protein Expression (NPX) standardization. Four configurable subpanels facilitate comprehensive immune profiling and targeted pathway studies, while NIST-traceable controls ensure robust data quality for cancer and systems biology research.

Features of the pane

• Species: Human-only applications.
• Proteins: 1536-plex oncology, immunology, neurology, and metabolic protein analysis.
• Sample: 1-4 µL plasma/serumt.
• Readout: NPX-normalized quantification.
• Platform: Olink Signature Q100 platform exclusive.

List of 1536 Human Derived Biomarkers

Protein category

The Olink Explore 1536 (4 Panel Combination) analyzed 1536 protein biomarkers. The expert group conducted a comprehensive analysis of key protein categories, including: enzymes and metabolic regulators, cell surface receptors and ligand-binding molecules, inflammatory mediators (cytokines/chemokines), extracellular matrix and cell adhesion components, intracellular signaling molecules, immune checkpoints and regulatory proteins, tissue growth factors and their binding partners, and special function proteins with different biological roles. (see Table. List of Olink Explore 1536 (4 Panel combination)). These targets include human proteins involved in key mechanisms of cardiovascular disease, neurological disease, inflammation, and tumorigenesis, including angiogenesis, cell-to-cell communication, metabolic regulation, programmed cell death, and proliferation/differentiation pathways. It reflects the physiological and pathological state of the body, plays an extremely important role in the clinical diagnosis of diseases, and has great research value.

Protein Functions

The Application of Olink Explore 1536 (4 Panel Combinations)

The Olink Explore 1536 (4 Panel Combinations) enables high-throughput quantification of 1,536 protein biomarkers across multiple biological pathways, providing researchers with a powerful tool for:

• Comprehensive profiling of protein networks in cancer biology and tumor microenvironment regulation;
• Investigating protein-protein interaction networks in neurological and inflammatory disorders
• Systems-level analysis of immune response dynamics and host-pathogen interactions;
• Identification of potential biomarkers for cohort stratification in translational research.

Workflow of Olink Proteomics

Why Creativ Proteomics

Multi-Disease Research Frameworks

Preconfigured analytical workflows for cancer biology, neuroinflammation, metabolic disorders, and immune responses, supported by 72 validated biomarker ratios.

Flexible Panel Design

48 customizable assay slots integrated with 1,488 fixed targets, enabling study-specific customization without compromising core proteome coverage.

Scalable Study Design

Supports integration with transcriptomic/epigenetic datasets for systems biology approaches, with compatibility for multi-omics platforms.

Transparent Biomarker Selection

All 1,536 targets are expert-curated with published associations to biological mechanisms, annotated in open-access protein databases.

Demo Results of Olink Data

Association between proteomic risk scores and incidental hip fractures. (Austin, T. R., et al. 2024)

Sample Requirements

Case Study

Proteomic and Metabolomic Signatures in Prediabetes Progressing to Diabetes or Reversing to Normoglycemia Within 1 Year

Journal: Diabetes care,
Year :2025

• Background
• Methods
• Results

Progression of prediabetes to type 2 diabetes is associated with β cell dysfunction, while remission to normal prediabetes is associated with improved insulin sensitivity. To understand the mechanisms associated with prediabetes trajectories and identify potential biomarkers, the investigators compared proteomic and metabolomic profiles of people with prediabetes who progressed to diabetes within 1 year or reversed to normoglycemia.

Olink in Uppsala, Sweden, performed proteomic analysis using pre-designed panels for cardiometabolic, inflammatory, neurology, and oncology. Analyses were performed by experienced personnel who were not knowledgeable about the different study groups. A total of 1,470 proteins were detected. We assayed 3 proteins (tumor necrosis factor-α [TNF-α], interleukin-6 [IL-6], and IL-8) in all 4 pre-designed panels, therefore, only assays obtained from the inflammation panel were included in the analysis of these proteins. 94% (248,410/264,600) of the data points passed three quality controls. Seventy-two > 60% of the proteins that failed the QC were completely excluded, and the final number of proteins analyzed was 1389. Values are expressed as protein relative abundance, and data are processed on the log2 scale in a protein expression format normalized to the Olink standard.

Fourteen proteins were elevated in the diabetic group compared to the NGT group (false discovery rate [FDR] <0.05) (Figure 1). The 14 proteins were significantly correlated with fasting blood glucose and area under the curve (AUC), but less correlated with HbA1c (Fig. 1B). They correlate more closely with the insulin sensitivity index (ISI, insulin resistance index [HOMA-ir]) than with β cell functional markers (HOMA-b, IGI). Most proteins are also associated with obesity indices (BMI, waist-to-hip ratio, subcutaneous and visceral adipose tissue volume, liver fat percentage). After adjusting for gender and PLIS intervention type, 13 of the 14 proteins remained significantly different between the diabetes group and the NGT group (adjusted P = 0.069 except for tartaric acid phosphatase 5 [ACP5]).

Figure 1. Differential abundance analysis was performed on proteomic data at follow-up time points based on glycemic status. (Barovic, M., et al. 2025)

FAQs

References

1. Austin, T. R., Nethander, M., Fink, H. A., et al (2024). A plasma protein-based risk score to predict hip fractures. Nature aging, 4(8), 1064–1075. https://doi.org/10.1038/s43587-024-00639-7 
2. Barovic, M., Hahn, J. J., Heinrich, A., et al. (2025). Proteomic and Metabolomic Signatures in Prediabetes Progressing to Diabetes or Reversing to Normoglycemia Within 1 Year. Diabetes care, 48(3), 405–415. https://doi.org/10.2337/dc24-1412