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- Panel Features
- Panels List
- Workflow
- Why CP
- Demo
- Sample Requirements
- Case
- FAQ
What is the Olink Explore 384 Neurology Panel
Customized panel for human
The Olink Explore 384 Neurology Panel employs PEA technology to quantify 367 neural biomarkers from 1 μL plasma/serum (88 samples/run), achieving <1 pg/mL sensitivity and <5% CV reproducibility via NPX normalization. Its modular design integrates eight specialized subpanels for comprehensive or targeted studies, with NIST-traceable QC ensuring robust biomarker discovery.
Features of the pane
- Species: Exclusively validated for human proteome applications.
- Proteins: Simultaneous analysis of 384 neural biomarkers.
- Sample: 1 microliter input volume (plasma or serum).
- Readout: NPX-normalized quantitative values.
- Platform : Olink Signature Q100 platform exclusive.
List of 384 human derived biomarkers
Protein category
The Olink Explore 384 Neurology Panel profiles 367 proteins across eight functional categories: neural cell adhesion & guidance molecules, neurotrophic factors & receptors, synaptic proteins & regulators, neuroinflammatory mediators, extracellular matrix & structural proteins, enzymes & metabolic regulators, growth factor modulators, and other functional proteins (see Table. List of Olink Explore 384 Neurology Panel). Each protein has been carefully selected by experts in the field and is involved in neural development, axon guidance, synaptic function or specific neurological diseases such as Alzheimer's disease. Each of the low-abundance protein analytes of interest has been evaluated in terms of sample material, specificity, precision, sensitivity, dynamic range, matrix effects, and interference.
Protein Functions
Biological process
Primarily linked to immune system, axun guidance, and developmental biology.
Disease area
Associated with metabolic, neurological, and developmental.
The Application of Olink Explore 384 Neurology Panel.
The Olink Explore 384 Neurology Panel enables simultaneous quantification of 384 protein biomarkers associated with neural pathways, providing researchers with a powerful tool for:
- Identification of novel protein signatures in neurodegenerative disease models;
- Mechanistic investigation of neuroinflammatory components (microglial activation, cytokine signaling);
- Discovery of potential biomarkers for synaptic dysfunction;
- Stratification of experimental groups based on molecular profiles.
Workflow of Olink Proteomics
Why CPR
Comprehensive Protein Coverage
Simultaneously quantifies 384 neurology-related protein biomarkers in a single assay, streamlining hypothesis generation.
Multi-Omics Integration
Proprietary bioinformatics pipelines enable seamless correlation with genomic, transcriptomic, or metabolomic datasets for systems-level insights.
Pre-Configured Neurological Workflows
Includes tailored analytical frameworks for neurodegeneration, synaptic function, and neuroinflammation research.
Technical Robustness
Achieves >95% inter-assay reproducibility via standardized protocols and NIST-traceable controls.
Demo Results of Olink Data
Results of Mendelian randomization analysis of 16 plasma proteins using inverse variance-weighting. (Shuangyi Zhang., et al. 2025)
Sample Requirements
| Sample Type | Recommended Sample Size | Sample Quality | Pre-treatment and Storage | Sample Transport |
| Plasma/Serum/Body Fluid | 40µL/sample | Protein concentration: 0.5mg/ml ~ 1mg/ml | Transfer the samples to sterile containers, distribute into either 1.5 milliliter tubes or 96-well plates, and preserve at -80 degrees Celsius through cryopreservation. | All specimens sealed with aluminum foil must be transported using dry ice to maintain a temperature of -80°C. |
| Tissue | ||||
| Cells | ||||
| Exosomes | ||||
| Other |
Case Study
Multiomics reveal key inflammatory drivers of severe obesity: IL4R, LILRA5, and OSM
Journal: Cell genomics
Year: 2025
- Background
- Methods
- Results
Polygenic severe obesity (body mass index [BMI]≥40 kg/m2) increases, particularly in the Hispanic/Latino population, but our underlying mechanistic pathways are poorly understood. Researchers analysed whole-blood multiomics data with the aim of identifying differentially regulated genes in severe obesity in Mexican-Americans from the Cameron County Hispanic Cohort.
Olink proteomics used the Explore 3072 panel (2,921 proteins, including low-abundance inflammatory proteins, proteins actively secreted into the bloodstream, approved and ongoing drug target proteins, organ-specific proteins that leak into the bloodstream, and proteins representing more exploratory potential biomarkers) for proteomic profiling of frozen plasma samples from 270 CCHC subjects. Each subject was measured at 1 or 2 time points (total n = 573 samples). Protein abundance levels for the complete dataset were normalized. Olink data is expressed as NPx values, where NPx is Olink's relative protein quantification unit on a log2 scale. The npx value is derived from the matched read counts in the sequencing. Measurements below the detection limit for all samples are reported.
To further validate the transcriptomic effects we observed, we tested the associations of each SO-DEG in the plasma proteome. After FDR correction, the protein abundance of 5 out of 23 available genes (LILRA5, OSM, CIRL, TNxB, IL4R) was significantly correlated with SO (Figure 1). Among these 5 genes, 3 showed significance in replication transcriptomics studies (LILRA5, OSM, and IL4R), and 4 were directionally consistent with the regulation observed in the discovery analysis. In contrast to the findings, TNxB showed an opposite direction of effect in the proteomic analysis.
Figure 1. The heat map summarized the intersection, effect estimates, and effect directions of 124 differentially expressed genes in SO and the control group. (Chen, H. H., et al. 2025)
FAQs
Where can I find the standard curve for the protein I ran on Olink Explore?
For the Explore product, Olink uses relative quantitation (NPX, any unit), so there is no need for a calibration curve for each run. However, in vitro standard curves for most of our assays can be found on our website during panel validation using recombinant antigens. For specific biomarkers, please contact our support team.
Note: These curves estimate the range of the assay and NPX results should not be converted to absolute units.
What is the maximum sample throughput of the Olink Explore series?
With one sample preparation line and 1-2 FTE, you can process 528 samples per week Olink Explore 3072 and 2064 samples per week Olink Explore HT. Please note that this may vary depending on the instrument used for sample preparation. For other arrangements, please contact our support team.
What are the recommendations for downstream analysis of the following LODs?
LODs may provide information for technical evaluation, including CV calculations, where it is recommended that CV calculations be based on data> LODs.
However, it is recommended to include data on < LODs in downstream statistical analyses as it does not increase the risk of detecting false positives.
References
- Shuangyi Zhang, Jiadong Ren, Bin Liu, et al. (2025). Proteome-wide Mendelian randomization study of plasma proteins associated with mastitis and prediction of potential candidates from herbal medicine. Clinical Traditional Medicine and Pharmacology, 6 (2025) 200205.https://doi.org/10.1016/j.ctmp.2025.200205
- Chen, H. H., Highland, H. M., Frankel, E. G., et al. (2025). Multiomics reveal key inflammatory drivers of severe obesity: IL4R, LILRA5, and OSM. Cell genomics, 5(3), 100784. https://doi.org/10.1016/j.xgen.2025.100784