The 27 VOC Biomarkers: Complete Guide to What Your Cerumen Reveals
Understanding VOC Biomarkers
The cerumenogram analyzes volatile organic compounds (VOCs)—small molecules that evaporate at relatively low temperatures and can be detected using gas chromatography-mass spectrometry. These are fundamentally different from the amino acids and proteins measured in blood tests.
The Complete 27-Biomarker Panel
The GA-PLS algorithm selected these 27 compounds from 158 detected VOCs as the most discriminative for metabolic classification:
Ketones (3 compounds)
| # | Compound | VOM # | Significance |
|---|---|---|---|
| 1 | 2-Butanone | VOM 5 | Energy metabolism marker |
| 2 | 2-Pentanone | VOM 11 | Cellular respiration indicator |
| 3 | 7-Octadecanone | VOM 134 | Long-chain ketone metabolism |
What ketones indicate: Ketones are produced when cells metabolize fats for energy. Altered ketone patterns may reflect changes in how efficiently cells are producing energy.
Pyrans & Lactones (5 compounds)
| # | Compound | VOM # | Significance |
|---|---|---|---|
| 4 | 6-Methyltetrahydro-2H-pyran-2-one | VOM 47 | Lipid oxidation product |
| 5 | 6-Propyltetrahydro-2H-pyran-2-one | VOM 72 | Fatty acid metabolism |
| 6 | 6-Butyltetrahydro-2H-pyran-2-one | VOM 85 | Lipid peroxidation |
| 7 | 6-Heptyltetrahydro-2H-pyran-2-one | VOM 128 | Long-chain lipid metabolism |
| 8 | 5-Ethyldihydro-2(3H)-furanone | VOM 43 | Oxidative stress marker |
What pyrans indicate: Pyrans are cyclic compounds formed during lipid oxidation. Elevated levels may indicate increased oxidative stress or altered lipid metabolism.
Carboxylic Acids (3 compounds)
| # | Compound | VOM # | Significance |
|---|---|---|---|
| 9 | Dodecanoic acid (Lauric acid) | VOM 105 | Medium-chain fatty acid |
| 10 | n-Tetradecanoic acid (Myristic acid) | VOM 130 | Saturated fatty acid |
| 11 | n-Octadecanoic acid (Stearic acid) | VOM 141 | Long-chain fatty acid |
What carboxylic acids indicate: These fatty acids reflect lipid metabolism and dietary patterns. Shifts in their ratios can indicate metabolic changes.
Alcohols (3 compounds)
| # | Compound | VOM # | Significance |
|---|---|---|---|
| 12 | 2-Methyl-3-buten-2-ol | VOM 6 | Metabolic byproduct |
| 13 | 1-Decanol | VOM 59 | Fatty alcohol metabolism |
| 14 | 1-Dodecanol | VOM 103 | Long-chain alcohol |
What alcohols indicate: Fatty alcohols are produced from fatty acid reduction and are involved in cell membrane synthesis and signaling.
Hydrocarbons (3 compounds)
| # | Compound | VOM # | Significance |
|---|---|---|---|
| 15 | 3-Methylhexane | VOM 10 | Lipid peroxidation product |
| 16 | 1-Methylcyclooctene | VOM 40 | Cellular membrane byproduct |
| 17 | Eicosane | VOM 126 | Long-chain alkane |
What hydrocarbons indicate: These compounds result from lipid peroxidation—the breakdown of fats by oxidative damage. Elevated levels may indicate oxidative stress.
Amines & Amides (3 compounds)
| # | Compound | VOM # | Significance |
|---|---|---|---|
| 18 | 2,5-Dimethylaniline | VOM 58 | Nitrogen metabolism |
| 19 | N-(3-Acetylphenyl)acetamide | VOM 99 | Protein metabolism product |
| 20 | 2,3-Dimethylquinoline | VOM 102 | Tryptophan metabolism |
What amines indicate: These nitrogen-containing compounds reflect protein and amino acid metabolism pathways.
Esters & Ethers (3 compounds)
| # | Compound | VOM # | Significance |
|---|---|---|---|
| 21 | 1-(Decyloxy)decane | VOM 120 | Lipid ester |
| 22 | Diisobutyl phthalate | VOM 147 | Plasticizer/metabolite |
| 23 | Bis(2-ethylhexyl) phthalate | VOM 157 | Environmental/metabolic |
Other Compounds (4 compounds)
| # | Compound | VOM # | Class |
|---|---|---|---|
| 24 | 2,5-Dihydrofuran | VOM 3 | Furanic |
| 25 | 6-Methyl-7-oxabicyclo[4.1.0]heptan-2-one | VOM 42 | Epoxide |
| 26 | 3-Phenylthiophene | VOM 88 | Organosulfur |
| 27 | n-Octadecanal | VOM 142 | Aldehyde |
How Binary Encoding Works
The cerumenogram uses binary encoding for classification:
- 1 = VOC present (Area/Height ratio > 3)
- 0 = VOC absent
This approach:
- Handles natural biological variability
- Enables pattern matching across populations
- Allows probabilistic classification
The Pattern, Not Individual Markers
Critical understanding: No single biomarker determines classification. The power comes from the pattern across all 27 compounds compared to reference populations.
A sample might have:
- Some ketones elevated, others normal
- Certain pyrans present, others absent
- Various combinations of alcohols and hydrocarbons
The GA-PLS model evaluates the entire pattern to determine which reference group (healthy vs. diseased) it most closely resembles.
Source: PMID 31409861 - Scientific Reports (Nature), 2019
*This article is for educational purposes only. The CeruLabs test is a wellness screening tool and is not intended to diagnose, treat, cure, or prevent any disease.*
