Use of Human Serum Albumin Cys34 (HSA-Cys34) Adductomics as a Multidimensional and Integrative Biomarker Approach to Assess Oxidative Stress
Abstract
1. Introduction
2. HSA-Cys34 Adductomics
3. Chemistry of HSA-Cys34 Modifications
3.1. Formation of HSA-Cys34-Sulfenic Acid (S-Sulfenic Acid)
3.2. Formation of HSA-Sulfinic Acid (S-Sulfinic Acid) and Sulfonic Acid (S-Sulfonic Acid)
3.3. Formation of HSA-Cys34 Small Thiol Adducts (HSA-S-SR)
3.4. Cys34 Modification by Reactive Aldehydes and Other Chemical Electrophiles
4. Oxidative Stress Biology Related to HSA-Cys34 Modifications
4.1. Direct Oxidation Products
4.2. Small Thiols
4.2.1. HSA-Cys34 Cysteine (S-Cys)
4.2.2. HSA-Cys34 Homocysteine (S-hCys)
4.2.3. HSA-Cys34 Glutathione (S-GSH)
4.2.4. HSA-Cys34 Cysteinylglycine (S-CysGly)
4.2.5. HSA-Cys34 γ-Glutamylcysteine (S-γ-GluCys)
4.2.6. HSA-Cys34 Methanethiol (S-Methanethiol)
4.2.7. HSA-Cys34 N-Acetyl Cysteine (S-NAC)
4.3. Reactive Electrophiles
4.3.1. HSA-Cys34 Crotonaldehyde (S-Crotonaldehyde)
4.3.2. HSA-Cys34 Acrolein (S-Acrolein)
5. Conclusions and Future Perspectives
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
| HSA | Human serum albumin |
| OS | Oxidative stress |
| ROS | Reactive oxygen species |
| RNS | Reactive nitrogen species |
| LPO | Lipid peroxidation |
| TAC | Total antioxidant capacity |
| SOD | Superoxide dismutase |
| MDA | Malondialdehyde |
| 4-HNE | 4-hydroxynonenal |
| GSH | Glutathione |
| GSSG | Glutathione dilsulfide |
| GST | glutathione S-transferase |
| RCS | Reactive carbonyl species |
| LMW | Low molecular weight |
| COPD | Chronic obstructive pulmonary disease |
| IHD | Ischemic heart disease |
| DBSs | Dried blood spots |
| BPD-PH | Bronchopulmonary dysplasia-associated pulmonary hypertension |
| CSO | Cumulative supplemental oxygen |
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| Adduct | Population | Metric | Reported Value | Adduct Altered | Key Association or Finding | Ref. |
|---|---|---|---|---|---|---|
| S-sulfenic acid (monooxidation) | benzene-exposed factory workers | PAR | Control: 2.46 Exposed: 2.85 | S-sulfenic acid ↑ | Increase in benzene-exposed workers | [39] |
| COPD and IHD | PAR | Controls: 1.21 COPD: 1.04 IHD: 1.37 | HSA-Cys34-Gln cross-link ↓ | Decrease in COPD and IHD | [40] | |
| S-sulfinic acid (dioxidation) | Smokers vs. non-smokers | PAR | 2.25 * | S-sulfinic acid ↓ S-sulfinic acid +(Na )↓ | Decrease in smokers; Negative association with smoking exposure | [41] |
| Benzene-exposed factory workers | PAR | Control: 2.41 Exposed: 3.32 | S-sulfinic acid ↑ | Increase in benzene-exposed workers | [39] | |
| COPD and IHD | PAR | Controls: 1.54 COPD: 1.30 IHD: 1.29 | S-sulfinic acid ↓ | Decrease in COPD and IHD | [40] | |
| Controls: 0.06 COPD: 0.05 IHD: 0.05 | S-sulfinic acid +( mCH3)↓ | |||||
| Prenatal air pollution exposures | PAR a | 5.48 * | S-sulfinic acid ↑↓ | Positively associated O3 exposure during 1st trimester, PM10 during 2nd trimester and NO2 during 3rd trimester Negatively associated with O3 during the 3rd trimester and the last 30 days of pregnancy | [42] | |
| Non-Hodgkin lymphoma | FC | 0.83 | S-sulfinic acid ↓ | Decrease in non-Hodgkin lymphoma cases (males) | [43] | |
| Infants (BPD-PH vs. BPD without PH) | PAR | 1.073 * | S-sulfinic acid (+CH3, −H2O) ↓ | Decrease in BPD-PH infants compared to infants with BPD without PH | [44] | |
| S-sulfonic acid (trioxidation) | Benzene-exposed factory workers | PAR | Control: 0.5 Exposed: 1.7 | S-sulfonic acid ↑ | Increase in benzene-exposed workers | [39] |
| COPD and IHD | PAR | Controls: 0.22 COPD: 0.214 IHD: 0.184 | S-sulfonic acid ↓ | Decrease in IHD | [40] | |
| Air pollution exposure in Central London | PAR | Controls: 0.22 COPD: 0.214 IHD: 0.184 | S-sulfonic acid ↓ | Negative association with O3 and NO2 exposure | [40] | |
| S-Cys | Smokers vs. non-smokers | PAR | 557.6 * | S-Cys ↓ | Decrease in smokers; negative association with smoking exposure | [41] |
| 1.59 | S-Cys(+Na )↓ | |||||
| 0.45 | S-Cys (+K) ↓ | |||||
| Diesel-engine factory workers (occupational PM2.5) | PAR, FC | 0.44 *, 0.91 b | S-Cys (NH⟶OH) ↓ | Decrease in diesel engine exhaust exposure in factory workers | [45] | |
| Shanghai Women’s Health Study (Lung cancer in never smokers with air pollution) | PAR, FC | 0.0005 *, 0.93 | S-Cys (−2O) ↓ | Decrease in lung cancer cases | [46] | |
| 0.002 *,1.03 | S-Cys (+Na) ↓ | |||||
| S-hCys | Colorectal cancer cohort | PAR, FC | 0.73 *, 0.83 | S-hCys (+CH3) ↓ | Decrease in colorectal cancer cases | [47] |
| 0.13 *, 0.82 | S-hCys (−2O) ↓ | |||||
| Diesel-engine factory workers (occupational PM2.5) | PAR, FC | 5.85 *, 0.92 b | S-hCys ↓ | Decrease in diesel engine exhaust exposure in factory workers | [45] | |
| 0.21 *, 0.77 b | S-hCys (+CH3) ↓ | |||||
| Benzene-exposed factory workers | PAR | Control: 0.10 Exposed: 0.17 | S-hCys (−2O) ↑ | Increase in benzene-exposed workers | [39] | |
| Control: 0.05 Exposed: 0.09 | S-hCys (NH2→OH) ↑ | |||||
| Shanghai Women’s Health Study (Lung cancer in non-smokers with air pollution) | PAR, FC | 0.2 *, 0.94 | S-hCys ↓ | Decrease in lung cancer cases | [46] | |
| S-GSH | Prenatal air pollution exposures | PAR a | 15.65 * | S-GSH ↑ | Positively associated with O3 exposure during the 3rd trimester | [42] |
| Rural Chinese women using solid fuel | PAR a | Control: 4.59 Smoky: 2.59 Wood: 3.13 Smokeless: 2.88 | S-GSH ↓ | Decrease in coal and wood users compared with gas users | [48] | |
| COPD and IHD | PAR | Controls: 2.92 COPD: 2.27 IHD: 2.36 | S-GSH ↓ | Decrease in COPD and IHD | [40] | |
| Diesel-engine factory workers (occupational PM2.5) | PAR, FC | 0.28 *, 1.22 b | S-GSH ↑ | DInrease in diesel engine exhaust exposure in factory workers | [45] | |
| S-CysGly | Prenatal air pollution exposures | PAR a | 0.31 * | S-CysGly ↑ | Positively associated with PM2.5 exposure during 1st trimester | [42] |
| EPIC-Italy nested case–control (lung cancer risk) | - | - | S-CysGly (−2O) ↓ | Decrease in lung cancer cases | [49] | |
| Non-Hodgkin lymphoma | FC | 0.94 | S-CysGly ↓ | Decrease in non-Hodgkin lymphoma cases (males) | [43] | |
| S-γ-GluCys | Prenatal air pollution exposures | PAR a | 0.18 * | S-γ-GluCys ↑ ↓ | Positive association with PM2.5 exposure Negative association with O3 exposure | [42] |
| Rural Chinese women using solid fuel | PAR a | Control: 2.89 Smoky: 2.02 Wood: 2.45 Smokeless: 1.91 | S-γ-GluCys ↓ | Decrease in coal and wood users compared with gas users | [48] | |
| Non-Hodgkin lymphoma | FC | 0.71 | S-γ-GluCys ↓ | Decrease in non-Hodgkin lymphoma cases, particularly in males | [43] | |
| S-Methanethiol | Colorectal cancer cohort | PAR, FC | 0.12 *, 1.20 | S-Methanethiol ↑ | Increase in colorectal cancer cases | [47] |
| Non-Hodgkin lymphoma | FC | 1.39 | S-Methanethiol ↑ | Increase in non-Hodgkin lymphoma cases (males) | [43] | |
| Prenatal air pollution exposures | PAR a | 0.27 * | S-Methanethiol ↓ | Negative association with NO2 exposure during 1st trimester | [42] | |
| S-NAC | EPIC-Italy nested case–control (lung cancer risk) | - | - | S-NAC ↓ | Decrease in lung cancer cases | [49] |
| S-Crotonaldehyde | Benzene-exposed factory workers | PAR | Control: 0.28 Exposed: 0.57 | S-Crotonaldehyde ↑ | Increase in benzene-exposed workers | [39] |
| Colorectal cancer cohort | PAR, FC | 0.32 *, 1.13 | S-Crotonaldehyde ↑ | Increase in colorectal cancer cases | [47] | |
| Prenatal air pollution exposures | PAR a | 1.38 * | S-Crotonaldehyde ↑↑ | Positive association with O3 exposure (3rd trimester and last 30 days of pregnancy) egative association with PM2.5, PM10, and O3 during early stages of pregnancy (first and second trimesters) | [42] | |
| Non-Hodgkin lymphoma | FC | 0.79 | S-Crotonaldehyde ↓ | Decrease in non-Hodgkin lymphoma cases, particularly in females | [43] | |
| S-Acrolein | Smoking mothers vs. non-smoking mothers | FC | 0.82 b | S-Acrolein ↓ | Decrease in newborns with smoking mothers | [50] |
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Jala, A.; Tayyari, F.; Funk, W.E. Use of Human Serum Albumin Cys34 (HSA-Cys34) Adductomics as a Multidimensional and Integrative Biomarker Approach to Assess Oxidative Stress. Antioxidants 2026, 15, 458. https://doi.org/10.3390/antiox15040458
Jala A, Tayyari F, Funk WE. Use of Human Serum Albumin Cys34 (HSA-Cys34) Adductomics as a Multidimensional and Integrative Biomarker Approach to Assess Oxidative Stress. Antioxidants. 2026; 15(4):458. https://doi.org/10.3390/antiox15040458
Chicago/Turabian StyleJala, Aishwarya, Fariba Tayyari, and William E. Funk. 2026. "Use of Human Serum Albumin Cys34 (HSA-Cys34) Adductomics as a Multidimensional and Integrative Biomarker Approach to Assess Oxidative Stress" Antioxidants 15, no. 4: 458. https://doi.org/10.3390/antiox15040458
APA StyleJala, A., Tayyari, F., & Funk, W. E. (2026). Use of Human Serum Albumin Cys34 (HSA-Cys34) Adductomics as a Multidimensional and Integrative Biomarker Approach to Assess Oxidative Stress. Antioxidants, 15(4), 458. https://doi.org/10.3390/antiox15040458

