Biomarkers as Predictive Factors of Anti-VEGF Response
Abstract
:1. Introduction
2. Macular Degeneration
3. Incidence, Prevalence and Risk Factors
4. Treatment Options for AMD
5. Predictive Factors of Anti-VEGF Resistance
5.1. Predictive Ranibizumab Biomarkers Based on Clinical Characteristics of Patients
5.2. Genomics, Proteomic and Metabolomic Predictive Ranibizumab Biomarkers
5.2.1. Predictive Ranibizumab Biomarkers in Saliva
- Complement System
- ARMS2
- VEGFA and related genes
- SERPINF1
- Other genes
5.2.2. Predictive Ranibizumab Biomarkers in Whole Blood
- Complement Factor H
- ARMS2
- VEGFA and related genes
- HTRA1
- OR52B4
- ApoE
- Other genes
5.2.3. Predictive Ranibizumab Biomarkers in Plasma
5.2.4. Blood Mononuclear Cells as a Source of Ranibizumab Predictive Biomarkers
- Complement System
- ARMS2
- Other genes
- MicroRNAs
- mRNAs
5.2.5. Predictive Ranibizumab Biomarkers in Aqueous Humor
Summary Predictive Biomarkers | |||||
---|---|---|---|---|---|
Sample | Biomarker Type | Symbol | Biomarker | Correlation Ranibizumab Response | Reference |
Saliva | SNPs | CFH | rs1061170 CC | Negative | [99,100,102,107] |
rs1061170 TT/CT | Positive | ||||
Saliva | SNPs | VEGFA | rs833069 | Positive | [101] |
Saliva | SNPs | VEGFR1 | rs7993418 | Positive | [103,104] |
Saliva | SNPs | SERPINF1 | rs512603486 | Negative | [103] |
rs1136287 | Negative | ||||
Whole blood | SNPs | CFH | rs1061170 CC | Negative | [19,118,119,120] |
rs1061170 TT/CT | Positive | ||||
rs800292 | Negative | ||||
rs1329428 | Negative | ||||
rs1410996 | Negative | ||||
Whole blood | SNPs | ARMS2 | rs10490924 | Negative | [19,124] |
Whole blood | SNPs | VEGFA | rs3025039 TT | Positive | [122] |
Whole blood | SNPs | OR52B4 | rs4910623 | Negative | [128] |
Whole blood | SNPs | ApoE | Ɛ4 | Positive | [126,130] |
Plasma | SNPs | IL23R | rs11465804 | Positive | [134] |
Blood mononuclear cells | SNPs | CFH | rs1061170 CC | Negative | [142] |
rs1061170 TT/CT | Positive | ||||
Blood mononuclear cells | miRNA | has-miR-20a-5p | ↑ has-miR-20a-5p | Positive | [7] |
↓ has-miR-20a-5p | Negative | ||||
Blood mononuclear cells | mRNA | Lnc-ADAMTS12-6 | ↓ Lnc-ADAMTS12-6 | Positive | [7] |
↑ Lnc-ADAMTS12-6 | Negative | ||||
Aqueous humor | Protein | CXCL12 | CXCL12 | Negative | [158] |
Aqueous humor | Protein | CCL11 | CCL11 | Positive | [151] |
Aqueous humor | Protein | IL-7 | IL-7 | Positive | [156,157] |
Aqueous humor | Protein | IL-10 | IL-10 | Negative | [158] |
Aqueous humor | Protein | MCP1 | MCP1 | Negative | [158] |
Aqueous humor | Protein | HGF | HGF | Negative | [157] |
Aqueous humor | Protein | PLGF | PLGF | Negative | [156,157] |
Aqueous humor | Protein | KRT8 | KRT8 | Negative | [159] |
Aqueous humor | Protein | sVCAM | sVCAM | Negative | [157] |
6. Limitations and Possible Future Directions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Genes Related to Susceptibility and Progression of AMD | ||
---|---|---|
Gene | Single Nucleotide Polymorphism | Reference |
CFH | rs1410996; rs1061170 (Y402H); rs800292 (V62I); rs2274700 | [43,44,45] |
C2 | rs1042663; rs3020644; rs2072632; rs9332739; rs547154 | [46,47] |
ARMS2 | rs10490924; rs3750848; rs10490923 | [42,45,47,48] |
HTRA1 | rs11200638; rs932275 | [48] |
CD36 | rs3173798; rs3211883; rs10499862; rs3173800; rs17154232 | [49] |
APOE | Ɛ2; Ɛ4 | [50,51] |
PON1 | M55L; Q192R | [52] |
ERCC6 | C−6530 > G | [53] |
CFB | rs641153; rs4151657; rs4151672; rs4151667 | [46] |
C3 | rs1047286; rs3745565; rs171094; rs2230199 (R102G); rs11569536 | [46] |
VEGFA | rs699947; rs1413711; rs2010963 | [54] |
CFI | rs10033900 | [42] |
VEGFR | rs9319425; rs622227; rs2387632 | [54,55] |
CXCR3CR1 | T280M; V249I | [56] |
TLR4 | D299G | [57] |
ELOVL4 | M299V | [58] |
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Bobadilla, M.; Pariente, A.; Oca, A.I.; Peláez, R.; Pérez-Sala, Á.; Larráyoz, I.M. Biomarkers as Predictive Factors of Anti-VEGF Response. Biomedicines 2022, 10, 1003. https://doi.org/10.3390/biomedicines10051003
Bobadilla M, Pariente A, Oca AI, Peláez R, Pérez-Sala Á, Larráyoz IM. Biomarkers as Predictive Factors of Anti-VEGF Response. Biomedicines. 2022; 10(5):1003. https://doi.org/10.3390/biomedicines10051003
Chicago/Turabian StyleBobadilla, Miriam, Ana Pariente, Ana I. Oca, Rafael Peláez, Álvaro Pérez-Sala, and Ignacio M. Larráyoz. 2022. "Biomarkers as Predictive Factors of Anti-VEGF Response" Biomedicines 10, no. 5: 1003. https://doi.org/10.3390/biomedicines10051003
APA StyleBobadilla, M., Pariente, A., Oca, A. I., Peláez, R., Pérez-Sala, Á., & Larráyoz, I. M. (2022). Biomarkers as Predictive Factors of Anti-VEGF Response. Biomedicines, 10(5), 1003. https://doi.org/10.3390/biomedicines10051003