Metabolomics and Age-Related Macular Degeneration

Brown, C.N.; Green, BD; Rb, Thompson; Ai, den Hollander; Lengyel, Imre

doi:10.3390/metabo9010004

Cited by 47 publications

(42 citation statements)

References 237 publications

(300 reference statements)

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“…Thirdly, current prediction models do not include molecular risk factors, while these factors can be measured quantitatively . Because some molecular risk factors are potentially modifiable, this could help to implement personalised preventive strategies for AMD.…”

Section: Future Prediction Modelsmentioning

confidence: 99%

Risk factors for progression of age‐related macular degeneration

Heesterbeek

Lorés‐Motta

Hoyng

et al. 2020

Ophthalmic Physiologic Optic

259

224

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Purpose Age‐related macular degeneration (AMD) is a degenerative disease of the macula, often leading to progressive vision loss. The rate of disease progression can vary among individuals and has been associated with multiple risk factors. In this review, we provide an overview of the current literature investigating phenotypic, demographic, environmental, genetic, and molecular risk factors, and propose the most consistently identified risk factors for disease progression in AMD based on these studies. Finally, we describe the potential use of these risk factors for personalised healthcare. Recent findings While phenotypic risk factors such as drusen and pigment abnormalities become more important to predict disease progression during the course of the disease, demographic, environmental, genetic and molecular risk factors are more valuable at earlier disease stages. Demographic and environmental risk factors such as age and smoking are consistently reported to be related to disease progression, while other factors such as sex, body mass index (BMI) and education are less often associated. Of all known AMD variants, variants that are most consistently reported with disease progression are rs10922109 and rs570618 in CFH, rs116503776 in C2/CFB/SKIV2L, rs3750846 in ARMS2/HTRA1 and rs2230199 in C3. However, it seems likely that other AMD variants also contribute to disease progression but to a lesser extent. Rare variants have probably a large effect on disease progression in highly affected families. Furthermore, current prediction models do not include molecular risk factors, while these factors can be measured accurately in the blood. Possible promising molecular risk factors are High‐Density Lipoprotein Cholesterol (HDL‐C), Docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), zeaxanthin and lutein. Summary Phenotypic, demographic, environmental, genetic and molecular risk factors can be combined in prediction models to predict disease progression, but the selection of the proper risk factors for personalised risk prediction will differ among individuals and is dependent on their current disease stage. Future prediction models should include a wider set of genetic variants to determine the genetic risk more accurately, and rare variants should be taken into account in highly affected families. In addition, adding molecular factors in prediction models may lead to preventive strategies and personalised advice.

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Section: Future Prediction Modelsmentioning

confidence: 99%

Risk factors for progression of age‐related macular degeneration

Heesterbeek

Lorés‐Motta

Hoyng

et al. 2020

Ophthalmic Physiologic Optic

259

224

View full text Add to dashboard Cite

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“… 2 The early stage of AMD has no obvious clinical symptoms and is not easy to detect. The advanced stage of AMD develops into two subtypes with different characteristics, including geographical atrophy (GA) and wet age-related macular degeneration, 3 , 4 leading to irreversible loss of vision. Studies have found that AMD has an obvious familial genetic predisposition, 5 and the genetic variation located at the complement factor H and ARMS2/HTRA1 sites has a great risk effect.…”

mentioning

confidence: 99%

Metabolomics in Age-Related Macular Degeneration: A Systematic Review

Hou

Wang

Pan

2020

Invest. Ophthalmol. Vis. Sci.

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Purpose Age-related macular degeneration (AMD) is one of the leading causes of blindness among the elderly, and the exact pathogenesis of the AMD remains unclear. The purpose of this review is to summarize potential metabolic biomarkers and pathways of AMD that might facilitate risk predictions and clinical diagnoses of AMD. Methods We obtained relevant publications of metabolomics studies of human beings by systematically searching the MEDLINE (PubMed) database before June 2020. Studies were included if they performed mass spectrometry–based or nuclear magnetic resonance–based metabolomics approach for humans. In addition, AMD was assessed from fundus photographs based on standardized protocols. The metabolic pathway analysis was performed using MetaboAnalyst 3.0. Results Thirteen studies were included in this review. Repeatedly identified metabolites including phenylalanine, adenosine, hypoxanthine, tyrosine, creatine, citrate, carnitine, proline, and maltose have the possibility of being biomarkers of AMD. Validation of the biomarker panels was observed in one study. Dysregulation of metabolic pathways involves lipid metabolism, carbohydrate metabolism, nucleotide metabolism, amino acid metabolism, and translation, which might play important roles in the development and progression of AMD. Conclusions This review summarizes the potential metabolic biomarkers and pathways related to AMD, providing opportunities for the construction of diagnostic or predictive models for AMD and the discovery of new therapeutic targets.

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“…It discloses anti-oxidant and anti-glycating properties [22] and was shown to be protective against aging and neurodegenerative diseases [23]. As increased oxidative stress and advanced glycation end products featuring AMD retina [6], it is tempting to speculate that the relative deficiency in carnosine could contribute to AMD pathogenesis. Since acetylcarnosine has been proposed as treatment in cataract and AMD a decade ago [24], we have carefully verified and excluded the consumption of acetylcarnosine and carnosine by patients and controls.…”

Section: Discussionmentioning

confidence: 99%

“…The few metabolic studies previously performed in AMD patients were recently reviewed [6]. A first study was performed using untargeted mass spectrometry in the plasma of neovascular AMD patients (n = 26) compared to controls (n = 19).…”

Section: Introductionmentioning

confidence: 99%

A Plasma Metabolomic Profiling of Exudative Age-Related Macular Degeneration Showing Carnosine and Mitochondrial Deficiencies

Barca

Rondet-Courbis

Ferré

et al. 2020

JCM

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To determine the plasma metabolomic profile of exudative age-related macular degeneration (AMD), we performed a targeted metabolomics study on the plasma from patients (n = 40, mean age = 81.1) compared to an age- and sex-matched control group (n = 40, mean age = 81.8). All included patients had documented exudative AMD, causing significant visual loss (mean logMAR visual acuity = 0.63), compared to the control group. Patients and controls did not differ in terms of body mass index and co-morbidities. Among the 188 metabolites analyzed, 150 (79.8%) were accurately measured. The concentrations of 18 metabolites were significantly modified in the AMD group, but only six of them remained significantly different after Benjamini–Hochberg correction. Valine, lysine, carnitine, valerylcarnitine and proline were increased, while carnosine, a dipeptide disclosing anti-oxidant and anti-glycating properties, was, on average, reduced by 50% in AMD compared to controls. Moreover, carnosine was undetectable for 49% of AMD patients compared to 18% in the control group (p-value = 0.0035). Carnitine is involved in the transfer of fatty acids within the mitochondria; proline, lysine and valerylcarnitine are substrates for mitochondrial electrons transferring flavoproteins, and proline is one of the main metabolites supplying energy to the retina. Overall, our results reveal six new metabolites involved in the plasma metabolomic profile of exudative AMD, suggesting mitochondrial energetic impairments and carnosine deficiency.

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Metabolomics and Age-Related Macular Degeneration

Cited by 47 publications

References 237 publications

Risk factors for progression of age‐related macular degeneration

Risk factors for progression of age‐related macular degeneration

Metabolomics in Age-Related Macular Degeneration: A Systematic Review

A Plasma Metabolomic Profiling of Exudative Age-Related Macular Degeneration Showing Carnosine and Mitochondrial Deficiencies

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