Human Plasma Metabolomics in Age-Related Macular Degeneration: Meta-Analysis of Two Cohorts
- Authors
- Lains, Ines; Chung, Wonil; Kelly, Rachel S.; Gil, Joao; Marques, Marco; Barreto, Patricia; Murta, Joaquim N.; Kim, Ivana K.; Vavvas, Demetrios G.; Miller, John B.; Silva, Rufino; Lasky-Su, Jessica; Liang, Liming; Miller, Joan W.; Husain, Deeba
- Issue Date
- Jul-2019
- Publisher
- MDPI
- Keywords
- age-related macular degeneration; metabolomics; mass spectrometry
- Citation
- METABOLITES, v.9, no.7
- Journal Title
- METABOLITES
- Volume
- 9
- Number
- 7
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/38969
- DOI
- 10.3390/metabo9070127
- ISSN
- 2218-1989
- Abstract
- The pathogenesis of age-related macular degeneration (AMD), a leading cause of blindness worldwide, remains only partially understood. This has led to the current lack of accessible and reliable biofluid biomarkers for diagnosis and prognosis, and absence of treatments for dry AMD. This study aimed to assess the plasma metabolomic profiles of AMD and its severity stages with the ultimate goal of contributing to addressing these needs. We recruited two cohorts: Boston, United States (n = 196) and Coimbra, Portugal (n = 295). Fasting blood samples were analyzed using ultra-high performance liquid chromatography mass spectrometry. For each cohort, we compared plasma metabolites of AMD patients versus controls (logistic regression), and across disease stages (permutation-based cumulative logistic regression considering both eyes). Meta-analyses were then used to combine results from the two cohorts. Our results revealed that 28 metabolites di ff ered significantly between AMDpatients versus controls (false discovery rate (FDR) q-value: 4.1 x 10 2-1.8 x 10 5), and 67 across disease stages (FDR q-value: 4.5 x 10 2-1.7 x 10 4). Pathway analysis showed significant enrichment of glycerophospholipid, purine, taurine and hypotaurine, and nitrogen metabolism (p-value x 0.04). In conclusion, our findings support that AMD patients present distinct plasma metabolomic profiles, which vary with disease severity. This work contributes to the understanding ofAMDpathophysiology, and can be the basis of future biomarkers and precision medicine for this blinding condition.
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