Lysolipids are prominent in subretinal drusenoid deposits, a high-risk phenotype in age-related macular degeneration
IntroductionAge related macular degeneration (AMD) causes legal blindness worldwide, with few therapeutic targets in early disease and no treatments for 80% of cases. Extracellular deposits, including drusen and subretinal drusenoid deposits (SDD; also called reticular pseudodrusen), disrupt cone an...
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| Format: | Article |
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Frontiers Media S.A.
2023-11-01
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| Series: | Frontiers in Ophthalmology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fopht.2023.1258734/full |
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| author | David M. G. Anderson Ankita Kotnala Ankita Kotnala Lukasz G. Migas N. Heath Patterson Léonore E. M. Tideman Dongfeng Cao Bibek Adhikari Jeffrey D. Messinger Thomas Ach Sara Tortorella Raf Van de Plas Raf Van de Plas Christine A. Curcio Kevin L. Schey |
| author_facet | David M. G. Anderson Ankita Kotnala Ankita Kotnala Lukasz G. Migas N. Heath Patterson Léonore E. M. Tideman Dongfeng Cao Bibek Adhikari Jeffrey D. Messinger Thomas Ach Sara Tortorella Raf Van de Plas Raf Van de Plas Christine A. Curcio Kevin L. Schey |
| author_sort | David M. G. Anderson |
| collection | DOAJ |
| description | IntroductionAge related macular degeneration (AMD) causes legal blindness worldwide, with few therapeutic targets in early disease and no treatments for 80% of cases. Extracellular deposits, including drusen and subretinal drusenoid deposits (SDD; also called reticular pseudodrusen), disrupt cone and rod photoreceptor functions and strongly confer risk for advanced disease. Due to the differential cholesterol composition of drusen and SDD, lipid transfer and cycling between photoreceptors and support cells are candidate dysregulated pathways leading to deposit formation. The current study explores this hypothesis through a comprehensive lipid compositional analysis of SDD.MethodsHistology and transmission electron microscopy were used to characterize the morphology of SDD. Highly sensitive tools of imaging mass spectrometry (IMS) and nano liquid chromatography tandem mass spectrometry (nLC-MS/MS) in positive and negative ion modes were used to spatially map and identify SDD lipids, respectively. An interpretable supervised machine learning approach was utilized to compare the lipid composition of SDD to regions of uninvolved retina across 1873 IMS features and to automatically discern candidate markers for SDD. Immunohistochemistry (IHC) was used to localize secretory phospholipase A2 group 5 (PLA2G5). ResultsAmong the 1873 detected features in IMS data, three lipid classes, including lysophosphatidylcholine (LysoPC), lysophosphatidylethanolamine (LysoPE) and lysophosphatidic acid (LysoPA) were observed nearly exclusively in SDD while presumed precursors, including phosphatidylcholine (PC), phosphatidylethanolamine (PE) and phosphatidic acid (PA) lipids were detected in SDD and adjacent photoreceptor outer segments. Molecular signals specific to SDD were found in central retina and elsewhere. IHC results indicated abundant PLA2G5 in photoreceptors and retinal pigment epithelium (RPE). DiscussionThe abundance of lysolipids in SDD implicates lipid remodeling or degradation in deposit formation, consistent with ultrastructural evidence of electron dense lipid-containing structures distinct from photoreceptor outer segment disks and immunolocalization of secretory PLA2G5 in photoreceptors and RPE. Further studies are required to understand the role of lipid signals observed in and around SDD. |
| first_indexed | 2024-03-09T18:11:33Z |
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| id | doaj.art-26cf13097cc94e109442e9a1e0f3b623 |
| institution | Directory Open Access Journal |
| issn | 2674-0826 |
| language | English |
| last_indexed | 2024-03-09T18:11:33Z |
| publishDate | 2023-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Ophthalmology |
| spelling | doaj.art-26cf13097cc94e109442e9a1e0f3b6232023-11-24T09:06:44ZengFrontiers Media S.A.Frontiers in Ophthalmology2674-08262023-11-01310.3389/fopht.2023.12587341258734Lysolipids are prominent in subretinal drusenoid deposits, a high-risk phenotype in age-related macular degenerationDavid M. G. Anderson0Ankita Kotnala1Ankita Kotnala2Lukasz G. Migas3N. Heath Patterson4Léonore E. M. Tideman5Dongfeng Cao6Bibek Adhikari7Jeffrey D. Messinger8Thomas Ach9Sara Tortorella10Raf Van de Plas11Raf Van de Plas12Christine A. Curcio13Kevin L. Schey14Department of Biochemistry, Vanderbilt University, Nashville, TN, United StatesDepartment of Biochemistry, Vanderbilt University, Nashville, TN, United StatesDepartment of Ophthalmology and Visual Sciences, University of Alabama at Birmingham, Birmingham, AL, United StatesDelft Center for Systems and Control (DCSC), Delft University of Technology, Delft, NetherlandsDepartment of Biochemistry, Vanderbilt University, Nashville, TN, United StatesDelft Center for Systems and Control (DCSC), Delft University of Technology, Delft, NetherlandsDepartment of Ophthalmology and Visual Sciences, University of Alabama at Birmingham, Birmingham, AL, United StatesVision Science Graduate Program, University of Alabama at Birmingham, Birmingham, AL, United StatesDepartment of Ophthalmology and Visual Sciences, University of Alabama at Birmingham, Birmingham, AL, United StatesDepartment of Ophthalmology, University Hospital Bonn, Bonn, GermanyMolecular Horizon Srl, Perugia, ItalyDepartment of Biochemistry, Vanderbilt University, Nashville, TN, United StatesDelft Center for Systems and Control (DCSC), Delft University of Technology, Delft, NetherlandsDepartment of Ophthalmology and Visual Sciences, University of Alabama at Birmingham, Birmingham, AL, United StatesDepartment of Biochemistry, Vanderbilt University, Nashville, TN, United StatesIntroductionAge related macular degeneration (AMD) causes legal blindness worldwide, with few therapeutic targets in early disease and no treatments for 80% of cases. Extracellular deposits, including drusen and subretinal drusenoid deposits (SDD; also called reticular pseudodrusen), disrupt cone and rod photoreceptor functions and strongly confer risk for advanced disease. Due to the differential cholesterol composition of drusen and SDD, lipid transfer and cycling between photoreceptors and support cells are candidate dysregulated pathways leading to deposit formation. The current study explores this hypothesis through a comprehensive lipid compositional analysis of SDD.MethodsHistology and transmission electron microscopy were used to characterize the morphology of SDD. Highly sensitive tools of imaging mass spectrometry (IMS) and nano liquid chromatography tandem mass spectrometry (nLC-MS/MS) in positive and negative ion modes were used to spatially map and identify SDD lipids, respectively. An interpretable supervised machine learning approach was utilized to compare the lipid composition of SDD to regions of uninvolved retina across 1873 IMS features and to automatically discern candidate markers for SDD. Immunohistochemistry (IHC) was used to localize secretory phospholipase A2 group 5 (PLA2G5). ResultsAmong the 1873 detected features in IMS data, three lipid classes, including lysophosphatidylcholine (LysoPC), lysophosphatidylethanolamine (LysoPE) and lysophosphatidic acid (LysoPA) were observed nearly exclusively in SDD while presumed precursors, including phosphatidylcholine (PC), phosphatidylethanolamine (PE) and phosphatidic acid (PA) lipids were detected in SDD and adjacent photoreceptor outer segments. Molecular signals specific to SDD were found in central retina and elsewhere. IHC results indicated abundant PLA2G5 in photoreceptors and retinal pigment epithelium (RPE). DiscussionThe abundance of lysolipids in SDD implicates lipid remodeling or degradation in deposit formation, consistent with ultrastructural evidence of electron dense lipid-containing structures distinct from photoreceptor outer segment disks and immunolocalization of secretory PLA2G5 in photoreceptors and RPE. Further studies are required to understand the role of lipid signals observed in and around SDD.https://www.frontiersin.org/articles/10.3389/fopht.2023.1258734/fullage-related macular degenerationimaging mass spectrometrysubretinal drusenoid depositretinal pigment epitheliumlysolipidinterpretable supervised machine learning |
| spellingShingle | David M. G. Anderson Ankita Kotnala Ankita Kotnala Lukasz G. Migas N. Heath Patterson Léonore E. M. Tideman Dongfeng Cao Bibek Adhikari Jeffrey D. Messinger Thomas Ach Sara Tortorella Raf Van de Plas Raf Van de Plas Christine A. Curcio Kevin L. Schey Lysolipids are prominent in subretinal drusenoid deposits, a high-risk phenotype in age-related macular degeneration Frontiers in Ophthalmology age-related macular degeneration imaging mass spectrometry subretinal drusenoid deposit retinal pigment epithelium lysolipid interpretable supervised machine learning |
| title | Lysolipids are prominent in subretinal drusenoid deposits, a high-risk phenotype in age-related macular degeneration |
| title_full | Lysolipids are prominent in subretinal drusenoid deposits, a high-risk phenotype in age-related macular degeneration |
| title_fullStr | Lysolipids are prominent in subretinal drusenoid deposits, a high-risk phenotype in age-related macular degeneration |
| title_full_unstemmed | Lysolipids are prominent in subretinal drusenoid deposits, a high-risk phenotype in age-related macular degeneration |
| title_short | Lysolipids are prominent in subretinal drusenoid deposits, a high-risk phenotype in age-related macular degeneration |
| title_sort | lysolipids are prominent in subretinal drusenoid deposits a high risk phenotype in age related macular degeneration |
| topic | age-related macular degeneration imaging mass spectrometry subretinal drusenoid deposit retinal pigment epithelium lysolipid interpretable supervised machine learning |
| url | https://www.frontiersin.org/articles/10.3389/fopht.2023.1258734/full |
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