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Systems genomics in age-related macular degeneration

Genomic studies in age-related macular degeneration (AMD) have identified genetic variants that account for the majority of AMD risk. An important next step is to understand the functional consequences and downstream effects of the identified AMD-associated genetic variants. Instrumental for this ne...

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Autores principales: den Hollander, Anneke I., Mullins, Robert F., Orozco, Luz D., Voigt, Andrew P., Chen, Hsu-Hsin, Strunz, Tobias, Grassmann, Felix, Haines, Jonathan L., Kuiper, Jonas J.W., Tumminia, Santa J., Allikmets, Rando, Hageman, Gregory S., Stambolian, Dwight, Klaver, Caroline C.W., Boeke, Jef D., Chen, Hao, Honigberg, Lee, Katti, Suresh, Frazer, Kelly A., Weber, Bernhard H.F., Gorin, Michael B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10150562/
https://www.ncbi.nlm.nih.gov/pubmed/36108770
http://dx.doi.org/10.1016/j.exer.2022.109248
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author den Hollander, Anneke I.
Mullins, Robert F.
Orozco, Luz D.
Voigt, Andrew P.
Chen, Hsu-Hsin
Strunz, Tobias
Grassmann, Felix
Haines, Jonathan L.
Kuiper, Jonas J.W.
Tumminia, Santa J.
Allikmets, Rando
Hageman, Gregory S.
Stambolian, Dwight
Klaver, Caroline C.W.
Boeke, Jef D.
Chen, Hao
Honigberg, Lee
Katti, Suresh
Frazer, Kelly A.
Weber, Bernhard H.F.
Gorin, Michael B.
author_facet den Hollander, Anneke I.
Mullins, Robert F.
Orozco, Luz D.
Voigt, Andrew P.
Chen, Hsu-Hsin
Strunz, Tobias
Grassmann, Felix
Haines, Jonathan L.
Kuiper, Jonas J.W.
Tumminia, Santa J.
Allikmets, Rando
Hageman, Gregory S.
Stambolian, Dwight
Klaver, Caroline C.W.
Boeke, Jef D.
Chen, Hao
Honigberg, Lee
Katti, Suresh
Frazer, Kelly A.
Weber, Bernhard H.F.
Gorin, Michael B.
author_sort den Hollander, Anneke I.
collection PubMed
description Genomic studies in age-related macular degeneration (AMD) have identified genetic variants that account for the majority of AMD risk. An important next step is to understand the functional consequences and downstream effects of the identified AMD-associated genetic variants. Instrumental for this next step are ‘omics’ technologies, which enable high-throughput characterization and quantification of biological molecules, and subsequent integration of genomics with these omics datasets, a field referred to as systems genomics. Single cell sequencing studies of the retina and choroid demonstrated that the majority of candidate AMD genes identified through genomic studies are expressed in non-neuronal cells, such as the retinal pigment epithelium (RPE), glia, myeloid and choroidal cells, highlighting that many different retinal and choroidal cell types contribute to the pathogenesis of AMD. Expression quantitative trait locus (eQTL) studies in retinal tissue have identified putative causal genes by demonstrating a genetic overlap between gene regulation and AMD risk. Linking genetic data to complement measurements in the systemic circulation has aided in understanding the effect of AMD-associated genetic variants in the complement system, and supports that protein QTL (pQTL) studies in plasma or serum samples may aid in understanding the effect of genetic variants and pinpointing causal genes in AMD. A recent epigenomic study fine-mapped AMD causal variants by determing regulatory regions in RPE cells differentiated from induced pluripotent stem cells (iPSC-RPE). Another approach that is being employed to pinpoint causal AMD genes is to produce synthetic DNA assemblons representing risk and protective haplotypes, which are then delivered to cellular or animal model systems. Pinpointing causal genes and understanding disease mechanisms is crucial for the next step towards clinical translation. Clinical trials targeting proteins encoded by the AMD-associated genomic loci C3, CFB, CFI, CFH, and ARMS2/HTRA1 are currently ongoing, and a phase III clinical trial for C3 inhibition recently showed a modest reduction of lesion growth in geographic atrophy. The EYERISK consortium recently developed a genetic test for AMD that allows genotyping of common and rare variants in AMD-associated genes. Polygenic risk scores (PRS) were applied to quantify AMD genetic risk, and may aid in predicting AMD progression. In conclusion, genomic studies represent a turning point in our exploration of AMD. The results of those studies now serve as a driving force for several clinical trials. Expanding to omics and systems genomics will further decipher function and causality from the associations that have been reported, and will enable the development of therapies that will lessen the burden of AMD.
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spelling pubmed-101505622023-05-01 Systems genomics in age-related macular degeneration den Hollander, Anneke I. Mullins, Robert F. Orozco, Luz D. Voigt, Andrew P. Chen, Hsu-Hsin Strunz, Tobias Grassmann, Felix Haines, Jonathan L. Kuiper, Jonas J.W. Tumminia, Santa J. Allikmets, Rando Hageman, Gregory S. Stambolian, Dwight Klaver, Caroline C.W. Boeke, Jef D. Chen, Hao Honigberg, Lee Katti, Suresh Frazer, Kelly A. Weber, Bernhard H.F. Gorin, Michael B. Exp Eye Res Article Genomic studies in age-related macular degeneration (AMD) have identified genetic variants that account for the majority of AMD risk. An important next step is to understand the functional consequences and downstream effects of the identified AMD-associated genetic variants. Instrumental for this next step are ‘omics’ technologies, which enable high-throughput characterization and quantification of biological molecules, and subsequent integration of genomics with these omics datasets, a field referred to as systems genomics. Single cell sequencing studies of the retina and choroid demonstrated that the majority of candidate AMD genes identified through genomic studies are expressed in non-neuronal cells, such as the retinal pigment epithelium (RPE), glia, myeloid and choroidal cells, highlighting that many different retinal and choroidal cell types contribute to the pathogenesis of AMD. Expression quantitative trait locus (eQTL) studies in retinal tissue have identified putative causal genes by demonstrating a genetic overlap between gene regulation and AMD risk. Linking genetic data to complement measurements in the systemic circulation has aided in understanding the effect of AMD-associated genetic variants in the complement system, and supports that protein QTL (pQTL) studies in plasma or serum samples may aid in understanding the effect of genetic variants and pinpointing causal genes in AMD. A recent epigenomic study fine-mapped AMD causal variants by determing regulatory regions in RPE cells differentiated from induced pluripotent stem cells (iPSC-RPE). Another approach that is being employed to pinpoint causal AMD genes is to produce synthetic DNA assemblons representing risk and protective haplotypes, which are then delivered to cellular or animal model systems. Pinpointing causal genes and understanding disease mechanisms is crucial for the next step towards clinical translation. Clinical trials targeting proteins encoded by the AMD-associated genomic loci C3, CFB, CFI, CFH, and ARMS2/HTRA1 are currently ongoing, and a phase III clinical trial for C3 inhibition recently showed a modest reduction of lesion growth in geographic atrophy. The EYERISK consortium recently developed a genetic test for AMD that allows genotyping of common and rare variants in AMD-associated genes. Polygenic risk scores (PRS) were applied to quantify AMD genetic risk, and may aid in predicting AMD progression. In conclusion, genomic studies represent a turning point in our exploration of AMD. The results of those studies now serve as a driving force for several clinical trials. Expanding to omics and systems genomics will further decipher function and causality from the associations that have been reported, and will enable the development of therapies that will lessen the burden of AMD. 2022-12 2022-09-13 /pmc/articles/PMC10150562/ /pubmed/36108770 http://dx.doi.org/10.1016/j.exer.2022.109248 Text en https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
den Hollander, Anneke I.
Mullins, Robert F.
Orozco, Luz D.
Voigt, Andrew P.
Chen, Hsu-Hsin
Strunz, Tobias
Grassmann, Felix
Haines, Jonathan L.
Kuiper, Jonas J.W.
Tumminia, Santa J.
Allikmets, Rando
Hageman, Gregory S.
Stambolian, Dwight
Klaver, Caroline C.W.
Boeke, Jef D.
Chen, Hao
Honigberg, Lee
Katti, Suresh
Frazer, Kelly A.
Weber, Bernhard H.F.
Gorin, Michael B.
Systems genomics in age-related macular degeneration
title Systems genomics in age-related macular degeneration
title_full Systems genomics in age-related macular degeneration
title_fullStr Systems genomics in age-related macular degeneration
title_full_unstemmed Systems genomics in age-related macular degeneration
title_short Systems genomics in age-related macular degeneration
title_sort systems genomics in age-related macular degeneration
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10150562/
https://www.ncbi.nlm.nih.gov/pubmed/36108770
http://dx.doi.org/10.1016/j.exer.2022.109248
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