Systemic Metabolomics in a Framework of Genetics and Lifestyle in Age-Related Macular Degeneration

for the European Eye Epidemiology Consortium and EYE-RISK Project

doi:10.3390/metabo13060701

Systemic Metabolomics in a Framework of Genetics and Lifestyle in Age-Related Macular Degeneration

for the European Eye Epidemiology Consortium and EYE-RISK Project

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

Insights into the pathogenesis of age-related macular degeneration (AMD), a leading cause of blindness, point towards a complex interplay of genetic and lifestyle factors triggering various systemic pathways. This study aimed to characterize metabolomic profiles for AMD and to evaluate their position in the trias with genetics and lifestyle. This study included 5923 individuals from five European studies. Blood metabolomics were assessed using a nuclear magnetic resonance platform of 146 metabolites. Associations were studied using regression analyses. A genetic risk score (GRS) was calculated using β-values of 49 AMD variants, a lifestyle risk score (LRS) using smoking and diet data, and a metabolite risk score (MRS) using metabolite values. We identified 61 metabolites associated with early-intermediate AMD, of which 94% were lipid-related, with higher levels of HDL-subparticles and apolipoprotein-A1, and lower levels of VLDL-subparticles, triglycerides, and fatty acids (false discovery rate (FDR) p-value < 1.4 × 10⁻²). Late AMD was associated with lower levels of the amino acids histidine, leucine, valine, tyrosine, and phenylalanine, and higher levels of the ketone bodies acetoacetate and 3-hydroxybutyrate (FDR p-value < 1.5 × 10⁻³). A favorable lifestyle characterized by a healthy diet was associated with higher levels of amino acids and lower levels of ketone bodies, while an unfavorable lifestyle, including smoking, showed opposite effects (FDR p-value < 2.7 × 10⁻²). The MRS mediated 5% of the effect of the GRS and 20% of that of the LRS on late AMD. Our findings show that metabolomic profiles differ between AMD stages and show that blood metabolites mostly reflect lifestyle. The severity-specific profiles spur further interest into the systemic effects related to disease conversion.

Original language	English
Article number	701
Journal	Metabolites
Volume	13
Issue number	6
DOIs	https://doi.org/10.3390/metabo13060701
Publication status	Published - 27 May 2023

Bibliographical note

Funding Information:
This research was supported by the European Union (Horizon 2020 grant no.: 634479 [EYE-RISK]). The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, The Netherlands; the Netherlands Organization for the Health Research and Development; the Research Institute for Diseases in the Elderly (RIDE); the Ministry of Education, Culture and Science; the Ministry of Health, Welfare and Sports; the European Commission (DG XII); and the Municipality of Rotterdam. The generation and management of GWAS genotype data for the Rotterdam Study (I, II, and III) was executed by the Human Genotyping Facility of the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands. The GWAS data sets are supported by the Netherlands Organization of Scientific Research NWO Investments (nos.: 175.010.2005.011 and 911-03-012); the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC; the Research Institute for Diseases in the Elderly (grant no.: 014-93-015 [RIDE2]); the Netherlands Genomics Initiative/Netherlands Organization for Scientific Research and Netherlands Consortium for Healthy Aging (grant no.: 050-060-810). The ophthalmic research within the Rotterdam Study was supported by Uitzicht grant number: 2015-36, Oogfonds, MaculaFonds, Landelijkse Stichting voor Blinden en Slechtzienden that contributed through Uitzicht (grant 2018-34), the Royal Dutch Academy of Sciences (Ammodo Award to C.C.W. Klaver), Novartis Fonds. The sponsors and funding organization had no role in the design or conduct of this research. EUGENDA was funded by grants from the Oogfonds, MaculaFonds, Landelijke Stiching voor Blinden en Slechtzienden, Stichting Blindenhulp, Stichting A.F. Deutman Oogheelkunde Researchfonds, the Netherlands Organization for Scientific Research (Vidi Innovational Research Award 016.096.309), and the European Research Council under the European Union’s Seventh Framework Program (FP/2007-2013) (ERC Grant Agreement no. 310644 MACULA). This research was supported by the Dutch Organization for Scientific Research (016.Vici.170.024 to AIdH).

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© 2023 by the authors.

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@article{bb45c60c0a9c4c03a8dffa3bd8e02065,

title = "Systemic Metabolomics in a Framework of Genetics and Lifestyle in Age-Related Macular Degeneration",

abstract = "Insights into the pathogenesis of age-related macular degeneration (AMD), a leading cause of blindness, point towards a complex interplay of genetic and lifestyle factors triggering various systemic pathways. This study aimed to characterize metabolomic profiles for AMD and to evaluate their position in the trias with genetics and lifestyle. This study included 5923 individuals from five European studies. Blood metabolomics were assessed using a nuclear magnetic resonance platform of 146 metabolites. Associations were studied using regression analyses. A genetic risk score (GRS) was calculated using β-values of 49 AMD variants, a lifestyle risk score (LRS) using smoking and diet data, and a metabolite risk score (MRS) using metabolite values. We identified 61 metabolites associated with early-intermediate AMD, of which 94% were lipid-related, with higher levels of HDL-subparticles and apolipoprotein-A1, and lower levels of VLDL-subparticles, triglycerides, and fatty acids (false discovery rate (FDR) p-value < 1.4 × 10−2). Late AMD was associated with lower levels of the amino acids histidine, leucine, valine, tyrosine, and phenylalanine, and higher levels of the ketone bodies acetoacetate and 3-hydroxybutyrate (FDR p-value < 1.5 × 10−3). A favorable lifestyle characterized by a healthy diet was associated with higher levels of amino acids and lower levels of ketone bodies, while an unfavorable lifestyle, including smoking, showed opposite effects (FDR p-value < 2.7 × 10−2). The MRS mediated 5% of the effect of the GRS and 20% of that of the LRS on late AMD. Our findings show that metabolomic profiles differ between AMD stages and show that blood metabolites mostly reflect lifestyle. The severity-specific profiles spur further interest into the systemic effects related to disease conversion.",

author = "Thee, {Eric F.} and Acar, {İlhan E.} and {for the European Eye Epidemiology Consortium and EYE-RISK Project} and Colijn, {Johanna M.} and Meester-Smoor, {Magda A.} and Timo Verzijden and Baart, {Sara J.} and Jarboui, {Mohamed A.} and Sascha Fauser and Hoyng, {Carel B.} and Marius Ueffing and {den Hollander}, {Anneke I.} and Klaver, {Caroline C.W.}",

note = "Funding Information: This research was supported by the European Union (Horizon 2020 grant no.: 634479 [EYE-RISK]). The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, The Netherlands; the Netherlands Organization for the Health Research and Development; the Research Institute for Diseases in the Elderly (RIDE); the Ministry of Education, Culture and Science; the Ministry of Health, Welfare and Sports; the European Commission (DG XII); and the Municipality of Rotterdam. The generation and management of GWAS genotype data for the Rotterdam Study (I, II, and III) was executed by the Human Genotyping Facility of the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands. The GWAS data sets are supported by the Netherlands Organization of Scientific Research NWO Investments (nos.: 175.010.2005.011 and 911-03-012); the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC; the Research Institute for Diseases in the Elderly (grant no.: 014-93-015 [RIDE2]); the Netherlands Genomics Initiative/Netherlands Organization for Scientific Research and Netherlands Consortium for Healthy Aging (grant no.: 050-060-810). The ophthalmic research within the Rotterdam Study was supported by Uitzicht grant number: 2015-36, Oogfonds, MaculaFonds, Landelijkse Stichting voor Blinden en Slechtzienden that contributed through Uitzicht (grant 2018-34), the Royal Dutch Academy of Sciences (Ammodo Award to C.C.W. Klaver), Novartis Fonds. The sponsors and funding organization had no role in the design or conduct of this research. EUGENDA was funded by grants from the Oogfonds, MaculaFonds, Landelijke Stiching voor Blinden en Slechtzienden, Stichting Blindenhulp, Stichting A.F. Deutman Oogheelkunde Researchfonds, the Netherlands Organization for Scientific Research (Vidi Innovational Research Award 016.096.309), and the European Research Council under the European Union{\textquoteright}s Seventh Framework Program (FP/2007-2013) (ERC Grant Agreement no. 310644 MACULA). This research was supported by the Dutch Organization for Scientific Research (016.Vici.170.024 to AIdH). Publisher Copyright: {\textcopyright} 2023 by the authors.",

year = "2023",

month = may,

day = "27",

doi = "10.3390/metabo13060701",

language = "English",

volume = "13",

journal = "Metabolites",

issn = "2218-1989",

publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",

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TY - JOUR

T1 - Systemic Metabolomics in a Framework of Genetics and Lifestyle in Age-Related Macular Degeneration

AU - Thee, Eric F.

AU - Acar, İlhan E.

AU - for the European Eye Epidemiology Consortium and EYE-RISK Project

AU - Colijn, Johanna M.

AU - Meester-Smoor, Magda A.

AU - Verzijden, Timo

AU - Baart, Sara J.

AU - Jarboui, Mohamed A.

AU - Fauser, Sascha

AU - Hoyng, Carel B.

AU - Ueffing, Marius

AU - den Hollander, Anneke I.

AU - Klaver, Caroline C.W.

N1 - Funding Information: This research was supported by the European Union (Horizon 2020 grant no.: 634479 [EYE-RISK]). The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, The Netherlands; the Netherlands Organization for the Health Research and Development; the Research Institute for Diseases in the Elderly (RIDE); the Ministry of Education, Culture and Science; the Ministry of Health, Welfare and Sports; the European Commission (DG XII); and the Municipality of Rotterdam. The generation and management of GWAS genotype data for the Rotterdam Study (I, II, and III) was executed by the Human Genotyping Facility of the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands. The GWAS data sets are supported by the Netherlands Organization of Scientific Research NWO Investments (nos.: 175.010.2005.011 and 911-03-012); the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC; the Research Institute for Diseases in the Elderly (grant no.: 014-93-015 [RIDE2]); the Netherlands Genomics Initiative/Netherlands Organization for Scientific Research and Netherlands Consortium for Healthy Aging (grant no.: 050-060-810). The ophthalmic research within the Rotterdam Study was supported by Uitzicht grant number: 2015-36, Oogfonds, MaculaFonds, Landelijkse Stichting voor Blinden en Slechtzienden that contributed through Uitzicht (grant 2018-34), the Royal Dutch Academy of Sciences (Ammodo Award to C.C.W. Klaver), Novartis Fonds. The sponsors and funding organization had no role in the design or conduct of this research. EUGENDA was funded by grants from the Oogfonds, MaculaFonds, Landelijke Stiching voor Blinden en Slechtzienden, Stichting Blindenhulp, Stichting A.F. Deutman Oogheelkunde Researchfonds, the Netherlands Organization for Scientific Research (Vidi Innovational Research Award 016.096.309), and the European Research Council under the European Union’s Seventh Framework Program (FP/2007-2013) (ERC Grant Agreement no. 310644 MACULA). This research was supported by the Dutch Organization for Scientific Research (016.Vici.170.024 to AIdH). Publisher Copyright: © 2023 by the authors.

PY - 2023/5/27

Y1 - 2023/5/27

N2 - Insights into the pathogenesis of age-related macular degeneration (AMD), a leading cause of blindness, point towards a complex interplay of genetic and lifestyle factors triggering various systemic pathways. This study aimed to characterize metabolomic profiles for AMD and to evaluate their position in the trias with genetics and lifestyle. This study included 5923 individuals from five European studies. Blood metabolomics were assessed using a nuclear magnetic resonance platform of 146 metabolites. Associations were studied using regression analyses. A genetic risk score (GRS) was calculated using β-values of 49 AMD variants, a lifestyle risk score (LRS) using smoking and diet data, and a metabolite risk score (MRS) using metabolite values. We identified 61 metabolites associated with early-intermediate AMD, of which 94% were lipid-related, with higher levels of HDL-subparticles and apolipoprotein-A1, and lower levels of VLDL-subparticles, triglycerides, and fatty acids (false discovery rate (FDR) p-value < 1.4 × 10−2). Late AMD was associated with lower levels of the amino acids histidine, leucine, valine, tyrosine, and phenylalanine, and higher levels of the ketone bodies acetoacetate and 3-hydroxybutyrate (FDR p-value < 1.5 × 10−3). A favorable lifestyle characterized by a healthy diet was associated with higher levels of amino acids and lower levels of ketone bodies, while an unfavorable lifestyle, including smoking, showed opposite effects (FDR p-value < 2.7 × 10−2). The MRS mediated 5% of the effect of the GRS and 20% of that of the LRS on late AMD. Our findings show that metabolomic profiles differ between AMD stages and show that blood metabolites mostly reflect lifestyle. The severity-specific profiles spur further interest into the systemic effects related to disease conversion.

AB - Insights into the pathogenesis of age-related macular degeneration (AMD), a leading cause of blindness, point towards a complex interplay of genetic and lifestyle factors triggering various systemic pathways. This study aimed to characterize metabolomic profiles for AMD and to evaluate their position in the trias with genetics and lifestyle. This study included 5923 individuals from five European studies. Blood metabolomics were assessed using a nuclear magnetic resonance platform of 146 metabolites. Associations were studied using regression analyses. A genetic risk score (GRS) was calculated using β-values of 49 AMD variants, a lifestyle risk score (LRS) using smoking and diet data, and a metabolite risk score (MRS) using metabolite values. We identified 61 metabolites associated with early-intermediate AMD, of which 94% were lipid-related, with higher levels of HDL-subparticles and apolipoprotein-A1, and lower levels of VLDL-subparticles, triglycerides, and fatty acids (false discovery rate (FDR) p-value < 1.4 × 10−2). Late AMD was associated with lower levels of the amino acids histidine, leucine, valine, tyrosine, and phenylalanine, and higher levels of the ketone bodies acetoacetate and 3-hydroxybutyrate (FDR p-value < 1.5 × 10−3). A favorable lifestyle characterized by a healthy diet was associated with higher levels of amino acids and lower levels of ketone bodies, while an unfavorable lifestyle, including smoking, showed opposite effects (FDR p-value < 2.7 × 10−2). The MRS mediated 5% of the effect of the GRS and 20% of that of the LRS on late AMD. Our findings show that metabolomic profiles differ between AMD stages and show that blood metabolites mostly reflect lifestyle. The severity-specific profiles spur further interest into the systemic effects related to disease conversion.

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DO - 10.3390/metabo13060701

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C2 - 37367859

AN - SCOPUS:85163735996

SN - 2218-1989

VL - 13

JO - Metabolites

JF - Metabolites

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ER -

Systemic Metabolomics in a Framework of Genetics and Lifestyle in Age-Related Macular Degeneration

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