Johanna M Colijn1, Anneke I den Hollander2, Ayse Demirkan3, Audrey Cougnard-Grégoire4, Timo Verzijden1, Eveline Kersten2, Magda A Meester-Smoor1, Benedicte M J Merle4, Grigorios Papageorgiou5, Shahzad Ahmad3, Monique T Mulder6, Miguel Angelo Costa7, Pascale Benlian8, Geir Bertelsen9, Alain M Bron10, Birte Claes11, Catherine Creuzot-Garcher10, Maja Gran Erke12, Sascha Fauser13, Paul J Foster14, Christopher J Hammond15, Hans-Werner Hense11, Carel B Hoyng2, Anthony P Khawaja16, Jean-Francois Korobelnik17, Stefano Piermarocchi18, Tatiana Segato18, Rufino Silva19, Eric H Souied20, Katie M Williams15, Cornelia M van Duijn3, Cécile Delcourt4, Caroline C W Klaver21. 1. Department of Ophthalmology, Erasmus University Medical Center, Rotterdam, The Netherlands; Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands. 2. Department of Ophthalmology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands. 3. Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands. 4. Bordeaux Population Health Research Center, UMR 1219, University of Bordeaux, Inserm, Bordeaux, France. 5. Department of Biostatistics, Erasmus Medical Center, Rotterdam, The Netherlands; Department of Cardiothoracic Surgery, Erasmus University Medical Center, Rotterdam, Netherlands. 6. Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands. 7. Association for Innovation and Biomedical Research on Light and Image (AIBILI), Coimbra, Portugal. 8. Univ. Lille, CHU Lille, UMR 8199 - EGID - European Genomic Institute for Diabetes, Lille, France. 9. Department of Community Medicine, UiT, The Arctic University of Norway, Tromsø, Norway; Department of Ophthalmology, University Hospital of North Norway, Tromsø, Norway. 10. Department of Ophthalmology, University Hospital, Eye and Nutrition Research Group, Dijon, France. 11. Institute of Epidemiology and Social Medicine, University of Muenster, Germany. 12. Department of Ophthalmology, Oslo University Hospital, Oslo, Norway. 13. Department of Ophthalmology, University Hospital Cologne, Cologne, Germany; Hoffmann-La Roche AG, Basel, Switzerland. 14. NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom; Integrative Epidemiology, UCL Institute of Ophthalmology, London, United Kingdom. 15. Section of Academic Ophthalmology, School of Life Course Sciences, King's College London, St. Thomas' Hospital, London, United Kingdom; Department of Twin Research & Genetic Epidemiology, King's College London, St. Thomas' Hospital, London, United Kingdom. 16. NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, United Kingdom; Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom. 17. Bordeaux Population Health Research Center, UMR 1219, University of Bordeaux, Inserm, Bordeaux, France; Service d'Ophtalmologie, Centre Hospitalier Universitaire de Bordeaux, Bordeaux, France. 18. Department of Ophthalmology, University of Padova, Padova, Italy. 19. Association for Innovation and Biomedical Research on Light and Image (AIBILI), Coimbra, Portugal; Department of Ophthalmology, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal; Coimbra Institute for Clinical and Biomedical Research, Faculty of Medicine, University of Coimbra, Coimbra, Portugal. 20. Department of Ophthalmology, Centre Hospitalier Intercommunal de Creteil, University Paris Est Creteil, Creteil, France. 21. Department of Ophthalmology, Erasmus University Medical Center, Rotterdam, The Netherlands; Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands; Department of Ophthalmology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands. Electronic address: c.c.w.klaver@erasmusmc.nl.
Abstract
PURPOSE: Genetic and epidemiologic studies have shown that lipid genes and high-density lipoproteins (HDLs) are implicated in age-related macular degeneration (AMD). We studied circulating lipid levels in relationship to AMD in a large European dataset. DESIGN: Pooled analysis of cross-sectional data. PARTICIPANTS: Individuals (N = 30 953) aged 50 years or older participating in the European Eye Epidemiology (E3) consortium and 1530 individuals from the Rotterdam Study with lipid subfraction data. METHODS: AMD features were graded on fundus photographs using the Rotterdam classification. Routine blood lipid measurements, genetics, medication, and potential confounders were extracted from the E3 database. In a subgroup of the Rotterdam Study, lipid subfractions were identified by the Nightingale biomarker platform. Random-intercepts mixed-effects models incorporating confounders and study site as a random effect were used to estimate associations. MAIN OUTCOME MEASURES: AMD features and stage; lipid measurements. RESULTS: HDL was associated with an increased risk of AMD (odds ratio [OR], 1.21 per 1-mmol/l increase; 95% confidence interval [CI], 1.14-1.29), whereas triglycerides were associated with a decreased risk (OR, 0.94 per 1-mmol/l increase; 95% CI, 0.91-0.97). Both were associated with drusen size. Higher HDL raised the odds of larger drusen, whereas higher triglycerides decreases the odds. LDL cholesterol reached statistical significance only in the association with early AMD (P = 0.045). Regarding lipid subfractions, the concentration of extra-large HDL particles showed the most prominent association with AMD (OR, 1.24; 95% CI, 1.10-1.40). The cholesteryl ester transfer protein risk variant (rs17231506) for AMD was in line with increased HDL levels (P = 7.7 × 10-7), but lipase C risk variants (rs2043085, rs2070895) were associated in an opposite way (P = 1.0 × 10-6 and P = 1.6 × 10-4). CONCLUSIONS: Our study suggested that HDL cholesterol is associated with increased risk of AMD and that triglycerides are negatively associated. Both show the strongest association with early AMD and drusen. Extra-large HDL subfractions seem to be drivers in the relationship with AMD, and variants in lipid genes play a more ambiguous role in this association. Whether systemic lipids directly influence AMD or represent lipid metabolism in the retina remains to be answered.
PURPOSE: Genetic and epidemiologic studies have shown that lipid genes and high-density lipoproteins (HDLs) are implicated in age-related macular degeneration (AMD). We studied circulating lipid levels in relationship to AMD in a large European dataset. DESIGN: Pooled analysis of cross-sectional data. PARTICIPANTS: Individuals (N = 30 953) aged 50 years or older participating in the European Eye Epidemiology (E3) consortium and 1530 individuals from the Rotterdam Study with lipid subfraction data. METHODS:AMD features were graded on fundus photographs using the Rotterdam classification. Routine blood lipid measurements, genetics, medication, and potential confounders were extracted from the E3 database. In a subgroup of the Rotterdam Study, lipid subfractions were identified by the Nightingale biomarker platform. Random-intercepts mixed-effects models incorporating confounders and study site as a random effect were used to estimate associations. MAIN OUTCOME MEASURES: AMD features and stage; lipid measurements. RESULTS: HDL was associated with an increased risk of AMD (odds ratio [OR], 1.21 per 1-mmol/l increase; 95% confidence interval [CI], 1.14-1.29), whereas triglycerides were associated with a decreased risk (OR, 0.94 per 1-mmol/l increase; 95% CI, 0.91-0.97). Both were associated with drusen size. Higher HDL raised the odds of larger drusen, whereas higher triglycerides decreases the odds. LDL cholesterol reached statistical significance only in the association with early AMD (P = 0.045). Regarding lipid subfractions, the concentration of extra-large HDL particles showed the most prominent association with AMD (OR, 1.24; 95% CI, 1.10-1.40). The cholesteryl ester transfer protein risk variant (rs17231506) for AMD was in line with increased HDL levels (P = 7.7 × 10-7), but lipase C risk variants (rs2043085, rs2070895) were associated in an opposite way (P = 1.0 × 10-6 and P = 1.6 × 10-4). CONCLUSIONS: Our study suggested that HDL cholesterol is associated with increased risk of AMD and that triglycerides are negatively associated. Both show the strongest association with early AMD and drusen. Extra-large HDL subfractions seem to be drivers in the relationship with AMD, and variants in lipid genes play a more ambiguous role in this association. Whether systemic lipids directly influence AMD or represent lipid metabolism in the retina remains to be answered.
Authors: Gavin W Roddy; Robert H Rosa; Kimberly B Viker; Bradley H Holman; Cheryl R Hann; Anuradha Krishnan; Gregory J Gores; Sophie J Bakri; Michael P Fautsch Journal: Curr Eye Res Date: 2019-12-02 Impact factor: 2.424
Authors: Una L Kelly; Daniel Grigsby; Martha A Cady; Michael Landowski; Nikolai P Skiba; Jian Liu; Alan T Remaley; Mikael Klingeborn; Catherine Bowes Rickman Journal: J Biol Chem Date: 2020-07-31 Impact factor: 5.157
Authors: Eveline Kersten; Sascha Dammeier; Soufiane Ajana; Joannes M M Groenewoud; Marius Codrea; Franziska Klose; Yara T Lechanteur; Sascha Fauser; Marius Ueffing; Cécile Delcourt; Carel B Hoyng; Eiko K de Jong; Anneke I den Hollander Journal: PLoS One Date: 2019-06-20 Impact factor: 3.240
Authors: Zhongjie Fu; Chuck T Chen; Gael Cagnone; Emilie Heckel; Ye Sun; Bertan Cakir; Yohei Tomita; Shuo Huang; Qian Li; William Britton; Steve S Cho; Timothy S Kern; Ann Hellström; Jean-Sébastien Joyal; Lois Eh Smith Journal: EMBO Mol Med Date: 2019-09-05 Impact factor: 14.260
Authors: Andrea R Waksmunski; Robert P Igo; Yeunjoo E Song; Jessica N Cooke Bailey; Renee Laux; Denise Fuzzell; Sarada Fuzzell; Larry D Adams; Laura Caywood; Michael Prough; Dwight Stambolian; William K Scott; Margaret A Pericak-Vance; Jonathan L Haines Journal: Hum Genet Date: 2019-07-31 Impact factor: 5.881