Ophthalmology (Eye & Ear Hospital) - Research Publications

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    Recommendations for OCT Angiography Reporting in Retinal Vascular Disease: A Delphi Approach by International Experts.
    Munk, MR ; Kashani, AH ; Tadayoni, R ; Korobelnik, J-F ; Wolf, S ; Pichi, F ; Koh, A ; Ishibazawa, A ; Gaudric, A ; Loewenstein, A ; Lumbroso, B ; Ferrara, D ; Sarraf, D ; Wong, DT ; Skondra, D ; Rodriguez, FJ ; Staurenghi, G ; Pearce, I ; Kim, JE ; Freund, KB ; Parodi, MB ; Waheed, NK ; Rosen, R ; Spaide, RF ; Nakao, S ; Sadda, S ; Vujosevic, S ; Wong, TY ; Murata, T ; Chakravarthy, U ; Ogura, Y ; Huf, W ; Tian, M (Elsevier BV, 2022-09)
    PURPOSE: To develop a consensus nomenclature for reporting OCT angiography (OCTA) findings in retinal vascular disease (e.g., diabetic retinopathy, retinal vein occlusion) by international experts. DESIGN: Delphi-based survey. SUBJECTS, PARTICIPANTS, AND/OR CONTROLS: Twenty-five retinal vascular disease and OCTA imaging experts. METHODS, INTERVENTION, OR TESTING: A Delphi method of consensus development was used, comprising 2 rounds of online questionnaires, followed by a face-to-face meeting conducted virtually. Twenty-five experts in retinal vascular disease and retinal OCTA imaging were selected to constitute the OCTA Nomenclature in Delphi Study Group for retinal vascular disease. The 4 main areas of consensus were: definition of the parameters of "wide-field (WF)" OCTA, measurement of decreased vascular flow on conventional and WF-OCTA, nomenclature of OCTA findings, and OCTA in retinal vascular disease management and staging. The study end point was defined by the degree of consensus for each question: "strong consensus" was defined as ≥85% agreement, "consensus" as 80% to 84%, and "near consensus" as 70% to 79%. MAIN OUTCOME MEASURES: Consensus and near consensus on OCTA nomenclature in retinal vascular disease. RESULTS: A consensus was reached that a meaningful change in percentage of flow on WF-OCTA imaging should be an increase or decrease ≥30% of the absolute imaged area of flow signal and that a "large area" of WF-OCTA reduced flow signal should also be defined as ≥30% of the absolute imaged area. The presence of new vessels and intraretinal microvascular abnormalities, the foveal avascular zone parameters, the presence and amount of "no-flow areas," and the assessment of vessel density in various retinal layers should be added for the staging and classification of diabetic retinopathy. Decreased flow ≥30% of the absolute imaged area should define an ischemic central retinal vein occlusion. Several other items did not meet consensus requirements or were rejected in the final discussion round. CONCLUSIONS: This study provides international consensus recommendations for reporting OCTA findings in retinal vascular disease, which may help to improve the interpretability and description in clinic and clinical trials. Further validation in these settings is warranted and ongoing. Efforts are continuing to address unresolved questions.
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    Retinal neural dysfunction in diabetes revealed with handheld chromatic pupillometry.
    Tan, T-E ; Finkelstein, MT ; Tan, GSW ; Tan, ACS ; Chan, CM ; Mathur, R ; Wong, EYM ; Cheung, CMG ; Wong, TY ; Milea, D ; Najjar, RP (Wiley, 2022-09)
    BACKGROUND: To evaluate the ability of handheld chromatic pupillometry to reveal and localise retinal neural dysfunction in diabetic patients with and without diabetic retinopathy (DR). METHODS: This cross-sectional study included 82 diabetics (DM) and 93 controls (60.4 ± 8.4 years, 44.1% males). DM patients included those without (n = 25, 64.7 ± 6.3 years, 44.0% males) and with DR (n = 57, 60.3 ± 8.5 years, 64.9% males). Changes in horizontal pupil radius in response to blue (469 nm) and red (640 nm) light stimuli were assessed monocularly, in clinics, using a custom-built handheld pupillometer. Pupillometric parameters (phasic constriction amplitudes [predominantly from the outer retina], maximal constriction amplitudes [from the inner and outer retina] and post-illumination pupillary responses [PIPRs; predominantly from the inner retina]) were extracted from baseline-adjusted pupillary light response traces and compared between controls, DM without DR, and DR. Net PIPR was defined as the difference between blue and red PIPRs. RESULTS: Phasic constriction amplitudes to blue and red lights were decreased in DR compared to controls (p < 0.001; p < 0.001). Maximal constriction amplitudes to blue and red lights were decreased in DR compared to DM without DR (p < 0.001; p = 0.02), and in DM without DR compared to controls (p < 0.001; p = 0.005). Net PIPR was decreased in both DR and DM without DR compared to controls (p = 0.02; p = 0.03), suggesting a wavelength-dependent (and hence retinal) pupillometric dysfunction in diabetic patients with or without DR. CONCLUSIONS: Handheld chromatic pupillometry can reveal retinal neural dysfunction in diabetes, even without DR. Patients with DM but no DR displayed primarily inner retinal dysfunction, while patients with DR showed both inner and outer retinal dysfunction.
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    Acceptance and Perception of Artificial Intelligence Usability in Eye Care (APPRAISE) for Ophthalmologists: A Multinational Perspective
    Gunasekeran, DVV ; Zheng, F ; Lim, GYS ; Chong, CCY ; Zhang, S ; Ng, WY ; Keel, S ; Xiang, Y ; Park, KH ; Park, SJ ; Chandra, A ; Wu, L ; Campbel, JP ; Lee, AYY ; Keane, PAA ; Denniston, A ; Lam, DSC ; Fung, ATT ; Chan, PRV ; Sadda, SR ; Loewenstein, A ; Grzybowski, A ; Fong, KCS ; Wu, W-C ; Bachmann, LM ; Zhang, X ; Yam, JC ; Cheung, CYY ; Pongsachareonnont, P ; Ruamviboonsuk, P ; Raman, R ; Sakamoto, T ; Habash, R ; Girard, M ; Milea, D ; Ang, M ; Tan, GSW ; Schmetterer, L ; Cheng, C-Y ; Lamoureux, E ; Lin, H ; van Wijngaarden, P ; Wong, TYY ; Ting, DSW (FRONTIERS MEDIA SA, 2022-10-13)
    BACKGROUND: Many artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract. METHODS: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning. RESULTS: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10-12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63-0.83. CONCLUSION: Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology.
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    System-wide vitreous proteome dissection reveals impaired sheddase activity in diabetic retinopathy.
    Alli-Shaik, A ; Qiu, B ; Lai, SL ; Cheung, N ; Tan, G ; Neo, SP ; Tan, A ; Cheung, CMG ; Hong, W ; Wong, TY ; Wang, X ; Gunaratne, J (Ivyspring International Publisher, 2022)
    Rationale: Diabetic retinopathy (DR) is a major complication of diabetes mellitus causing significant vision loss. DR is a multifactorial disease involving changes in retinal microvasculature and neuronal layers, and aberrations in vascular endothelial growth factors (VEGF) and inflammatory pathways. Despite the success of anti-VEGF therapy, many DR patients do not respond well to the treatment, emphasizing the involvement of other molecular players in neuronal and vascular aberrations in DR. Methods: We employed advanced mass spectrometry-based proteome profiling to obtain a global snapshot of altered protein abundances in vitreous humor from patients with proliferative DR (PDR) in comparison to individuals with epiretinal membrane without active DR or other retinal vascular complications. Global proteome correlation map and protein-protein interaction networks were used to probe into the functional inclination of proteins and aberrated molecular networks in PDR vitreous. In addition, peptide-centric analysis of the proteome data was carried out to identify proteolytic processing, primarily ectodomain shedding events in PDR vitreous. Functional validation experiments were performed using preclinical models of ocular angiogenesis. Results: The vitreous proteome landscape revealed distinct dysregulations in several metabolic, signaling, and immune networks in PDR. Systematic analysis of altered proteins uncovered specific impairment in ectodomain shedding of several transmembrane proteins playing critical roles in neurodegeneration and angiogenesis, pointing to defects in their regulating sheddases, particularly ADAM10, which emerged as the predominant sheddase. We confirmed that ADAM10 protease activity was reduced in animal models of ocular angiogenesis and established that activation of ADAM10 can suppress endothelial cell activation and angiogenesis. Furthermore, we identified the impaired ADAM10-AXL axis as a driver of retinal angiogenesis. Conclusion: We demonstrate restoration of aberrant ectodomain shedding as an effective strategy for treating PDR and propose ADAM10 as an attractive therapeutic target. In all, our study uncovered impaired ectodomain shedding as a prominent feature of PDR, opening new possibilities for advancement in the DR therapeutic space.
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    Analysis of clinically relevant variants from ancestrally diverse Asian genomes.
    Chan, SH ; Bylstra, Y ; Teo, JX ; Kuan, JL ; Bertin, N ; Gonzalez-Porta, M ; Hebrard, M ; Tirado-Magallanes, R ; Tan, JHJ ; Jeyakani, J ; Li, Z ; Chai, JF ; Chong, YS ; Davila, S ; Goh, LL ; Lee, ES ; Wong, E ; Wong, TY ; SG10K_Health Consortium, ; Prabhakar, S ; Liu, J ; Cheng, C-Y ; Eisenhaber, B ; Karnani, N ; Leong, KP ; Sim, X ; Yeo, KK ; Chambers, JC ; Tai, E-S ; Tan, P ; Jamuar, SS ; Ngeow, J ; Lim, WK (Springer Science and Business Media LLC, 2022-11-05)
    Asian populations are under-represented in human genomics research. Here, we characterize clinically significant genetic variation in 9051 genomes representing East Asian, South Asian, and severely under-represented Austronesian-speaking Southeast Asian ancestries. We observe disparate genetic risk burden attributable to ancestry-specific recurrent variants and identify individuals with variants specific to ancestries discordant to their self-reported ethnicity, mostly due to cryptic admixture. About 27% of severe recessive disorder genes with appreciable carrier frequencies in Asians are missed by carrier screening panels, and we estimate 0.5% Asian couples at-risk of having an affected child. Prevalence of medically-actionable variant carriers is 3.4% and a further 1.6% harbour variants with potential for pathogenic classification upon additional clinical/experimental evidence. We profile 23 pharmacogenes with high-confidence gene-drug associations and find 22.4% of Asians at-risk of Centers for Disease Control and Prevention Tier 1 genetic conditions concurrently harbour pharmacogenetic variants with actionable phenotypes, highlighting the benefits of pre-emptive pharmacogenomics. Our findings illuminate the diversity in genetic disease epidemiology and opportunities for precision medicine for a large, diverse Asian population.
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    Classification of diabetic retinopathy: Past, present and future.
    Yang, Z ; Tan, T-E ; Shao, Y ; Wong, TY ; Li, X (Frontiers Media SA, 2022)
    Diabetic retinopathy (DR) is a leading cause of visual impairment and blindness worldwide. Since DR was first recognized as an important complication of diabetes, there have been many attempts to accurately classify the severity and stages of disease. These historical classification systems evolved as understanding of disease pathophysiology improved, methods of imaging and assessing DR changed, and effective treatments were developed. Current DR classification systems are effective, and have been the basis of major research trials and clinical management guidelines for decades. However, with further new developments such as recognition of diabetic retinal neurodegeneration, new imaging platforms such as optical coherence tomography and ultra wide-field retinal imaging, artificial intelligence and new treatments, our current classification systems have significant limitations that need to be addressed. In this paper, we provide a historical review of different classification systems for DR, and discuss the limitations of our current classification systems in the context of new developments. We also review the implications of new developments in the field, to see how they might feature in a future, updated classification.
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    Diabetic retinopathy: Looking forward to 2030.
    Tan, T-E ; Wong, TY (Frontiers Media SA, 2022)
    Diabetic retinopathy (DR) is the major ocular complication of diabetes mellitus, and is a problem with significant global health impact. Major advances in diagnostics, technology and treatment have already revolutionized how we manage DR in the early part of the 21st century. For example, the accessibility of imaging with optical coherence tomography, and the development of anti-vascular endothelial growth factor (VEGF) treatment are just some of the landmark developments that have shaped the DR landscape over the last few decades. Yet, there are still more exciting advances being made. Looking forward to 2030, many of these ongoing developments are likely to further transform the field. First, epidemiologic projections show that the global burden of DR is not only increasing, but also shifting from high-income countries towards middle- and low-income areas. Second, better understanding of disease pathophysiology is placing greater emphasis on retinal neural dysfunction and non-vascular aspects of diabetic retinal disease. Third, a wealth of information is becoming available from newer imaging modalities such as widefield imaging systems and optical coherence tomography angiography. Fourth, artificial intelligence for screening, diagnosis and prognostication of DR will become increasingly accessible and important. Fifth, new pharmacologic agents targeting other non-VEGF-driven pathways, and novel therapeutic strategies such as gene therapy are being developed for DR. Finally, the classification system for diabetic retinal disease will need to be continually updated to keep pace with new developments. In this article, we discuss these major trends in DR that we expect to see in 2030 and beyond.
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    Genomics of perivascular space burden unravels early mechanisms of cerebral small vessel disease.
    Duperron, M-G ; Knol, MJ ; Le Grand, Q ; Evans, TE ; Mishra, A ; Tsuchida, A ; Roshchupkin, G ; Konuma, T ; Trégouët, D-A ; Romero, JR ; Frenzel, S ; Luciano, M ; Hofer, E ; Bourgey, M ; Dueker, ND ; Delgado, P ; Hilal, S ; Tankard, RM ; Dubost, F ; Shin, J ; Saba, Y ; Armstrong, NJ ; Bordes, C ; Bastin, ME ; Beiser, A ; Brodaty, H ; Bülow, R ; Carrera, C ; Chen, C ; Cheng, C-Y ; Deary, IJ ; Gampawar, PG ; Himali, JJ ; Jiang, J ; Kawaguchi, T ; Li, S ; Macalli, M ; Marquis, P ; Morris, Z ; Muñoz Maniega, S ; Miyamoto, S ; Okawa, M ; Paradise, M ; Parva, P ; Rundek, T ; Sargurupremraj, M ; Schilling, S ; Setoh, K ; Soukarieh, O ; Tabara, Y ; Teumer, A ; Thalamuthu, A ; Trollor, JN ; Valdés Hernández, MC ; Vernooij, MW ; Völker, U ; Wittfeld, K ; Wong, TY ; Wright, MJ ; Zhang, J ; Zhao, W ; Zhu, Y-C ; Schmidt, H ; Sachdev, PS ; Wen, W ; Yoshida, K ; Joutel, A ; Satizabal, CL ; Sacco, RL ; Bourque, G ; CHARGE consortium, ; Lathrop, M ; Paus, T ; Fernandez-Cadenas, I ; Yang, Q ; Mazoyer, B ; Boutinaud, P ; Okada, Y ; Grabe, HJ ; Mather, KA ; Schmidt, R ; Joliot, M ; Ikram, MA ; Matsuda, F ; Tzourio, C ; Wardlaw, JM ; Seshadri, S ; Adams, HHH ; Debette, S (Springer Science and Business Media LLC, 2023-04)
    Perivascular space (PVS) burden is an emerging, poorly understood, magnetic resonance imaging marker of cerebral small vessel disease, a leading cause of stroke and dementia. Genome-wide association studies in up to 40,095 participants (18 population-based cohorts, 66.3 ± 8.6 yr, 96.9% European ancestry) revealed 24 genome-wide significant PVS risk loci, mainly in the white matter. These were associated with white matter PVS already in young adults (N = 1,748; 22.1 ± 2.3 yr) and were enriched in early-onset leukodystrophy genes and genes expressed in fetal brain endothelial cells, suggesting early-life mechanisms. In total, 53% of white matter PVS risk loci showed nominally significant associations (27% after multiple-testing correction) in a Japanese population-based cohort (N = 2,862; 68.3 ± 5.3 yr). Mendelian randomization supported causal associations of high blood pressure with basal ganglia and hippocampal PVS, and of basal ganglia PVS and hippocampal PVS with stroke, accounting for blood pressure. Our findings provide insight into the biology of PVS and cerebral small vessel disease, pointing to pathways involving extracellular matrix, membrane transport and developmental processes, and the potential for genetically informed prioritization of drug targets.
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    A saturated map of common genetic variants associated with human height
    Yengo, L ; Vedantam, S ; Marouli, E ; Sidorenko, J ; Bartell, E ; Sakaue, S ; Graff, M ; Eliasen, AU ; Jiang, Y ; Raghavan, S ; Miao, J ; Arias, JD ; Graham, SE ; Mukamel, RE ; Spracklen, CN ; Yin, X ; Chen, S-H ; Ferreira, T ; Highland, HH ; Ji, Y ; Karaderi, T ; Lin, K ; Lull, K ; Malden, DE ; Medina-Gomez, C ; Machado, M ; Moore, A ; Rueger, S ; Sim, X ; Vrieze, S ; Ahluwalia, TS ; Akiyama, M ; Allison, MA ; Alvarez, M ; Andersen, MK ; Ani, A ; Appadurai, V ; Arbeeva, L ; Bhaskar, S ; Bielak, LF ; Bollepalli, S ; Bonnycastle, LL ; Bork-Jensen, J ; Bradfield, JP ; Bradford, Y ; Braund, PS ; Brody, JA ; Burgdorf, KS ; Cade, BE ; Cai, H ; Cai, Q ; Campbell, A ; Canadas-Garre, M ; Catamo, E ; Chai, J-F ; Chai, X ; Chang, L-C ; Chang, Y-C ; Chen, C-H ; Chesi, A ; Choi, SH ; Chung, R-H ; Cocca, M ; Concas, MP ; Couture, C ; Cuellar-Partida, G ; Danning, R ; Daw, EW ; Degenhard, F ; Delgado, GE ; Delitala, A ; Demirkan, A ; Deng, X ; Devineni, P ; Dietl, A ; Dimitriou, M ; Dimitrov, L ; Dorajoo, R ; Ekici, AB ; Engmann, JE ; Fairhurst-Hunter, Z ; Farmaki, A-E ; Faul, JD ; Fernandez-Lopez, J-C ; Forer, L ; Francescatto, M ; Freitag-Wolf, S ; Fuchsberger, C ; Galesloot, TE ; Gao, Y ; Gao, Z ; Geller, F ; Giannakopoulou, O ; Giulianini, F ; Gjesing, AP ; Goel, A ; Gordon, SD ; Gorski, M ; Grove, J ; Guo, X ; Gustafsson, S ; Haessler, J ; Hansen, TF ; Havulinna, AS ; Haworth, SJ ; He, J ; Heard-Costa, N ; Hebbar, P ; Hindy, G ; Ho, Y-LA ; Hofer, E ; Holliday, E ; Horn, K ; Hornsby, WE ; Hottenga, J-J ; Huang, H ; Huang, J ; Huerta-Chagoya, A ; Huffman, JE ; Hung, Y-J ; Huo, S ; Hwang, MY ; Iha, H ; Ikeda, DD ; Isono, M ; Jackson, AU ; Jager, S ; Jansen, IE ; Johansson, I ; Jonas, JB ; Jonsson, A ; Jorgensen, T ; Kalafati, I-P ; Kanai, M ; Kanoni, S ; Karhus, LL ; Kasturiratne, A ; Katsuya, T ; Kawaguchi, T ; Kember, RL ; Kentistou, KA ; Kim, H-N ; Kim, YJ ; Kleber, ME ; Knol, MJ ; Kurbasic, A ; Lauzon, M ; Le, P ; Lea, R ; Lee, J-Y ; Leonard, HL ; Li, SA ; Li, X ; Li, X ; Liang, J ; Lin, H ; Lin, S-Y ; Liu, J ; Liu, X ; Lo, KS ; Long, J ; Lores-Motta, L ; Luan, J ; Lyssenko, V ; Lyytikainen, L-P ; Mahajan, A ; Mamakou, V ; Mangino, M ; Manichaikul, A ; Marten, J ; Mattheisen, M ; Mavarani, L ; McDaid, AF ; Meidtner, K ; Melendez, TL ; Mercader, JM ; Milaneschi, Y ; Miller, JE ; Millwood, IY ; Mishra, PP ; Mitchell, RE ; Mollehave, LT ; Morgan, A ; Mucha, S ; Munz, M ; Nakatochi, M ; Nelson, CP ; Nethander, M ; Nho, CW ; Nielsen, AA ; Nolte, IM ; Nongmaithem, SS ; Noordam, R ; Ntalla, I ; Nutile, T ; Pandit, A ; Christofidou, P ; Parna, K ; Pauper, M ; Petersen, ERB ; Petersen, L ; Pitkanen, N ; Polasek, O ; Poveda, A ; Preuss, MH ; Pyarajan, S ; Raffield, LM ; Rakugi, H ; Ramirez, J ; Rasheed, A ; Raven, D ; Rayner, NW ; Riveros, C ; Rohde, R ; Ruggiero, D ; Ruotsalainen, SE ; Ryan, KA ; Sabater-Lleal, M ; Saxena, R ; Scholz, M ; Sendamarai, A ; Shen, B ; Shi, J ; Shin, JH ; Sidore, C ; Sitlani, CM ; Slieker, RKC ; Smit, RAJ ; Smith, A ; Smith, JA ; Smyth, LJ ; Southam, LE ; Steinthorsdottir, V ; Sun, L ; Takeuchi, F ; Tallapragada, D ; Taylor, KD ; Tayo, BO ; Tcheandjieu, C ; Terzikhan, N ; Tesolin, P ; Teumer, A ; Theusch, E ; Thompson, DJ ; Thorleifsson, G ; Timmers, PRHJ ; Trompet, S ; Turman, C ; Vaccargiu, S ; van der Laan, SW ; van der Most, PJ ; van Klinken, JB ; van Setten, J ; Verma, SS ; Verweij, N ; Veturi, Y ; Wang, CA ; Wang, C ; Wang, L ; Wang, Z ; Warren, HR ; Wei, WB ; Wickremasinghe, AR ; Wielscher, M ; Wiggins, KL ; Winsvold, BS ; Wong, A ; Wu, Y ; Wuttke, M ; Xia, R ; Xie, T ; Yamamoto, K ; Yang, J ; Yao, J ; Young, H ; Yousri, NA ; Yu, L ; Zeng, L ; Zhang, W ; Zhang, X ; Zhao, J-H ; Zhao, W ; Zhou, W ; Zimmermann, ME ; Zoledziewska, M ; Adair, LS ; Adams, HHH ; Aguilar-Salinas, CA ; Al-Mulla, F ; Arnett, DK ; Asselbergs, FW ; Asvold, BO ; Attia, J ; Banas, B ; Bandinelli, S ; Bennett, DA ; Bergler, T ; Bharadwaj, D ; Biino, G ; Bisgaard, H ; Boerwinkle, E ; Boger, CA ; Bonnelykke, K ; Boomsma, D ; Borglum, AD ; Borja, JB ; Bouchard, C ; Bowden, DW ; Brandslund, I ; Brumpton, B ; Buring, JE ; Caulfield, MJ ; Chambers, JC ; Chandak, GR ; Chanock, SJ ; Chaturvedi, N ; Chen, Y-DI ; Chen, Z ; Cheng, C-Y ; Christophersen, IE ; Ciullo, M ; Cole, JW ; Collins, FS ; Cooper, RS ; Cruz, M ; Cucca, F ; Cupples, LA ; Cutler, MJ ; Damrauer, SM ; Dantoft, TM ; de Borst, GJ ; de Groot, LCPGM ; De Jager, PL ; de Kleijn, DP ; de Silva, HJ ; Dedoussis, G ; den Hollander, A ; Du, S ; Easton, DF ; Elders, PJM ; Eliassen, AH ; Ellinor, PT ; Elmstahl, S ; Erdmann, J ; Evans, MK ; Fatkin, D ; Feenstra, B ; Feitosa, MF ; Ferrucci, L ; Ford, I ; Fornage, M ; Franke, A ; Franks, PW ; Freedman, B ; Gasparini, P ; Gieger, C ; Girotto, G ; Goddard, ME ; Golightly, YM ; Gonzalez-Villalpando, C ; Gordon-Larsen, P ; Grallert, H ; Grant, SFA ; Grarup, N ; Griffiths, L ; Gudnason, V ; Haiman, C ; Hakonarson, H ; Hansen, T ; Hartman, CA ; Hattersley, AT ; Hayward, C ; Heckbert, SR ; Heng, C-K ; Hengstenberg, C ; Hewitt, AW ; Hishigaki, H ; Hoyng, CB ; Huang, PL ; Huang, W ; Hunt, SC ; Hveem, K ; Hypponen, E ; Iacono, WG ; Ichihara, S ; Ikram, MA ; Isasi, CR ; Jackson, RD ; Jarvelin, M-R ; Jin, Z-B ; Jockel, K-H ; Joshi, PK ; Jousilahti, P ; Jukema, JW ; Kahonen, M ; Kamatani, Y ; Kang, KD ; Kaprio, J ; Kardia, SLR ; Karpe, F ; Kato, N ; Kee, F ; Kessler, T ; Khera, A ; Khor, CC ; Kiemeney, LALM ; Kim, B-J ; Kim, EK ; Kim, H-L ; Kirchhof, P ; Kivimaki, M ; Koh, W-P ; Koistinen, HA ; Kolovou, GD ; Kooner, JS ; Kooperberg, C ; Kottgen, A ; Kovacs, P ; Kraaijeveld, A ; Kraft, P ; Krauss, RM ; Kumari, M ; Kutalik, Z ; Laakso, M ; Lange, LA ; Langenberg, C ; Launer, LJ ; Le Marchand, L ; Lee, H ; Lee, NR ; Lehtimaki, T ; Li, H ; Li, L ; Lieb, W ; Lin, X ; Lind, L ; Linneberg, A ; Liu, C-T ; Liu, J ; Loeffler, M ; London, B ; Lubitz, SA ; Lye, SJ ; Mackey, DA ; Magi, R ; Magnusson, PKE ; Marcus, GM ; Vidal, PM ; Martin, NG ; Marz, W ; Matsuda, F ; McGarrah, RW ; McGue, M ; McKnight, AJ ; Medland, SE ; Mellstrom, D ; Metspalu, A ; Mitchell, BD ; Mitchell, P ; Mook-Kanamori, DO ; Morris, AD ; Mucci, LA ; Munroe, PB ; Nalls, MA ; Nazarian, S ; Nelson, AE ; Neville, MJ ; Newton-Cheh, C ; Nielsen, CS ; Nothen, MM ; Ohlsson, C ; Oldehinkel, AJ ; Orozco, L ; Pahkala, K ; Pajukanta, P ; Palmer, CNA ; Parra, EJ ; Pattaro, C ; Pedersen, O ; Pennell, CE ; Penninx, BWJH ; Perusse, L ; Peters, A ; Peyser, PA ; Porteous, DJ ; Posthuma, D ; Power, C ; Pramstaller, PP ; Province, MA ; Qi, Q ; Qu, J ; Rader, DJ ; Raitakari, OT ; Ralhan, S ; Rallidis, LS ; Rao, DC ; Redline, S ; Reilly, DF ; Reiner, AP ; Rhee, SY ; Ridker, PM ; Rienstra, M ; Ripatti, S ; Ritchie, MD ; Roden, DM ; Rosendaal, FR ; Rotter, J ; Rudan, I ; Rutters, F ; Sabanayagam, C ; Saleheen, D ; Salomaa, V ; Samani, NJ ; Sanghera, DK ; Sattar, N ; Schmidt, B ; Schmidt, H ; Schmidt, R ; Schulze, MB ; Schunkert, H ; Scott, LJ ; Scott, RJ ; Sever, P ; Shiroma, EJ ; Shoemaker, MB ; Shu, X-O ; Simonsick, EM ; Sims, M ; Singh, JR ; Singleton, AB ; Sinner, MF ; Smith, JG ; Snieder, H ; Spector, TD ; Stampfer, MJ ; Stark, KJ ; Strachan, DP ; t' Hart, LM ; Tabara, Y ; Tang, H ; Tardif, J-C ; Thanaraj, TA ; Timpson, NJ ; Tonjes, A ; Tremblay, A ; Tuomi, T ; Tuomilehto, J ; Tusie-Luna, M-T ; Uitterlinden, AG ; van Dam, RM ; van der Harst, P ; Van der Velde, N ; van Duijn, CM ; van Schoor, NM ; Vitart, V ; Volker, U ; Vollenweider, P ; Volzke, H ; Wacher-Rodarte, NH ; Walker, M ; Wang, YX ; Wareham, NJ ; Watanabe, RM ; Watkins, H ; Weir, DR ; Werge, TM ; Widen, E ; Wilkens, LR ; Willemsen, G ; Willett, WC ; Wilson, JF ; Wong, T-Y ; Woo, J-T ; Wright, AF ; Wu, J-Y ; Xu, H ; Yajnik, CS ; Yokota, M ; Yuan, J-M ; Zeggini, E ; Zemel, BS ; Zheng, W ; Zhu, X ; Zmuda, JM ; Zonderman, AB ; Zwart, J-A ; Chasman, D ; Cho, YS ; Heid, IM ; McCarthy, M ; Ng, MCY ; O'Donnell, CJ ; Rivadeneira, F ; Thorsteinsdottir, U ; Sun, Y ; Tai, ES ; Boehnke, M ; Deloukas, P ; Justice, AE ; Lindgren, CM ; Loos, RJF ; Mohlke, KL ; North, KE ; Stefansson, K ; Walters, RG ; Winkler, TW ; Young, KL ; Loh, P-R ; Yang, J ; Esko, T ; Assimes, TL ; Auton, A ; Abecasis, GR ; Willer, CJ ; Locke, AE ; Berndt, S ; Lettre, G ; Frayling, TM ; Okada, Y ; Wood, AR ; Visscher, PM ; Hirschhorn, JN (NATURE PORTFOLIO, 2022-10-27)
    Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.
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    A genome-wide association study of corneal astigmatism: The CREAM Consortium
    Shah, RL ; Li, Q ; Zhao, W ; Tedja, MS ; Tideman, JWL ; Khawaja, AP ; Fan, Q ; Yazar, S ; Williams, KM ; Verhoeven, VJM ; Xie, J ; Wang, YX ; Hess, M ; Nickels, S ; Lackner, KJ ; Parssinen, O ; Wedenoja, J ; Biino, G ; Concas, MP ; Uitterlinden, A ; Rivadeneira, F ; Jaddoe, VWV ; Hysi, PG ; Sim, X ; Tan, N ; Tham, Y-C ; Sensaki, S ; Hofman, A ; Vingerling, JR ; Jonas, JB ; Mitchell, P ; Hammond, CJ ; Hoehn, R ; Baird, PN ; Wong, T-Y ; Cheng, C-Y ; Teo, YY ; Mackey, DA ; Williams, C ; Saw, S-M ; Klaver, CCW ; Guggenheim, JA ; Bailey-Wilson, JE (MOLECULAR VISION, 2018-02-05)
    PURPOSE: To identify genes and genetic markers associated with corneal astigmatism. METHODS: A meta-analysis of genome-wide association studies (GWASs) of corneal astigmatism undertaken for 14 European ancestry (n=22,250) and 8 Asian ancestry (n=9,120) cohorts was performed by the Consortium for Refractive Error and Myopia. Cases were defined as having >0.75 diopters of corneal astigmatism. Subsequent gene-based and gene-set analyses of the meta-analyzed results of European ancestry cohorts were performed using VEGAS2 and MAGMA software. Additionally, estimates of single nucleotide polymorphism (SNP)-based heritability for corneal and refractive astigmatism and the spherical equivalent were calculated for Europeans using LD score regression. RESULTS: The meta-analysis of all cohorts identified a genome-wide significant locus near the platelet-derived growth factor receptor alpha (PDGFRA) gene: top SNP: rs7673984, odds ratio=1.12 (95% CI:1.08-1.16), p=5.55×10-9. No other genome-wide significant loci were identified in the combined analysis or European/Asian ancestry-specific analyses. Gene-based analysis identified three novel candidate genes for corneal astigmatism in Europeans-claudin-7 (CLDN7), acid phosphatase 2, lysosomal (ACP2), and TNF alpha-induced protein 8 like 3 (TNFAIP8L3). CONCLUSIONS: In addition to replicating a previously identified genome-wide significant locus for corneal astigmatism near the PDGFRA gene, gene-based analysis identified three novel candidate genes, CLDN7, ACP2, and TNFAIP8L3, that warrant further investigation to understand their role in the pathogenesis of corneal astigmatism. The much lower number of genetic variants and genes demonstrating an association with corneal astigmatism compared to published spherical equivalent GWAS analyses suggest a greater influence of rare genetic variants, non-additive genetic effects, or environmental factors in the development of astigmatism.