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Cao K, Yeung J, Arafat Y, Qiao J, Gartrell R, Master M, Yeung JMC, Baird PN. Using a new artificial intelligence-aided method to assess body composition CT segmentation in colorectal cancer patients. J Med Radiat Sci 2024. [PMID: 38777346 DOI: 10.1002/jmrs.798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 05/04/2024] [Indexed: 05/25/2024] Open
Abstract
INTRODUCTION This study aimed to evaluate the accuracy of our own artificial intelligence (AI)-generated model to assess automated segmentation and quantification of body composition-derived computed tomography (CT) slices from the lumber (L3) region in colorectal cancer (CRC) patients. METHODS A total of 541 axial CT slices at the L3 vertebra were retrospectively collected from 319 patients with CRC diagnosed during 2012-2019 at a single Australian tertiary institution, Western Health in Melbourne. A two-dimensional U-Net convolutional network was trained on 338 slices to segment muscle, visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). Manual reading of these same slices of muscle, VAT and SAT was created to serve as ground truth data. The Dice similarity coefficient was used to assess the U-Net-based segmentation performance on both a validation dataset (68 slices) and a test dataset (203 slices). The measurement of cross-sectional area and Hounsfield unit (HU) density of muscle, VAT and SAT were compared between two methods. RESULTS The segmentation for muscle, VAT and SAT demonstrated excellent performance for both the validation (Dice similarity coefficients >0.98, respectively) and test (Dice similarity coefficients >0.97, respectively) datasets. There was a strong positive correlation between manual and AI segmentation measurements of body composition for both datasets (Spearman's correlation coefficients: 0.944-0.999, P < 0.001). CONCLUSIONS Compared to the gold standard, this fully automated segmentation system exhibited a high accuracy for assessing segmentation and quantification of abdominal muscle and adipose tissues of CT slices at the L3 in CRC patients.
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Affiliation(s)
- Ke Cao
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
| | - Josephine Yeung
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
| | - Yasser Arafat
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
- Department of Colorectal Surgery, Western Health, Melbourne, Victoria, Australia
| | - Jing Qiao
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
| | - Richard Gartrell
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
| | - Mobin Master
- Department of Radiology, Western Health, Melbourne, Victoria, Australia
| | - Justin M C Yeung
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
- Department of Colorectal Surgery, Western Health, Melbourne, Victoria, Australia
| | - Paul N Baird
- Department of Surgery, University of Melbourne, Melbourne, Victoria, Australia
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Suthakaran R, Cao K, Arafat Y, Yeung J, Chan S, Master M, Faragher IG, Baird PN, Yeung JMC. Body composition assessment by artificial intelligence can be a predictive tool for short-term postoperative complications in Hartmann's reversals. BMC Surg 2024; 24:111. [PMID: 38622633 PMCID: PMC11017666 DOI: 10.1186/s12893-024-02408-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 04/09/2024] [Indexed: 04/17/2024] Open
Abstract
BACKGROUND Hartmann's reversal, a complex elective surgery, reverses and closes the colostomy in individuals who previously underwent a Hartmann's procedure due to colonic pathology like cancer or diverticulitis. It demands careful planning and patient optimisation to help reduce postoperative complications. Preoperative evaluation of body composition has been useful in identifying patients at high risk of short-term postoperative outcomes following colorectal cancer surgery. We sought to explore the use of our in-house derived Artificial Intelligence (AI) algorithm to measure body composition within patients undergoing Hartmann's reversal procedure in the prediction of short-term postoperative complications. METHODS A retrospective study of all patients who underwent Hartmann's reversal within a single tertiary referral centre (Western) in Melbourne, Australia and who had a preoperative Computerised Tomography (CT) scan performed. Body composition was measured using our previously validated AI algorithm for body segmentation developed by the Department of Surgery, Western Precinct, University of Melbourne. Sarcopenia in our study was defined as a skeletal muscle index (SMI), calculated as Skeletal Muscle Area (SMA) /height2 < 38.5 cm2/m2 in women and < 52.4 cm2/m2 in men. RESULTS Between 2010 and 2020, 47 patients (mean age 63.1 ± 12.3 years; male, n = 28 (59.6%) underwent body composition analysis. Twenty-one patients (44.7%) were sarcopenic, and 12 (25.5%) had evidence of sarcopenic obesity. The most common postoperative complication was surgical site infection (SSI) (n = 8, 17%). Sarcopenia (n = 7, 87.5%, p = 0.02) and sarcopenic obesity (n = 5, 62.5%, p = 0.02) were significantly associated with SSIs. The risks of developing an SSI were 8.7 times greater when sarcopenia was present. CONCLUSION Sarcopenia and sarcopenic obesity were related to postoperative complications following Hartmann's reversal. Body composition measured by a validated AI algorithm may be a beneficial tool for predicting short-term surgical outcomes for these patients.
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Affiliation(s)
- Reshi Suthakaran
- Department of Colorectal Surgery, Western Health, Footscray, Melbourne, VIC, 3011, Australia.
- Department of Surgery, Western Precinct, University of Melbourne, Level 3, WCHRE, Sunshine Hospital, St Albans, Melbourne, VIC, 3021, Australia.
| | - Ke Cao
- Department of Surgery, Western Precinct, University of Melbourne, Level 3, WCHRE, Sunshine Hospital, St Albans, Melbourne, VIC, 3021, Australia
| | - Yasser Arafat
- Department of Colorectal Surgery, Western Health, Footscray, Melbourne, VIC, 3011, Australia
- Department of Surgery, Western Precinct, University of Melbourne, Level 3, WCHRE, Sunshine Hospital, St Albans, Melbourne, VIC, 3021, Australia
| | - Josephine Yeung
- Department of Surgery, Western Precinct, University of Melbourne, Level 3, WCHRE, Sunshine Hospital, St Albans, Melbourne, VIC, 3021, Australia
| | - Steven Chan
- Department of Surgery, Western Precinct, University of Melbourne, Level 3, WCHRE, Sunshine Hospital, St Albans, Melbourne, VIC, 3021, Australia
| | - Mobin Master
- Department of Radiology, Western Health, Melbourne, Australia
| | - Ian G Faragher
- Department of Colorectal Surgery, Western Health, Footscray, Melbourne, VIC, 3011, Australia
| | - Paul N Baird
- Department of Surgery, Western Precinct, University of Melbourne, Level 3, WCHRE, Sunshine Hospital, St Albans, Melbourne, VIC, 3021, Australia
| | - Justin M C Yeung
- Department of Colorectal Surgery, Western Health, Footscray, Melbourne, VIC, 3011, Australia.
- Department of Surgery, Western Precinct, University of Melbourne, Level 3, WCHRE, Sunshine Hospital, St Albans, Melbourne, VIC, 3021, Australia.
- Western Health Chronic Disease Alliance, Western Health, Footscray Hospital, Melbourne, VIC, 3011, Australia.
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Wei MY, Cao K, Hong W, Yeung J, Lee M, Gibbs P, Faragher IG, Baird PN, Yeung JM. Artificial intelligence measured 3D body composition to predict pathological response in rectal cancer patients. ANZ J Surg 2024. [PMID: 38456517 DOI: 10.1111/ans.18929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 02/24/2024] [Accepted: 02/26/2024] [Indexed: 03/09/2024]
Abstract
BACKGROUND The treatment of locally advanced rectal cancer (LARC) is moving towards total neoadjuvant therapy and potential organ preservation. Of particular interest are predictors of pathological complete response (pCR) that can guide personalized treatment. There are currently no clinical biomarkers which can accurately predict neoadjuvant therapy (NAT) response but body composition (BC) measures present as an emerging contender. The primary aim of the study was to determine if artificial intelligence (AI) derived body composition variables can predict pCR in patients with LARC. METHODS LARC patients who underwent NAT followed by surgery from 2012 to 2023 were identified from the Australian Comprehensive Cancer Outcomes and Research Database registry (ACCORD). A validated in-house pre-trained 3D AI model was used to measure body composition via computed tomography images of the entire Lumbar-3 vertebral level to produce a volumetric measurement of visceral fat (VF), subcutaneous fat (SCF) and skeletal muscle (SM). Multivariate analysis between patient body composition and histological outcomes was performed. RESULTS Of 214 LARC patients treated with NAT, 22.4% of patients achieved pCR. SM volume (P = 0.015) and age (P = 0.03) were positively associated with pCR in both male and female patients. SCF volume was associated with decreased likelihood of pCR (P = 0.059). CONCLUSION This is the first study in the literature utilizing AI-measured 3D Body composition in LARC patients to assess their impact on pathological response. SM volume and age were positive predictors of pCR disease in both male and female patients following NAT for LARC. Future studies investigating the impact of body composition on clinical outcomes and patients on other neoadjuvant regimens such as TNT are potential avenues for further research.
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Affiliation(s)
- Matthew Y Wei
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
- Department of Colorectal Surgery, Western Health, Melbourne, Victoria, Australia
| | - Ke Cao
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
| | - Wei Hong
- Gibbs Lab, Walter and Eliza Hall Institute, Melbourne, Victoria, Australia
| | - Josephine Yeung
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
| | - Margaret Lee
- Department of Medical Oncology, Western Health, Melbourne, Victoria, Australia
| | - Peter Gibbs
- Gibbs Lab, Walter and Eliza Hall Institute, Melbourne, Victoria, Australia
- Department of Medical Oncology, Western Health, Melbourne, Victoria, Australia
| | - Ian G Faragher
- Department of Colorectal Surgery, Western Health, Melbourne, Victoria, Australia
| | - Paul N Baird
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
| | - Justin M Yeung
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
- Department of Colorectal Surgery, Western Health, Melbourne, Victoria, Australia
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Choi CS, Kin K, Cao K, Hutcheon E, Lee M, Chan STF, Arafat Y, Baird PN, Yeung JMC. The association of body composition on chemotherapy toxicities in non-metastatic colorectal cancer patients: a systematic review. ANZ J Surg 2024; 94:327-334. [PMID: 38059530 DOI: 10.1111/ans.18812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 11/22/2023] [Accepted: 11/24/2023] [Indexed: 12/08/2023]
Abstract
BACKGROUND In recent years, certain body composition measures, assessed by computed tomography (CT), have been found to be associated with chemotherapy toxicities. This review aims to explore available data on the relationship between skeletal muscle and adiposity, including visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), intramuscular and intermuscular adipose tissue and their association with chemotherapy toxicity in non-metastatic colorectal cancer (CRC) patients. METHODS A systematic literature search following PRISMA guidelines was conducted in Medline, Embase, Cochrane and Web of Science, for papers published between 2011 and 2023. The search strategy combined keywords and MESH terms relevant to 'body composition', 'chemotherapy toxicities', and 'non-metastatic colorectal cancer'. RESULTS Out of 3868 studies identified, six retrospective studies fulfilled the inclusion criteria with 1024 eligible patients. Low skeletal muscle mass was strongly associated with increased incidence of both chemotherapy toxicities and dose-limiting toxicity (DLT). The association of VAT, intramuscular and intermuscular adiposity was heterogeneous and inconclusive. There was no association between SAT and chemotherapy intolerance. No universal definitions or cut-offs for sarcopenia and obesity were noted. All studies utilized 2-dimensional (2D) CT slices for CT body composition assessment with varied selection on the vertebral landmark and inconsistent reporting of tissue-defining Hounsfield unit (HU) measurements. CONCLUSION Low skeletal muscle is associated with chemotherapy toxicities in non-metastatic CRC. However, quality evidence on the role of adiposity is limited and heterogeneous. More studies are needed to confirm these associations with an emphasis on a more coherent body composition definition and an approach to its assessment, especially regarding sarcopenia.
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Affiliation(s)
- Cheuk Shan Choi
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
| | - Kamol Kin
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
| | - Ke Cao
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
| | - Evelyn Hutcheon
- Western Health Library Service, Western Health, Melbourne, Victoria, Australia
| | - Margaret Lee
- Department of Medical Oncology, Western Health, Melbourne, Victoria, Australia
| | - Steven T F Chan
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
| | - Yasser Arafat
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
- Department of Colorectal Surgery, Western Health, Melbourne, Victoria, Australia
| | - Paul N Baird
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
| | - Justin M C Yeung
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Victoria, Australia
- Department of Colorectal Surgery, Western Health, Melbourne, Victoria, Australia
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Cao K, Yeung J, Arafat Y, Choi C, Wei MYK, Chan S, Lee M, Baird PN, Yeung JMC. Can AI-based body composition assessment outperform body surface area in predicting dose-limiting toxicities for colonic cancer patients on chemotherapy? J Cancer Res Clin Oncol 2023; 149:13915-13923. [PMID: 37540253 PMCID: PMC10590342 DOI: 10.1007/s00432-023-05227-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 07/28/2023] [Indexed: 08/05/2023]
Abstract
PURPOSE Gold standard chemotherapy dosage is based on body surface area (BSA); however many patients experience dose-limiting toxicities (DLT). We aimed to evaluate the effectiveness of BSA, two-dimensional (2D) and three-dimensional (3D) body composition (BC) measurements derived from Lumbar 3 vertebra (L3) computed tomography (CT) slices, in predicting DLT in colon cancer patients. METHODS 203 patients (60.87 ± 12.42 years; 97 males, 47.8%) receiving adjuvant chemotherapy (Oxaliplatin and/or 5-Fluorouracil) were retrospectively evaluated. An artificial intelligence segmentation model was used to extract 2D and 3D body composition measurements from each patients' single mid-L3 CT slice as well as multiple-L3 CT scans to produce a 3D BC report. DLT was defined as any incidence of dose reduction or discontinuation due to chemotherapy toxicities. A receiver operating characteristic (ROC) analysis was performed on BSA and individual body composition measurements to demonstrate their predictive performance. RESULTS A total of 120 (59.1%) patients experienced DLT. Age and BSA did not vary significantly between DLT and non-DLT group. Females were significantly more likely to experience DLT (p = 4.9 × 10-3). In all patients, the predictive effectiveness of 2D body composition measurements (females: AUC = 0.50-0.54; males: AUC = 0.50-0.61) was equivalent to that of BSA (females: AUC = 0.49; males: AUC = 0.58). The L3 3D skeletal muscle volume was the most predictive indicator of DLT (AUC of 0.66 in females and 0.64 in males). CONCLUSION Compared to BSA and 2D body composition measurements, 3D L3 body composition measurements had greater potential to predict DLT in CRC patients receiving chemotherapy and this was sex dependent.
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Affiliation(s)
- Ke Cao
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Australia
| | - Josephine Yeung
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Australia
| | - Yasser Arafat
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Australia
- Department of Colorectal Surgery, Western Health, Melbourne, Australia
| | - CheukShan Choi
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Australia
| | - Matthew Y K Wei
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Australia
- Department of Colorectal Surgery, Western Health, Melbourne, Australia
| | - Steven Chan
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Australia
| | - Margaret Lee
- Department of Oncology, Western Health, Melbourne, Australia
| | - Paul N Baird
- Department of Surgery, University of Melbourne, Melbourne, Australia
| | - Justin M C Yeung
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Australia.
- Department of Colorectal Surgery, Western Health, Melbourne, Australia.
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Pan Y, Fu Y, Baird PN, Guymer RH, Das T, Iwata T. Exploring the contribution of ARMS2 and HTRA1 genetic risk factors in age-related macular degeneration. Prog Retin Eye Res 2023; 97:101159. [PMID: 36581531 DOI: 10.1016/j.preteyeres.2022.101159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 12/21/2022] [Accepted: 12/23/2022] [Indexed: 12/29/2022]
Abstract
Age-related macular degeneration (AMD) is the leading cause of severe irreversible central vision loss in individuals over 65 years old. Genome-wide association studies (GWASs) have shown that the region at chromosome 10q26, where the age-related maculopathy susceptibility (ARMS2/LOC387715) and HtrA serine peptidase 1 (HTRA1) genes are located, represents one of the strongest associated loci for AMD. However, the underlying biological mechanism of this genetic association has remained elusive. In this article, we extensively review the literature by us and others regarding the ARMS2/HTRA1 risk alleles and their functional significance. We also review the literature regarding the presumed function of the ARMS2 protein and the molecular processes of the HTRA1 protein in AMD pathogenesis in vitro and in vivo, including those of transgenic mice overexpressing HtrA1/HTRA1 which developed Bruch's membrane (BM) damage, choroidal neovascularization (CNV), and polypoidal choroidal vasculopathy (PCV), similar to human AMD patients. The elucidation of the molecular mechanisms of the ARMS2 and HTRA1 susceptibility loci has begun to untangle the complex biological pathways underlying AMD pathophysiology, pointing to new testable paradigms for treatment.
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Affiliation(s)
- Yang Pan
- Division of Molecular and Cellular Biology, National Institute of Sensory Organs, National Hospital Organization Tokyo Medical Center, 2-5-1, Higashigaoka, Meguro-ku, Tokyo, 152-8902, Japan
| | - Yingbin Fu
- Department of Ophthalmology, Baylor College of Medicine, One Baylor Plaza, NC506, Houston, TX, 77030, USA
| | - Paul N Baird
- Department of Surgery, (Ophthalmology), Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Australia
| | - Robyn H Guymer
- Department of Surgery, (Ophthalmology), Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Australia; Centre for Eye Research Australia, Royal Victorian Eye & Ear Hospital, East Melbourne, Victoria, 3002, Australia
| | - Taraprasad Das
- Anant Bajaj Retina Institute-Srimati Kanuri Santhamma Centre for Vitreoretinal Diseases, Kallam Anji Reddy Campus, L. V. Prasad Eye Institute, Hyderabad, 500034, India
| | - Takeshi Iwata
- Division of Molecular and Cellular Biology, National Institute of Sensory Organs, National Hospital Organization Tokyo Medical Center, 2-5-1, Higashigaoka, Meguro-ku, Tokyo, 152-8902, Japan.
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Cao K, Yeung J, Arafat Y, Wei MYK, Yeung JMC, Baird PN. Identification of Differences in Body Composition Measures Using 3D-Derived Artificial Intelligence from Multiple CT Scans across the L3 Vertebra Compared to a Single Mid-Point L3 CT Scan. Radiol Res Pract 2023; 2023:1047314. [PMID: 37881809 PMCID: PMC10597731 DOI: 10.1155/2023/1047314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 10/06/2023] [Accepted: 10/10/2023] [Indexed: 10/27/2023] Open
Abstract
Purpose Body composition analysis in colorectal cancer (CRC) typically utilises a single 2D-abdominal axial CT slice taken at the mid-L3 level. The use of artificial intelligence (AI) allows for analysis of the entire L3 vertebra (non-mid-L3 and mid-L3). The goal of this study was to determine if the use of an AI approach offered any additional information on capturing body composition measures. Methods A total of 2203 axial CT slices of the entire L3 level (4-46 slices were available per patient) were retrospectively collected from 203 CRC patients treated at Western Health, Melbourne (97 males; 47.8%). A pretrained artificial intelligence (AI) model was used to segment muscle, visceral adipose tissue (VAT), and subcutaneous adipose tissue (SAT) on these slices. The difference in body composition measures between mid-L3 and non-mid-L3 scans was compared for each patient, and for males and females separately. Results Body composition measures derived from non-mid-L3 scans exhibited a median range of 0.85% to 6.28% (average percent difference) when compared to the use of a single mid-L3 scan. Significant variation in the VAT surface area (p = 0.02) was observed in females compared to males, whereas male patients exhibited a greater variation in SAT surface area (p < 0.001) and radiodensity (p = 0.007). Conclusion Significant differences in various body composition measures were observed when comparing non-mid-L3 slices to only the mid-L3 slice. Researchers should be aware that considering only the use of a single midpoint L3 CT scan slice will impact the estimate of body composition measurements.
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Affiliation(s)
- Ke Cao
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Australia
| | - Josephine Yeung
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Australia
| | - Yasser Arafat
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Australia
- Department of Colorectal Surgery, Western Health, University of Melbourne, Melbourne, Australia
| | - Matthew Y. K. Wei
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Australia
- Department of Colorectal Surgery, Western Health, University of Melbourne, Melbourne, Australia
| | - Justin M. C. Yeung
- Department of Surgery, Western Precinct, University of Melbourne, Melbourne, Australia
- Department of Colorectal Surgery, Western Health, University of Melbourne, Melbourne, Australia
| | - Paul N. Baird
- Department of Surgery, University of Melbourne, Melbourne, Australia
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Gartrell R, Qiao J, Kiss N, Faragher I, Chan S, Baird PN, Yeung JM. Can sarcopenia predict survival in locally advanced rectal cancer patients? ANZ J Surg 2023; 93:2166-2171. [PMID: 37209307 DOI: 10.1111/ans.18512] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 04/20/2023] [Accepted: 05/02/2023] [Indexed: 05/22/2023]
Abstract
BACKGROUND There is mounting evidence that suggests sarcopenia can be used to predict survival outcomes in patients with colon cancer. However, the effect on locally advanced rectal cancer (LARC) is less clear. We sought to determine the association between sarcopenia on Overall Survival and Recurrence-free Survival (OS and RFS) in patients with LARC undergoing multimodal treatment. METHODS A retrospective study was undertaken of all pre-treatment stage 2-3 rectal cancer patients who underwent neo-adjuvant treatment and surgery with curative intent between January 2010 and September 2016 at Western Health. Sarcopenia was measured on pre-treatment staging scans at the third lumbar vertebrae and defined using cohort-derived, sex-specific thresholds. Primary outcomes were OS and RFS. RESULTS A total of 132 patients with LARC were analysed. Sarcopenia: Hazard ratio (HR) 3.71; 95% CI, 1.28-10.75, P = 0.016 was independently associated with worse Overall Survival following multivariate analysis. There was no significant relationship between sarcopenia and RFS: Time ratio (TR) 1.67; 95% CI 0.52-5.34, P = 0.386. CONCLUSION Sarcopenia was found to be an independent risk factor for worse overall survival, but not recurrence free survival, in patients with locally advanced rectal cancer undergoing neo-adjuvant chemo-radiotherapy and surgery with curative intent.
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Affiliation(s)
- Richard Gartrell
- Department of Colorectal Surgery, Western Health, Melbourne, Victoria, Australia
- Department of Surgery (Western Precinct), University of Melbourne, Melbourne, Victoria, Australia
| | - Jing Qiao
- Department of Colorectal Surgery, Western Health, Melbourne, Victoria, Australia
| | - Nicole Kiss
- Institute for Physical Activity and Nutrition, Deakin University, Melbourne, Victoria, Australia
- Allied Health Research, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Ian Faragher
- Department of Colorectal Surgery, Western Health, Melbourne, Victoria, Australia
| | - Steven Chan
- Department of Surgery (Western Precinct), University of Melbourne, Melbourne, Victoria, Australia
| | - Paul N Baird
- Department of Surgery (Western Precinct), University of Melbourne, Melbourne, Victoria, Australia
- Department of Surgery, Ophthalmology, University of Melbourne, Melbourne, Victoria, Australia
| | - Justin M Yeung
- Department of Colorectal Surgery, Western Health, Melbourne, Victoria, Australia
- Department of Surgery (Western Precinct), University of Melbourne, Melbourne, Victoria, Australia
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Sahebjada S, Chan E, Sutton G, Pang CPC, Kerdraon Y, Natarajan S, Meteoukki W, Ang A, Daniell M, Baird PN. Keratoconus International Consortium (KIC)- advancing keratoconus research. BMC Ophthalmol 2023; 23:337. [PMID: 37501133 PMCID: PMC10375634 DOI: 10.1186/s12886-023-03087-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 07/16/2023] [Indexed: 07/29/2023] Open
Abstract
CLINICAL RELEVANCE The Keratoconus International Consortium (KIC) will allow better understanding of keratoconus. BACKGROUND Keratoconus is a disorder characterised by corneal elevation and thinning, leading to reduced vision. The current gaps in understanding of this disease will be discussed and the need for a multi-pronged and multi-centre engagement to enhance our understanding of keratoconus will be highlighted. DESIGN KIC has been established to address the gaps in our understanding of keratoconus with the aim of collecting baseline as well as longitudinal data on several fields. PARTICIPANTS Keratoconus and control (no corneal condition) subjects from different sites globally will be recruited in the study. METHODS KIC collects data using an online, secure database, which enables standardised data collection at member sites. Data fields collected include medical history, clinical features, quality of life and economic burden questionnaires and possible genetic sample collection from patients of different ethnicities across different geographical locations. RESULTS There are currently 40 Australian and international clinics or hospital departments who have joined the KIC. Baseline data has so far been collected on 1130 keratoconus patients and indicates a median age of 29.70 years with 61% being male. A total of 15.3% report a positive family history of keratoconus and 57.7% self-report a history of frequent eye rubbing. CONCLUSION The strength of this consortium is its international, collaborative design and use of a common data collection tool. Inclusion and analyses of cross-sectional and longitudinal data will help answer many questions that remain in keratoconus, including factors affecting progression and treatment outcomes.
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Affiliation(s)
- Srujana Sahebjada
- Centre for Eye Research Australia, Level 7, 32 Gisborne St, East Melbourne, Victoria, 3002, Australia.
- Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, Australia.
| | - Elsie Chan
- Centre for Eye Research Australia, Level 7, 32 Gisborne St, East Melbourne, Victoria, 3002, Australia
- Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, Australia
- Royal Victorian Eye and Ear Hospital, Melbourne, Australia
| | - Gerard Sutton
- Sydney Medical School, The University of Sydney, Sydney, Australia
- NSW Tissue Banks, Sydney, Australia
| | | | - Yves Kerdraon
- Sydney Medical School, The University of Sydney, Sydney, Australia
- Envision Eye Centre, Sydney, Australia
| | | | - Wafaa Meteoukki
- Molecular and Cellular Genetics Laboratory, Oran University of Science and Technology - Mohamed Boudiaf (USTOMB), Oran, Algeria
| | | | - Mark Daniell
- Centre for Eye Research Australia, Level 7, 32 Gisborne St, East Melbourne, Victoria, 3002, Australia
- Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, Australia
- Royal Victorian Eye and Ear Hospital, Melbourne, Australia
| | - Paul N Baird
- Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, Australia
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Arayne AA, Gartrell R, Qiao J, Baird PN, Yeung JMC. Comparison of CT derived body composition at the thoracic T4 and T12 with lumbar L3 vertebral levels and their utility in patients with rectal cancer. BMC Cancer 2023; 23:56. [PMID: 36647027 PMCID: PMC9843961 DOI: 10.1186/s12885-023-10522-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 01/09/2023] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Computed tomography (CT) derived body composition measurements of sarcopenia are an emerging form of prognostication in many disease processes. Although the L3 vertebral level is commonly used to measure skeletal muscle mass, other studies have suggested the utilisation of other segments. This study was performed to assess the variation and reproducibility of skeletal muscle mass at vertebral levels T4, T12 and L3 in pre-operative rectal cancer patients. If thoracic measurements were equivalent to those at L3, it will allow for body composition comparisons in a larger range of cancers where lumbar CT images are not routinely measured. RESEARCH METHODS Patients with stage I - III rectal cancer, undergoing curative resection from 2010 - 2014, were assessed. CT based quantification of skeletal muscle was used to determine skeletal muscle cross sectional area (CSA) and skeletal muscle index (SMI). Systematic differences between the measurements at L3 with T4 and T12 vertebral levels were evaluated by percentile rank differences to assess distribution of differences and ordinary least product regression (OLP) to detect and distinguish fixed and proportional bias. RESULTS Eighty eligible adult patients were included. Distribution of differences between T12 SMI and L3 SMI were more marked than differences between T4 SMI and L3 SMI. There was no fix or proportional bias with T4 SMI, but proportional bias was detected with T12 SMI measurements. T4 CSA duplicate measurements had higher test-retest reliability: coefficient of repeatability was 34.10 cm2 for T4 CSA vs 76.00 cm2 for T12 CSA. Annotation time (minutes) with L3 as reference, the median difference was 0.85 for T4 measurements and -0.03 for T12 measurements. Thirty-seven patients (46%) had evidence of sarcopenia at the L3 vertebral level, with males exhibiting higher rates of sarcopenia. However, there was no association between sarcopenia and post-operative complications, recurrence or hospital LOS (length of stay) in patients undergoing curative resection. CONCLUSIONS Quantifying skeletal muscle mass at the T4 vertebral level is comparable to measures achieved at L3 in patients with rectal cancer, notwithstanding annotation time for T4 measurements are longer.
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Affiliation(s)
- Aisha A Arayne
- grid.417072.70000 0004 0645 2884Department of Surgery, Western Health, Footscray, VIC Australia
| | - Richard Gartrell
- grid.417072.70000 0004 0645 2884Department of Surgery, Western Health, Footscray, VIC Australia ,grid.1008.90000 0001 2179 088XDepartment of Surgery, Western Precinct, University of Melbourne, VIC, Australia ,grid.417072.70000 0004 0645 2884Department of Colorectal Surgery, Western Health, Footscray, VIC Australia
| | - Jing Qiao
- grid.417072.70000 0004 0645 2884Department of Surgery, Western Health, Footscray, VIC Australia
| | - Paul N Baird
- grid.1008.90000 0001 2179 088XDepartment of Surgery, Western Precinct, University of Melbourne, VIC, Australia ,grid.1008.90000 0001 2179 088XDepartment of Surgery, Ophthalmology, University of Melbourne, Victoria, Australia
| | - Justin MC Yeung
- grid.1008.90000 0001 2179 088XDepartment of Surgery, Western Precinct, University of Melbourne, VIC, Australia ,grid.417072.70000 0004 0645 2884Department of Colorectal Surgery, Western Health, Footscray, VIC Australia ,grid.417072.70000 0004 0645 2884Western Chronic Disease Alliance, Western Health, Sunshine, VIC Australia ,grid.1008.90000 0001 2179 088XDepartment of Surgery, Melbourne Medical School – Western Health, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Level 3, WCHRE Building, Sunshine Hospital, 176 Furlong Road, St Albans, VIC 3021 Australia
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11
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Moshegov S, Seth I, Wawryk O, Sandhu SS, Lanteri M, Baird PN, Sahebjada S. Vision-Related Quality of Life and Ocular Parameters in End-Stage Renal Disease Patients Undergoing Hemodialysis. J Curr Ophthalmol 2023; 35:66-72. [PMID: 37680282 PMCID: PMC10481989 DOI: 10.4103/joco.joco_56_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Revised: 12/01/2022] [Accepted: 12/02/2022] [Indexed: 09/09/2023] Open
Abstract
Purpose To evaluate the vision-related quality of life (VRQoL) of patients receiving hemodialysis through the assessment of the impact of vision impairment (IVI) questionnaire and ocular parameters, including best-corrected visual acuity (BCVA), intraocular pressure (IOP), and refraction as calculated by spherical equivalent (SE) of each eye. Methods Fifty-one patients with end-stage renal disease undergoing hemodialysis at a single center were recruited, and a total of 77 eyes were evaluated. BCVA, IOP, and SE were evaluated before and after hemodialysis (within 30 min). Results Of the 51 patients recruited, 13 (25%) were female, 37 (73%) were male, and one (2%) chose not to specify gender. The mean age was 61.85 ± 32 years. The mobility IVI score was correlated significantly with the presence of hypertension (P = 0.01), eye drop usage (P = 0.04), and gender (P = 0.04). Emotional IVI scores were correlated significantly with diabetes (P = 0.03) and hypertension (P < 0.01). IOP significantly correlated with the IVI overall score (P = 0.02), including the reading IVI subscale and the emotional IVI subscale. Several factors were associated with posthemodialysis ocular parameters, including predialysis ocular parameters, age, and hypertension (P < 0.05 for all). Conclusions IOP significantly correlated with VRQoL in hemodialysis patients. Demographic variables such as diabetes status, hypertension, eye drop usage, and gender also significantly correlated with subsections of the IVI questionnaire. This study investigated the relationship between ocular parameters and VRQoL in hemodialysis patients, and future longitudinal research is needed to further elucidate the mechanisms.
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Affiliation(s)
- Sophia Moshegov
- Centre for Eye Research Australia, Melbourne, Australia
- Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, Australia
| | - Ishith Seth
- Centre for Eye Research Australia, Melbourne, Australia
- Department of Surgery, Bendigo Health, Bendigo, Victoria, Australia
| | - Olivia Wawryk
- Department of General Practice, The University of Melbourne, Melbourne, Australia
| | - Sukhpal Singh Sandhu
- Centre for Eye Research Australia, Melbourne, Australia
- Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, Australia
- Royal Victorian Eye and Ear Hospital, Melbourne, Australia
| | | | - Paul N. Baird
- Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, Australia
| | - Srujana Sahebjada
- Centre for Eye Research Australia, Melbourne, Australia
- Royal Victorian Eye and Ear Hospital, Melbourne, Australia
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12
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Biasella F, Plössl K, Baird PN, Weber BHF. The extracellular microenvironment in immune dysregulation and inflammation in retinal disorders. Front Immunol 2023; 14:1147037. [PMID: 36936905 PMCID: PMC10014728 DOI: 10.3389/fimmu.2023.1147037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 02/15/2023] [Indexed: 03/05/2023] Open
Abstract
Inherited retinal dystrophies (IRDs) as well as genetically complex retinal phenotypes represent a heterogenous group of ocular diseases, both on account of their phenotypic and genotypic characteristics. Therefore, overlaps in clinical features often complicate or even impede their correct clinical diagnosis. Deciphering the molecular basis of retinal diseases has not only aided in their disease classification but also helped in our understanding of how different molecular pathologies may share common pathomechanisms. In particular, these relate to dysregulation of two key processes that contribute to cellular integrity, namely extracellular matrix (ECM) homeostasis and inflammation. Pathological changes in the ECM of Bruch's membrane have been described in both monogenic IRDs, such as Sorsby fundus dystrophy (SFD) and Doyne honeycomb retinal dystrophy (DHRD), as well as in the genetically complex age-related macular degeneration (AMD) or diabetic retinopathy (DR). Additionally, complement system dysfunction and distorted immune regulation may also represent a common connection between some IRDs and complex retinal degenerations. Through highlighting such overlaps in molecular pathology, this review aims to illuminate how inflammatory processes and ECM homeostasis are linked in the healthy retina and how their interplay may be disturbed in aging as well as in disease.
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Affiliation(s)
- Fabiola Biasella
- Institute of Human Genetics, University of Regensburg, Regensburg, Germany
| | - Karolina Plössl
- Institute of Human Genetics, University of Regensburg, Regensburg, Germany
| | - Paul N. Baird
- Institute of Human Genetics, University of Regensburg, Regensburg, Germany
- Department of Surgery, Ophthalmology, University of Melbourne, Melbourne, VIC, Australia
- *Correspondence: Paul N. Baird, ; Bernhard H. F. Weber,
| | - Bernhard H. F. Weber
- Institute of Human Genetics, University of Regensburg, Regensburg, Germany
- Institute of Clinical Human Genetics, University Hospital Regensburg, Regensburg, Germany
- *Correspondence: Paul N. Baird, ; Bernhard H. F. Weber,
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13
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Song M, Fang QY, Seth I, Baird PN, Daniell MD, Sahebjada S. Non-genetic risk factors for keratoconus. Clin Exp Optom 2022; 106:362-372. [PMID: 35504720 DOI: 10.1080/08164622.2022.2062222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022] Open
Abstract
Keratoconus is a complex and multifactorial disease and its exact aetiology remains unknown. This current study examined the important environmental risk factors and their association with keratoconus. This study was registered in the PROSPERO International Prospective Register of systematic reviews under registration number CRD42021256792 in 2021. Scopus, Web of Science, PubMed, and Cochrane CENTRAL databases were searched for all relevant articles published from 1 January 1900 to 31 July 2021. National Institutes of Health Quality Assessment Tool was used to assess the methodological quality of the studies. The assessment for statistical heterogeneity was assessed using the Z-statistics on RevMan v5.4. P-value of <0.05 was considered as statistically significant and I2 < 25% as homogenous. Thirty studies were included in this meta-analysis. Pooled odds ratio was calculated with 95% CI. The pooled odds ratio (OR) of eye rubbing, atopy, asthma, and eczema was 3.64 (95% CI, 2.02, 6.57), 1.90 (95% CI, 1.22, 2.94), 1.36 (95% CI, 1.15, 1.61) and 1.90 (95% CI, 1.22, 2.94), respectively. The OR for diabetes was 0.86 (95% CI 0.73, 1.02), and use of sunglasses, contact lens, allergic conjunctivitis, side sleep position and prone sleep position was 0.40 (95% CI, 0.16, 0.99), 1.68 (0.70, 4.00), 2.24 (95% CI, 0.68, 7.36), 3.81 (95% CI, 0.31, 46.23), 12.76 (95% CI, 0.27, 598.58), respectively. Twenty studies were considered to be of high quality, nine to be moderate and one to be low. Environmental risk factors have been identified to play a role in the susceptibility of keratoconus. However, further large-scale longitudinal studies are needed to understand the mechanisms between environmental risk factors and keratoconus.
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Affiliation(s)
- Minji Song
- Centre for Eye Research Australia, Melbourne, Australia
| | - Qing Yi Fang
- Centre for Eye Research Australia, Melbourne, Australia
| | - Ishith Seth
- Centre for Eye Research Australia, Melbourne, Australia
| | - Paul N Baird
- Ophthalmology, Department of Surgery, The University of Melbourne, Melbourne, Australia
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Machin H, Sutton G, Baird PN. Examining Corneal Tissue Exportation Fee and Its Impact on Equitable Allocation. Cornea 2022; 41:390-395. [PMID: 34483277 DOI: 10.1097/ico.0000000000002856] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 07/07/2021] [Indexed: 11/26/2022]
Abstract
METHODS We conducted grounded theory semistructured interviews, purposively inviting participants until themed saturation was met. Sentiment analysis was used to determine opinion. RESULTS We interviewed n = 92 global eye tissue and eye bank professionals. We determined that corneal tissue, which is exported, costs between US $100 and US $6000 or is provided as gratis. Collectively, interviewees indicated that, globally, there were no fixed fee structures in place, and the fee was influenced by multiple factors on both export and import sides. They indicated that ultimately corneas were allocated based on the importers' ability to pay the price determined by the exporting eye bank. DISCUSSION Allocation of corneal tissue, which is exported, is influenced by the fees charged by the exporters to meet their bottom line and the funds available to importers. Therefore, export allocation is not equitable, with those who can pay a higher fee, prioritized. Steps to guide and support exporters with the development of fee structures that promote equitable allocation are essential. This will assist both export and import eye bank development, corneal tissue access development, and those awaiting a corneal transplant.
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Affiliation(s)
- Heather Machin
- Lions Eye Donation Service, Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
- Department of Surgery, Ophthalmology, University of Melbourne, Victoria, Australia
| | - Gerard Sutton
- The University of Sydney, Save Sight Institute, Discipline of Ophthalmology, Sydney Medical School, Sydney, New South Wales, Australia; and
- The University of Technology Sydney, Graduate School of Health, New South Wales, Australia
| | - Paul N Baird
- Department of Surgery, Ophthalmology, University of Melbourne, Victoria, Australia
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Cao K, Verspoor K, Sahebjada S, Baird PN. Accuracy of Machine Learning Assisted Detection of Keratoconus: A Systematic Review and Meta-Analysis. J Clin Med 2022; 11:jcm11030478. [PMID: 35159930 PMCID: PMC8836961 DOI: 10.3390/jcm11030478] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 01/10/2022] [Accepted: 01/13/2022] [Indexed: 12/26/2022] Open
Abstract
(1) Background: The objective of this review was to synthesize available data on the use of machine learning to evaluate its accuracy (as determined by pooled sensitivity and specificity) in detecting keratoconus (KC), and measure reporting completeness of machine learning models in KC based on TRIPOD (the transparent reporting of multivariable prediction models for individual prognosis or diagnosis) statement. (2) Methods: Two independent reviewers searched the electronic databases for all potential articles on machine learning and KC published prior to 2021. The TRIPOD 29-item checklist was used to evaluate the adherence to reporting guidelines of the studies, and the adherence rate to each item was computed. We conducted a meta-analysis to determine the pooled sensitivity and specificity of machine learning models for detecting KC. (3) Results: Thirty-five studies were included in this review. Thirty studies evaluated machine learning models for detecting KC eyes from controls and 14 studies evaluated machine learning models for detecting early KC eyes from controls. The pooled sensitivity for detecting KC was 0.970 (95% CI 0.949–0.982), with a pooled specificity of 0.985 (95% CI 0.971–0.993), whereas the pooled sensitivity of detecting early KC was 0.882 (95% CI 0.822–0.923), with a pooled specificity of 0.947 (95% CI 0.914–0.967). Between 3% and 48% of TRIPOD items were adhered to in studies, and the average (median) adherence rate for a single TRIPOD item was 23% across all studies. (4) Conclusions: Application of machine learning model has the potential to make the diagnosis and monitoring of KC more efficient, resulting in reduced vision loss to the patients. This review provides current information on the machine learning models that have been developed for detecting KC and early KC. Presently, the machine learning models performed poorly in identifying early KC from control eyes and many of these research studies did not follow established reporting standards, thus resulting in the failure of these clinical translation of these machine learning models. We present possible approaches for future studies for improvement in studies related to both KC and early KC models to more efficiently and widely utilize machine learning models for diagnostic process.
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Affiliation(s)
- Ke Cao
- Centre for Eye Research Australia, Melbourne, VIC 3002, Australia; (K.C.); (S.S.)
- Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, VIC 3002, Australia
| | - Karin Verspoor
- School of Computing Technologies, RMIT University, Melbourne, VIC 3000, Australia;
- School of Computing and Information Systems, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - Srujana Sahebjada
- Centre for Eye Research Australia, Melbourne, VIC 3002, Australia; (K.C.); (S.S.)
- Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, VIC 3002, Australia
| | - Paul N. Baird
- Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, VIC 3002, Australia
- Correspondence: ; Tel.: +61-3-9929-8613
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16
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Cao K, Verspoor K, Chan E, Daniell M, Sahebjada S, Baird PN. Machine learning with a reduced dimensionality representation of comprehensive Pentacam tomography parameters to identify subclinical keratoconus. Comput Biol Med 2021; 138:104884. [PMID: 34607273 DOI: 10.1016/j.compbiomed.2021.104884] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 09/15/2021] [Accepted: 09/19/2021] [Indexed: 12/26/2022]
Abstract
PURPOSE To investigate the performance of a machine learning model based on a reduced dimensionality parameter space derived from complete Pentacam parameters to identify subclinical keratoconus (KC). METHODS All 1692 available parameters were obtained from the Pentacam imaging machine on 145 subclinical KC and 122 control eyes. We applied a principal component analysis (PCA) to the complete Pentacam dataset to reduce its parameter dimensionality. Subsequently, we investigated machine learning performance of the random forest algorithm with increasing numbers of components to identify their optimal number for detecting subclinical KC from control eyes. RESULTS The dimensionality of the complete set of 1692 Pentacam parameters was reduced to 267 principal components using PCA. Subsequent selection of 15 of these principal components explained over 85% of the variance of the original Pentacam-derived parameters and input to train a random forest machine learning model to achieve the best accuracy of 98% in detecting subclinical KC eyes. The model established also reached a high sensitivity of 97% in identification of subclinical KC and a specificity of 98% in recognizing control eyes. CONCLUSIONS A random forest-based model trained using a modest number of components derived from a reduced dimensionality representation of complete Pentacam system parameters allowed for high accuracy of subclinical KC identification.
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Affiliation(s)
- Ke Cao
- Centre for Eye Research Australia, Melbourne, Victoria, Australia; Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Karin Verspoor
- School of Computing Technologies, RMIT University, Melbourne, Australia; School of Computing and Information Systems, The University of Melbourne, Melbourne, Australia
| | - Elsie Chan
- Centre for Eye Research Australia, Melbourne, Victoria, Australia; Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, Victoria, Australia; Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia
| | - Mark Daniell
- Centre for Eye Research Australia, Melbourne, Victoria, Australia; Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, Victoria, Australia; Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia
| | - Srujana Sahebjada
- Centre for Eye Research Australia, Melbourne, Victoria, Australia; Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Paul N Baird
- Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, Victoria, Australia.
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Machin H, Buckland L, Georges P, Ghabcha M, Golding-Holbrook T, Leighton C, Mackey A, Weinel L, Whiting V, Sutton G, Baird PN. Supply and Demand of Domestic Corneal Tissue and Its Implications on Export Potential-Using Australia as an Example. Cornea 2021; 40:1229-1235. [PMID: 33290321 DOI: 10.1097/ico.0000000000002599] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 09/22/2020] [Indexed: 11/26/2022]
Abstract
PURPOSE Corneal tissue importation is only possible if another country is able to export corneas without impacting its own domestic demand. Currently, there is little evidence to indicate whether export nations have such surplus capacity and in a position to export. To explore this concept, we examined our nation, Australia, which is reported to routinely decline donations because of its ability to meet domestic corneal transplant demand. Our research offers insights and opportunities for Australia and other nations to evaluate their domestic and international supply and allocation of corneal tissue in this space. METHOD We collated 12 months of data on collected and noncollected donations, through participating Australian Eye Banks. The explanation of why some known donors were declined or not pursued indicated if demand was met and potential surplus-for-export levels. RESULTS There were 7.5% (n = 11,889) of deaths in Australia that were notified to Australian Eye Banks during our reporting period. Of those, 9.3% (n = 1106/11,889) were recovered and allocated, 15.7% (n = 1863/11,889) were known but declined, and 75% (n = 8920/11,889) were not pursued. Of those that were declined, 64.3% (n = 1197/1863) were declined because of limitations with service/manpower at the eye bank, whereas 35.7% (n = 666/1863) were declined because demand was met. CONCLUSIONS Australia did not meet demand all the time, during our data period. There were adequate quantities of potential donors to support increasing recovery for domestic allocation and provide for exportation without hindrance to Australian demand. Further examination of domestic supply and demand cycles and the export process is required before routine exportation.
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Affiliation(s)
- Heather Machin
- Lions Eye Donation Service, Center for Eye Research Australia, University of Melbourne, East Melbourne, Australia
| | - Lisa Buckland
- Lions Eye Bank of Western Australia, Lions Eye Institute, Perth, Australia
| | - Pierre Georges
- New South Wales Tissue Banks, New South Wales Organ and Tissue Donation Service, Sydney, Australia
| | - Mona Ghabcha
- New South Wales Tissue Banks, New South Wales Organ and Tissue Donation Service, Sydney, Australia
| | - Tamme Golding-Holbrook
- Eye Bank of South Australia, Department of Ophthalmology, Surgical and Perioperative Medicine, Flinders Medical Centre, Southern Adelaide Local Health Network, Adelaide, Australia
| | - Candice Leighton
- Queensland Eye Bank, Queensland Tissue Bank, Organ and Tissue Donation Service, Metro South Health, Brisbane, Australia
| | - Adrienne Mackey
- Lions Eye Donation Service, Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
- Department of Surgery|Ophthalmology, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Australia
| | - Luke Weinel
- Eye Bank of South Australia, Department of Ophthalmology, Surgical and Perioperative Medicine, Flinders Medical Centre, Southern Adelaide Local Health Network, Adelaide, Australia
| | - Victoria Whiting
- Queensland Eye Bank, Queensland Tissue Bank, Organ and Tissue Donation Service, Metro South Health, Brisbane, Australia
| | - Gerard Sutton
- New South Wales Tissue Banks, New South Wales Organ and Tissue Donation Service, Sydney, Australia
- Discipline of Ophthalmology, Sydney Medical School, Save Sight Institute, The University of Sydney, Sydney, Australia; and
- Graduate School of Health, The University of Technology Sydney, Sydney, Australia
| | - Paul N Baird
- Department of Surgery|Ophthalmology, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Australia
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Han X, Liu T, Ding X, Liu J, Lin X, Wang D, Riaz M, Baird PN, Xie Z, Cheng Y, Li Y, Mori Y, Miyake M, Li H, Cheng CY, Zeng C, Ohno-Matsui K, Zhou X, Liu F, He M. Identification of novel loci influencing refractive error in East Asian populations using an extreme phenotype design. J Genet Genomics 2021; 49:54-62. [PMID: 34520856 DOI: 10.1016/j.jgg.2021.08.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 08/09/2021] [Accepted: 08/12/2021] [Indexed: 11/27/2022]
Abstract
The global "myopia boom" has raised significant international concerns. Despite a higher myopia prevalence in Asia, previous large-scale genome-wide association studies (GWASs) were mostly based on European descendants. Here, we report a GWAS of spherical equivalent (SE) in 1852 Chinese Han individuals with extreme SE from Guangzhou (631 < -6D and 574 > 0D) and Wenzhou (593 < -6D and 54 > -1.75 D), followed by a replication study in two independent cohorts with totaling 3538 East Asian individuals. The discovery GWAS and meta-analysis identify three novel loci which show genome-wide significant associations with SE, including 1q25.2 FAM163A, 10p11.22 NRP1/PRAD3, and 10p11.21 ANKRD30A/MTRNR2L7, together explaining 3.34% of SE variance. 10p11.21 was successfully replicated. The allele frequencies of all three loci show significant differences between major continental groups (P < 0.001). The SE reducing (more myopic) allele of rs10913877 (1q25.2 FAM163A) demonstrates the highest frequency in East Asians and much lower frequencies in Europeans and Africans (EAS = 0.60, EUR = 0.20, AFR = 0.18). The gene-based analysis additionally identifies three novel genes associated with SE, including EI24, LHX5 and ARPP19. These results provide new insights into myopia pathogenesis, and indicate the role of genetic heterogeneity in myopia epidemiology among different ethnicities.
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Affiliation(s)
- Xiaotong Han
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510000, China
| | - Tianzi Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; China National Center for Bioinformation, Beijing 100101, China
| | - Xiaohu Ding
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510000, China
| | - Jialin Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; China National Center for Bioinformation, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100101, China
| | - Xingyan Lin
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510000, China
| | - Decai Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510000, China
| | - Moeen Riaz
- School of Public Health and Preventive Medicine, Monash University 3800, Australia
| | - Paul N Baird
- Department of Surgery, Ophthalmology, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Zhi Xie
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510000, China
| | - Yuan Cheng
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; China National Center for Bioinformation, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100101, China
| | - Yi Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; China National Center for Bioinformation, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100101, China
| | - Yuki Mori
- Department of Ophthalmology and Visual Science, Tokyo Medical and Dental University, Tokyo 113-8510, Japan
| | - Masahiro Miyake
- Department of Ophthalmology and Visual Science, Tokyo Medical and Dental University, Tokyo 113-8510, Japan
| | - Hengtong Li
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 168751, Singapore; Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore 119077, Singapore; Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Changqing Zeng
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; China National Center for Bioinformation, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100101, China
| | - Kyoko Ohno-Matsui
- Department of Ophthalmology and Visual Science, Tokyo Medical and Dental University, Tokyo 113-8510, Japan
| | - Xiangtian Zhou
- School of Optometry and Ophthalmology and Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang 325035, China; State Key Laboratory of Optometry, Ophthalmology and Vision Science, Wenzhou, Zhejiang 325035, China
| | - Fan Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; China National Center for Bioinformation, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100101, China
| | - Mingguang He
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510000, China.
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Baird PN, Machin H, Brown KD. Corneal supply and the use of technology to reduce its demand: A review. Clin Exp Ophthalmol 2021; 49:1078-1090. [PMID: 34310836 DOI: 10.1111/ceo.13978] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 07/13/2021] [Accepted: 07/14/2021] [Indexed: 11/26/2022]
Abstract
Recovery and access to end-of-life corneal tissue for corneal transplantation, training and research is globally maldistributed. The reasons for the maldistribution are complex and multifaceted, and not well defined or understood. Currently there are few solutions available to effectively address these issues. This review provides an overview of the system, key issues impacting recovery and allocation and emphasises how end-user ophthalmologists and researchers, with support from administrators and the wider sector, can assist in increasing access long-term through sustaining eye banks nationally and globally. We posit that prevention measures and improved surgical techniques, together with the development of novel therapies will play a significant role in reducing demand and enhance the equitable allocation of corneas.
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Affiliation(s)
- Paul N Baird
- Department of Surgery, Ophthalmology, University of Melbourne, Melbourne, Victoria, Australia
| | - Heather Machin
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
- Lions Eye Donation Service, Melbourne, Australia
| | - Karl D Brown
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
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20
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Machin H, Sutton G, Baird PN. Do Eye Bank Models and Competitive Practice Affect International Cornea Allocation? Cornea 2021; 40:936-941. [PMID: 33605630 DOI: 10.1097/ico.0000000000002693] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 01/12/2021] [Indexed: 11/26/2022]
Abstract
PURPOSE International export and import of corneas is dependent on the stakeholders involved in the process and how those organizations engage to move corneas from one point to another. Our article presents the pathway of corneal donation from the export nation until its use in the import nation. It presents opinion on how aspects, such as competition and promotional behaviors, the use of online systems, and third-party engagement may influence allocation. METHODS We interviewed n = 92 international eye tissue and eye bank (EB) professionals to garner their opinion. We used saturation and sentiment methods to extract and consolidate group opinion. RESULTS Interviewees indicated that competition and promotional behaviors existed in some EB nations-although it was not universal. They indicated that the behavioral approach used by the individual EB, rather than the act of information sharing, influenced allocation. They also indicated that organizational models and allocation systems (eg, online ordering) and engagement with nonstate actors were important in allocation practice and decision making. CONCLUSION We mapped the pathways for corneas involved in export and import from the point of recovery to their point of transplantation. Although generalist in nature and limited by the paucity of the existing literature, our article outlines that different business models, partnerships, and applied methods influence corneal export and import.
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Affiliation(s)
- Heather Machin
- Lions Eye Donation Service, Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital
- Department of Surgery, Ophthalmology, University of Melbourne, Victoria, Australia
| | - Gerard Sutton
- The University of Sydney, Save Sight Institute, Discipline of Ophthalmology, Sydney Medical School, Sydney, New South Wales, Australia; and
- The University of Technology Sydney, Graduate School of Health, New South Wales, Australia
| | - Paul N Baird
- Department of Surgery, Ophthalmology, University of Melbourne, Victoria, Australia
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21
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Arslan J, Samarasinghe G, Sowmya A, Benke KK, Hodgson LAB, Guymer RH, Baird PN. Deep Learning Applied to Automated Segmentation of Geographic Atrophy in Fundus Autofluorescence Images. Transl Vis Sci Technol 2021; 10:2. [PMID: 34228106 PMCID: PMC8267211 DOI: 10.1167/tvst.10.8.2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 05/23/2021] [Indexed: 11/02/2022] Open
Abstract
Purpose This study describes the development of a deep learning algorithm based on the U-Net architecture for automated segmentation of geographic atrophy (GA) lesions in fundus autofluorescence (FAF) images. Methods Image preprocessing and normalization by modified adaptive histogram equalization were used for image standardization to improve effectiveness of deep learning. A U-Net-based deep learning algorithm was developed and trained and tested by fivefold cross-validation using FAF images from clinical datasets. The following metrics were used for evaluating the performance for lesion segmentation in GA: dice similarity coefficient (DSC), DSC loss, sensitivity, specificity, mean absolute error (MAE), accuracy, recall, and precision. Results In total, 702 FAF images from 51 patients were analyzed. After fivefold cross-validation for lesion segmentation, the average training and validation scores were found for the most important metric, DSC (0.9874 and 0.9779), for accuracy (0.9912 and 0.9815), for sensitivity (0.9955 and 0.9928), and for specificity (0.8686 and 0.7261). Scores for testing were all similar to the validation scores. The algorithm segmented GA lesions six times more quickly than human performance. Conclusions The deep learning algorithm can be implemented using clinical data with a very high level of performance for lesion segmentation. Automation of diagnostics for GA assessment has the potential to provide savings with respect to patient visit duration, operational cost and measurement reliability in routine GA assessments. Translational Relevance A deep learning algorithm based on the U-Net architecture and image preprocessing appears to be suitable for automated segmentation of GA lesions on clinical data, producing fast and accurate results.
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Affiliation(s)
- Janan Arslan
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye & Ear Hospital, East Melbourne, Victoria, Australia
- Department of Surgery, Ophthalmology, University of Melbourne, Parkville, Victoria, Australia
| | - Gihan Samarasinghe
- School of Computer Science and Engineering, University of New South Wales, Kensington, New South Wales, Australia
| | - Arcot Sowmya
- School of Computer Science and Engineering, University of New South Wales, Kensington, New South Wales, Australia
| | - Kurt K. Benke
- School of Engineering, University of Melbourne, Parkville, Victoria, Australia
- Centre for AgriBioscience, AgriBio, Bundoora, Victoria, Australia
| | - Lauren A. B. Hodgson
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye & Ear Hospital, East Melbourne, Victoria, Australia
| | - Robyn H. Guymer
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye & Ear Hospital, East Melbourne, Victoria, Australia
- Department of Surgery, Ophthalmology, University of Melbourne, Parkville, Victoria, Australia
| | - Paul N. Baird
- Department of Surgery, Ophthalmology, University of Melbourne, Parkville, Victoria, Australia
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22
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Arslan J, Benke KK, Samarasinghe G, Sowmya A, Guymer RH, Baird PN. Model Structure Uncertainty in the Characterization and Growth of Geographic Atrophy. Transl Vis Sci Technol 2021; 10:2. [PMID: 34111247 PMCID: PMC8107635 DOI: 10.1167/tvst.10.6.2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Purpose To identify the most suitable model for assessing the rate of growth of total geographic atrophy (GA) by analysis of model structure uncertainty. Methods Model structure uncertainty refers to unexplained variability arising from the choice of mathematical model and represents an example of epistemic uncertainty. In this study, we quantified this uncertainty to help identify a model most representative of GA progression. Fundus autofluorescence (FAF) images and GA progression data (i.e., total GA area estimation at each presentation) were acquired using Spectralis HRA+OCT instrumentation and RegionFinder software. Six regression models were evaluated. Models were compared using various statistical tests, [i.e., coefficient of determination (r2), uncertainty metric (U), and test of significance for the correlation coefficient, r], as well as adherence to expected physical and clinical assumptions of GA growth. Results Analysis was carried out for 81 GA-affected eyes, 531 FAF images (range: 3–17 images per eye), over median of 57 months (IQR: 42, 74), with a mean baseline lesion size of 2.62 ± 4.49 mm2 (range: 0.11–20.69 mm2). The linear model proved to be the most representative of total GA growth, with lowest average uncertainty (original scale: U = 0.025, square root scale: U = 0.014), high average r2 (original scale: 0.92, square root scale: 0.93), and applicability of the model was supported by a high correlation coefficient, r, with statistical significance (P = 0.01). Conclusions Statistical analysis of uncertainty suggests that the linear model provides an effective and practical representation of the rate and progression of total GA growth based on data from patient presentations in clinical settings. Translational Relevance Identification of correct model structure to characterize rate of growth of total GA in the retina using FAF images provides an objective metric for comparing interventions and charting GA progression in clinical presentations.
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Affiliation(s)
- Janan Arslan
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye & Ear Hospital, East Melbourne, Victoria, Australia.,Department of Surgery, Ophthalmology, University of Melbourne, Parkville, Victoria, Australia
| | - Kurt K Benke
- School of Engineering, University of Melbourne, Parkville, Victoria, Australia.,Centre for AgriBioscience, AgriBio, Bundoora, Victoria, Australia
| | - Gihan Samarasinghe
- School of Computer Science and Engineering, University of New South Wales, Kensington, NSW, Australia
| | - Arcot Sowmya
- School of Computer Science and Engineering, University of New South Wales, Kensington, NSW, Australia
| | - Robyn H Guymer
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye & Ear Hospital, East Melbourne, Victoria, Australia.,Department of Surgery, Ophthalmology, University of Melbourne, Parkville, Victoria, Australia
| | - Paul N Baird
- Department of Surgery, Ophthalmology, University of Melbourne, Parkville, Victoria, Australia
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23
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Machin H, Sutton G, Baird PN. Should Donors Consent to Export Their Corneas? Examination of Eye Tissue and Eye Care Sector Opinion. Cornea 2021; 40:398-403. [PMID: 33252381 DOI: 10.1097/ico.0000000000002559] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 08/23/2020] [Indexed: 11/26/2022]
Abstract
PURPOSE Corneal tissue international activity is only possible because of the willingness of export populations to donate their corneas on their death. Current predonation public education campaigns and at-the-point-of-donation consent practice generally includes consent for transplantation, research, and/or training. It is unclear whether a consent-for-export step is universally included in the consent process or, indeed, whether it should. We interviewed eye tissue and eye care professionals from around the world, who exported, imported, or did neither to understand current consent-for-export awareness and determine opinion on future practice. METHOD During wider qualitative grounded-theory semistructured interviews with sector experts, to determine whether Australia should export, we captured sector opinion on consent-for-export. We used saturation and sentiment methods to determine opinion and χ2 correlation coefficients to examine association, using an α of P = 0.05. RESULTS We interviewed 92 individuals, 83 of whom discussed consent-for-export. Of those, 51% (42/83) demonstrated some awareness of the practice; however, there were contradictions between interviewees from the same location. Regardless of current awareness, 57% (41/72) believed donors should be informed or consented for export. Their approval did not extend to donor-directed decisions, which would allow donors to decide which nation their donation should be sent, with 62.5% (45/72) opposing that notion. CONCLUSIONS Our research indicates that the consent-for-export practice is not universally applied by exporting nations and that eye tissue and eye care professionals have limited awareness of the practice. Universally implementing a consent-for-export step within general consent practice would improve awareness, reduce confusion, and support donor wishes.
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Affiliation(s)
- Heather Machin
- Lions Eye Donation Service, Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
- Department of Surgery, Ophthalmology, University of Melbourne, Melbourne, Victoria, Australia
| | - Gerard Sutton
- The University of Sydney, Save Sight Institute, Discipline of Ophthalmology, Sydney Medical School, Sydney, New South Wales, Australia; and
- The University of Technology Sydney, Graduate School of Health, Sydney, New South Wales, Australia
| | - Paul N Baird
- Department of Surgery, Ophthalmology, University of Melbourne, Melbourne, Victoria, Australia
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24
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Hardcastle AJ, Liskova P, Bykhovskaya Y, McComish BJ, Davidson AE, Inglehearn CF, Li X, Choquet H, Habeeb M, Lucas SEM, Sahebjada S, Pontikos N, Lopez KER, Khawaja AP, Ali M, Dudakova L, Skalicka P, Van Dooren BTH, Geerards AJM, Haudum CW, Faro VL, Tenen A, Simcoe MJ, Patasova K, Yarrand D, Yin J, Siddiqui S, Rice A, Farraj LA, Chen YDI, Rahi JS, Krauss RM, Theusch E, Charlesworth JC, Szczotka-Flynn L, Toomes C, Meester-Smoor MA, Richardson AJ, Mitchell PA, Taylor KD, Melles RB, Aldave AJ, Mills RA, Cao K, Chan E, Daniell MD, Wang JJ, Rotter JI, Hewitt AW, MacGregor S, Klaver CCW, Ramdas WD, Craig JE, Iyengar SK, O'Brart D, Jorgenson E, Baird PN, Rabinowitz YS, Burdon KP, Hammond CJ, Tuft SJ, Hysi PG. A multi-ethnic genome-wide association study implicates collagen matrix integrity and cell differentiation pathways in keratoconus. Commun Biol 2021; 4:266. [PMID: 33649486 PMCID: PMC7921564 DOI: 10.1038/s42003-021-01784-0] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 02/02/2021] [Indexed: 12/14/2022] Open
Abstract
Keratoconus is characterised by reduced rigidity of the cornea with distortion and focal thinning that causes blurred vision, however, the pathogenetic mechanisms are unknown. It can lead to severe visual morbidity in children and young adults and is a common indication for corneal transplantation worldwide. Here we report the first large scale genome-wide association study of keratoconus including 4,669 cases and 116,547 controls. We have identified significant association with 36 genomic loci that, for the first time, implicate both dysregulation of corneal collagen matrix integrity and cell differentiation pathways as primary disease-causing mechanisms. The results also suggest pleiotropy, with some disease mechanisms shared with other corneal diseases, such as Fuchs endothelial corneal dystrophy. The common variants associated with keratoconus explain 12.5% of the genetic variance, which shows potential for the future development of a diagnostic test to detect susceptibility to disease.
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Affiliation(s)
- Alison J Hardcastle
- UCL Institute of Ophthalmology, London, UK.
- Moorfields Eye Hospital, NHS Foundation Trust, London, UK.
| | - Petra Liskova
- UCL Institute of Ophthalmology, London, UK
- Department of Paediatrics and Inherited Metabolic Disorders, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- Department of Ophthalmology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Yelena Bykhovskaya
- The Cornea Eye Institute, Beverly Hills, CA, USA
- Department of Surgery and Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Bennet J McComish
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | | | - Chris F Inglehearn
- Division of Molecular Medicine, Leeds Institute of Medical Research, University of Leeds, Leeds, UK
| | - Xiaohui Li
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center; Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Hélène Choquet
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Mahmoud Habeeb
- Department of Ophthalmology, Erasmus Medical Center GD, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center GD, Rotterdam, The Netherlands
| | - Sionne E M Lucas
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | - Srujana Sahebjada
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia
- Department of Surgery, Ophthalmology, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia
| | | | | | - Anthony P Khawaja
- UCL Institute of Ophthalmology, London, UK
- Moorfields Eye Hospital, NHS Foundation Trust, London, UK
- NIHR Biomedical Research Centre, Moorfields Eye Hospital, London, UK
| | - Manir Ali
- Division of Molecular Medicine, Leeds Institute of Medical Research, University of Leeds, Leeds, UK
| | - Lubica Dudakova
- Department of Paediatrics and Inherited Metabolic Disorders, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Pavlina Skalicka
- Department of Ophthalmology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Bart T H Van Dooren
- Department of Ophthalmology, Erasmus Medical Center GD, Rotterdam, The Netherlands
- Amphia Hospital, Breda, The Netherlands
| | | | - Christoph W Haudum
- Division of Endocrinology and Diabetology, Endocrinology Lab Platform, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Valeria Lo Faro
- Department of Ophthalmology, University Medical Center Groningen (UMCG), Groningen, the Netherlands
- Department of Ophthalmology, Academic Medical Center, Amsterdam, The Netherlands
| | - Abi Tenen
- Vision Eye Institute, Melbourne, VIC, Australia
- School of Primary and Allied Health Care, Monash University, Melbourne, VIC, Australia
- Melbourne Stem Cell Centre, Melbourne, VIC, 3800, Australia
| | - Mark J Simcoe
- Section of Ophthalmology, School of Life Course Sciences, King's College London, London, UK
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Karina Patasova
- Section of Ophthalmology, School of Life Course Sciences, King's College London, London, UK
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Darioush Yarrand
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Jie Yin
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Salina Siddiqui
- Division of Molecular Medicine, Leeds Institute of Medical Research, University of Leeds, Leeds, UK
- Department of Ophthalmology, St James's University Hospital, Leeds, UK
| | - Aine Rice
- Division of Molecular Medicine, Leeds Institute of Medical Research, University of Leeds, Leeds, UK
| | - Layal Abi Farraj
- Division of Molecular Medicine, Leeds Institute of Medical Research, University of Leeds, Leeds, UK
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center; Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jugnoo S Rahi
- UCL Great Ormond Street Hospital Institute of Child Health, London, UK
| | | | | | - Jac C Charlesworth
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | | | - Carmel Toomes
- Division of Molecular Medicine, Leeds Institute of Medical Research, University of Leeds, Leeds, UK
| | - Magda A Meester-Smoor
- Department of Ophthalmology, Erasmus Medical Center GD, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center GD, Rotterdam, The Netherlands
| | - Andrea J Richardson
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia
| | - Paul A Mitchell
- Centre for Vision Research, Department of Ophthalmology, Westmead Institute for Medical Research, University of Sydney, Westmead, NSW, Australia
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center; Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Ronald B Melles
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Anthony J Aldave
- The Jules Stein Institute, University of California Los Angeles, Los Angeles, CA, USA
| | - Richard A Mills
- Department of Ophthalmology, Flinders University, Adelaide, SA, Australia
| | - Ke Cao
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia
- Department of Surgery, Ophthalmology, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia
| | - Elsie Chan
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia
- Department of Surgery, Ophthalmology, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia
| | - Mark D Daniell
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia
- Department of Surgery, Ophthalmology, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia
| | - Jie Jin Wang
- Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation (formerly Los Angeles Biomedical Research Institute) at Harbor-UCLA Medical Center; Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Alex W Hewitt
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
- Vision Eye Institute, Melbourne, VIC, Australia
- School of Primary and Allied Health Care, Monash University, Melbourne, VIC, Australia
- Melbourne Stem Cell Centre, Melbourne, VIC, 3800, Australia
| | - Stuart MacGregor
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Caroline C W Klaver
- Department of Ophthalmology, Erasmus Medical Center GD, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center GD, Rotterdam, The Netherlands
| | - Wishal D Ramdas
- Department of Ophthalmology, Erasmus Medical Center GD, Rotterdam, The Netherlands
| | - Jamie E Craig
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
- Department of Ophthalmology, Flinders University, Adelaide, SA, Australia
| | - Sudha K Iyengar
- Department of Ophthalmology, Case Western Reserve University, Cleveland, OH, USA
| | - David O'Brart
- Section of Ophthalmology, School of Life Course Sciences, King's College London, London, UK
- St Thomas Hospital, Guy's and St. Thomas NHS Trust, London, London, UK
| | - Eric Jorgenson
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Paul N Baird
- Department of Surgery, Ophthalmology, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, VIC, Australia
| | - Yaron S Rabinowitz
- The Cornea Eye Institute, Beverly Hills, CA, USA
- Department of Surgery and Board of Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Kathryn P Burdon
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
- Department of Ophthalmology, Flinders University, Adelaide, SA, Australia
| | - Chris J Hammond
- Section of Ophthalmology, School of Life Course Sciences, King's College London, London, UK
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- St Thomas Hospital, Guy's and St. Thomas NHS Trust, London, London, UK
| | - Stephen J Tuft
- UCL Institute of Ophthalmology, London, UK.
- Moorfields Eye Hospital, NHS Foundation Trust, London, UK.
| | - Pirro G Hysi
- Section of Ophthalmology, School of Life Course Sciences, King's College London, London, UK.
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
- UCL Great Ormond Street Hospital Institute of Child Health, London, UK.
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25
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Machin HM, Buckland L, Critchley C, Wiffen S, Sutton G, Baird PN. Determining the willingness of Australians to export their corneas on death. PLoS One 2021; 16:e0246622. [PMID: 33606737 PMCID: PMC7894941 DOI: 10.1371/journal.pone.0246622] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 01/22/2021] [Indexed: 11/19/2022] Open
Abstract
Background 12.7 million people await a corneal transplant, but 53% are without access to corneal tissue. Sharing corneal tissue across nations can provide some access, however the willingness of export populations, like Australians, to export their donation on death, has never been evaluated. Our research samples the Australian population, determining their willingness to export. Materials and method We conducted e-surveys. N = 1044 Australians participated. The sample represented the Australian population, based on population demographics. Chi-Square and bivariate correlation coefficients examined associations between categorical variables, with a sample size of N = 1044, power of 0.80, and alpha of p = 0.05. Outcome measures were based on population sampling, by exploring willingness export, through the e-survey method. Results 38% (n = 397) of respondents said yes to exportation, 23.8% (n = 248) said no, and 38.2% (n = 399) were undecided. We found no relationship between willingness to export and general demographics, though those registered on the Donatelife Register (p = < .001), and those already willing to donate their eyes (p = < .001) were significantly more willing to export. Discussion More Australians are willing to export their corneas than not, though a significant portion remain undecided. The Donatelife Register, and donation awareness, are key components of respondent decision making. Therefore, the provision of information about exportation prior to, and at the point-of-donation, is essential for assisting Australian’s to decide to export or not. Further examination and development of consent-for-export systems are necessary before routine exportation is undertaken.
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Affiliation(s)
- Heather M. Machin
- Lions Eye Donation Service, Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia
- University of Melbourne, Melbourne, Australia
- * E-mail:
| | - Lisa Buckland
- Lions Eye Bank of Western Australia, Lions Eye Institute, Nedlands, Australia
| | - Christine Critchley
- Swinburne University of Technology, Melbourne, Australia
- Centre for Law and Genetics, University of Tasmania, Hobart, Australia
| | - Steven Wiffen
- Lions Eye Bank of Western Australia, Lions Eye Institute, Nedlands, Australia
| | - Gerard Sutton
- The University of Sydney, Save Sight Institute, Discipline of Ophthalmology, Sydney Medical School, Sydney, New South Wales, Australia
- The University of Technology Sydney, Graduate School of Health, Ultimo, New South Wales, Australia
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26
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Sahebjada S, Al-Mahrouqi HH, Moshegov S, Panchatcharam SM, Chan E, Daniell M, Baird PN. Eye rubbing in the aetiology of keratoconus: a systematic review and meta-analysis. Graefes Arch Clin Exp Ophthalmol 2021; 259:2057-2067. [PMID: 33484296 DOI: 10.1007/s00417-021-05081-8] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 01/03/2021] [Accepted: 01/09/2021] [Indexed: 12/14/2022] Open
Abstract
PURPOSE Keratoconus is a potentially blinding condition that slowly deforms the cornea in young people. Despite the increasing prevalence of keratoconus, the exact aetiology of the condition is unknown. This first systematic review examines the evidence of eye rubbing and its association with keratoconus and presents the findings of the meta-analysis. METHODS Two independent reviewers searched the electronic databases for all potential articles published from 1st of January 1900 to 31st of July 2020 on eye rubbing and keratoconus. The researchers assessed the methodological quality of the studies using the Newcastle-Ottawa scale for observational studies. The assessment for statistical heterogeneity was estimated using chi-square and I-square (I2) tests. A p value of < 0.05 was considered as statistically significant and I2 < 30% as homogenous. Begg funnel plot was used to interpret the asymmetry or small study effects. RESULTS Eight case-control studies were included in this systematic review. Two studies assessed eye rubbing without odds ratios and thus were excluded. The pooled odds ratios for the six remaining studies included in the meta-analysis was 6.46 (95% CI 4.12-10.1). The study results were heterogenous (I2 = 71.69 [95% CI 35.14-87.88]). All the studies scored moderate quality methodology on the Newcastle-Ottawa scale. Begg funnel plot showed asymmetry supporting heterogeneity. CONCLUSION Eye rubbing showed consistent association with keratoconus. However, the current evidence is limited to only a small number of case-control studies which present as heterogeneous and of sub-optimal methodological quality. Additionally, the cause-effect temporal relationship cannot be determined. Further studies are needed to address this intricate relationship of eye rubbing and its induction, ongoing progression, and severity of keratoconus.
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Affiliation(s)
- Srujana Sahebjada
- Department of Surgery, Ophthalmology, The University of Melbourne, Level 7, 32 Gisborne St, East Melbourne, VIC, 3002, Australia.
- Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Level 7, 32 Gisborne St, East Melbourne, VIC, 3002, Australia.
- Centre for Eye Research Australia, Melbourne, Australia.
| | | | - Sophia Moshegov
- Department of Surgery, Ophthalmology, The University of Melbourne, Level 7, 32 Gisborne St, East Melbourne, VIC, 3002, Australia
- Centre for Eye Research Australia, Melbourne, Australia
| | | | - Elsie Chan
- Department of Surgery, Ophthalmology, The University of Melbourne, Level 7, 32 Gisborne St, East Melbourne, VIC, 3002, Australia
- Centre for Eye Research Australia, Melbourne, Australia
- Royal Victorian Eye and Ear Hospital, Melbourne, Australia
| | - Mark Daniell
- Department of Surgery, Ophthalmology, The University of Melbourne, Level 7, 32 Gisborne St, East Melbourne, VIC, 3002, Australia
- Centre for Eye Research Australia, Melbourne, Australia
- Royal Victorian Eye and Ear Hospital, Melbourne, Australia
| | - Paul N Baird
- Department of Surgery, Ophthalmology, The University of Melbourne, Level 7, 32 Gisborne St, East Melbourne, VIC, 3002, Australia
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Pan Y, Iejima D, Nakayama M, Suga A, Noda T, Kaur I, Das T, Chakrabarti S, Guymer RH, DeAngelis MM, Yamamoto M, Baird PN, Iwata T. Binding of Gtf2i-β/δ transcription factors to the ARMS2 gene leads to increased circulating HTRA1 in AMD patients and in vitro. J Biol Chem 2021; 296:100456. [PMID: 33636181 PMCID: PMC8039566 DOI: 10.1016/j.jbc.2021.100456] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 02/05/2021] [Accepted: 02/22/2021] [Indexed: 12/12/2022] Open
Abstract
The disease-initiating molecular events for age-related macular degeneration (AMD), a multifactorial retinal disease affecting many millions of elderly individuals worldwide, are still unknown. Of the over 30 risk and protective loci so far associated with AMD through whole genome-wide association studies (GWAS), the Age-Related Maculopathy Susceptibility 2 (ARMS2) gene locus represents one of the most highly associated risk regions for AMD. A unique insertion/deletion (in/del) sequence located immediately upstream of the High Temperature Requirement A1 (HTRA1) gene in this region confers high risk for AMD. Using electrophoretic mobility shift assay (EMSA), we identified that two Gtf2i-β/δ transcription factor isoforms bind to the cis-element 5'- ATTAATAACC-3' contained in this in/del sequence. The binding of these transcription factors leads to enhanced upregulation of transcription of the secretory serine protease HTRA1 in transfected cells and AMD patient-derived induced pluripotent stem cells (iPSCs). Overexpression of Htra1 in mice using a CAG-promoter demonstrated increased blood concentration of Htra1 protein, caused upregulation of vascular endothelial growth factor (VEGF), and produced a choroidal neovascularization (CNV)-like phenotype. Finally, a comparison of 478 AMD patients to 481 healthy, age-matched controls from Japan, India, Australia, and the USA showed a statistically increased level of secreted HTRA1 blood concentration in AMD patients compared with age-matched controls. Taken together, these results suggest a common mechanism across ethnicities whereby increased systemic blood circulation of secreted serine protease HTRA1 leads to subsequent degradation of Bruch's membrane and eventual CNV in AMD.
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Affiliation(s)
- Yang Pan
- Division of Molecular and Cellular Biology, National Institute of Sensory Organs, National Hospital Organization Tokyo Medical Center, Tokyo, Japan
| | - Daisuke Iejima
- Division of Molecular and Cellular Biology, National Institute of Sensory Organs, National Hospital Organization Tokyo Medical Center, Tokyo, Japan
| | - Mao Nakayama
- Division of Molecular and Cellular Biology, National Institute of Sensory Organs, National Hospital Organization Tokyo Medical Center, Tokyo, Japan
| | - Akiko Suga
- Division of Molecular and Cellular Biology, National Institute of Sensory Organs, National Hospital Organization Tokyo Medical Center, Tokyo, Japan
| | - Toru Noda
- Division of Ophthalmology, National Hospital Organization Tokyo Medical Center, Tokyo, Japan
| | - Inderjeet Kaur
- Kallam Anji Reddy Molecular Genetics lab, Prof Brien Holden Eye Research Centre, L. V. Prasad Eye Institute, Hyderabad, India
| | - Taraprasad Das
- Kallam Anji Reddy Molecular Genetics lab, Prof Brien Holden Eye Research Centre, L. V. Prasad Eye Institute, Hyderabad, India
| | - Subhabrata Chakrabarti
- Kallam Anji Reddy Molecular Genetics lab, Prof Brien Holden Eye Research Centre, L. V. Prasad Eye Institute, Hyderabad, India
| | - Robyn H Guymer
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye & Ear Hospital, East Melbourne, Victoria, Australia; Department of Surgery, Ophthalmology, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, East Melbourne, Victoria, Australia
| | - Margaret M DeAngelis
- Department of Ophthalmology and Ira G. Ross Eye Institute, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, USA
| | - Megumi Yamamoto
- Division of Molecular and Cellular Biology, National Institute of Sensory Organs, National Hospital Organization Tokyo Medical Center, Tokyo, Japan; JAC Ltd, Tokyo, Japan
| | - Paul N Baird
- Department of Surgery, Ophthalmology, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, East Melbourne, Victoria, Australia
| | - Takeshi Iwata
- Division of Molecular and Cellular Biology, National Institute of Sensory Organs, National Hospital Organization Tokyo Medical Center, Tokyo, Japan.
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28
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McComish BJ, Sahebjada S, Bykhovskaya Y, Willoughby CE, Richardson AJ, Tenen A, Charlesworth JC, MacGregor S, Mitchell P, Lucas SEM, Mills RA, Mackey DA, Li X, Wang JJ, Jensen RA, Rotter JI, Taylor KD, Hewitt AW, Rabinowitz YS, Baird PN, Craig JE, Burdon KP. Association of Genetic Variation With Keratoconus. JAMA Ophthalmol 2020; 138:174-181. [PMID: 31855235 DOI: 10.1001/jamaophthalmol.2019.5293] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Importance Keratoconus is a condition in which the cornea progressively thins and protrudes in a conical shape, severely affecting refraction and vision. It is a major indication for corneal transplant. To discover new genetic loci associated with keratoconus and better understand the causative mechanism of this disease, we performed a genome-wide association study on patients with keratoconus. Objective To identify genetic susceptibility regions for keratoconus in the human genome. Design, Setting, and Participants This study was conducted with data from eye clinics in Australia, the United States, and Northern Ireland. The discovery cohort of individuals with keratoconus and control participants from Australia was genotyped using the Illumina HumanCoreExome single-nucleotide polymorphism array. After quality control and data cleaning, genotypes were imputed against the 1000 Genomes Project reference panel (phase III; version 5), and association analyses were completed using PLINK version 1.90. Single-nucleotide polymorphisms with P < 1.00 × 10-6 were assessed for replication in 3 additional cohorts. Control participants were drawn from the cohorts of the Blue Mountains Eye Study and a previous study of glaucoma. Replication cohorts were from a previous keratoconus genome-wide association study data set from the United States, a cohort of affected and control participants from Australia and Northern Ireland, and a case-control cohort from Victoria, Australia. Data were collected from January 2006 to March 2019. Main Outcomes and Measures Associations between keratoconus and 6 252 612 genetic variants were estimated using logistic regression after adjusting for ancestry using the first 3 principal components. Results The discovery cohort included 522 affected individuals and 655 control participants, while the replication cohorts included 818 affected individuals (222 from the United States, 331 from Australia and Northern Ireland, and 265 from Victoria, Australia) and 3858 control participants (2927 from the United States, 229 from Australia and Northern Ireland, and 702 from Victoria, Australia). Two novel loci reached genome-wide significance (defined as P < 5.00 × 10-8), with a P value of 7.46 × 10-9 at rs61876744 in patatin-like phospholipase domain-containing 2 gene (PNPLA2) on chromosome 11 and a P value of 6.35 × 10-12 at rs138380, 2.2 kb upstream of casein kinase I isoform epsilon gene (CSNK1E) on chromosome 22. One additional locus was identified with a P value less than 1.00 × 10-6 in mastermind-like transcriptional coactivator 2 (MAML2) on chromosome 11 (P = 3.91 × 10-7). The novel locus in PNPLA2 reached genome-wide significance in an analysis of all 4 cohorts (P = 2.45 × 10-8). Conclusions and Relevance In this relatively large keratoconus genome-wide association study, we identified a genome-wide significant locus for keratoconus in the region of PNPLA2 on chromosome 11.
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Affiliation(s)
- Bennet J McComish
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Srujana Sahebjada
- Centre for Eye Research Australia, Melbourne, Victoria, Australia.,Department of Surgery (Ophthalmology), Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Victoria, Australia
| | - Yelena Bykhovskaya
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, California.,Cornea Genetic Eye Institute, Beverly Hills, California.,Board of the Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Colin E Willoughby
- Biomedical Sciences Research Institute, Ulster University, Coleraine, Northern Ireland, United Kingdom.,Belfast Health and Social Care Trust, Belfast, Northern Ireland, United Kingdom
| | | | - Abi Tenen
- Vision Eye Institute, Melbourne, Victoria, Australia.,School of Primary and Allied Health Care, Monash University, Melbourne, Victoria, Australia.,Melbourne Stem Cell Centre, Melbourne, Victoria, Australia
| | - Jac C Charlesworth
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | | | - Paul Mitchell
- Centre for Vision Research, Westmead Institute for Medical Research, University of Sydney, Sydney, New South Wales, Australia
| | - Sionne E M Lucas
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Richard A Mills
- Department of Ophthalmology, Flinders University, Adelaide, South Australia, Australia
| | - David A Mackey
- Lions Eye Institute, University of Western Australia, Perth, Western Australia, Australia
| | - Xiaohui Li
- Institute for Translational Genomics and Population Science, Los Angeles Biomedical Research Institute, Los Angeles, California.,Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California
| | - Jie Jin Wang
- Centre for Vision Research, Westmead Institute for Medical Research, University of Sydney, Sydney, New South Wales, Australia
| | - Richard A Jensen
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Science, Los Angeles Biomedical Research Institute, Los Angeles, California.,Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California
| | - Kent D Taylor
- Institute for Translational Genomics and Population Science, Los Angeles Biomedical Research Institute, Los Angeles, California.,Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, California
| | - Alex W Hewitt
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia.,Centre for Eye Research Australia, Melbourne, Victoria, Australia
| | - Yaron S Rabinowitz
- Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, California.,Cornea Genetic Eye Institute, Beverly Hills, California.,Board of the Governors Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Paul N Baird
- Centre for Eye Research Australia, Melbourne, Victoria, Australia.,Department of Surgery (Ophthalmology), Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Victoria, Australia
| | - Jamie E Craig
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia.,Department of Ophthalmology, Flinders University, Adelaide, South Australia, Australia
| | - Kathryn P Burdon
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia.,Department of Ophthalmology, Flinders University, Adelaide, South Australia, Australia
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Sahebjada S, Chan E, Xie J, Snibson GR, Daniell M, Baird PN. Risk factors and association with severity of keratoconus: the Australian study of Keratoconus. Int Ophthalmol 2020; 41:891-899. [PMID: 33200389 DOI: 10.1007/s10792-020-01644-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 10/29/2020] [Indexed: 01/12/2023]
Abstract
SIGNIFICANCE Our results show that asthmatic patients tend to have more severe KC and thus close monitoring for disease progression would be advised, and appropriate treatment strategies may be actioned stabilise the condition that may reduce the need for future corneal transplantation. PURPOSE To explore a wide range of risk factors associated with the severity of keratoconus (KC). METHODS A cross-sectional study of KC patients was undertaken in Melbourne, Australia. A questionnaire addressing age, gender, educational background, ocular and medical history, smoking and alcohol consumption, and physical examination comprising anthropometric measurements was collected; eye examination was undertaken. The associations between a range of risk factors and the severity of KC were determined using univariate and multivariable linear regression analyses. RESULTS A total of 260 KC subjects were included in this study. Mean age of subject was 35.5 (SD = 14.8) years and the majority of the subjects were European 171 (68.2%). Initial univariate regression analysis identified the following risk factors at the p < 0.1 level with KC: higher body mass index, smoking cigarettes, diabetes, rheumatoid arthritis and asthma were associated with increased severity of KC, whereas eczema was associated with less severe KC. Following multivariable regression analysis, only asthma remained as a significant risk factor associated with 2.2 diopters (D) steeper average mean keratometry compared to KC subjects having no asthma [p = 0.03; β = 2.18; 95% confidence intervals: 1.22, 4.14]. CONCLUSION Our study describes the comprehensive assessment of all the known risk factors in a large KC cohort recruited in Australia. Our study has reported asthma as the only risk factor found to be significantly associated with the severity of KC. The results of this study allow us to better understand the aetiology of KC and such knowledge could be useful in instigate systemic management of patients to slow or prevent KC.
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Affiliation(s)
- Srujana Sahebjada
- Centre for Eye Research Australia, Melbourne, VIC, Australia. .,The University of Melbourne, Melbourne, VIC, Australia.
| | - Elsie Chan
- Centre for Eye Research Australia, Melbourne, VIC, Australia.,The University of Melbourne, Melbourne, VIC, Australia.,Royal Victorian Eye and Ear Hospital, Melbourne, VIC, Australia
| | - Jing Xie
- Centre for Eye Research Australia, Melbourne, VIC, Australia.,Monash University Melbourne, Melbourne, VIC, Australia
| | - Grant R Snibson
- Centre for Eye Research Australia, Melbourne, VIC, Australia.,The University of Melbourne, Melbourne, VIC, Australia.,Royal Victorian Eye and Ear Hospital, Melbourne, VIC, Australia
| | - Mark Daniell
- Centre for Eye Research Australia, Melbourne, VIC, Australia.,The University of Melbourne, Melbourne, VIC, Australia.,Royal Victorian Eye and Ear Hospital, Melbourne, VIC, Australia
| | - Paul N Baird
- The University of Melbourne, Melbourne, VIC, Australia
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30
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Arslan J, Samarasinghe G, Benke KK, Sowmya A, Wu Z, Guymer RH, Baird PN. Artificial Intelligence Algorithms for Analysis of Geographic Atrophy: A Review and Evaluation. Transl Vis Sci Technol 2020; 9:57. [PMID: 33173613 PMCID: PMC7594588 DOI: 10.1167/tvst.9.2.57] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 09/28/2020] [Indexed: 12/28/2022] Open
Abstract
Purpose The purpose of this study was to summarize and evaluate artificial intelligence (AI) algorithms used in geographic atrophy (GA) diagnostic processes (e.g. isolating lesions or disease progression). Methods The search strategy and selection of publications were both conducted in accordance with the Preferred of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed and Web of Science were used to extract literary data. The algorithms were summarized by objective, performance, and scope of coverage of GA diagnosis (e.g. lesion automation and GA progression). Results Twenty-seven studies were identified for this review. A total of 18 publications focused on lesion segmentation only, 2 were designed to detect and classify GA, 2 were designed to predict future overall GA progression, 3 focused on prediction of future spatial GA progression, and 2 focused on prediction of visual function in GA. GA-related algorithms reported sensitivities from 0.47 to 0.98, specificities from 0.73 to 0.99, accuracies from 0.42 to 0.995, and Dice coefficients from 0.66 to 0.89. Conclusions Current GA-AI publications have a predominant focus on lesion segmentation and a minor focus on classification and progression analysis. AI could be applied to other facets of GA diagnoses, such as understanding the role of hyperfluorescent areas in GA. Using AI for GA has several advantages, including improved diagnostic accuracy and faster processing speeds. Translational Relevance AI can be used to quantify GA lesions and therefore allows one to impute visual function and quality-of-life. However, there is a need for the development of reliable and objective models and software to predict the rate of GA progression and to quantify improvements due to interventions.
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Affiliation(s)
- Janan Arslan
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
- Department of Surgery, Ophthalmology, University of Melbourne, Victoria, Australia
| | - Gihan Samarasinghe
- School of Computer Science and Engineering, University of New South Wales, Kensington, New South Wales, Australia
| | - Kurt K. Benke
- School of Engineering, University of Melbourne, Parkville, Victoria, Australia
- Centre for AgriBioscience, AgriBio, Bundoora, Victoria, Australia
| | - Arcot Sowmya
- School of Computer Science and Engineering, University of New South Wales, Kensington, New South Wales, Australia
| | - Zhichao Wu
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
| | - Robyn H. Guymer
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
- Department of Surgery, Ophthalmology, University of Melbourne, Victoria, Australia
| | - Paul N. Baird
- Department of Surgery, Ophthalmology, University of Melbourne, Victoria, Australia
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Cao K, Verspoor K, Sahebjada S, Baird PN. Evaluating the Performance of Various Machine Learning Algorithms to Detect Subclinical Keratoconus. Transl Vis Sci Technol 2020; 9:24. [PMID: 32818085 PMCID: PMC7396174 DOI: 10.1167/tvst.9.2.24] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 02/05/2020] [Indexed: 12/26/2022] Open
Abstract
Purpose Keratoconus (KC) represents one of the leading causes of corneal transplantation worldwide. Detecting subclinical KC would lead to better management to avoid the need for corneal grafts, but the condition is clinically challenging to diagnose. We wished to compare eight commonly used machine learning algorithms using a range of parameter combinations by applying them to our KC dataset and build models to better differentiate subclinical KC from non-KC eyes. Methods Oculus Pentacam was used to obtain corneal parameters on 49 subclinical KC and 39 control eyes, along with clinical and demographic parameters. Eight machine learning methods were applied to build models to differentiate subclinical KC from control eyes. Dominant algorithms were trained with all combinations of the considered parameters to select important parameter combinations. The performance of each model was evaluated and compared. Results Using a total of eleven parameters, random forest, support vector machine and k-nearest neighbors had better performance in detecting subclinical KC. The highest area under the curve of 0.97 for detecting subclinical KC was achieved using five parameters by the random forest method. The highest sensitivity (0.94) and specificity (0.90) were obtained by the support vector machine and the k-nearest neighbor model, respectively. Conclusions This study showed machine learning algorithms can be applied to identify subclinical KC using a minimal parameter set that are routinely collected during clinical eye examination. Translational Relevance Machine learning algorithms can be built using routinely collected clinical parameters that will assist in the objective detection of subclinical KC.
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Affiliation(s)
- Ke Cao
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia.,Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Karin Verspoor
- Department of Computing and Information Systems, The University of Melbourne, Melbourne, Victoria, Australia
| | - Srujana Sahebjada
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia.,Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Paul N Baird
- Department of Surgery, Ophthalmology, The University of Melbourne, Melbourne, Victoria, Australia
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Chan E, Baird PN, Vogrin S, Sundararajan V, Daniell MD, Sahebjada S. Economic impact of keratoconus using a health expenditure questionnaire: A patient perspective. Clin Exp Ophthalmol 2020; 48:287-300. [DOI: 10.1111/ceo.13704] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2019] [Revised: 11/27/2019] [Accepted: 12/14/2019] [Indexed: 11/28/2022]
Affiliation(s)
- Elsie Chan
- Centre for Eye Research Australia Melbourne Victoria Australia
- Division of Ophthalmology, Department of SurgeryThe University of Melbourne Melbourne Victoria Australia
- Royal Victorian Eye and Ear Hospital Melbourne Victoria Australia
| | - Paul N. Baird
- Centre for Eye Research Australia Melbourne Victoria Australia
- Division of Ophthalmology, Department of SurgeryThe University of Melbourne Melbourne Victoria Australia
| | - Sara Vogrin
- Division of Ophthalmology, Department of SurgeryThe University of Melbourne Melbourne Victoria Australia
- St. Vincent's Hospital Melbourne Victoria Australia
| | - Vijaya Sundararajan
- St. Vincent's Hospital Melbourne Victoria Australia
- Department of Public HealthLa Trobe University Melbourne Victoria Australia
| | - Mark D. Daniell
- Centre for Eye Research Australia Melbourne Victoria Australia
- Division of Ophthalmology, Department of SurgeryThe University of Melbourne Melbourne Victoria Australia
- Royal Victorian Eye and Ear Hospital Melbourne Victoria Australia
| | - Srujana Sahebjada
- Centre for Eye Research Australia Melbourne Victoria Australia
- Division of Ophthalmology, Department of SurgeryThe University of Melbourne Melbourne Victoria Australia
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Baird PN, Jonas JB. Uncorrected refractive error in the Australian National Eye Health Survey. Clin Exp Ophthalmol 2020; 48:9-11. [PMID: 32036632 DOI: 10.1111/ceo.13698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Paul N Baird
- Department of Surgery, Ophthalmology, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia
| | - Jost B Jonas
- Department of Ophthalmology, Medical Faculty Mannheim of the Ruprecht-Karls-University of Heidelberg, Mannheim, Germany
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Cao K, Sahebjada S, Richardson AJ, Baird PN. Do age-related macular degeneration genes show association with keratoconus? Eye Vis (Lond) 2019; 6:38. [PMID: 31819893 PMCID: PMC6885317 DOI: 10.1186/s40662-019-0164-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Accepted: 11/03/2019] [Indexed: 01/06/2023]
Abstract
Background Keratoconus (KC) is a common corneal condition with an unknown gender predominance. Although numerous studies have investigated the genetic component of KC, no specific genes have yet been attributed to the condition. We recently reported posterior segment changes occurring in the eyes of KC patients. However, it is not clear whether these changes are part of KC pathogenesis or reflect changes in anatomical features of the eye manifested by changes at the cornea. Given retinal changes represent the main characteristics observed in age-related macular degeneration (AMD) and that pleiotropy has been demonstrated between different eye diseases, we wished to assess if known AMD associated genes were also associated with KC. Methods A total of 248 KC subjects and 366 non-KC (control) subjects were recruited from public and private clinics in Melbourne for this analysis. Nineteen single nucleotide polymorphisms (SNPs) previously associated with AMD, including rs10490924 (ARMS2/HTRA1), rs10737680 (CFH), rs13278062 (TNFRSF10A), rs1864163 (CETP), rs2230199 (C3), rs3130783 (IER3/DDR1), rs334353 (TGFBR1), rs3812111 (COL10A1), rs429608 (C2/CFB), rs4420638 (APOE), rs4698775 (CFI), rs5749482 (TIMP3), rs6795735 (ADAMTS9), rs8017304 (RAD51B), rs8135665 (SLC16A8), rs920915 (LIPC), rs943080 (VEGFA), rs9542236 (B3GALTL) and rs13081855 (COL8A1/FILIP1L), were genotyped in this cohort. Logistic regression was applied to evaluate the association between these SNPs and KC on both genders together, as well as each gender separately. Linear regression was also applied to assess the association between SNPs and corneal curvature. Bonferroni correction was applied to adjust for multiple testing. Results Genotyping data were available for 18 SNPs. The SNP, rs6795735 (ADAMTS9) was significantly associated with KC (p = 3.5 × 10- 4) when both genders were assessed, whereas rs5749482 (TIMP3) was only associated in males (p = 7.7 × 10- 4) following Bonferroni multiple correction. However, when the covariates of age and gender were included, the associations became non-significant. In addition, none of the SNPs appeared significant for corneal curvature. Conclusions Our study suggested a potential association of rs6795735 in the ADAMTS9 gene and rs5749482 in the TIMP3 gene in KC and that different associations may be gender specific. Overall, SNPs initially identified as associated with AMD following multiple correction may be further impacted by other factors such as age or gender and further studies are needed to resolve this issue.
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Affiliation(s)
- Ke Cao
- 1Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Australia.,2Department of Surgery, Ophthalmology, The University of Melbourne, 32 Gisborne Street, East Melbourne, VIC 3000 Australia
| | - Srujana Sahebjada
- 1Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Australia.,2Department of Surgery, Ophthalmology, The University of Melbourne, 32 Gisborne Street, East Melbourne, VIC 3000 Australia
| | - Andrea J Richardson
- 1Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
| | - Paul N Baird
- 2Department of Surgery, Ophthalmology, The University of Melbourne, 32 Gisborne Street, East Melbourne, VIC 3000 Australia
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Srinivasalu N, McFadden SA, Medcalf C, Fuchs L, Chung J, Philip G, Richardson A, Riaz M, Baird PN. Gene Expression and Pathways Underlying Form Deprivation Myopia in the Guinea Pig Sclera. Invest Ophthalmol Vis Sci 2018; 59:1425-1434. [PMID: 29625465 DOI: 10.1167/iovs.16-21278] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Purpose Posterior scleral remodeling accompanies myopia. In guinea pigs developing myopia, the region around the optic nerve (peripapillary zone, PPZ) rapidly expands followed by inhibition in eye size in the periphery. We studied the differential gene expression in the sclera that accompanies these changes. Methods Guinea pigs were form-deprived (FD) for 2 weeks to induce myopia, while the fellow eye served as a control. After 2 weeks, the PPZ and the peripheral temporal sclera were isolated in representative animals to extract the RNA. RNA sequencing was undertaken using an Illumina HiSeq 2000, with differential expression analyzed using Voom and pathways analyzed using the Ingenuity Pathway Analysis tool. RNA from additional PPZ and peripheral temporal sclera in FD and fellow eyes was used for validation of gene expression using quantitative real-time PCR (qRT-PCR). Results In myopic sclera, 348 genes were differentially expressed between PPZ and the peripheral temporal region (corrected P < 0.05), of which 61 were differentially expressed in the PPZ between myopic and control eyes. Pathway analyses of these gene sets showed the involvement of Gαi signaling along with previously reported gamma-aminobutyric acid (GABA) and glutamate receptors among numerous novel pathways. The expression pattern of three novel genes and two myopia-related genes was validated using qRT-PCR. Conclusions Gene expression changes are associated with the rapid elongation that occurs around the optic nerve region during the development of myopia. A prominent change in Gαi signaling, which affects cAMP synthesis and thus collagen levels, may be critical in mediating the regional changes in myopic sclera.
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Affiliation(s)
- Nethrajeith Srinivasalu
- Ocular Genetics Unit, Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia.,Vision Sciences, School of Psychology, Faculty of Science and Hunter Medical Research Institute, University of Newcastle, Callaghan, New South Wales, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, East Melbourne, Victoria, Australia
| | - Sally A McFadden
- Vision Sciences, School of Psychology, Faculty of Science and Hunter Medical Research Institute, University of Newcastle, Callaghan, New South Wales, Australia
| | - Callan Medcalf
- Vision Sciences, School of Psychology, Faculty of Science and Hunter Medical Research Institute, University of Newcastle, Callaghan, New South Wales, Australia
| | - Lena Fuchs
- Vision Sciences, School of Psychology, Faculty of Science and Hunter Medical Research Institute, University of Newcastle, Callaghan, New South Wales, Australia
| | - Jessica Chung
- Melbourne Bioinformatics, University of Melbourne, Melbourne, Victoria, Australia
| | - Gayle Philip
- Melbourne Bioinformatics, University of Melbourne, Melbourne, Victoria, Australia
| | - Andrea Richardson
- Ocular Genetics Unit, Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
| | - Moeen Riaz
- Ocular Genetics Unit, Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, East Melbourne, Victoria, Australia
| | - Paul N Baird
- Ocular Genetics Unit, Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, East Melbourne, Victoria, Australia
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Lorés-Motta L, Riaz M, Grunin M, Corominas J, van Asten F, Pauper M, Leenders M, Richardson AJ, Muether P, Cree AJ, Griffiths HL, Pham C, Belanger MC, Meester-Smoor MA, Ali M, Heid IM, Fritsche LG, Chakravarthy U, Gale R, McKibbin M, Inglehearn CF, Schlingemann RO, Omar A, Chen J, Koenekoop RK, Fauser S, Guymer RH, Hoyng CB, de Jong EK, Lotery AJ, Mitchell P, den Hollander AI, Baird PN, Chowers I. Association of Genetic Variants With Response to Anti-Vascular Endothelial Growth Factor Therapy in Age-Related Macular Degeneration. JAMA Ophthalmol 2018; 136:875-884. [PMID: 29852030 PMCID: PMC6142943 DOI: 10.1001/jamaophthalmol.2018.2019] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 04/02/2018] [Indexed: 02/04/2023]
Abstract
Importance Visual acuity (VA) outcomes differ considerably among patients with neovascular age-related macular degeneration (nAMD) treated with anti-vascular endothelial growth factor (VEGF) drugs. Identification of pharmacogenetic associations may help clinicians understand the mechanisms underlying this variability as well as pave the way for personalized treatment in nAMD. Objective To identify genetic factors associated with variability in the response to anti-VEGF therapy for patients with nAMD. Design, Setting, and Participants In this multicenter genome-wide association study, 678 patients with nAMD with genome-wide genotyping data were included in the discovery phase; 1380 additional patients with nAMD were genotyped for selected common variants in the replication phase. All participants received 3 monthly injections of bevacizumab or ranibizumab. Clinical data were evaluated for inclusion/exclusion criteria from October 2014 to October 2015, followed by data analysis from October 2015 to February 2016. For replication cohort genotyping, clinical data collection and analysis (including meta-analysis) was performed from March 2016 to April 2017. Main Outcomes and Measures Change in VA after the loading dose of 3 monthly anti-VEGF injections compared with baseline. Results Of the 2058 included patients, 1210 (58.8%) were women, and the mean (SD) age across all cohorts was 78 (7.4) years. Patients included in the discovery cohort and most of the patients in the replication cohorts were of European descent. The mean (SD) baseline VA was 51.3 (20.3) Early Treatment Diabetic Retinopathy Study (ETDRS) score letters, and the mean (SD) change in VA after the loading dose of 3 monthly injections was a gain of 5.1 (13.9) ETDRS score letters (ie, 1-line gain). Genome-wide single-variant analyses of common variants revealed 5 independent loci that reached a P value less than 10 × 10-5. After replication and meta-analysis of the lead variants, rs12138564 located in the CCT3 gene remained nominally associated with a better treatment outcome (ETDRS letter gain, 1.7; β, 0.034; SE, 0.008; P = 1.38 × 10-5). Genome-wide gene-based optimal unified sequence kernel association test of rare variants showed genome-wide significant associations for the C10orf88 (P = 4.22 × 10-7) and UNC93B1 (P = 6.09 × 10-7) genes, in both cases leading to a worse treatment outcome. Patients carrying rare variants in the C10orf88 and UNC93B1 genes lost a mean (SD) VA of 30.6 (17.4) ETDRS score letters (ie, loss of 6.09 lines) and 26.5 (13.8) ETDRS score letters (ie, loss of 5.29 lines), respectively, after 3 months of anti-VEGF treatment. Conclusions and Relevance We propose that there is a limited contribution of common genetic variants to variability in nAMD treatment response. Our results suggest that rare protein-altering variants in the C10orf88 and UNC93B1 genes are associated with a worse response to anti-VEGF therapy in patients with nAMD, but these results require further validation in other cohorts.
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Affiliation(s)
- Laura Lorés-Motta
- Department of Ophthalmology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Moeen Riaz
- Centre for Eye Research Australia, Department of Surgery in Ophthalmology, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
- Public Health Genomics, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Michelle Grunin
- Department of Ophthalmology, Hebrew University Hadassah Medical School, Hadassah Medical Center–Hebrew University, Jerusalem, Israel
| | - Jordi Corominas
- Department of Ophthalmology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Human Genetics, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Freekje van Asten
- Division of Epidemiology and Clinical Application, National Eye Institute, National Institutes of Health, Bethesda, Maryland
- Neurobiology, Neurodegeneration, and Repair Laboratory, National Eye Institute, National Institutes of Health, Bethesda, Maryland
| | - Marc Pauper
- Department of Ophthalmology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Human Genetics, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Mathieu Leenders
- Department of Ophthalmology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Andrea J. Richardson
- Centre for Eye Research Australia, Department of Surgery in Ophthalmology, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
| | - Philipp Muether
- Department of Ophthalmology, University Hospital of Cologne, Cologne, Germany
| | - Angela J. Cree
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, England
| | - Helen L. Griffiths
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, England
| | - Connie Pham
- Department Ophthalmology, McGill University Health Centre, Montreal, Québec, Canada
| | | | | | - Manir Ali
- Section of Ophthalmology and Neuroscience, Leeds Institute of Molecular Medicine, University of Leeds, Leeds, England
| | - Iris M. Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Lars G. Fritsche
- Norwegian University of Science and Technology, Trondheim, Norway
| | | | | | | | - Chris F. Inglehearn
- Section of Ophthalmology and Neuroscience, Leeds Institute of Molecular Medicine, University of Leeds, Leeds, England
- Eye Clinic, St James’s University Hospital, Leeds, England
| | - Reinier O. Schlingemann
- Department of Ophthalmology, Ocular Angiogenesis Group, Academic Medical Center, Amsterdam, the Netherlands
- Netherlands Institute for Neuroscience, Amsterdam, the Netherlands
| | - Amer Omar
- Montreal Retina Institute, Westmount, Québec, Canada
| | - John Chen
- Department of Pediatric Surgery, McGill University Health Centre, Montreal, Québec, Canada
- Department of Human Genetics, McGill University Health Centre, Montreal, Québec, Canada
- Department of Ophthalmology, McGill University Health Centre, Montreal, Québec, Canada
| | - Robert K. Koenekoop
- Department of Pediatric Surgery, McGill University Health Centre, Montreal, Québec, Canada
- Department of Human Genetics, McGill University Health Centre, Montreal, Québec, Canada
- Department of Ophthalmology, McGill University Health Centre, Montreal, Québec, Canada
| | - Sascha Fauser
- Department of Ophthalmology, University Hospital of Cologne, Cologne, Germany
- Roche Pharma Research and Early Development, Hoffmann–La Roche, Basel, Switzerland
| | - Robyn H. Guymer
- Centre for Eye Research Australia, Department of Surgery in Ophthalmology, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
| | - Carel B. Hoyng
- Department of Ophthalmology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Eiko K. de Jong
- Department of Ophthalmology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Andrew J. Lotery
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, England
| | - Paul Mitchell
- Centre for Vision Research, Department of Ophthalmology and Westmead Millennium Institute for Medical Research, University of Sydney, Sydney, New South Wales, Australia
| | - Anneke I. den Hollander
- Department of Ophthalmology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Human Genetics, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Paul N. Baird
- Centre for Eye Research Australia, Department of Surgery in Ophthalmology, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
| | - Itay Chowers
- Department of Ophthalmology, Hebrew University Hadassah Medical School, Hadassah Medical Center–Hebrew University, Jerusalem, Israel
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Tedja MS, Wojciechowski R, Hysi PG, Eriksson N, Furlotte NA, Verhoeven VJ, Iglesias AI, Meester-Smoor MA, Tompson SW, Fan Q, Khawaja AP, Cheng CY, Höhn R, Yamashiro K, Wenocur A, Grazal C, Haller T, Metspalu A, Wedenoja J, Jonas JB, Wang YX, Xie J, Mitchell P, Foster PJ, Klein BE, Klein R, Paterson AD, Hosseini SM, Shah RL, Williams C, Teo YY, Tham YC, Gupta P, Zhao W, Shi Y, Saw WY, Tai ES, Sim XL, Huffman JE, Polašek O, Hayward C, Bencic G, Rudan I, Wilson JF, Joshi PK, Tsujikawa A, Matsuda F, Whisenhunt KN, Zeller T, van der Spek PJ, Haak R, Meijers-Heijboer H, van Leeuwen EM, Iyengar SK, Lass JH, Hofman A, Rivadeneira F, Uitterlinden AG, Vingerling JR, Lehtimäki T, Raitakari OT, Biino G, Concas MP, Schwantes-An TH, Igo RP, Cuellar-Partida G, Martin NG, Craig JE, Gharahkhani P, Williams KM, Nag A, Rahi JS, Cumberland PM, Delcourt C, Bellenguez C, Ried JS, Bergen AA, Meitinger T, Gieger C, Wong TY, Hewitt AW, Mackey DA, Simpson CL, Pfeiffer N, Pärssinen O, Baird PN, Vitart V, Amin N, van Duijn CM, Bailey-Wilson JE, Young TL, Saw SM, Stambolian D, MacGregor S, Guggenheim JA, Tung JY, Hammond CJ, Klaver CC. Genome-wide association meta-analysis highlights light-induced signaling as a driver for refractive error. Nat Genet 2018; 50:834-848. [PMID: 29808027 PMCID: PMC5980758 DOI: 10.1038/s41588-018-0127-7] [Citation(s) in RCA: 191] [Impact Index Per Article: 31.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Accepted: 03/26/2018] [Indexed: 12/18/2022]
Abstract
Refractive errors, including myopia, are the most frequent eye disorders worldwide and an increasingly common cause of blindness. This genome-wide association meta-analysis in 160,420 participants and replication in 95,505 participants increased the number of established independent signals from 37 to 161 and showed high genetic correlation between Europeans and Asians (>0.78). Expression experiments and comprehensive in silico analyses identified retinal cell physiology and light processing as prominent mechanisms, and also identified functional contributions to refractive-error development in all cell types of the neurosensory retina, retinal pigment epithelium, vascular endothelium and extracellular matrix. Newly identified genes implicate novel mechanisms such as rod-and-cone bipolar synaptic neurotransmission, anterior-segment morphology and angiogenesis. Thirty-one loci resided in or near regions transcribing small RNAs, thus suggesting a role for post-transcriptional regulation. Our results support the notion that refractive errors are caused by a light-dependent retina-to-sclera signaling cascade and delineate potential pathobiological molecular drivers.
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Affiliation(s)
- Milly S. Tedja
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Robert Wojciechowski
- Department of Epidemiology and Medicine, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
- Wilmer Eye Institute, Johns Hopkins Medical Institutions, Baltimore, Maryland, USA
| | - Pirro G. Hysi
- Section of Academic Ophthalmology, School of Life Course Sciences, King’s College London, London, UK
| | | | | | - Virginie J.M. Verhoeven
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Adriana I. Iglesias
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Magda A. Meester-Smoor
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Stuart W. Tompson
- Department of Ophthalmology and Visual Sciences, University of Wisconsin–Madison, Madison, Wisconsin, USA
| | - Qiao Fan
- Centre for Quantitative Medicine, DUKE-National University of Singapore, Singapore
| | - Anthony P. Khawaja
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
| | - Ching-Yu Cheng
- Centre for Quantitative Medicine, DUKE-National University of Singapore, Singapore
- Ocular Epidemiology Research Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - René Höhn
- Department of Ophthalmology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
- Department of Ophthalmology, University Medical Center Mainz, Mainz, Germany
| | - Kenji Yamashiro
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Adam Wenocur
- Department of Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Clare Grazal
- Department of Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Toomas Haller
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | | | - Juho Wedenoja
- Department of Ophthalmology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Jost B. Jonas
- Department of Ophthalmology, Medical Faculty Mannheim of the Ruprecht-Karls-University of Heidelberg, Mannheim, Germany
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Jing Xie
- Centre for Eye Research Australia, Ophthalmology, Department of Surgery, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
| | - Paul Mitchell
- Department of Ophthalmology, Centre for Vision Research, Westmead Institute for Medical Research, University of Sydney, Sydney, Australia
| | - Paul J. Foster
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
| | - Barbara E.K. Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin–Madison, Madison, Wisconsin, USA
| | - Ronald Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin–Madison, Madison, Wisconsin, USA
| | - Andrew D. Paterson
- Program in Genetics and Genome Biology, Hospital for Sick Children and University of Toronto, Toronto, Ontario, Canada
| | - S. Mohsen Hosseini
- Program in Genetics and Genome Biology, Hospital for Sick Children and University of Toronto, Toronto, Ontario, Canada
| | - Rupal L. Shah
- School of Optometry & Vision Sciences, Cardiff University, Cardiff, UK
| | - Cathy Williams
- Department of Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Yik Ying Teo
- Department of Statistics and Applied Probability, National University of Singapore, Singapore
- Saw Swee Hock School of Public Health, National University Health Systems, National University of Singapore, Singapore
| | - Yih Chung Tham
- Ocular Epidemiology Research Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Preeti Gupta
- Department of Health Service Research, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Wanting Zhao
- Centre for Quantitative Medicine, DUKE-National University of Singapore, Singapore
- Statistics Support Platform, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Yuan Shi
- Statistics Support Platform, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Woei-Yuh Saw
- Life Sciences Institute, National University of Singapore, Singapore
| | - E-Shyong Tai
- Saw Swee Hock School of Public Health, National University Health Systems, National University of Singapore, Singapore
| | - Xue Ling Sim
- Saw Swee Hock School of Public Health, National University Health Systems, National University of Singapore, Singapore
| | - Jennifer E. Huffman
- MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Ozren Polašek
- Faculty of Medicine, University of Split, Split, Croatia
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Goran Bencic
- Department of Ophthalmology, Sisters of Mercy University Hospital, Zagreb, Croatia
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - James F. Wilson
- MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | | | | | | | - Peter K. Joshi
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Akitaka Tsujikawa
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Kristina N. Whisenhunt
- Department of Ophthalmology and Visual Sciences, University of Wisconsin–Madison, Madison, Wisconsin, USA
| | - Tanja Zeller
- Clinic for General and Interventional Cardiology, University Heart Center Hamburg, Hamburg, Germany
| | | | - Roxanna Haak
- Department of Bioinformatics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Hanne Meijers-Heijboer
- Department of Clinical Genetics, Academic Medical Center, Amsterdam, The Netherlands
- Department of Clinical Genetics, VU University Medical Center, Amsterdam, The Netherlands
| | - Elisabeth M. van Leeuwen
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Sudha K. Iyengar
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Ophthalmology and Visual Sciences, Case Western Reserve University and University Hospitals Eye Institute, Cleveland, Ohio, USA
- Department of Genetics, Case Western Reserve University, Cleveland, Ohio, USA
| | - Jonathan H. Lass
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Ophthalmology and Visual Sciences, Case Western Reserve University and University Hospitals Eye Institute, Cleveland, Ohio, USA
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Harvard T.HChan School of Public Health, Boston, Massachusetts, USA
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, the Hague, the Netherlands
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, the Hague, the Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, the Hague, the Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Terho Lehtimäki
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Life Sciences, University of Tampere
- Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere, Tampere, Finland
| | - Olli T. Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Ginevra Biino
- Institute of Molecular Genetics, National Research Council of Italy, Sassari, Italy
| | - Maria Pina Concas
- Institute for Maternal and Child Health - IRCCS “Burlo Garofolo”, Trieste, Italy
| | - Tae-Hwi Schwantes-An
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
- Department of Medical and Molecular Genetics, Indiana University, School of Medicine, Indianapolis, Indiana, USA
| | - Robert P. Igo
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | | | - Nicholas G. Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Jamie E. Craig
- Department of Ophthalmology, Flinders University, Adelaide, Australia
| | - Puya Gharahkhani
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Katie M. Williams
- Section of Academic Ophthalmology, School of Life Course Sciences, King’s College London, London, UK
| | - Abhishek Nag
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK
| | - Jugnoo S. Rahi
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
- Great Ormond Street Institute of Child Health, University College London, London, UK
- Ulverscroft Vision Research Group, University College London, London, UK
| | | | - Cécile Delcourt
- Université de Bordeaux, Inserm, Bordeaux Population Health Research Center, team LEHA, UMR 1219, F-33000 Bordeaux, France
| | - Céline Bellenguez
- Institut Pasteur de Lille, Lille, France
- Inserm, U1167, RID-AGE - Risk factors and molecular determinants of aging-related diseases, Lille, France
- Université de Lille, U1167 - Excellence Laboratory LabEx DISTALZ, Lille, France
| | - Janina S. Ried
- Institute of Genetic Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
| | - Arthur A. Bergen
- Department of Clinical Genetics, Academic Medical Center, Amsterdam, The Netherlands
- Department of Ophthalmology, Academic Medical Center, Amsterdam, The Netherlands
- The Netherlands Institute for Neurosciences (NIN-KNAW), Amsterdam, The Netherlands
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, Neuherberg, Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, Munich, Germany
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
| | - Tien Yin Wong
- Academic Medicine Research Institute, Singapore
- Retino Center, Singapore National Eye Centre, Singapore, Singapore
| | - Alex W. Hewitt
- Centre for Eye Research Australia, Ophthalmology, Department of Surgery, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
- Department of Ophthalmology, Menzies Institute of Medical Research, University of Tasmania, Hobart, Australia
- Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, Australia
| | - David A. Mackey
- Centre for Eye Research Australia, Ophthalmology, Department of Surgery, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
- Department of Ophthalmology, Menzies Institute of Medical Research, University of Tasmania, Hobart, Australia
- Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, Australia
| | - Claire L. Simpson
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, Memphis, Tenessee
| | - Norbert Pfeiffer
- Department of Ophthalmology, University Medical Center Mainz, Mainz, Germany
| | - Olavi Pärssinen
- Department of Ophthalmology, Central Hospital of Central Finland, Jyväskylä, Finland
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Paul N. Baird
- Centre for Eye Research Australia, Ophthalmology, Department of Surgery, University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne, Australia
| | - Veronique Vitart
- MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Joan E. Bailey-Wilson
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Terri L. Young
- Department of Ophthalmology and Visual Sciences, University of Wisconsin–Madison, Madison, Wisconsin, USA
| | - Seang-Mei Saw
- Saw Swee Hock School of Public Health, National University Health Systems, National University of Singapore, Singapore
- Myopia Research Group, Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Dwight Stambolian
- Department of Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Stuart MacGregor
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | | | | | - Christopher J. Hammond
- Section of Academic Ophthalmology, School of Life Course Sciences, King’s College London, London, UK
| | - Caroline C.W. Klaver
- Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Ophthalmology, Radboud University Medical Center, Nijmegen, The Netherlands
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38
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Arslan J, Baird PN. Changing vision: a review of pharmacogenetic studies for treatment response in age-related macular degeneration patients. Pharmacogenomics 2018; 19:435-461. [DOI: 10.2217/pgs-2017-0183] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Nonresponsiveness to age-related macular degeneration (AMD) treatments has become a growing concern in ophthalmology. Disparity among publications that have assessed pharmacogenetic (PGx) connections between AMD disease genes and treatments has delayed the implementation of PGx testing in AMD. We assessed all AMD PGx publications to identify the degree of agreement for publications within similar ethnic cohorts and worldwide, and the causes for differences in study outcomes. There are no accepted genotype–phenotype correlations, either within similar ethnic cohorts or worldwide. The diversity of measured outcomes, treatment protocols and statistical methods used may be causing this discrepancy. A universally accepted treatment protocol and the creation of agreed response group classification may bridge the gap between AMD PGx publications.
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Affiliation(s)
- Janan Arslan
- Department of Surgery (Ophthalmology), Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye & Ear Hospital, East Melbourne, Victoria, 3002, Australia
| | - Paul N Baird
- Department of Surgery (Ophthalmology), Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye & Ear Hospital, East Melbourne, Victoria, 3002, Australia
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39
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Affiliation(s)
- Mohamed Dirani
- Centre for Eye Research Australia University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne
- Vision Cooperative Research Centre, Sydney - Australia
| | - Maria Schache
- Centre for Eye Research Australia University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne
- Vision Cooperative Research Centre, Sydney - Australia
| | - Paul N. Baird
- Centre for Eye Research Australia University of Melbourne, Royal Victorian Eye and Ear Hospital, Melbourne
- Vision Cooperative Research Centre, Sydney - Australia
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40
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Shah RL, Li Q, Zhao W, Tedja MS, Tideman JWL, Khawaja AP, Fan Q, Yazar S, Williams KM, Verhoeven VJ, Xie J, Wang YX, Hess M, Nickels S, Lackner KJ, Pärssinen O, Wedenoja J, Biino G, Concas MP, Uitterlinden A, Rivadeneira F, Jaddoe VW, Hysi PG, Sim X, Tan N, Tham YC, Sensaki S, Hofman A, Vingerling JR, Jonas JB, Mitchell P, Hammond CJ, Höhn R, Baird PN, Wong TY, Cheng CY, Teo YY, Mackey DA, Williams C, Saw SM, Klaver CC, Guggenheim JA, Bailey-Wilson JE. A genome-wide association study of corneal astigmatism: The CREAM Consortium. Mol Vis 2018; 24:127-142. [PMID: 29422769 PMCID: PMC5800430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2017] [Accepted: 02/03/2018] [Indexed: 11/03/2022] Open
Abstract
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.
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Affiliation(s)
- Rupal L. Shah
- School of Optometry & Vision Sciences, Cardiff University, Cardiff, UK
| | - Qing Li
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, USA
| | - Wanting Zhao
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore,Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore
| | - Milly S. Tedja
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands,Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - J. Willem L. Tideman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands,Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Anthony P. Khawaja
- Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge School of Clinical Medicine, Cambridge, UK,NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK
| | - Qiao Fan
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore,Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore
| | - Seyhan Yazar
- Institute of Genetics and Molecular Medicine, Medical Research Council Human Genetics Unit, University of Edinburgh, Edinburgh, UK,Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, Australia
| | | | - Virginie J.M. Verhoeven
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands,Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Jing Xie
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia,Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, Australia
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University; Beijing, China
| | - Moritz Hess
- Institute for Medical Biostatistics, Epidemiology and Informatics, University Medical Center Mainz, Mainz, Germany
| | - Stefan Nickels
- Department of Ophthalmology, University Medical Center Mainz, Mainz, Germany
| | - Karl J. Lackner
- Institute for Clinical Chemistry and Laboratory Medicine, University Medical Center Mainz, Mainz, Germany
| | - Olavi Pärssinen
- Department of Ophthalmology, Central Hospital of Central Finland, Jyväskylä, Finland,Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, Finland,Department of Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Juho Wedenoja
- Department of Ophthalmology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland,Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Ginevra Biino
- Institute of Molecular Genetics, National Research Council of Italy, Pavia, Italy
| | - Maria Pina Concas
- Institute for Maternal and Child Health - IRCCS ‘Burlo Garofolo’, Trieste, Italy
| | - André Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands,Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands,Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Vincent W.V. Jaddoe
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands,Department of Pediatrics Erasmus Medical Center, Rotterdam, the Netherlands
| | - Pirro G. Hysi
- Department of Ophthalmology, King's College London, London, UK
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Nicholas Tan
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore,Department of Ophthalmology, National University Hospital, Singapore
| | - Yih-Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Sonoko Sensaki
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | | | - Jost B. Jonas
- Beijing Institute of Ophthalmology, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University; Beijing, China,Department of Ophthalmology, Medical Faculty Mannheim of the University Heidelberg, Mannheim, Germany
| | - Paul Mitchell
- Department of Ophthalmology, Western Sydney Local Health District, Sydney, Australia,Centre for Vision Research, Westmead Institute for Medical Research, University of Sydney, Sydney, Australia
| | | | - René Höhn
- Department of Ophthalmology, University Medical Center Mainz, Mainz, Germany,Department of Ophthalmology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Paul N. Baird
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia,Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, Australia
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore,Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore,Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Chinfsg-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore,Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore,Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Yik Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore,Department of Statistics and Applied Probability, National University of Singapore, Singapore,Division of Human Genetics, Genome Institute of Singapore, Singapore
| | - David A. Mackey
- Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, Australia
| | - Cathy Williams
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Seang-Mei Saw
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore,Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Caroline C.W. Klaver
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands,Department of Ophthalmology, Erasmus Medical Center, Rotterdam, The Netherlands,Department of Ophthalmology, Radboud University Medical Center, Nijmegen, the Netherlands
| | | | - Joan E. Bailey-Wilson
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, MD, USA
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41
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Persad PJ, Heid IM, Weeks DE, Baird PN, de Jong EK, Haines JL, Pericak-Vance MA, Scott WK. Joint Analysis of Nuclear and Mitochondrial Variants in Age-Related Macular Degeneration Identifies Novel Loci TRPM1 and ABHD2/RLBP1. Invest Ophthalmol Vis Sci 2017; 58:4027-4038. [PMID: 28813576 PMCID: PMC5559178 DOI: 10.1167/iovs.17-21734] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
Purpose Presently, 52 independent nuclear single nucleotide polymorphisms (nSNPs) have been associated with age-related macular degeneration (AMD) but their effects do not explain all its variance. Genetic interactions between the nuclear and mitochondrial (mt) genome may unearth additional genetic loci previously unassociated with AMD risk. Methods Joint effects of nSNPs and selected mtSNPs were analyzed by two degree of freedom (2df) joint tests of association in the International AMD Genomics Consortium (IAMDGC) dataset (17,832 controls and 16,144 advanced AMD cases of European ancestry). Subjects were genotyped on the Illumina HumanCoreExome array. After imputation using MINIMAC and the 1000 Genomes Project Phase I reference panel, pairwise linkage disequilibrium pruning, and quality control, 3.9 million nSNPs were analyzed for interaction with mtSNPs chosen based on association in this dataset or publications: A4917G, T5004C, G12771A, and C16069T. Results Novel locus TRPM1 was identified with genome-wide significant joint effects (P < 5.0 × 10−8) of two intronic TRPM1 nSNPs and AMD-associated nonsynonymous MT-ND2 mtSNP A4917G. Stratified analysis by mt allele identified an association only in 4917A (major allele) carriers (P = 4.4 × 10−9, odds ratio [OR] = 0.90, 95% confidence interval [CI] = 0.87–0.93). Intronic and intergenic ABHD2/RLBP1 nSNPs demonstrated genome-wide significant joint effects (2df joint test P values from 1.8 × 10−8 to 4.9 × 10−8) and nominally statistically significant interaction effects with MT-ND5 synonymous mtSNP G12771A. Although a positive association was detected in both strata, the association was stronger in 12771A subjects (P = 0.0020, OR = 2.17, 95% CI = 1.34–3.60). Conclusions These results show that joint tests of main effects and gene–gene interaction reveal associations at some novel loci that were missed when considering main effects alone.
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Affiliation(s)
- Patrice J Persad
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida, United States
| | - Iris M Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Daniel E Weeks
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States.,Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States
| | - Paul N Baird
- Centre for Eye Research Australia, Department of Surgery (Ophthalmology) University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
| | - Eiko K de Jong
- Department of Ophthalmology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jonathan L Haines
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, United States
| | - Margaret A Pericak-Vance
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida, United States
| | - William K Scott
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida, United States
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42
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Vessey KA, Gu BJ, Jobling AI, Phipps JA, Greferath U, Tran MX, Dixon MA, Baird PN, Guymer RH, Wiley JS, Fletcher EL. Loss of Function of P2X7 Receptor Scavenger Activity in Aging Mice: A Novel Model for Investigating the Early Pathogenesis of Age-Related Macular Degeneration. Am J Pathol 2017. [PMID: 28628761 DOI: 10.1016/j.ajpath.2017.04.016] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Age-related macular degeneration (AMD) is a leading cause of irreversible, severe vision loss in Western countries. Recently, we identified a novel pathway involving P2X7 receptor scavenger function expressed on ocular immune cells as a risk factor for advanced AMD. In this study, we investigate the effect of loss of P2X7 receptor function on retinal structure and function during aging. P2X7-null and wild-type C57bl6J mice were investigated at 4, 12, and 18 months of age for macrophage phagocytosis activity, ocular histological changes, and retinal function. Phagocytosis activity of blood-borne macrophages decreased with age at 18 months in the wild-type mouse. Lack of P2X7 receptor function reduced phagocytosis at all ages compared to wild-type mice. At 12 months of age, P2X7-null mice had thickening of Bruchs membrane and retinal pigment epithelium dysfunction. By 18 months of age, P2X7-null mice displayed phenotypic characteristics consistent with early AMD, including Bruchs membrane thickening, retinal pigment epithelium cell loss, retinal functional deficits, and signs of subretinal inflammation. Our present study shows that loss of function of the P2X7 receptor in mice induces retinal changes representing characteristics of early AMD, providing a valuable model for investigating the role of scavenger receptor function and the immune system in the development of this age-related disease.
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Affiliation(s)
- Kirstan A Vessey
- Department of Anatomy and Neuroscience, The University of Melbourne, Melbourne, Victoria, Australia
| | - Ben J Gu
- Florey Institute of Neuroscience, Melbourne, Victoria, Australia
| | - Andrew I Jobling
- Department of Anatomy and Neuroscience, The University of Melbourne, Melbourne, Victoria, Australia
| | - Joanna A Phipps
- Department of Anatomy and Neuroscience, The University of Melbourne, Melbourne, Victoria, Australia
| | - Ursula Greferath
- Department of Anatomy and Neuroscience, The University of Melbourne, Melbourne, Victoria, Australia
| | - Mai X Tran
- Department of Anatomy and Neuroscience, The University of Melbourne, Melbourne, Victoria, Australia
| | - Michael A Dixon
- Department of Anatomy and Neuroscience, The University of Melbourne, Melbourne, Victoria, Australia
| | - Paul N Baird
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia; Division of Ophthalmology, Department of Surgery, The University of Melbourne, Melbourne, Victoria, Australia
| | - Robyn H Guymer
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Victoria, Australia; Division of Ophthalmology, Department of Surgery, The University of Melbourne, Melbourne, Victoria, Australia
| | - James S Wiley
- Florey Institute of Neuroscience, Melbourne, Victoria, Australia
| | - Erica L Fletcher
- Department of Anatomy and Neuroscience, The University of Melbourne, Melbourne, Victoria, Australia.
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Riaz M, Baird PN. Recent advances and future directions for the pharmacogenetic basis of anti-VEGF treatment response in neovascular age-related macular degeneration. Neural Regen Res 2017; 12:584-585. [PMID: 28553337 PMCID: PMC5436355 DOI: 10.4103/1673-5374.205094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Affiliation(s)
- Moeen Riaz
- Centre for Eye Research Australia, Department of Surgery (Ophthalmology) University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
| | - Paul N Baird
- Centre for Eye Research Australia, Department of Surgery (Ophthalmology) University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
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Abstract
The genomic revolution has revealed the complexity of multifactorial diseases, making the development of effective diagnostics extremely challenging. In turn, the prospect of precision medicine as applied through targeted therapeutic treatments continues to remain largely elusive. Age-related macular degeneration (AMD) as a complex disease falls under this category, despite it being one of the most well characterized multifactorial diseases. This reflects both the extent of identified genetic components and known environmental risk factors. Additional considerations in dissecting out the roles played by genetic and non-genetic risk factors arise through the rapid increase in prevalence of AMD with age and the varying time periods over which disease progression can occur, complicating efforts to discriminate between "progressors" and non-"progressors." As a consequence, extensive research into the aetiology of AMD is yet to realize a clinically acceptable predictive test. This review covers the current climate of risk models in late AMD but will focus mainly on genetic risk factors as well as the types of models that have currently been employed in the AMD modelling literature.
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Affiliation(s)
- Michael Zhang
- a Centre for Eye Research Australia, University of Melbourne , East Melbourne , Victoria , Australia
| | - Paul N Baird
- a Centre for Eye Research Australia, University of Melbourne , East Melbourne , Victoria , Australia
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45
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Riaz M, Lorés-Motta L, Richardson AJ, Lu Y, Montgomery G, Omar A, Koenekoop RK, Chen J, Muether P, Altay L, Schick T, Fauser S, Smailhodzic D, van Asten F, de Jong EK, Hoyng CB, Burdon KP, MacGregor S, Guymer RH, den Hollander AI, Baird PN. GWAS study using DNA pooling strategy identifies association of variant rs4910623 in OR52B4 gene with anti-VEGF treatment response in age-related macular degeneration. Sci Rep 2016; 6:37924. [PMID: 27892514 PMCID: PMC5124940 DOI: 10.1038/srep37924] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Accepted: 11/02/2016] [Indexed: 12/20/2022] Open
Abstract
Pooled DNA based GWAS to determine genetic association of SNPs with visual acuity (VA) outcome in anti-vascular endothelial growth factor (anti-VEGF) treated neovascular age-related macular degeneration (nAMD) patients. We performed pooled DNA based GWAS on 285 anti-VEGF treated nAMD patients using high density Illumina 4.3 M array. Primary outcome was change in VA in Early Treatment Diabetic Retinopathy Study (ETDRS) letters after 6 months of anti-VEGF treatment (patients who lost ≥5 ETDRS letters classified as non-responders and all remaining classified as responders). GWAS analysis identified 44 SNPs of interest: 37 with strong evidence of association (p < 9 × 10−8), 2 in drug resistance genes (p < 5 × 10−6) and 5 nonsynonymous changes (p < 1 × 10−4). In the validation phase, individual genotyping of 44 variants showed three SNPs (rs4910623 p = 5.6 × 10−5, rs323085 p = 6.5 × 10−4 and rs10198937 p = 1.30 × 10−3) remained associated with VA response at 6 months. SNP rs4910623 also associated with treatment response at 3 months (p = 1.5 × 10−3). Replication of these three SNPs in 376 patients revealed association of rs4910623 with poor VA response after 3 and 6 months of treatment (p = 2.4 × 10−3 and p = 3.5 × 10−2, respectively). Meta-analysis of both cohorts (673 samples) confirmed association of rs4910623 with poor VA response after 3 months (p = 1.2 × 10−5) and 6 months (p = 9.3 × 10−6) of treatment in nAMD patients.
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Affiliation(s)
- Moeen Riaz
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, Australia
| | - Laura Lorés-Motta
- Department of Ophthalmology, Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, the Netherlands
| | - Andrea J Richardson
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, Australia
| | - Yi Lu
- Statistical Genetics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Grant Montgomery
- Molecular Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Amer Omar
- Montreal Retina Institute, Westmount, Canada
| | - Robert K Koenekoop
- Paediatric Surgery, Human Genetics, and Ophthalmology, McGill University Health Centre, Montreal, Quebec, Canada
| | - John Chen
- Department of Ophthalmology, McGill University Health Centre, Montreal, Quebec, Canada
| | - Philipp Muether
- Department of Ophthalmology, University Hospital of Cologne, Cologne, Germany
| | - Lebriz Altay
- Department of Ophthalmology, University Hospital of Cologne, Cologne, Germany
| | - Tina Schick
- Department of Ophthalmology, University Hospital of Cologne, Cologne, Germany
| | - Sascha Fauser
- Department of Ophthalmology, University Hospital of Cologne, Cologne, Germany
| | - Dzenita Smailhodzic
- Department of Ophthalmology, Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, the Netherlands
| | - Freekje van Asten
- Department of Ophthalmology, Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, the Netherlands
| | - Eiko K de Jong
- Department of Ophthalmology, Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, the Netherlands
| | - Carel B Hoyng
- Department of Ophthalmology, Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, the Netherlands
| | - Kathryn P Burdon
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS and Dept: Ophthalmology, Flinders University, Adelaide, SA, Australia
| | - Stuart MacGregor
- Statistical Genetics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Robyn H Guymer
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, Australia
| | - Anneke I den Hollander
- Department of Ophthalmology, Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, the Netherlands.,Department of Human Genetics, Radboud university medical center, Nijmegen, the Netherlands
| | - Paul N Baird
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, Australia
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46
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Khong JJ, Burdon KP, Lu Y, Laurie K, Leonardos L, Baird PN, Sahebjada S, Walsh JP, Gajdatsy A, Ebeling PR, Hamblin PS, Wong R, Forehan SP, Fourlanos S, Roberts AP, Doogue M, Selva D, Montgomery GW, Macgregor S, Craig JE. Pooled genome wide association detects association upstream of FCRL3 with Graves' disease. BMC Genomics 2016; 17:939. [PMID: 27863461 PMCID: PMC5116198 DOI: 10.1186/s12864-016-3276-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2016] [Accepted: 11/09/2016] [Indexed: 12/29/2022] Open
Abstract
Background Graves’ disease is an autoimmune thyroid disease of complex inheritance. Multiple genetic susceptibility loci are thought to be involved in Graves’ disease and it is therefore likely that these can be identified by genome wide association studies. This study aimed to determine if a genome wide association study, using a pooling methodology, could detect genomic loci associated with Graves’ disease. Results Nineteen of the top ranking single nucleotide polymorphisms including HLA-DQA1 and C6orf10, were clustered within the Major Histo-compatibility Complex region on chromosome 6p21, with rs1613056 reaching genome wide significance (p = 5 × 10−8). Technical validation of top ranking non-Major Histo-compatablity complex single nucleotide polymorphisms with individual genotyping in the discovery cohort revealed four single nucleotide polymorphisms with p ≤ 10−4. Rs17676303 on chromosome 1q23.1, located upstream of FCRL3, showed evidence of association with Graves’ disease across the discovery, replication and combined cohorts. A second single nucleotide polymorphism rs9644119 downstream of DPYSL2 showed some evidence of association supported by finding in the replication cohort that warrants further study. Conclusions Pooled genome wide association study identified a genetic variant upstream of FCRL3 as a susceptibility locus for Graves’ disease in addition to those identified in the Major Histo-compatibility Complex. A second locus downstream of DPYSL2 is potentially a novel genetic variant in Graves’ disease that requires further confirmation. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3276-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jwu Jin Khong
- Melbourne Medical School Western Campus, Department of Medicine, University of Melbourne, Sunshine Hospital, 176 Furlong Road, St Albans, VIC, 3021, Australia. .,Orbital, Plastics and Lacrimal Unit, The Royal Victorian Eye and Ear Hospital, Heidelberg, VIC, Australia. .,Department of Ophthalmology and Department of Surgery, University of Melbourne, Austin Health, Heidelberg, VIC, Australia.
| | - Kathryn P Burdon
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | - Yi Lu
- Statistical Genetics, Queensland Institute of Medical Research (QIMR) Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Kate Laurie
- Department of Ophthalmology, Flinders University of South Australia, Bedford Park, South Australia, Australia
| | - Lefta Leonardos
- Department of Ophthalmology, Flinders University of South Australia, Bedford Park, South Australia, Australia
| | - Paul N Baird
- Department of Surgery, Centre for Eye Research Australia and Ophthalmology, University of Melbourne, East Melbourne, VIC, Australia
| | - Srujana Sahebjada
- Department of Surgery, Centre for Eye Research Australia and Ophthalmology, University of Melbourne, East Melbourne, VIC, Australia
| | - John P Walsh
- Department of Endocrinology and Diabetes, Sir Charles Gairdner Hospital, Nedlands, WA, Australia.,School of Medicine and Pharmacology, The University of Western Australia, Crawley, WA, Australia
| | - Adam Gajdatsy
- Centre for Ophthalmology and Visual Sciences, University of Western Australia, Western Australia, Australia
| | - Peter R Ebeling
- Department of Medicine, School of Clinical Sciences, Monash University, Clayton, VIC, Australia
| | - Peter Shane Hamblin
- Melbourne Medical School Western Campus, Department of Medicine, University of Melbourne, Sunshine Hospital, 176 Furlong Road, St Albans, VIC, 3021, Australia.,Department of Endocrinology and Diabetes, Western Health, St Albans, VIC, Australia
| | - Rosemary Wong
- Department of Endocrinology and Diabetes, Western Health, St Albans, VIC, Australia
| | - Simon P Forehan
- Department of Diabetes and Endocrinology, Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Spiros Fourlanos
- Department of Diabetes and Endocrinology, Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Anthony P Roberts
- Department of Endocrinology, The Royal Adelaide Hospital, Adelaide, South Australia, Australia
| | - Matthew Doogue
- Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Dinesh Selva
- South Australian Institute of Ophthalmology, University of Adelaide, South Australia, Australia
| | - Grant W Montgomery
- Molecular Epidemiology, Queensland Institute of Medical Research (QIMR) Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Stuart Macgregor
- Statistical Genetics, Queensland Institute of Medical Research (QIMR) Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Jamie E Craig
- Department of Ophthalmology, Flinders University of South Australia, Bedford Park, South Australia, Australia
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47
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Fan Q, Verhoeven VJM, Wojciechowski R, Barathi VA, Hysi PG, Guggenheim JA, Höhn R, Vitart V, Khawaja AP, Yamashiro K, Hosseini SM, Lehtimäki T, Lu Y, Haller T, Xie J, Delcourt C, Pirastu M, Wedenoja J, Gharahkhani P, Venturini C, Miyake M, Hewitt AW, Guo X, Mazur J, Huffman JE, Williams KM, Polasek O, Campbell H, Rudan I, Vatavuk Z, Wilson JF, Joshi PK, McMahon G, St Pourcain B, Evans DM, Simpson CL, Schwantes-An TH, Igo RP, Mirshahi A, Cougnard-Gregoire A, Bellenguez C, Blettner M, Raitakari O, Kähönen M, Seppala I, Zeller T, Meitinger T, Ried JS, Gieger C, Portas L, van Leeuwen EM, Amin N, Uitterlinden AG, Rivadeneira F, Hofman A, Vingerling JR, Wang YX, Wang X, Tai-Hui Boh E, Ikram MK, Sabanayagam C, Gupta P, Tan V, Zhou L, Ho CEH, Lim W, Beuerman RW, Siantar R, Tai ES, Vithana E, Mihailov E, Khor CC, Hayward C, Luben RN, Foster PJ, Klein BEK, Klein R, Wong HS, Mitchell P, Metspalu A, Aung T, Young TL, He M, Pärssinen O, van Duijn CM, Jin Wang J, Williams C, Jonas JB, Teo YY, Mackey DA, Oexle K, Yoshimura N, Paterson AD, Pfeiffer N, Wong TY, Baird PN, Stambolian D, Wilson JEB, Cheng CY, Hammond CJ, Klaver CCW, Saw SM, Rahi JS, Korobelnik JF, Kemp JP, Timpson NJ, Smith GD, Craig JE, Burdon KP, Fogarty RD, Iyengar SK, Chew E, Janmahasatian S, Martin NG, MacGregor S, Xu L, Schache M, Nangia V, Panda-Jonas S, Wright AF, Fondran JR, Lass JH, Feng S, Zhao JH, Khaw KT, Wareham NJ, Rantanen T, Kaprio J, Pang CP, Chen LJ, Tam PO, Jhanji V, Young AL, Döring A, Raffel LJ, Cotch MF, Li X, Yip SP, Yap MK, Biino G, Vaccargiu S, Fossarello M, Fleck B, Yazar S, Tideman JWL, Tedja M, Deangelis MM, Morrison M, Farrer L, Zhou X, Chen W, Mizuki N, Meguro A, Mäkelä KM. Meta-analysis of gene-environment-wide association scans accounting for education level identifies additional loci for refractive error. Nat Commun 2016; 7:11008. [PMID: 27020472 PMCID: PMC4820539 DOI: 10.1038/ncomms11008] [Citation(s) in RCA: 85] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2015] [Accepted: 02/10/2016] [Indexed: 02/07/2023] Open
Abstract
Myopia is the most common human eye disorder and it results from complex genetic and environmental causes. The rapidly increasing prevalence of myopia poses a major public health challenge. Here, the CREAM consortium performs a joint meta-analysis to test single-nucleotide polymorphism (SNP) main effects and SNP × education interaction effects on refractive error in 40,036 adults from 25 studies of European ancestry and 10,315 adults from 9 studies of Asian ancestry. In European ancestry individuals, we identify six novel loci (FAM150B-ACP1, LINC00340, FBN1, DIS3L-MAP2K1, ARID2-SNAT1 and SLC14A2) associated with refractive error. In Asian populations, three genome-wide significant loci AREG, GABRR1 and PDE10A also exhibit strong interactions with education (P<8.5 × 10(-5)), whereas the interactions are less evident in Europeans. The discovery of these loci represents an important advance in understanding how gene and environment interactions contribute to the heterogeneity of myopia.
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Affiliation(s)
- Qiao Fan
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
- Duke-NUS Medical School, Singapore 169857, Singapore
| | - Virginie J. M. Verhoeven
- Department of Ophthalmology, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands
| | - Robert Wojciechowski
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland 21224, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 20205, USA
| | - Veluchamy A. Barathi
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
- Duke-NUS Medical School, Singapore 169857, Singapore
- Department of Ophthalmology, National University Health Systems, National University of Singapore Singapore 119228, Singapore
| | - Pirro G. Hysi
- Department of Twin Research and Genetic Epidemiology, King's College London School of Medicine, London SE1 7EH, UK
| | - Jeremy A. Guggenheim
- School of Optometry and Vision Sciences, Cardiff University, Cardiff CF24 4HQ, UK
| | - René Höhn
- Department of Ophthalmology, University Medical Center Mainz, 55131 Mainz, Germany
- Department of Ophthalmology, Inselspital, University Hospital Bern, CH-3010 Bern, Switzerland
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, Scotland
| | - Anthony P. Khawaja
- Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge School of Clinical Medicine, Cambridge CB2 0SR, UK
| | - Kenji Yamashiro
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto 6068507, Japan
| | - S Mohsen Hosseini
- Program in Genetics and Genome Biology, The Hospital for Sick Children and Institute for Medical Sciences, University of Toronto, Toronto Ontario, Canada M5G 1X8
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine, University of Tampere, Tampere 33520, Finland
| | - Yi Lu
- Statistical Genetics Laboratory, QIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland 4029, Australia
| | - Toomas Haller
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Jing Xie
- Centre for Eye Research Australia (CERA), Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Victoria 3002, Australia
| | - Cécile Delcourt
- Université de Bordeaux, ISPED (Institut de Santé Publique d'Épidémiologie et de Développement), Bordeaux 33000, France
- INSERM, U1219-Bordeaux Population Health Research Center, Bordeaux 33000, France
| | - Mario Pirastu
- Institute of Population Genetics, National Research Council, Sassari 07100, Italy
| | - Juho Wedenoja
- Department of Public Health, University of Helsinki, Helsinki 00014, Finland
- Department of Ophthalmology, University of Helsinki and Helsinki University Hospital, Helsinki 00014, Finland
| | - Puya Gharahkhani
- Statistical Genetics Laboratory, QIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland 4029, Australia
| | - Cristina Venturini
- Department of Twin Research and Genetic Epidemiology, King's College London School of Medicine, London SE1 7EH, UK
- UCL Institute of Ophthalmology, London SE1 7EH, UK
| | - Masahiro Miyake
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto 6068507, Japan
| | - Alex W. Hewitt
- Centre for Eye Research Australia (CERA), Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Victoria 3002, Australia
- Menzies Research Institute Tasmania, University of Tasmania, Hobart, Tasmania 7000, Australia
| | - Xiaobo Guo
- Department of Statistical Science, School of Mathematics and Computational Science, Sun Yat-Sen University, Guangzhou 510275, China
| | - Johanna Mazur
- Institute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center Mainz, 55131 Mainz, Germany
| | - Jenifer E. Huffman
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, Scotland
| | - Katie M. Williams
- Department of Twin Research and Genetic Epidemiology, King's College London School of Medicine, London SE1 7EH, UK
- Department of Ophthalmology, King's College London, London SE1 7EH, UK
| | - Ozren Polasek
- Faculty of Medicine, University of Split, Split 21000, Croatia
| | - Harry Campbell
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, Scotland
| | - Igor Rudan
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, Scotland
| | - Zoran Vatavuk
- Department of Ophthalmology, Sisters of Mercy University Hospital, Zagreb 10000, Croatia
| | - James F. Wilson
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, Scotland
| | - Peter K. Joshi
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, Scotland
| | - George McMahon
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol BS8 2BN, UK
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
| | - Beate St Pourcain
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol BS8 2BN, UK
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
- Max Planck Institute for Psycholinguistics, Wundtlaan 1, 6525 XD Nijmegen, The Netherlands
| | - David M. Evans
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol BS8 2BN, UK
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
- University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland 4102, Australia
| | - Claire L. Simpson
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland 21224, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee 38163, USA
| | - Tae-Hwi Schwantes-An
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland 21224, USA
| | - Robert P. Igo
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio 44106, USA
| | - Alireza Mirshahi
- Department of Ophthalmology, University Medical Center Mainz, 55131 Mainz, Germany
- Dardenne Eye Hospital, Bonn-Bad Godesberg, 53177 Bonn, Germany
| | - Audrey Cougnard-Gregoire
- Université de Bordeaux, ISPED (Institut de Santé Publique d'Épidémiologie et de Développement), Bordeaux 33000, France
- INSERM, U1219-Bordeaux Population Health Research Center, Bordeaux 33000, France
| | - Céline Bellenguez
- Inserm, U1167, Lille 59000, France
- Univ. Lille, U1167, Lille 59000, France
- Université Lille 2, Lille 59000, France
| | - Maria Blettner
- Institute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center Mainz, 55131 Mainz, Germany
| | - Olli Raitakari
- Research Centre of Applied and Preventive Medicine, University of Turku, Turku 20520, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20520, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and School of Medicine, University of Tampere, Tampere 33520, Finland
| | - Ilkka Seppala
- Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine, University of Tampere, Tampere 33520, Finland
| | - Tanja Zeller
- Clinic for General and Interventional Cardiology, University Heart Center Hamburg, 20246 Hamburg, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, 81675 Munich, Germany
| | | | - Janina S. Ried
- Institute of Genetic Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Laura Portas
- Institute of Population Genetics, National Research Council, Sassari 07100, Italy
| | | | - Najaf Amin
- Department of Epidemiology, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, 2518 AD Hague, The Netherlands
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, 2518 AD Hague, The Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Ageing, Netherlands Genomics Initiative, 2518 AD Hague, The Netherlands
| | | | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing 100044, China
| | - Xu Wang
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health Systems, Singapore 117549, Singapore
| | - Eileen Tai-Hui Boh
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health Systems, Singapore 117549, Singapore
| | - M. Kamran Ikram
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
- Duke-NUS Medical School, Singapore 169857, Singapore
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
- Duke-NUS Medical School, Singapore 169857, Singapore
| | - Preeti Gupta
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
| | - Vincent Tan
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
| | - Lei Zhou
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
| | - Candice E. H. Ho
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
| | - Wan'e Lim
- Department of Ophthalmology, National University Health Systems, National University of Singapore Singapore 119228, Singapore
| | - Roger W. Beuerman
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
- Duke-NUS Medical School, Singapore 169857, Singapore
- Department of Ophthalmology, National University Health Systems, National University of Singapore Singapore 119228, Singapore
| | - Rosalynn Siantar
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
- National Healthcare Group Eye Institute, Tan Tock Seng Hospital, Singapore 308433, Singapore
| | - E-Shyong Tai
- Duke-NUS Medical School, Singapore 169857, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health Systems, Singapore 117549, Singapore
- Department of Medicine, National University of Singapore, Singapore 119228, Singapore
| | - Eranga Vithana
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
- Duke-NUS Medical School, Singapore 169857, Singapore
- Department of Ophthalmology, National University Health Systems, National University of Singapore Singapore 119228, Singapore
| | - Evelin Mihailov
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Chiea-Chuen Khor
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health Systems, Singapore 117549, Singapore
- Division of Human Genetics, Genome Institute of Singapore, Singapore 138672, Singapore
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, Scotland
| | - Robert N. Luben
- Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge School of Clinical Medicine, Cambridge CB2 0SR, UK
| | - Paul J. Foster
- Division of Genetics and Epidemiology, UCL Institute of Ophthalmology, London EC1V 9EL, UK
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL Institute of Ophthalmology, London EC1V 2PD, UK
| | - Barbara E. K. Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin 53726, USA
| | - Ronald Klein
- Department of Ophthalmology and Visual Sciences, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin 53726, USA
| | - Hoi-Suen Wong
- Program in Genetics and Genome Biology, The Hospital for Sick Children and Institute for Medical Sciences, University of Toronto, Toronto Ontario, Canada M5G 1X8
| | - Paul Mitchell
- Department of Ophthalmology, Centre for Vision Research, Westmead Institute for Medical Research, University of Sydney, Sydney, New South Wales 2145, Australia
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Tin Aung
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
- Department of Ophthalmology, National University Health Systems, National University of Singapore Singapore 119228, Singapore
| | - Terri L. Young
- Department of Ophthalmology and Visual Sciences, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin 53705, USA
| | - Mingguang He
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangzhou 510060, China
| | - Olavi Pärssinen
- Department of Ophthalmology, Central Hospital of Central Finland, Jyväskylä 40620, Finland
- Gerontology Research Center and Department of Health Sciences, University of Jyväskylä, Jyväskylä 40014, Finland
| | - Cornelia M. van Duijn
- Department of Epidemiology, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands
| | - Jie Jin Wang
- Department of Ophthalmology, Centre for Vision Research, Westmead Institute for Medical Research, University of Sydney, Sydney, New South Wales 2145, Australia
| | - Cathy Williams
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK
| | - Jost B. Jonas
- Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing 100044, China
- Medical Faculty Mannheim, Department of Ophthalmology, Ruprecht-Karls-University Heidelberg, 69115 Mannheim, Germany
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health Systems, Singapore 117549, Singapore
- Division of Human Genetics, Genome Institute of Singapore, Singapore 138672, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore 117546, Singapore
| | - David A. Mackey
- Menzies Research Institute Tasmania, University of Tasmania, Hobart, Tasmania 7000, Australia
- Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, Western Australia 6009, Australia
| | - Konrad Oexle
- Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, 81675 Munich, Germany
| | - Nagahisa Yoshimura
- Department of Ophthalmology and Visual Sciences, Kyoto University Graduate School of Medicine, Kyoto 6068507, Japan
| | - Andrew D. Paterson
- Program in Genetics and Genome Biology, The Hospital for Sick Children and Institute for Medical Sciences, University of Toronto, Toronto Ontario, Canada M5G 1X8
| | - Norbert Pfeiffer
- Department of Ophthalmology, University Medical Center Mainz, 55131 Mainz, Germany
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
- Duke-NUS Medical School, Singapore 169857, Singapore
- Department of Ophthalmology, National University Health Systems, National University of Singapore Singapore 119228, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health Systems, Singapore 117549, Singapore
| | - Paul N. Baird
- Centre for Eye Research Australia (CERA), Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Victoria 3002, Australia
| | - Dwight Stambolian
- Department of Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Joan E. Bailey Wilson
- Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland 21224, USA
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
- Duke-NUS Medical School, Singapore 169857, Singapore
- Department of Ophthalmology, National University Health Systems, National University of Singapore Singapore 119228, Singapore
| | - Christopher J. Hammond
- Department of Twin Research and Genetic Epidemiology, King's College London School of Medicine, London SE1 7EH, UK
- Department of Ophthalmology, King's College London, London SE1 7EH, UK
| | - Caroline C. W. Klaver
- Department of Ophthalmology, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands
| | - Seang-Mei Saw
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore 169856, Singapore
- Duke-NUS Medical School, Singapore 169857, Singapore
- Department of Ophthalmology, National University Health Systems, National University of Singapore Singapore 119228, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health Systems, Singapore 117549, Singapore
| | - Jugnoo S. Rahi
- Medical Research Council Centre of Epidemiology for Child Health, Institute of Child Health, University College London, London WC1E 6BT, UK
- Institute of Ophthalmology, Moorfields Eye Hospital, London EC1V 2PD, UK
- Ulverscroft Vision Research Group, University College London, London WC1E 6BT, UK
| | - Jean-François Korobelnik
- Université de Bordeaux, 33400 Talence, France
- INSERM (Institut National de la Santé Et de la Recherche Médicale), ISPED (Institut de Santé Publique d'épidémiologie et de Développement), Centre INSERM U897-Epidemiologie-Biostatistique, 33076 Bordeaux, France
| | - John P. Kemp
- MRC Integrative Epidemiology Unit (IEU), The University of Bristol, Bristol BS8 2BN, UK
| | - Nicholas J. Timpson
- MRC Integrative Epidemiology Unit (IEU), The University of Bristol, Bristol BS8 2BN, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), The University of Bristol, Bristol BS8 2BN, UK
| | - Jamie E. Craig
- Department of Ophthalmology, Flinders University, Adelaide, South Australia 5001, Australia
| | - Kathryn P. Burdon
- Department of Ophthalmology, Flinders University, Adelaide, South Australia 5001, Australia
| | - Rhys D. Fogarty
- Department of Ophthalmology, Flinders University, Adelaide, South Australia 5001, Australia
| | - Sudha K. Iyengar
- Department of Epidemiology and Biostatistics, CaseWestern Reserve University, Cleveland, Ohio 44106, USA
- Department of Ophthalmology and Visual Sciences, Case Western Reserve University and University Hospitals Eye Institute, Cleveland, Ohio 44106, USA
- Department of Genetics, Case Western Reserve University, Cleveland, Ohio 44106, USA
| | - Emily Chew
- National Eye Institute, National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Sarayut Janmahasatian
- Department of Epidemiology and Biostatistics, CaseWestern Reserve University, Cleveland, Ohio 44106, USA
| | - Nicholas G. Martin
- Genetic Epidemiology Laboratory, QIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland 4029, Australia
| | - Stuart MacGregor
- Statistical Genetics Laboratory, QIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland 4029, Australia
| | - Liang Xu
- Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing 100044, China
| | - Maria Schache
- Centre for Eye Research Australia (CERA), Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Victoria 3002, Australia
| | - Vinay Nangia
- Suraj Eye Institute, Nagpur, Maharashtra 440001, India
| | | | - Alan F. Wright
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, Scotland
| | - Jeremy R. Fondran
- Department of Epidemiology and Biostatistics, CaseWestern Reserve University, Cleveland, Ohio 44106, USA
| | - Jonathan H. Lass
- Department of Epidemiology and Biostatistics, CaseWestern Reserve University, Cleveland, Ohio 44106, USA
- Department of Ophthalmology and Visual Sciences, Case Western Reserve University and University Hospitals Eye Institute, Cleveland, Ohio 44106, USA
| | - Sheng Feng
- Department of Pediatric Ophthalmology, Duke Eye Center For Human Genetics, Durham, North Carolina 27710, USA
| | - Jing Hua Zhao
- MRC Epidemiology Unit, Institute of Metabolic Sciences, University of Cambridge, Cambridge CB2 1TN, UK
| | - Kay-Tee Khaw
- Department of Public Health and Primary Care, Institute of Public Health, University of Cambridge School of Clinical Medicine, Cambridge CB2 0SR, UK
| | - Nick J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Taina Rantanen
- Gerontology Research Center, University of Jyväskylä, Jyväskylä Finland
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki 00014, Finland
- Institute for Molecular Medicine, University of Helsinki, Helsinki 00014, Finland
- Department of Mental Health and Alcohol Abuse Services, National Institute for Health and Welfare, Helsinki 00271, Finland
| | - Chi Pui Pang
- Department of Ophthalmology and Visual Sciences, Hong Kong Eye Hospital, The Chinese University of Hong Kong, Kowloon, Hong Kong
| | - Li Jia Chen
- Department of Ophthalmology and Visual Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Pancy O. Tam
- Department of Ophthalmology and Visual Sciences, Hong Kong Eye Hospital, The Chinese University of Hong Kong, Kowloon, Hong Kong
| | - Vishal Jhanji
- Department of Ophthalmology and Visual Sciences, Hong Kong Eye Hospital, The Chinese University of Hong Kong, Kowloon, Hong Kong
- Department of Ophthalmology and Visual Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Alvin L. Young
- Department of Ophthalmology and Visual Sciences, Hong Kong Eye Hospital, The Chinese University of Hong Kong, Kowloon, Hong Kong
- Department of Ophthalmology and Visual Sciences, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Angela Döring
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Leslie J. Raffel
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA
| | - Mary-Frances Cotch
- Division of Epidemiology and Clinical Applications, National Eye Institute, Bethesda, Maryland 20892, USA
| | - Xiaohui Li
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Los Angeles, California 90502, USA
| | - Shea Ping Yip
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, Hong Kong
| | - Maurice K.H. Yap
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, Hong Kong
| | - Ginevra Biino
- Institute of Molecular Genetics, National Research Council, Pavia 27100, Italy
| | - Simona Vaccargiu
- Institute of Population Genetics, National Research Council, Sassari 07100, Italy
| | - Maurizio Fossarello
- Institute of Population Genetics, National Research Council, Sassari 07100, Italy
| | - Brian Fleck
- Princess Alexandra Eye Pavilion, Edinburgh EH3 9HA, UK
| | - Seyhan Yazar
- Centre for Eye Research Australia (CERA), Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Victoria 3002, Australia
- Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, Western Australia 6009, Australia
| | - Jan Willem L. Tideman
- Department of Ophthalmology, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands
| | - Milly Tedja
- Department of Ophthalmology, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus Medical Center, 3000 CA Rotterdam, The Netherlands
| | - Margaret M. Deangelis
- Department of Ophthalmology and Visual Sciences, Moran Eye Center, University of Utah, Salt Lake City, Utah 84132, USA
| | - Margaux Morrison
- Department of Ophthalmology and Visual Sciences, John Moran Eye Center, University of Utah, Salt Lake City, Utah 84132, USA
| | - Lindsay Farrer
- Departments of Medicine (Biomedical Genetics), Ophthalmology, Neurology, Epidemiology and Biostatistics, Boston University Schools of Medicine and Public Health, Boston, Massachusetts 02118, USA
| | - Xiangtian Zhou
- School of ophthalmology and optometry, Wenzhou Medical University, Wenzhou 325035, China
| | - Wei Chen
- School of ophthalmology and optometry, Wenzhou Medical University, Wenzhou 325035, China
| | - Nobuhisa Mizuki
- Department of Ophthalmology, Yokohama City University School of Medicine, Yokohama, Kanagawa 236-0027, Japan
| | - Akira Meguro
- Department of Ophthalmology, Yokohama City University School of Medicine, Yokohama, Kanagawa 236-0027, Japan
| | - Kari Matti Mäkelä
- Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine, University of Tampere, Tampere 33014, Finland
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Wu Z, Ayton LN, Luu CD, Baird PN, Guymer RH. Reticular Pseudodrusen in Intermediate Age-Related Macular Degeneration: Prevalence, Detection, Clinical, Environmental, and Genetic Associations. ACTA ACUST UNITED AC 2016; 57:1310-6. [DOI: 10.1167/iovs.15-18682] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Affiliation(s)
- Zhichao Wu
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia 2Ophthalmology, Department of Surgery, The University of Melbourne, Melbourne, Australia
| | - Lauren N. Ayton
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia 2Ophthalmology, Department of Surgery, The University of Melbourne, Melbourne, Australia
| | - Chi D. Luu
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia 2Ophthalmology, Department of Surgery, The University of Melbourne, Melbourne, Australia
| | - Paul N. Baird
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia 2Ophthalmology, Department of Surgery, The University of Melbourne, Melbourne, Australia
| | - Robyn H. Guymer
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia 2Ophthalmology, Department of Surgery, The University of Melbourne, Melbourne, Australia
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49
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Finger RP, Chong E, McGuinness MB, Robman LD, Aung KZ, Giles G, Baird PN, Guymer RH. Reticular Pseudodrusen and Their Association with Age-Related Macular Degeneration: The Melbourne Collaborative Cohort Study. Ophthalmology 2015; 123:599-608. [PMID: 26681391 DOI: 10.1016/j.ophtha.2015.10.029] [Citation(s) in RCA: 79] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2015] [Revised: 10/15/2015] [Accepted: 10/16/2015] [Indexed: 11/30/2022] Open
Abstract
PURPOSE To determine the prevalence of reticular pseudodrusen (RPD) and its association with age-related macular degeneration (AMD) and AMD risk factors in a large sample. DESIGN Community-based cohort study in Melbourne, Victoria, Australia. PARTICIPANTS A total of 21,130 participants 48 to 86 years of age available for ophthalmic assessment at follow-up from 2003 through 2007. METHODS Lifestyle, diet, and anthropometric measurements were obtained at baseline and follow-up. At follow-up, digital macular color photographs were graded for early, intermediate, and late AMD as well as the presence of RPD. Data were analyzed using multinomial logistic regression controlling for age, gender, smoking, country of birth, and diet. MAIN OUTCOME MEASURES Detection of RPD based on color fundus photographs. RESULTS Prevalence of RPD was 0.41% (87 of 21,130 participants), with 51% having bilateral RPD. Patients with RPD were older compared with patients with large drusen (>125 μm; 76±4 vs. 68±9 years; P < 0.001). Increasing age, female gender, being a current smoker, as well as focal pigmentary abnormalities and large drusen (>125 μm) were associated with a higher prevalence of RPD. Presence of geographic atrophy (GA) was associated with the highest odds of having RPD (odds ratio [OR], 153; 95% confidence interval [CI], 53-442), followed by choroidal neovascularization (CNV; OR, 90; 95% CI, 26-310), intermediate AMD (OR, 33; 95% CI, 14-77), and early AMD (OR, 12; 95% CI, 5-31) compared with those with no AMD. The ARMS2 single nucleotide polymorphism (SNP) rs10490924, HTRA1 SNPs rs11200638 and rs3793917, and CFH SNPs rs393955, rs1061170, and rs2274700 were associated with increased prevalence of RPD (all P < 0.05). CONCLUSIONS Reticular pseudodrusen are highly concurrent with AMD and have similar associations with known AMD risk factors such as age, gender, smoking, and genetic risk factors. Reticular pseudodrusen are associated more strongly with GA than with CNV. Although RPD are not specific to AMD, they are likely to be a strong risk factor for progression to late-stage AMD, similar to focal pigmentary abnormalities and large drusen.
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Affiliation(s)
- Robert P Finger
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia.
| | - Elaine Chong
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia
| | - Myra B McGuinness
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia
| | - Luba D Robman
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia
| | - Khin Zaw Aung
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia
| | - Graham Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia
| | - Paul N Baird
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia
| | - Robyn H Guymer
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, University of Melbourne, Melbourne, Australia
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50
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Osthoff M, Dean MM, Baird PN, Richardson AJ, Daniell M, Guymer RH, Eisen DP. Association Study of Mannose-Binding Lectin Levels and Genetic Variants in Lectin Pathway Proteins with Susceptibility to Age-Related Macular Degeneration: A Case-Control Study. PLoS One 2015; 10:e0134107. [PMID: 26207622 PMCID: PMC4514807 DOI: 10.1371/journal.pone.0134107] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2015] [Accepted: 07/06/2015] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND In age-related macular degeneration (AMD) the complement system is thought to be activated by chronic oxidative damage with genetic variants identified in the alternative pathway as susceptibility factors. However, the involvement of the lectin pathway of complement, a key mediator of oxidative damage, is controversial. This study investigated whether mannose-binding lectin (MBL) levels and genetic variants in lectin pathway proteins, are associated with the predisposition to and severity of AMD. METHODS MBL levels and single nucleotide polymorphisms (SNPs) in the MBL2 and the ficolin-2 (FCN2) gene were determined in 109 patients with AMD and 109 age- and sex-matched controls. RESULTS MBL expression levels were equally distributed in both cases (early and late AMD) and controls (p>0.05). However, there was a trend towards higher median MBL levels in cases with late AMD compared to cases with early AMD (1.0 vs. 0.4 μg/ml, p = 0.09) and MBL deficiency (<0.5 μg/ml) was encountered less frequently in the late AMD group (35% vs 56%, p = 0.03). FCN2 and MBL2 allele frequencies were similarly distributed in early and late AMD cases compared with controls (p>0.05 for all analyses) as were MBL2 genotypes. Similarly, there was no significant difference in allele frequencies in any SNPs in either the MBL2 or FCN2 gene in cases with early vs. late AMD. CONCLUSIONS SNPs of lectin pathway proteins investigated in this study were not associated with AMD or AMD severity. However, MBL levels deserve further study in a larger cohort of early vs. late AMD patients to elucidate any real effect on AMD severity.
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Affiliation(s)
- Michael Osthoff
- Victorian Infectious Diseases Service at the Doherty Institute, Melbourne Health, Melbourne, Victoria, Australia
- Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Melbourne, Victoria, Australia
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Basel, Switzerland
| | - Melinda M. Dean
- Research and Development, Australian Red Cross Blood Service, Kelvin Grove, Queensland, Australia
| | - Paul N. Baird
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
| | - Andrea J. Richardson
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
| | - Mark Daniell
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
| | - Robyn H. Guymer
- Centre for Eye Research Australia, University of Melbourne, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
| | - Damon P. Eisen
- Victorian Infectious Diseases Service at the Doherty Institute, Melbourne Health, Melbourne, Victoria, Australia
- Department of Medicine, Royal Melbourne Hospital, University of Melbourne, Melbourne, Victoria, Australia
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