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1,204 results on '"Singapore Eye Research Institute, Singapore National Eye Centre"'

1. Three-Year Outcomes of Neovascular Age-Related Macular Degeneration in Eyes That Do Not Develop Macular Atrophy or Subretinal Fibrosis

Author

Francesco Viola, Pierre-Henry Gabrielle, Sanjeeb Bhandari, Daniel Barthelmes, Vuong Nguyen, Jennifer J. Arnold, Odette A. M. Tigchelaar-Besling, Mark C Gillies, Gonzaga Garay-Aramburu, Catherine Creuzot-Garcher, Louise O'Toole, Chui Ming Gemmy Cheung, University of Zurich, Gabrielle, Pierre-Henry, The University of Sydney, Service d'Ophtalmologie (CHU de Dijon), Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), Marsden Eye Research - Marsden Eye Specialists, University of Milan, Amphia Hospital, Araba University Hospital, Mater Private Hospital Dublin, Singapore Eye Research Institute, Singapore National Eye Centre, and University hospital of Zurich [Zurich]

Subjects
Vascular Endothelial Growth Factor A, 10018 Ophthalmology Clinic, medicine.medical_specialty, Visual acuity, genetic structures, Biomedical Engineering, 2204 Biomedical Engineering, 610 Medicine & health, Macular Degeneration, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Fibrosis, Ranibizumab, Ophthalmology, medicine, Humans, [SDV.MHEP.OS]Life Sciences [q-bio]/Human health and pathology/Sensory Organs, Retrospective Studies, business.industry, Macular atrophy, Retinal, Odds ratio, Macular degeneration, medicine.disease, 2731 Ophthalmology, eye diseases, 3. Good health, Vascular endothelial growth factor, chemistry, 030221 ophthalmology & optometry, Subretinal fibrosis, Atrophy, Erratum, medicine.symptom, business, 030217 neurology & neurosurgery
Abstract

International audience; PURPOSE: To report the 36-month treatment outcomes of eyes with neovascular age-related macular degeneration (nAMD) receiving vascular endothelial growth factor (VEGF) inhibitors in daily practice who did not develop either subretinal fibrosis (SRFi) or macular atrophy (MA). METHODS: This is a retrospective analysis of data from the Fight Retinal Blindness registry. Treatment-naïve eyes starting intravitreal injection of VEGF inhibitors for nAMD from January 1, 2010, to September 1, 2017, and did not have SRFI and MA at baseline were tracked. RESULTS: We identified 2478 eligible eyes, of which 1712 eyes did not develop SRFi or MA, 291 developed extrafoveal SRFI or MA, and 475 developed subfoveal SRFi or MA over 36 months. The estimated visual acuity stabilized from 6 months to 36 months in eyes that did not develop SRFI or MA with a mean (95% confidence interval [CI]) change in VA of -1 (-2, 0) letters, whereas eyes that developed extrafoveal (-3 [-5, -2] letters) or subfoveal (-10 [-11, -8] letters) SRFi or MA declined in vision in the same period. Eyes with no or extrafoveal SRFi or MA over 36 months were more likely to maintain their visual improvement from six months to 36 months (odds ratio [OR; 95% CI] = 2.3 [1.5, 3.3] for absence vs. subfoveal SRFi or MA, P ≤ 0.01 and OR = 2.0 [1.2, 3.4] for extrafoveal vs. subfoveal MA or SRFi, P = 0.01). CONCLUSIONS: Treatment-naïve nAMD eyes receiving VEGF inhibitors maintain their initial six-month visual improvement over three years if they do not develop SRFI or MA. TRANSLATIONAL RELEVANCE: The nAMD is still a major cause of blindness despite antiangiogenic treatments. We found that eyes that did not develop subretinal fibrosis or macular atrophy maintained their initial vision improvement for at least three years, suggesting that identifying treatments for these complications is the final barrier to achieving excellent outcomes in nAMD.

Published
2021

2. OPA1: 516 unique variants and 831 patients registered in an updated centralized Variome database

Author

Le Roux, Bastien, Lenaers, Guy, Zanlonghi, Xavier, Amati-Bonneau, Patrizia, Chabrun, Floris, Foulonneau, Thomas, Caignard, Angélique, Leruez, Stéphanie, Gohier, Philippe, Procaccio, Vincent, Milea, Dan, den Dunnen, Johan T., Reynier, Pascal, Ferré, Marc, Physiopathologie Cardiovasculaire et Mitochondriale (MITOVASC), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université d'Angers (UA), Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM), Service Exploration Fonctionnelle de la Vision, Clinique Sourdille, Département de Biochimie et Génétique [Angers], Université d'Angers (UA)-Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM)-PRES Université Nantes Angers Le Mans (UNAM), Université d'Angers (UA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Biologie Neurovasculaire et Mitochondriale Intégrée (BNMI), Singapore Eye Research Institute, Singapore National Eye Centre, Human Genetics, Mitochondrie : Régulations et Pathologie, Université d'Angers (UA)-Institut National de la Santé et de la Recherche Médicale (INSERM), LENAERS, Guy, and MitoVasc - Physiopathologie Cardiovasculaire et Mitochondriale (MITOVASC)

Subjects
endocrine system, Dominant optic atrophy, Research, [SDV]Life Sciences [q-bio], lcsh:R, lcsh:Medicine, Interoperability, OPA1, eye diseases, GTP Phosphohydrolases, Pedigree, Database, [SDV] Life Sciences [q-bio], Sequence variant, Phenotype, Mutation, Optic Atrophy, Autosomal Dominant, Humans, Genetic Association Studies, Neurological disorders, ComputingMilieux_MISCELLANEOUS
Abstract

Background The dysfunction of OPA1, a dynamin GTPase involved in mitochondrial fusion, is responsible for a large spectrum of neurological disorders, each of which includes optic neuropathy. The database dedicated to OPA1 (https://www.lovd.nl/OPA1), created in 2005, has now evolved towards a centralized and more reliable database using the Global Variome shared Leiden Open-source Variation Database (LOVD) installation. Results The updated OPA1 database, which registers all the patients from our center as well as those reported in the literature, now covers a total of 831 patients: 697 with isolated dominant optic atrophy (DOA), 47 with DOA “plus”, and 83 with asymptomatic or unclassified DOA. It comprises 516 unique OPA1 variants, of which more than 80% (414) are considered pathogenic. Full clinical data for 118 patients are documented using the Human Phenotype Ontology, a standard vocabulary for referencing phenotypic abnormalities. Contributors may now make online submissions of phenotypes related to OPA1 mutations, giving clinical and molecular descriptions together with detailed ophthalmological and neurological data, according to an international thesaurus. Conclusions The evolution of the OPA1 database towards the LOVD, using unified nomenclature, should ensure its interoperability with other databases and prove useful for molecular diagnoses based on gene-panel sequencing, large-scale mutation statistics, and genotype-phenotype correlations. Electronic supplementary material The online version of this article (10.1186/s13023-019-1187-1) contains supplementary material, which is available to authorized users.

Published
2019

3. An anomaly detection approach for the identification of DME patients using spectral domain optical coherence tomography images

Author

Guillaume Lematre, Mojdeh Rastgoo, Joan Massich, Carol Y. Cheung, Dan Milea, Tien Yin Wong, Shrinivasan Sankar, Dsir Sidib, Ecosse L. Lamoureux, Fabrice Mriaudeau, Gavin Tan, Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Singapore Eye Research Institute, Singapore National Eye Centre, Department of Ophthalmology and Visual Science, The Chinese University of Hong Kong [Hong Kong], Centre for Intelligent Signal and Imaging Research (Universiti Teknologi Petronas) ( CISIR ), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Centre for Intelligent Signal and Imaging Research [Petronas] (CISIR), Universiti Teknologi PETRONAS (UTP), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement

Subjects
Male, SD-OCT, genetic structures, Computer science, Diabetic macular edema, Health Informatics, Anomaly detection, [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, Macular Edema, 030218 nuclear medicine & medical imaging, Diabetes Complications, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Optical coherence tomography, Diabetic retinopathy, medicine, Medical imaging, Humans, Computer vision, Sensitivity (control systems), Macular edema, medicine.diagnostic_test, business.industry, Retinal, Classification, medicine.disease, Mixture model, eye diseases, Computer Science Applications, Identification (information), chemistry, Outlier, 030221 ophthalmology & optometry, Female, sense organs, Tomography, Artificial intelligence, business, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Tomography, Optical Coherence, Software
Abstract

We propose a method to detect abnormal B-scans in SD-OCT volumes.We develop an anomaly detection approach for classification of SD-OCT volumes.The proposed method achieves high sensitivity and specificity compared to other supervised classification methods. This paper proposes a method for automatic classification of spectral domain OCT data for the identification of patients with retinal diseases such as Diabetic Macular Edema (DME). We address this issue as an anomaly detection problem and propose a method that not only allows the classification of the OCT volume, but also allows the identification of the individual diseased B-scans inside the volume. Our approach is based on modeling the appearance of normal OCT images with a Gaussian Mixture Model (GMM) and detecting abnormal OCT images as outliers. The classification of an OCT volume is based on the number of detected outliers. Experimental results with two different datasets show that the proposed method achieves a sensitivity and a specificity of 80% and 93% on the first dataset, and 100% and 80% on the second one. Moreover, the experiments show that the proposed method achieves better classification performance than other recently published works.

Published
2017

4. Nicotinamide Deficiency in Primary Open-Angle Glaucoma

Author

Kouassi Nzoughet, Judith, Chao de La Barca, Juan Manuel, Guehlouz, Khadidja, Coulbault, Laurent, Allouche, Stéphane, Bocca, Cinzia, Muller, Jeanne, Gohier, Philippe, Simard, Gilles, Milea, Dan, Desquiret-Dumas, Valérie, Leman, Géraldine, Wetterwald, Celine, Chupin, Stéphanie, Lebert, Anaïs, Khiati, Salim, Le Mao, Morgane, Geffroy, Guillaume, Kane, Mariame Selma, Chevrollier, Arnaud, Goudenège, David, Gadras, Cédric, Tessier, Lydie, Barth, Magalie, Leruez, Stéphanie, Amati-Bonneau, Patrizia, Henrion, Daniel, Bonneau, Dominique, Procaccio, Vincent, Reynier, Pascal, Lenaers, Guy, Gueguen, Naïg, Physiopathologie Cardiovasculaire et Mitochondriale (MITOVASC), Université d'Angers (UA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Biologie Neurovasculaire et Mitochondriale Intégrée (BNMI), CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN), Service de biochimie [CHU Caen], Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Tumorothèque de Caen Basse-Normandie (TCBN), Singapore Eye Research Institute, Singapore National Eye Centre, ARN : régulations naturelle et artificielle, Université Bordeaux Segalen - Bordeaux 2-Institut Européen de Chimie et de Biologie-Institut National de la Santé et de la Recherche Médicale (INSERM), Mitochondrie : Régulations et Pathologie, Université d'Angers (UA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Département de Biochimie et Génétique [Angers], Université d'Angers (UA)-Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM)-PRES Université Nantes Angers Le Mans (UNAM), Réseau Maladies Métaboliques, Hôpitaux Universitaires du Grand Ouest, Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM), Physiopathologie et thérapie des déficits sensoriels et moteurs, Université Montpellier 2 - Sciences et Techniques (UM2)-IFR76-Institut National de la Santé et de la Recherche Médicale (INSERM), and Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université d'Angers (UA)

Subjects
0301 basic medicine, Adult, Male, Niacinamide, Intraocular pressure, Spectrometry, Mass, Electrospray Ionization, medicine.medical_specialty, Open angle glaucoma, [SDV]Life Sciences [q-bio], Urology, Glaucoma, Cohort Studies, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Internal medicine, medicine, Humans, Intraocular Pressure, ComputingMilieux_MISCELLANEOUS, Aged, 030304 developmental biology, Therapeutic strategy, Aged, 80 and over, 0303 health sciences, Nicotinamide, Case-control study, Nicotinamide deficiency, Middle Aged, medicine.disease, 3. Good health, 030104 developmental biology, Endocrinology, chemistry, Case-Control Studies, Plasma concentration, Cohort, 030221 ophthalmology & optometry, Female, 030217 neurology & neurosurgery, Glaucoma, Open-Angle, Cohort study, Chromatography, Liquid
Abstract

PurposeTo investigate the plasma concentration of nicotinamide in primary open-angle glaucoma (POAG).MethodsPlasma of 34 POAG individuals were compared to that of 30 age-and sex-matched controls using a semi-quantitative method based on liquid chromatography coupled to high-resolution mass spectrometry. Subsequently, an independent quantitative method, based on liquid chromatography coupled to mass spectrometry, was used to assess nicotinamide concentration in the plasma from the same initial cohort and from a replicative cohort of 20 POAG individuals and 15 controls.ResultsUsing the semi-quantitative method, the plasma nicotinamide concentration was significantly lower in the initial cohort of POAG individuals compared to and further confirmed in the same cohort, using the targeted quantitative method, with mean concentrations of 0.14 µM (median: 0.12 µM; range: 0.06-0.28 µM) in the POAG group (−30 %;p= 0.022), and 0.19 µM (median: 0.18 µM; range: 0.08-0.47 µM) in the control group. The quantitative dosage also disclosed a significantly lower plasma nicotinamide concentration (−33 %;p= 0.011) in the replicative cohort with mean concentrations of 0.14 µM (median: 0.14 µM; range: 0.09-0.25 µM) in the POAG group, and 0.19 µM (median: 0.21 µM; range: 0.09-0.26 µM) in the control group.ConclusionsGlaucoma is associated with lower plasmatic nicotinamide levels, compared to controls, suggesting that nicotinamide supplementation might become a future therapeutic strategy. Further studies are needed, in larger cohorts, to confirm these preliminary findings.

Published
2019

5. Metabolomic Profiling of Aqueous Humor in Glaucoma Points to Taurine and Spermine Deficiency: Findings from the Eye-D Study

Author

Jeanne Muller, Gilles Simard, Philippe Gohier, Dan Milea, Juan Manuel Chao de la Barca, Cédric Annweiler, Vincent Procaccio, Patrizia Amati-Bonneau, Dominique Bonneau, Pascal Reynier, Adrien Buisset, Guy Lenaers, Stéphanie Leruez, Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM), Mitochondrie : Régulations et Pathologie, Université d'Angers (UA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Physiopathologie et thérapie des déficits sensoriels et moteurs, Université Montpellier 2 - Sciences et Techniques (UM2)-IFR76-Institut National de la Santé et de la Recherche Médicale (INSERM), Biologie Neurovasculaire et Mitochondriale Intégrée (BNMI), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université d'Angers (UA), Robarts Research Institute [Canada], University of Western Ontario (UWO), Laboratoire de Psychologie des Pays de la Loire (LPPL), Université d'Angers (UA)-Université de Nantes - UFR Lettres et Langages (UFRLL), Université de Nantes (UN)-Université de Nantes (UN), Singapore Eye Research Institute, Singapore National Eye Centre, Université d'Angers (UA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Physiopathologie Cardiovasculaire et Mitochondriale (MITOVASC), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université d'Angers (UA)

Subjects
0301 basic medicine, Male, medicine.medical_specialty, Taurine, primary open-angle glaucoma, genetic structures, [SDV]Life Sciences [q-bio], Spermine, Cataract Extraction, Biochemistry, Aqueous Humor, 03 medical and health sciences, chemistry.chemical_compound, Internal medicine, Carnitine, Lipidomics, medicine, Humans, Metabolomics, Amino Acids, ComputingMilieux_MISCELLANEOUS, Aged, chemistry.chemical_classification, Aged, 80 and over, 030102 biochemistry & molecular biology, General Chemistry, Middle Aged, eye diseases, Amino acid, Glutamine, Hydroxyproline, 030104 developmental biology, Endocrinology, glaucoma, chemistry, lipidomics, Female, Leucine, Isoleucine, Glaucoma, Open-Angle, medicine.drug
Abstract

International audience; We compared the metabolomic profile of aqueous humor from patients with primary open-angle glaucoma (POAG; n = 26) with that of a group of age- and sex-matched non-POAG controls (n = 26), all participants undergoing cataract surgery. Supervised paired partial least-squares discriminant analysis showed good predictive performance for test sets with a median area under the receiver operating characteristic of 0.89 and a p-value of 0.0087. Twenty-three metabolites allowed discrimination between the two groups. Univariate analysis after the Benjamini–Hochberg correction showed significant differences for 13 of these metabolites. The POAG metabolomic signature indicated reduced concentrations of taurine and spermine and increased concentrations of creatinine, carnitine, three short-chain acylcarnitines, 7 amino acids (glutamine, glycine, alanine, leucine, isoleucine, hydroxyl-proline, and acetyl-ornithine), 7 phosphatidylcholines, one lysophosphatidylcholine, and one sphingomyelin. This suggests an alteration of metabolites involved in osmoprotection (taurine and creatinine), neuroprotection (spermine, taurine, and carnitine), amino acid metabolism (7 amino acids and three acylcarnitines), and the remodeling of cell membranes drained by the aqueous humor (hydroxyproline and phospholipids). Five of these metabolic alterations, already reported in POAG plasma, concern spermine, C3 and C4 acylcarnitines, PC aa 34:2, and PC aa 36:4, thus highlighting their importance in the pathogenesis of glaucoma.

Published
2019

6. U-Shaped Relationship between Serum Leptin Concentration and Cognitive Performance in Older Asian Adults

Author

Annweiler, Cédric, Duval, Guillaume, Cheng, Ching-Yu, Wong, Tien-Yin, Lamoureux, Ecosse, Milea, Dan, Sabanayagam, Charumathi, Laboratoire de Psychologie des Pays de la Loire (LPPL), Université d'Angers (UA)-Université de Nantes - UFR Lettres et Langages (UFRLL), Université de Nantes (UN)-Université de Nantes (UN), Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM), Northwestern Polytechnical University [Xi'an] (NPU), Singapore Eye Research Institute, Partenaires INRAE, and Singapore Eye Research Institute, Singapore National Eye Centre

Subjects
Male, Singapore, digestive, oral, and skin physiology, lcsh:TX341-641, Middle Aged, leptin, Article, [SHS]Humanities and Social Sciences, Cognition, Asian People, Case-Control Studies, Humans, Cognitive Dysfunction, Female, lcsh:Nutrition. Foods and food supply, hormones, hormone substitutes, and hormone antagonists, Biomarkers, older adults, Aged
Abstract

The role of leptin (a hormone related to fat mass) in cognition remains equivocal. Our objective was to investigate the relationship between circulating leptin concentration and cognition in older adults, accounting for potential confounders. We categorized 1061 community-dwelling older participants &ge, 60 years (mean &plusmn, SD, 70.6 &plusmn, 6.4 years, 41.6% female) from the Singapore Kidney Eye Study according to quintiles of leptin concentration (&le, 2.64, 2.64&ndash, 5.1, 5.2&ndash, 8.6, 8.7&ndash, 17.96, &ge, 18 ng/mL). Cognition was assessed using the total and domain scores of the Abbreviated Mental Test (AMT). Age, gender, body mass index, mean arterial pressure, smoking, alcohol, education, memory complaint, anxiodepressive disorders, circulating concentrations of 25-hydroxyvitamin D, glycosylated hemoglobin, low-density lipoprotein cholesterol, and estimated glomerular filtration rate were used as potential confounders. Participants within the lowest (Q1) and highest (Q5) leptin quintiles exhibited lower (i.e., worse) mean total AMT scores compared to those within the intermediate quintiles (Q2, Q3, and Q4). Compared to Q3 as the reference, Q1 and Q5 were associated with decreased total AMT score (respectively, &beta, = &minus, 0.53 p = 0.018, &beta, 0.60 p = 0.036). Compared to Q3, Q5 was also associated with decreased subscores on anterograde (&beta, 0.19 p = 0.020) and retrograde episodic memories (&beta, 0.18 p = 0.039). We found a non-linear U-shaped relationship between circulating leptin and cognition, with both lower and higher concentrations of leptin being associated with more severe cognitive impairment in community-dwelling older Asians.

Published
2019

7. A Metabolomics Profiling of Glaucoma Points to Mitochondrial Dysfunction, Senescence, and Polyamines Deficiency

Author

Dan Milea, Stéphanie Leruez, Jeanne Muller, Juan Manuel Chao de la Barca, Vincent Procaccio, Pascal Reynier, Gilles Simard, Dominique Bonneau, Thomas Bresson, Christophe Verny, Patrizia Amati-Bonneau, Adrien Buisset, Alexandre Marill, Philippe Gohier, Lydie Tessier, Guy Lenaers, Cédric Gadras, Grégoire de Saint Martin, Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM), Département de Biochimie et Génétique [Angers], Université d'Angers (UA)-Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM)-PRES Université Nantes Angers Le Mans (UNAM), Biologie Neurovasculaire Intégrée (BNVI), Université d'Angers (UA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Mitochondrie : Régulations et Pathologie, Université d'Angers (UA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Physiopathologie Cardiovasculaire et Mitochondriale (MITOVASC), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université d'Angers (UA), Biologie Neurovasculaire et Mitochondriale Intégrée (BNMI), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université d'Angers (UA), Singapore Eye Research Institute, Singapore National Eye Centre, LENAERS, Guy, and MitoVasc - Physiopathologie Cardiovasculaire et Mitochondriale (MITOVASC)

Subjects
0301 basic medicine, Senescence, Male, Aging, primary open-angle glaucoma, Mitochondrial Diseases, Spermidine, [SDV]Life Sciences [q-bio], Spermine, Mitochondrion, Biology, Retinal ganglion, Mass Spectrometry, 03 medical and health sciences, chemistry.chemical_compound, Metabolomics, mitochondrial dysfunction, Metabolome, Humans, Eye Proteins, Aged, Principal Component Analysis, eye diseases, 3. Good health, [SDV] Life Sciences [q-bio], glaucoma, 030104 developmental biology, Biochemistry, chemistry, Female, Polyamine, Glaucoma, Open-Angle
Abstract

International audience; Purpose: To determine the plasma metabolomic signature of primary open-angle glaucoma (POAG).Methods: We compared the metabolomic profiles of plasma from individuals with POAG (n = 36) with age- and sex-matched controls with cataract (n = 27). A targeted metabolomics study was performed using the standardized p180 Biocrates Absolute IDQ p180 kit with a QTRAP 5500 mass spectrometer. Multivariate analyses were performed using principal component analysis (PCA) and the least absolute shrinkage and selection operator (LASSO) method.Results: Among the 151 metabolites accurately measured, combined univariate and multivariate analyses revealed 18 discriminant metabolites belonging to the carbohydrate, acyl-carnitine, phosphatidylcholine, amino acids, and polyamine families. The metabolomic signature of POAG points to three closely interdependent pathophysiologic conditions; that is, defective mitochondrial oxidation of energetic substrates, altered metabolism resembling that observed in senescence, and a deficiency in spermidine and spermine, both polyamines being involved in the protection of retinal ganglion cells.Conclusions: Our results highlight a systemic and age-related mitochondrial defect in the pathogenesis of POAG.

Published
2018

8. Classification of SD-OCT volumes with multi pyramids, LBP and HOG descriptors: application to DME detections

Author

Dan Milea, Join Massich Vall, Tien Yin Wong, Mojdeh Rastgoo, Désiré Sidibé, Guillaume Lemaitre, Ecosse L. Lamoureux, Khaled Alsaih, Fabrice Meriaudeau, Carol Y. Cheung, Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Singapore Eye Research Institute, Singapore National Eye Centre, Lemaitre, Guillaume, Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)

Subjects
Support Vector Machine, genetic structures, Databases, Factual, Computer science, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, 02 engineering and technology, [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, [ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 01 natural sciences, [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 0202 electrical engineering, electronic engineering, information engineering, Image Processing, Computer-Assisted, Segmentation, Computer vision, medicine.diagnostic_test, [ INFO.INFO-IM ] Computer Science [cs]/Medical Imaging, Diabetic retinopathy, Histogram of oriented gradients, medicine.anatomical_structure, 020201 artificial intelligence & image processing, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Tomography, Optical Coherence, Local binary patterns, Feature vector, Diabetic macular edema, Feature extraction, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Image processing, Sensitivity and Specificity, Macular Edema, 010309 optics, Optical coherence tomography, Histogram, 0103 physical sciences, medicine, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Humans, Macular edema, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, Retina, Diabetic Retinopathy, business.industry, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Pattern recognition, Image segmentation, medicine.disease, eye diseases, Support vector machine, ComputingMethodologies_PATTERNRECOGNITION, sense organs, Artificial intelligence, business
Abstract

This paper deals with the automated detection of Diabetic Macular Edema (DME) on Optical Coherence Tomography (OCT) volumes. Our method considers a generic classification pipeline with preprocessing for noise removal and flattening of each B-Scan. Features such as Histogram of Oriented Gradients (HOG) and Local Binary Patterns (LBP) are extracted and combined to create a set of different feature vectors which are fed to a linear-Support Vector Machines (SVM) Classifier. Experimental results show a promising sensitivity/specificity of 0.75/0.87 on a challenging dataset.

Published
2017

9. Classifying DME vs Normal SD-OCT volumes: A review

Author

Carol Y. Cheung, Mojdeh Rastgoo, Joan Massich, Guillaume Lemaitre, Désiré Sidibé, Fabrice Meriaudeau, Tien Yin Wong, Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Singapore Eye Research Institute, Singapore National Eye Centre, Centre for Intelligent Signal and Imaging Research (Universiti Teknologi Petronas) ( CISIR ), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Centre for Intelligent Signal and Imaging Research [Petronas] (CISIR), Universiti Teknologi PETRONAS (UTP), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), and Lemaitre, Guillaume

Subjects
genetic structures, Computer science, Diabetic macular edema, Early detection, [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, Machine learning, computer.software_genre, 01 natural sciences, 010309 optics, 03 medical and health sciences, 0302 clinical medicine, benchmark, 0103 physical sciences, medicine, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, Retina, Blindness, business.industry, Machine Learning (ML), medicine.disease, eye diseases, Spectral Domain OCT (SD-OCT), medicine.anatomical_structure, 030221 ophthalmology & optometry, Benchmark (computing), Artificial intelligence, Data mining, sense organs, Diabetic Macular Edema (DME), business, computer, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

International audience; This article reviews the current state of automatic classification methodologies to identify Diabetic Macular Edema (DME) versus normal subjects based on Spectral Domain OCT (SD-OCT) data. Addressing this classification problem has valuable interest since early detection and treatment of DME play a major role to prevent eye adverse effects such as blindness. The main contribution of this article is to cover the lack of a public dataset and benchmark suited for classifying DME and normal SD-OCT volumes, providing our own implementation of the most relevant methodologies in the literature. Subsequently, 6 different methods were implemented and evaluated using this common benchmark and dataset to produce reliable comparison.

Published
2016

10. Novel genetic loci underlying human intracranial volume identified through genome-wide association

Author

G. Bruce Pike, Marcel P. Zwiers, Andreas Meyer-Lindenberg, Jeroen van der Grond, Randy L. Gollub, Karen A. Mather, Andrew J. Schork, Vidar M. Steen, Marc M. Bohlken, Nhat Trung Doan, Derek W. Morris, John B.J. Kwok, Emma J. Rose, Johanna Hass, Andrew Simmons, Tian Ge, Reinhold Schmidt, Micael Andersson, Ian J. Deary, Christopher Chen, Derrek P. Hibar, Simon E. Fisher, Lucija Abramovic, Marcella Rietschel, Edith Hofer, Simon Lovestone, Clyde Francks, Christopher R.K. Ching, Srdjan Djurovic, Lachlan T. Strike, Lorna M. Lopez, Rene L. Olvera, Owen Carmichael, M. Arfan Ikram, Andre F. Marquand, Christine Macare, W.T. Longstreth, Philippe Amouyel, Aaron L. Goldman, Wolfgang Hoffmann, Philip L. De Jager, David C. Liewald, Harald H H Göring, Aad van der Lugt, David Ames, Neeltje E.M. van Haren, Lars Nyberg, Nina Romanczuk-Seiferth, Lukas Pirpamer, Stefan Ehrlich, Alexa S. Beiser, Lianne Schmaal, Hilkka Soininen, Mark Jenkinson, Kazima B. Bulayeva, Anderson M. Winkler, Mike A. Nalls, Diana Tordesillas-Gutiérrez, Martine Hoogman, Lars T. Westlye, Loes M. Olde Loohuis, Andrew Singleton, Gabriel Cuellar-Partida, Randy L. Buckner, Dorret I. Boomsma, Dena G. Hernandez, Steven G. Potkin, Sudha Seshadri, Bertram Müller-Myhsok, D. Hoehn, Gareth E. Davies, Chantal Depondt, Henrik Walter, Michael E. Weale, Deborah Janowitz, Susanne Erk, Iryna O. Fedko, Daniel R. Weinberger, Nic J A van der Wee, Jean-Luc Martinot, Jessica A. Turner, Marieke Klein, Sandra Barral, Sebastian Mohnke, Albert Hofman, Ingrid Melle, Saud Alhusaini, Vincent Chouraki, Stephen M. Lawrie, Mark E. Bastin, Juan C. Troncoso, Jean Shin, Wiro J. Niessen, Diane M. Becker, Laura Almasy, Anders M. Dale, Benjamin S. Aribisala, Dennis van 't Ent, Marco P. Boks, M. Mallar Chakravarty, Paul M. Thompson, David Reese McKay, Michael Griswold, John Blangero, Narelle K. Hansell, Eco J. C. de Geus, Paul A. Nyquist, Susana Muñoz Maniega, Sampath Arepalli, Tatjana Rundek, Dan L. Longo, Anton J. M. de Craen, Rebekah McWhirter, Nazanin Mirza-Schreiber, Henning Tiemeier, Girma Woldehawariat, Sven Cichon, Irene Pappa, Amelia A. Assareh, Sudheer Giddaluru, Pieter J. Hoekstra, Hieab H.H. Adams, Hilleke E. Hulshoff Pol, Grant W. Montgomery, Roel A. Ophoff, Markus M. Nöthen, Sara Pudas, Sigurdur Sigurdsson, Arthur W. Toga, Tien Yin Wong, Massimo Pandolfo, Corina U. Greven, Esther Walton, Tianye Jia, David J. Stott, Gunter Schumann, Marie-José van Tol, Dalia Kasperaviciute, Thomas Wolfers, Henry Völzke, Ian Ford, Shannon L. Risacher, Jessika E. Sussmann, Nicholas G. Martin, Wei Wen, Daniah Trabzuni, Iwona Kłoszewska, Kwangsik Nho, Gianpiero L. Cavalleri, Adam M. Brickman, Sungeun Kim, Andreas Heinz, Ralph L. Sacco, Neda Jahanshad, Velandai Srikanth, Elena Shumskaya, Susan H. Blanton, Katharina Wittfeld, Badri N. Vardarajan, Joshua C. Bis, Joanne E. Curran, Helena Schmidt, Peter T. Fox, Clifford R. Jack, Jason L. Stein, Laura M. E. Blanken, Thomas Espeseth, Dick J. Veltman, Sebastian Guelfi, Margaret J. Wright, Norman Delanty, Michael Czisch, Martina Papmeyer, Oscar L. Lopez, Marjolein M. J. Van Donkelaar, Bruce M. Psaty, Jan K. Buitelaar, Sven J. van der Lee, David A. Bennett, Beng-Choon Ho, Oliver Martinez, Wiepke Cahn, Li Shen, J. Wouter Jukema, Janita Bralten, Peter Kochunov, Greig I. Zubicaray, Marcel P. van der Brug, Ching-Yu Cheng, Philipp G. Sämann, Stella Trompet, Roberto Roiz-Santiañez, David C. Glahn, Allissa Dillman, Venkata S. Mattay, Dara M. Cannon, Michael W. Weiner, Christopher D. Whelan, Alexander Teumer, Sylvane Desrivières, Ole A. Andreassen, Thomas E. Nichols, Manuel Mattheisen, Matthias Nauck, René S. Kahn, Albert V. Smith, Colin Smith, Vilmundur Gudnason, Denis A. Evans, Anouk den Braber, Katie L. McMahon, Han G. Brunner, Florian Holsboer, Yuri Milaneschi, Andrew J. Saykin, Jiemin Liao, Vince D. Calhoun, Neelum T. Aggarwal, Dennis van der Meer, Hans J. Grabe, Anita L. DeStefano, Claudia L. Satizabal, Alan B. Zonderman, Alex P. Zijdenbos, Tulio Guadalupe, Ingrid Agartz, Jordan W. Smoller, Allison C. Nugent, Alejandro Arias-Vasquez, Masashi Ikeda, Avram J. Holmes, Brenda W.J.H. Penninx, John Hardy, Herve Lemaitre, Charles DeCarli, Patrizia Mecocci, Catharina A. Hartman, Tomas Axelsson, Oliver Grimm, Irina Filippi, Wayne C. Drevets, Hans van Bokhoven, Miguel E. Rentería, Aiden Corvin, Ryota Kanai, Kristel R. van Eijk, Andrew M. McIntosh, Jouke-Jan Hottenga, Roberto Toro, Lavinia Athanasiu, Joanna M. Wardlaw, Thomas H. Mosley, Mina Ryten, Meike W. Vernooij, Michelle Luciano, Joshua L. Roffman, Rebecca F. Gottesman, Dhananjay Vaidya, Ryota Hashimoto, Mar Matarin, Adaikalavan Ramasamy, Jerome I. Rotter, Ryan L. Muetzel, Konstantinos Arfanakis, Theo G.M. van Erp, Ganesh Chauhan, Xinmin Liu, Tomáš Paus, Emma Sprooten, Christiane Wolf, David S. Knopman, Manon Bernard, Zdenka Pausova, Bryan J. Traynor, Maria C. Valdés Hernández, Robert C. Green, Russell Thomson, Ravi Duggirala, Lisa R. Yanek, Luigi Ferrucci, Bing Xu, Thomas D. Dyer, Thomas H. Wassink, Eric Westman, Jennifer S. Richards, Phil H. Lee, Benno Pütz, Mark R. Cookson, Benedicto Crespo-Facorro, Natalie A. Royle, Bernd Kraemer, Katrin Hegenscheid, Francis J. McMahon, Tatiana Foroud, M. Kamran Ikram, Myriam Fornage, Nanda Rommelse, Saima Hilal, Perminder S. Sachdev, Qiang Chen, Najaf Amin, Lenore J. Launer, Norbert Hosten, Guillén Fernández, Simone Reppermund, Ashley Beecham, Dirk J. Heslenfeld, Masaki Fukunaga, Cornelia M. van Duijn, Clinton B. Wright, Erik G. Jönsson, Sanjay M. Sisodiya, Oliver Gruber, Christophe Tzourio, André G. Uitterlinden, Robert Johnson, Jaap Oosterlaan, Bernard Mazoyer, H. Ronald Zielke, Stephanie Le Hellard, Jingyun Yang, Georg Homuth, Stéphanie Debette, Nicola J. Armstrong, Sarah E. Medland, Henry Brodaty, Beverly G Windham, Gary Donohoe, Rachel M. Brouwer, James T. Becker, Kumar B. Rajan, Daan van Rooij, Thomas W. Mühleisen, Kazutaka Ohi, Peter R. Schofield, Tonya White, Barbara Franke, Unn K. Haukvik, Debra A. Fleischman, J. Raphael Gibbs, Colm McDonald, Anbupalam Thalamuthu, Erasmus University Medical Center [Rotterdam] (Erasmus MC), Keck School of Medicine [Los Angeles], University of Southern California (USC), Boston University School of Medicine (BUSM), Boston University [Boston] (BU), Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement - U 1167 (RID-AGE), Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Johns Hopkins University (JHU), QIMR Berghofer Medical Research Institute, Leiden University Medical Center (LUMC), Radboud University Medical Center [Nijmegen], Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, University of Miami Leonard M. Miller School of Medicine (UMMSM), German Research Center for Neurodegenerative Diseases - Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Greifswald University Hospital, Department of Neurology and Neurosurgery [Montreal], Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], Royal College of Surgeons in Ireland (RCSI), Umeå University, Illinois Institute of Technology (IIT), Rush University Medical Center [Chicago], University of Edinburgh, Lagos State University (LASU), University of New South Wales [Sydney] (UNSW), Murdoch University, University of Oslo (UiO), Uppsala University, Framingham Heart Study, Boston University [Boston] (BU)-National Heart, Lung, and Blood Institute [Bethesda] (NHLBI), University of Toronto, University of Washington [Seattle], Donders Institute for Brain, Cognition and Behaviour, Radboud university [Nijmegen], Columbia University Medical Center (CUMC), Columbia University [New York], Pennington Biomedical Research Center, Louisiana State University (LSU), McGill University = Université McGill [Montréal, Canada], Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Lieber Institute for Brain Development [Baltimore] (LIBD), University of California [Los Angeles] (UCLA), University of California, Vrije Universiteit Amsterdam [Amsterdam] (VU), Technische Universität Dresden = Dresden University of Technology (TU Dresden), Massachusetts General Hospital [Boston], Neuroimagerie en psychiatrie (U1000), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Sud - Paris 11 (UP11), Maison de Solenn [CHU Cochin], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Cochin [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], University of Bergen (UiB), Haukeland University Hospital, Johns Hopkins University School of Medicine [Baltimore], Universität Heidelberg [Heidelberg], University of Mississippi Medical Center (UMMC), International Max Planck Research School for Language Sciences (IMPRS ), Max Planck Institute for Psycholinguistics, Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, Language and Genetics Department [Nijmegen], National University of Singapore (NUS), Medical University Graz, Max Planck Institute of Psychiatry, Max-Planck-Gesellschaft, Yale University [New Haven], University College of London [London] (UCL), Imperial College London, Structure et Réactivité des Systèmes Moléculaires Complexes (SRSMC), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC), Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center, Goettingen 37075, Germany, Medstar Research Institute, Clinical And Experimental Epilepsy, Centre for Healthy Brain Ageing, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia, Department of Biomedicine and the Centre for Integrative Sequencing, Aarhus University [Aarhus], Institute of Human Genetics, University of Bonn, Department of Genomics, Life and Brain Center, Groupe d'imagerie neurofonctionnelle (GIN), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), Dpt of Psychiatry [New Haven], Yale University School of Medicine, Department of Psychiatry, VU University Medical Center [Amsterdam], Department of Psychology [Minneapolis], University of Minnesota [Twin Cities] (UMN), University of Minnesota System-University of Minnesota System, Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indiana University System-Indiana University System, Indiana University System, Institute of Food & Health, University College Dublin, University College Dublin [Dublin] (UCD), Statistical Genetics Group, Respiratory Epidemiology and Public Health, Imperial College London-School of public health, The University of Hong Kong (HKU)-The University of Hong Kong (HKU)-MRC-HPA Centre for Environment and Health, Centro de Investigación Biomédica en Red Salud Mental [Madrid] (CIBER-SAM), Karakter Child and Adolescent Psychiatry University Centre [Nijmegen], Institut Parisien de Chimie Moléculaire (IPCM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), INSERM, Neuroepidemiology U708, Bordeaux, France, Department of Cognitive Sciences [San Diego], University of California [San Diego] (UC San Diego), University of California-University of California, Department of Neurosciences [San Diego], Centre for Advanced Imaging, University of Queensland, Brisbane 4072, Australia, School of Psychology, University of Queensland, Brisbane 4072, Australia, University of Queensland [Brisbane], Queensland Institute of Medical Research, Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Institut Pasteur [Paris]-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Department of Genetics, King Faisal Specialist Hospital and Research Centre, Reta Lila Weston Institute and Department of Molecular Neuroscience, UCL, Institute of Neurology [London], Depts of Radiology, University of Twente [Netherlands], Department of Psychiatry and Human Behavior [Irvine], University of California [Irvine] (UCI), Donders Center for Cognitive Neuroimaging, Donders Centre for Cognitive Neuroimaging, Radboud university [Nijmegen]-Radboud university [Nijmegen], Centre épigénétique et destin cellulaire (EDC (UMR_7216)), Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7), Department of Psychology [Oslo], Faculty of Social Sciences [Oslo], University of Oslo (UiO)-University of Oslo (UiO), Deutsche Bundesbank, National Institutes of Health [Bethesda] (NIH), General Internal Medicine, Johns Hopkins School of Medicine, Biospective [Montréal], KG Jebsen Centre for Psychosis Research, University of Oslo (UiO)-Institute of Clinical Medicine-Oslo University Hospital [Oslo], Southwest Foundation for Biomedical Research, Department of Psychiatry and National Ageing Research Institute, University of Melbourne, Department of Clinical Genetics, Department of Medical Parasitology and Mycology, School of public health, The University of Hong Kong (HKU)-The University of Hong Kong (HKU)-Tehran University of Medical Siences, Institute for Advanced Biosciences / Institut pour l'Avancée des Biosciences (Grenoble) (IAB), Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Departments of Psychiatry, Neurology, and Psychology, University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), The University of Texas Health Science Center at Houston (UTHealth), Texas Biomedical Research Institute [San Antonio, TX], 849 Department of Human Genetics, Dementia Collaborative Research Centre, Centre for Healthy Brain Ageing, Brain Center Rudolf Magnus, Department of Psychiatry, UMC Utrecht, Utrecht 3584 CX, The Netherlands, Université de Lausanne (UNIL), Department of Psychiatry [Boston], N.I. Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow 119333, Russia, Icahn School of Medicine at Mount Sinai [New York] (MSSM), The Mind Research Network, Department of Electrical and Computer Engineering [Albuquerque] (ECE Department), The University of New Mexico [Albuquerque], Human Genetics Branch, National Institutes of Health [Bethesda] (NIH)-National Institute of Mental Health (NIMH), Division of Molecular and Cellular Therapeutics, Metacohorts Consortium, Division of Medical Genetics, University of Basel (Unibas), Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Cell Biology and Gene Expression Section, National Institute of Health, Bethesda, Neuropsychiatric Genetics Research Group, Trinity College Dublin, Trinity College Dublin-St. James's Hospital, Department of Materials Science & Metallurgy, University of Cambridge [UK] (CAM), Bijvoet Center of Biomolecular Research [Utrecht], Utrecht University [Utrecht], VU University Amsterdam, Program in Translational NeuroPsychiatric Genomics, Brigham and Women's Hospital [Boston], Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA, Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston]-Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Harvard Medical School [Boston] (HMS), School of Psychology, University of Queensland, Neurology Division, Beaumont Hospital, Dublin 9, Ireland, Beaumont Hospital, Molecular and Cellular Therapeutics, Department of Neurology, Hôpital Erasme [Bruxelles] (ULB), Faculté de Médecine [Bruxelles] (ULB), Université libre de Bruxelles (ULB)-Université libre de Bruxelles (ULB)-Faculté de Médecine [Bruxelles] (ULB), Université libre de Bruxelles (ULB)-Université libre de Bruxelles (ULB), Laboratory of Neurogenetics, Department of Genomics, Biological Psychology, Neuroscience Campus Amsterdam & EMGO Institute for Health and Care Research, VU University & VU Medical Center, Amsterdam 1081 BT, The Netherlands, Department of Radiology, Mayo Clinic, Department of Medical and Molecular Genetics, South Texas Veterans Health Care System, San Antonio, Texas 78229, USA, Department of Physics, Okayama University, Okayama University, National Institute of Aging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital [Boston]-Harvard Medical School [Boston] (HMS), Public Health Genomics Unit, Department of Psychiatry and Psychotherapy, HELIOS Klinikum Stralsund Hanseatic-Greifswald University Hospital, Department of Mathematics, University of Colorado, University of Colorado [Boulder], Icelandic Heart Association, Kopavogur, Iceland., Faculty of Medicine, University of Iceland [Reykjavik], Department of Molecular Neurosciences, Institute of Neurology, UCL, Molecular Research Center for Children’s Mental Development, United Graduate School of Child Development, Osaka University [Osaka], Department of Psychiatry, University of Iowa, University of Iowa [Iowa City], University Medical Center Groningen [Groningen] (UMCG), Neuronal Plasticity / Mouse Behaviour, Interfaculty Institute for Genetics and Functional Genomics, Universität Greifswald - University of Greifswald, Tohoku University [Sendai], Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands, Stony Brook University [SUNY] (SBU), State University of New York (SUNY), Department of Medicine, Clinical Pharmacology Unit, Karolinska University Hospital [Stockholm], Centre for Allergy Research, Karolinska Institutet [Stockholm], Interuniversity Cardiology Institute Netherlands, Institute of Cognitive Neuroscience, School of Psychology, University of Sussex, Brighton BN1 9QH, UK, University of Sussex, Medical University of Łódź (MUL), Mayo Clinic [Rochester], University of Maryland School of Medicine, University of Maryland System-University of Maryland System-University of Maryland [Baltimore County] (UMBC), University of Maryland System, Department of Civil and Structural Engineering, The Hong Kong Polytechnic University [Hong Kong] (POLYU)-The Hong Kong Polytechnic University [Hong Kong] (POLYU), Université de Cergy Pontoise (UCP), Université Paris-Seine, Lymphocyte Cell Biology Unit, Laboratory of Genetics, Laboratoire de Statistique Théorique et Appliquée (LSTA), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Psychiatry Institute, Department of Health and Human Services, Department of Life Sciences, Mathematical Sciences Institute (MSI), Australian National University (ANU), Centre for Advanced Imaging, Institute of Gerontology and Geriatrics, Università degli Studi di Perugia (UNIPG), Division of Mental Health and Addiction, Oslo University Hospital [Oslo], Institute of Clinical Medicine [Oslo], Faculty of Medicine [Oslo], Medical Faculty [Mannheim], Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Genetic Epidemiology Unit, Université de Toulon - UFR Lettres et Sciences Humaines (UTLN UFR LSH), Université de Toulon (UTLN), Translational Centre for Regenerative Medicine (TRM), Department of Cell Therapy, Universität Leipzig [Leipzig]-Universität Leipzig [Leipzig], Institute of Clinical Chemistry and Laboratory Medicine, Warwick Manufacturing Group [Coventry] (WMG), University of Warwick [Coventry], Department of Statistics [Warwick], Delft University of Technology (TU Delft), Rheinische Friedrich-Wilhelms-Universität Bonn, Department of Health Science, Division of Health and Rehabilitation, Luleå University of Technology (LUT), University Medical Center [Utrecht]-Brain Center Rudolf Magnus, McConnell Brain Imaging Centre (MNI), Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Canada, Psychiatry and Human Behavior, University of California, Irvine, California 92617, USA, Group Health Research Institute, Group Health Cooperative, Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health [Mannheim], Medical Faculty [Mannheim]-Medical Faculty [Mannheim], Cedars-Sinai Medical Center, Centre for Healthy Brain Ageing [Sydney], The University of Sydney, Genetics of Mental Illness and Brain Function, Neuroscience Research Australia, Broad Institute [Cambridge], Harvard University [Cambridge]-Massachusetts Institute of Technology (MIT), Department of Medical Biochemistry and Microbiology, Department of Clinical and Experimental Epilepsy, Department of neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland, Department of neurology, University of Eastern Finland-University Hospital of Kuopio-University of Eastern Finland-University Hospital of Kuopio, Stroke and Ageing Research Centre, Southern Clinical School, Department of Medicine, Monash University, Monash University [Melbourne], Menzies Research Institute Tasmania, University of Tasmania, Hobart, Tasmania, Australia, University of Tasmania [Hobart, Australia] (UTAS), Institute of Cardiovascular and Medical Sciences [Glasgow], University of Glasgow, Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney 2052, Australia, Department of Epidemiology, Laboratory of Neuro Imaging [Los Angeles] (LONI), University of York [York, UK], Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Genentech, Inc. [San Francisco], Departments of Radiology and of Epidemiology [Rotterdam], Psychiatry and Leiden Institute for Brain and Cognition, Department of Neurology [Rotterdam], Institute for Community Medicine, Berlin School of Mind and Brain [Berlin], Humboldt-Universität zu Berlin, Carver College of Medicine [Iowa City], University of Iowa [Iowa City]-University of Iowa [Iowa City], Centre for Population Health Sciences, Department of Physics [Hong Kong University of Science and Technology], Hong Kong University of Science and Technology (HKUST), Department of Neurobiology, Care Sciences and Society, Research Laboratory for Archaeology & the History of Art, Singapore Eye Research Institute, Singapore National Eye Centre, School of Life Sciences, Arizona State University [Tempe] (ASU), Department of Neurology and Center for Neuroscience, University of California at Davis, Sacramento, University of California [Davis] (UC Davis), Dpt of Pharmacology and Personalised Medicine [Maastricht], Maastricht University [Maastricht], University of Missouri [Columbia] (Mizzou), University of Missouri System, Göttingen Zentrum Geowissenschaften, Georg-August-University [Göttingen], Human Genetics Center, Psychiatry, EMGO - Mental health, Amsterdam Neuroscience - Complex Trait Genetics, Anatomy and neurosciences, Klinische Genetica, MUMC+: DA Klinische Genetica (5), RS: FHML non-thematic output, RS: GROW - School for Oncology and Reproduction, RS: GROW - R4 - Reproductive and Perinatal Medicine, Genetica & Celbiologie, Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de Chimie du CNRS (INC)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Institut de Chimie du CNRS (INC)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), University of Maryland [Baltimore County] (UMBC), University of Maryland System-University of Maryland System-University of Maryland School of Medicine, Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Universidad de Cantabria, Universiteit Leiden, Radboud University [Nijmegen], University of California (UC), Universität Heidelberg [Heidelberg] = Heidelberg University, Universität Bonn = University of Bonn, [GIN] Grenoble Institut des Neurosciences (GIN), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Yale School of Medicine [New Haven, Connecticut] (YSM), Department of Cognitive Sciences [Univ California San Diego] (CogSci - UC San Diego), University of California (UC)-University of California (UC), Department of Neurosciences [Univ California San Diego] (Neuro - UC San Diego), School of Medicine [Univ California San Diego] (UC San Diego), University of California (UC)-University of California (UC)-University of California [San Diego] (UC San Diego), Institut Pasteur [Paris] (IP)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), King Faisal Specialist Hospital and Research Centre (KFSH & RC), Universiteit Leiden-Universiteit Leiden, University of Twente, University of California [Irvine] (UC Irvine), Radboud University [Nijmegen]-Radboud University [Nijmegen], Centre épigénétique et destin cellulaire (EDC), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Université de Lausanne = University of Lausanne (UNIL), Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], Università degli Studi di Perugia = University of Perugia (UNIPG), University Hospital Mannheim | Universitätsmedizin Mannheim, Universität Leipzig-Universität Leipzig, University Hospital Mannheim | Universitätsmedizin Mannheim-University Hospital Mannheim | Universitätsmedizin Mannheim, Harvard University-Massachusetts Institute of Technology (MIT), University of Eastern Finland, Humboldt University Of Berlin, Georg-August-University = Georg-August-Universität Göttingen, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Clinical Cognitive Neuropsychiatry Research Program (CCNP), Epidemiology, Child and Adolescent Psychiatry / Psychology, Ophthalmology, Radiology & Nuclear Medicine, Internal Medicine, Neurosciences, Obstetrics & Gynecology, Neurology, EMGO+ - Mental Health, Biological Psychology, Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement (Inserm U1167 - RID-AGE - Institut Pasteur), McGill University-McGill University, National Heart, Lung, and Blood Institute [Bethesda] (NHLBI)-Boston University [Boston] (BU), McGill University, Technische Universität Dresden (TUD), Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-CHU Cochin [AP-HP], University of Bergen (UIB), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), University of Minnesota [Twin Cities], Karakter Child and Adolescent Psychiatry University Center Nijmegen, Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Institut Pasteur [Paris], Centre Hospitalier Universitaire [Grenoble] (CHU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang - Auvergne-Rhône-Alpes (EFS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Texas Biomedical Research Institute [San Antonio, Texas], Bijvoet Center of Biomolecular Research, Université Libre de Bruxelles [Bruxelles] (ULB)-Hôpital Erasme (Bruxelles), Okayama University [Okayama], Charité - Universitätsmedizin Berlin / Charite - University Medicine Berlin, Massachusetts Institute of Technology (MIT)-Harvard University [Cambridge], University of Tasmania (UTAS), Humboldt Universität zu Berlin, Department of Physics [Kowloon], University of Missouri [Columbia], Georg-August-Universität Göttingen, and the Alzheimer's Disease Neuroimaging Initiative, EPIGEN, IMAGEN, SYS

Subjects
0301 basic medicine, Netherlands Twin Register (NTR), Genome-wide association study, Disease, methods [Genome-Wide Association Study], Genome-wide association studies, Phosphatidylinositol 3-Kinases, 0302 clinical medicine, Cognition, PARKINSONS-DISEASE, pathology [Brain], genetics [Parkinson Disease], 610 Medicine & health, General Neuroscience, growth & development [Brain], physiology [Cognition], 220 Statistical Imaging Neuroscience, COMMON VARIANTS, Brain, Parkinson Disease, Phenotype, 17Q21.31 MICRODELETION, IGF-I, genetics [Oncogene Protein v-akt], Oncogene Protein v-akt, ALZHEIMERS-DISEASE, HEAD CIRCUMFERENCE, Brain size, genetics [Polymorphism, Single Nucleotide], Medical genetics, GROWTH, Neuroinformatics, medicine.medical_specialty, Neuroscience(all), European Continental Ancestry Group, genetics [Genetic Loci], Biology, Genetic correlation, Polymorphism, Single Nucleotide, 150 000 MR Techniques in Brain Function, Article, White People, 03 medical and health sciences, Image processing, SDG 3 - Good Health and Well-being, ddc:570, medicine, Journal Article, Humans, Genetic Predisposition to Disease, Gene, METAANALYSIS, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], Neurology & Neurosurgery, Neuroscience (all), Height, [SCCO.NEUR]Cognitive science/Neuroscience, CONSORTIUM, Development of the nervous system, 1702 Cognitive Science, 030104 developmental biology, Genetic Loci, Human genome, BRAIN SIZE, 1109 Neurosciences, genetics [Phosphatidylinositol 3-Kinases], Neuroscience, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Contains fulltext : 165723pub.pdf (Publisher’s version ) (Closed access) Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (rhogenetic = 0.748), which indicates a similar genetic background and allowed us to identify four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, and Parkinson's disease, and were enriched near genes involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial volume and their link to physiological and pathological traits.

Published
2016

11. Circulating vitamin D concentration and age-related macular degeneration: Systematic review and meta-analysis

Author

Dan Milea, Guillaume T. Duval, Mickael Dinomais, Stéphanie Leruez, Cédric Annweiler, Morgane Drouet, Pierre-Yves Paré, Service de médecine interne et gérontologie clinique [Angers], Université d'Angers (UA)-Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM)-PRES Université Nantes Angers Le Mans (UNAM), Laboratoire de Mathématiques de l'INSA de Rouen Normandie (LMI), Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA), Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM), Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), Université d'Angers (UA), Singapore Eye Research Institute, Singapore National Eye Centre, Service d'ophtalmologie [Angers], and Singapore Eye Research Institute [Singapore] (SERI)

Subjects
medicine.medical_specialty, genetic structures, Cross-sectional study, [SDV]Life Sciences [q-bio], Eye, Gastroenterology, General Biochemistry, Genetics and Molecular Biology, vitamin D deficiency, Macular Degeneration, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Internal medicine, medicine, Vitamin D and neurology, Humans, Vitamin D, business.industry, Age-related macular degeneration, Obstetrics and Gynecology, Odds ratio, Neuroendocrinology, Macular degeneration, Vitamin D Deficiency, medicine.disease, eye diseases, 3. Good health, Surgery, Meta-analysis, Cross-Sectional Studies, chemistry, Older adults, Cohort, 030221 ophthalmology & optometry, sense organs, Cholecalciferol, business, 030217 neurology & neurosurgery
Abstract

International audience; Vitamin D may be involved in ocular function in older adults, but there is no current consensus on a possible association between circulating concentrations of 25-hydroxyvitamin D (25OHD) and the occurrence of age-related macular degeneration (AMD). Our objective was to systematically review and quantitatively assess the association of circulating 25OHD concentration with AMD. A Medline search was conducted in November 2015, with no date limit, using the MeSH terms "Vitamin D" OR "Vitamin D deficiency" OR "Ergocalciferols" OR 'Cholecalciferol' combined with "Age-related macular degeneration" OR "Macular degeneration" OR "Retinal degeneration" OR "Macula lutea" OR "Retina". Fixed and random-effects meta-analyses were performed to compute (i) standard mean difference in 25OHD concentration between AMD and non-AMD patients; (ii) AMD risk according to circulating 25OHD concentration. Of the 243 retrieved studies, 11 observational studies-10 cross-sectional studies and 1 cohort study-met the selection criteria. The number of participants ranged from 65 to 17,045 (52-100% women), and the number with AMD ranged from 31 to 1440. Circulating 25OHD concentration was 15% lower in AMD compared with non-AMD on average. AMD was inversely associated with the highest 25OHD quintile compared with the lowest (summary odds ratio (OR)=0.83 [95%CI:0.71-0.97]), notably late AMD (summary OR=0.47 [95%CI:0.28-0.79]). Circulating 25OHD

Published
2016

12. Vitamin D insufficiency and cognitive impairment in Asians: a multi-ethnic population-based study and meta-analysis

Author

C.-Y. Cheng, Tien Yin Wong, Mohammad Kamran Ikram, Charumathi Sabanayagam, Dan Milea, Heather E. Whitson, Cédric Annweiler, Ecosse L. Lamoureux, Laboratoire de Psychologie des Pays de la Loire (LPPL), Université d'Angers (UA)-Université de Nantes - UFR Lettres et Langages (UFRLL), Université de Nantes (UN)-Université de Nantes (UN), Singapore Eye Research Institute, Singapore National Eye Centre, Duke University Medical Center, Institut des Sciences Chimiques de Rennes (ISCR), Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Ecole Nationale Supérieure de Chimie de Rennes (ENSCR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), and Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Nationale Supérieure de Chimie de Rennes (ENSCR)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Gerontology, Male, medicine.medical_specialty, Asia, Cross-sectional study, Population, vitamin D deficiency, 03 medical and health sciences, 0302 clinical medicine, Cognition, Asian People, Risk Factors, Internal medicine, Internal Medicine, medicine, Vitamin D and neurology, Humans, 030212 general & internal medicine, Effects of sleep deprivation on cognitive performance, Vitamin D, education, Aged, education.field_of_study, Singapore, business.industry, Middle Aged, medicine.disease, Vitamin D Deficiency, Confidence interval, Cross-Sectional Studies, Meta-analysis, Older adults, [SCCO.PSYC]Cognitive science/Psychology, Female, business, Cognition Disorders, 030217 neurology & neurosurgery
Abstract

International audience; The relationship between vitamin D insufficiency and cognitive impairment remains equivocal in Asians. We examined the association between circulating 25-hydroxyvitamin D (25OHD) concentration and cognitive performance in a large multi-ethnic Singaporean population-based study. We also conducted a meta-analysis of 25OHD concentrations amongst cognitively impaired older adults in Asia. Methods Our population-based cross-sectional study included 2273 persons ≥60 years of age from the Singapore Epidemiology of Eye Diseases (SEED) study (mean ± SD age 70.4 ± 6.2 years; 44.7% female), who were categorized according to 25OHD concentration (i.e. ≤10, 10.1–20 and \textgreater20 ng mL−1). The 25OHD concentration was measured and adjusted to reflect a deseasonalized value. Cognition was assessed using the total and domain scores of the Abbreviated Mental Test (AMT). Global cognitive impairment was defined as AMT score of ≤6 if 0–6 years of education and AMT score of ≤8 if \textgreater7 years of education. Fully adjusted multivariate models were used. We included seven studies in a meta-analysis of 25OHD and cognition in Asia (6068 participants; 1179 cognitively impaired cases). Results Participants with 25OHD levels \textgreater20 ng mL−1 (n = 1302) had higher AMT total scores (mean ± SD 8.5 ± 1.9) and were less likely to have cognitive impairment (14.1%) than participants with lower 25OHD levels (overall P \textless 0.001, P-trend \textless 0.001). Deseasonalized 25OHD concentration was associated with AMT score (β = 0.10 per 10 ng mL−1, P = 0.035). Vitamin D insufficiency (25OHD ≤20 ng mL−1) was associated with global cognitive impairment (OR 1.56, P = 0.028). Specifically, 25OHD concentration correlated with semantic memory (r = 0.08, P = 0.009) and orientation in time (r = 0.09, P = 0.003). In the meta-analysis, the pooled mean 25OHD difference was −6.83 ng mL−1 (95% confidence interval −11.36; −2.30), indicating lower 25OHD concentrations amongst cognitively impaired compared to cognitively healthy participants in Asia. Conclusion Vitamin D insufficiency is associated with a greater likelihood of and more severe cognitive impairment in Asian populations.

Published
2016

13. New Linear and Star-Shaped Thermogelling Poly([R]-3-hydroxybutyrate) Copolymers

Author

Qingqing Dou, Sing Shy Liow, Ghislaine Barouti, Xian Jun Loh, Hongye Ye, Clément Orione, Sophie M. Guillaume, Institut des Sciences Chimiques de Rennes (ISCR), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Ecole Nationale Supérieure de Chimie de Rennes (ENSCR)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Institute of Materials Research and Engineering (IMRE), Agency for science, technology and research [Singapore] (A*STAR), Centre Régional de Mesures Physiques de l'Ouest (CRMPO), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), National University of Singapore (NUS), Singapore Eye Research Institute, Singapore National Eye Centre, Rennes Métropole, Fondation pour la Recherche Médicale, A*STAR, IMRE, A*STAR Personal Care Program Grant, Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Nationale Supérieure de Chimie de Rennes (ENSCR)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), and Université de Rennes (UR)

Subjects
Polymers, Acrylic Resins, Hydroxybutyrates, 02 engineering and technology, 01 natural sciences, Micelle, Polyethylene Glycols, Polymerization, chemistry.chemical_compound, Copolymer, Poly([R]-3-hydroxybutyrate) (PHB), Micelles, chemistry.chemical_classification, Drug Carriers, Molecular Structure, Atom-transfer radical-polymerization, Chemistry, Temperature, Hydrogels, Polymer, 021001 nanoscience & nanotechnology, Methacrylates, 0210 nano-technology, Hydrophobic and Hydrophilic Interactions, Cell Survival, Polyesters, thermo-responsive polymer, 010402 general chemistry, Methacrylate, Catalysis, Cell Line, Differential scanning calorimetry, Polymethacrylic Acids, Polymer chemistry, Prohibitins, Humans, polyester, multi-arm polymer, Organic Chemistry, technology, industry, and agriculture, water-soluble polymer, General Chemistry, Fibroblasts, 0104 chemical sciences, Drug Liberation, [CHIM.POLY]Chemical Sciences/Polymers, Doxorubicin, Propylene Glycols, drug delivery, hydrogel, Ethylene glycol
Abstract

International audience; The synthesis of multi-arm poly([R]-3-hydroxybutyrate) (PHB)-based triblock copolymers (poly([R]-3-hydroxybutyrate)-b-poly(N-isopropylacrylamide)-b-[[poly(methyl ether methacrylate)-g-poly(ethylene glycol)]-co-[poly(methacrylate)-g-poly(propylene glycol)]], PHB-b-PNIPAAM-b-(PPEGMEMA-co-PPPGMA), and their subsequent self-assembly into thermo-responsive hydrogels is described. Atom transfer radical polymerization (ATRP) of N-isopropylacrylamide (NIPAAM) followed by poly(ethylene glycol) methyl ether methacrylate (PEGMEMA) and poly(propylene glycol) methacrylate (PPGMA) was achieved from bromoesterified multi-arm PHB macroinitiators. The composition of the resulting copolymers was investigated by 1H and 13C J-MOD NMR spectroscopy as well as size-exclusion chromatography (SEC), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). The copolymers featuring different architectures and distinct hydrophilic/hydrophobic contents were found to self-assemble into thermo-responsive gels in aqueous solution. Rheological studies indicated that the linear one-arm PHB-based copolymer tend to form a micellar solution, whereas the two- and four-arm PHB-based copolymers afforded gels with enhanced mechanical properties and solid-like behavior. These investigations are the first to correlate the gelation properties to the arm number of a PHB-based copolymer. All copolymers revealed a double thermo-responsive behavior due to the NIPAAM and PPGMA blocks, thus allowing first the copolymer self-assembly at room temperature, and then the delivery of a drug at body temperature (37 °C). The non-significant toxic response of the gels, as assessed by the cell viability of the CCD-112CoN human fibroblast cell line with different concentrations of the triblock copolymers ranging from 0.03 to 1 mg mL−1, suggest that these PHB-based thermo-responsive gels are promising candidate biomaterials for drug-delivery applications.

Published
2016

14. Classification of SD-OCT Volumes for DME Detection: An Anomaly Detection Approach

Author

Désiré Sidibé, Shrinivasan Sankar, Dan Milea, Tien Yin Wong, Yin Bun Cheung, Ecosse L. Lamoureux, Fabrice Meriaudeau, Sidibé, Désiré, Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Singapore Eye Research Institute, Singapore National Eye Centre, Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, and HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement

Subjects
SD-OCT, genetic structures, Computer science, Local binary patterns, Diabetic macular edema, [ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 01 natural sciences, 010309 optics, 03 medical and health sciences, Gaussian Mixture Model, 0302 clinical medicine, [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Optical coherence tomography, 0103 physical sciences, medicine, Computer vision, Sensitivity (control systems), Local Binary Pattern, Blindness, medicine.diagnostic_test, business.industry, Anomaly (natural sciences), [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], medicine.disease, Mixture model, eye diseases, Diabetic Macular Edema, Outlier, Anomaly detection, Artificial intelligence, business, 030217 neurology & neurosurgery
Abstract

International audience; Diabetic Macular Edema (DME) is the leading cause of blindness amongst diabetic patients worldwide. It is characterized by accumulation of water molecules in the macula leading to swelling. Early detection of the disease helps prevent further loss of vision. Naturally, automated detection of DME from Optical Coherence Tomography (OCT) volumes plays a key role. To this end, a pipeline for detecting DME diseases in OCT volumes is proposed in this paper. The method is based on anomaly detection using Gaussian Mixture Model (GMM). It starts with pre-processing the B-scans by resizing, flattening, filtering and extracting features from them. Both intensity and Local Binary Pattern (LBP) features are considered. The dimensionality of the extracted features is reduced using PCA. As the last stage, a GMM is fitted with features from normal volumes. During testing, features extracted from the test volume are evaluated with the fitted model for anomaly and classification is made based on the number of B-scans detected as outliers. The proposed method is tested on two OCT datasets and achieved a sensitivity and a specificity of 80% and 93% on the first dataset, and 100% and 80% on the second one. Moreover, the experiments show that the proposed method achieves better classification performances than other recently published works.

Published
2016

15. Classification of SD-OCT Volumes Using Local Binary Patterns: Experimental Validation for DME Detection

Author

Désiré Sidibé, Ecosse L. Lamoureux, Fabrice Meriaudeau, Guillaume Lemaitre, Carol Y. Cheung, Joan Massich, Dan Milea, Mojdeh Rastgoo, Tien Yin Wong, Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Department of Ophthalmology and Visual Science, The Chinese University of Hong Kong [Hong Kong], Singapore Eye Research Institute, Singapore National Eye Centre, Centre for Intelligent Signal and Imaging Research (Universiti Teknologi Petronas) ( CISIR ), Singapore French Institute (IFS), Singapore Eye Research Institute (SERI), Regional Council of Burgundy 2015-9201AAO050S02760, Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Centre for Intelligent Signal and Imaging Research [Petronas] (CISIR), Universiti Teknologi PETRONAS (UTP), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Arts et Métiers (ENSAM), HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, and Lemaitre, Guillaume

Subjects
genetic structures, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, [ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing, [ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], 0302 clinical medicine, [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Segmentation, lcsh:Ophthalmology, Speckle, LBP, Diagnosis, Prevalence, Preprocessor, Computer vision, medicine.diagnostic_test, [ INFO.INFO-IM ] Computer Science [cs]/Medical Imaging, Experimental validation, Diabetic Macular Edema, [ SDV.MHEP.OS ] Life Sciences [q-bio]/Human health and pathology/Sensory Organs, Optical Coherence Tomography, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Research Article, Article Subject, Local binary patterns, 03 medical and health sciences, Speckle pattern, Optical coherence tomography, [ SDV.MHEP ] Life Sciences [q-bio]/Human health and pathology, Medical imaging, medicine, DME, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Coherence (signal processing), Texture, [SDV.MHEP.OS]Life Sciences [q-bio]/Human health and pathology/Sensory Organs, Retinopathy, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, business.industry, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Pattern recognition, eye diseases, Ophthalmology, OCT, lcsh:RE1-994, 030221 ophthalmology & optometry, Images, Artificial intelligence, business, 030217 neurology & neurosurgery, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

International audience; This paper addresses the problem of automatic classification of Spectral Domain OCT (SD-OCT) data for automatic identification of patients with Diabetic Macular Edema (DME) versus normal subjects. Optical Coherence Tomography (OCT) has been a valuable diagnostic tool for DME, which is among the most common causes of irreversible vision loss in individuals with diabetes. Here, a classification framework with five distinctive steps is proposed and we present an extensive study of each step. Our method considers combination of various pre-processings in conjunction with Local Binary Patterns (LBP) features and different mapping strategies. Using linear and non-linear classifiers, we tested the developed framework on a balanced cohort of 32 patients. Experimental results show that the proposed method outperforms the previous studies by achieving a Sensitivity (SE) and Specificity (SP) of 81.2% and 93.7%, respectively. Our study concludes that the 3D features and high-level representation of 2D features using patches achieve the best results. However, the effects of pre-processing is inconsistent with respect to different classifiers and feature configurations.

Published
2016

16. Multiethnic Genome-Wide Association Study of Cerebral White Matter Hyperintensities on MRI

Author

Susan H. Blanton, Ashley Beecham, Pamela J. Schreiner, Ralph L. Sacco, Stéphanie Debette, Ben A. Oostra, Marian Beekman, M. Arfan Ikram, Edith Hofer, Anna Maria Töglhofer, Alexander Teumer, Ganesh Chauhan, Clinton B. Wright, Meike W. Vernooij, Wiro J. Niessen, Aad van der Lugt, Cornelia M. van Duijn, Christophe Tzourio, Matthias Nauck, Bernard Mazoyer, Bettina von Sarnowski, Alexa S. Beiser, Susan R. Heckbert, André G. Uitterlinden, Alex P. Zijdenbos, David S. Knopman, Paul Freudenberger, Myriam Fornage, Maaike Schuur, Stephen Turner, Matthew Traylor, Qiong Yang, Fabrice Crivello, P. Eline Slagboom, Ian J. Deary, Sharon L.R. Kardia, Cora E. Lewis, Stella Trompet, Mike A. Nalls, Jennifer A. Smith, Katrin Hegenscheid, Hans J. Grabe, Lenore J. Launer, Reinhold Schmidt, Albert V. Smith, M. Kamran Ikram, Kumar B. Rajan, Mariza de Andrade, Sudha Seshadri, Lorna M. Lopez, Philip L. De Jager, Albert Hofman, Joshua C. Bis, Gerardo Heiss, Neelum T. Aggarwal, Elizabeth J. Atkinson, Carla A. Ibrahim-Verbaas, David C. Liewald, Anton J. M. de Craen, Jing Wang, David J. Stott, Sandra Barral, Adam M. Brickman, Mohamad Habes, Eric Boerwinkle, Katharina Wittfeld, Jerome I. Rotter, Saima Hilal, R. Nick Bryan, Charles C. DeCarli, Mark A. van Buchem, Mitchell S.V. Elkind, Rebecca F. Gottesman, Christiane Wolf, Vincent Chouraki, Jeroen van der Grond, Jiemin Liao, Joris Deelen, Stephen Sidney, Kenneth Rice, Vilmundur Guðnason, Hieab H.H. Adams, Benjamin F.J. Verhaaren, Tien Yin Wong, Oliver Martinez, Denis A. Evans, Helena Schmidt, W. T. Longstreth, J. Wouter Jukema, Richard Mayeux, Joanna M. Wardlaw, Thomas H. Mosley, Michelle Luciano, Sigurdur Sigurdsson, Carole Dufouil, Christopher Chen, Philippe Amouyel, Wei Zhao, John C. van Swieten, Bruce M. Psaty, Hae-Won Uh, B. Gwen Windham, Erasmus University Medical Center [Rotterdam] (Erasmus MC), INSERM U897, University of Bordeaux, France, University of Washington [Seattle], University of Michigan [Ann Arbor], University of Michigan System, Netherlands Consortium for Healthy Ageing, Leiden, The Netherlands, Institut Gilbert-Laustriat : Biomolécules, Biotechnologie, Innovation Thérapeutique, Université Louis Pasteur - Strasbourg I-Centre National de la Recherche Scientifique (CNRS), John P. Hussman Institute for Human Genomics, University of Miami Leonard M. Miller School of Medicine (UMMSM), Rush University Medical Center [Chicago], University of Edinburgh, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands, Depts of Radiology, Leiden University Medical Center (LUMC), Universiteit Leiden-Universiteit Leiden, Department of Materials Science and Metallurgy [Cambridge University] (DMSM), University of Cambridge [UK] (CAM), JRC Institute for Transuranium Elements [Karlsruhe] (ITU ), European Commission - Joint Research Centre [Karlsruhe] (JRC), Greifswald University Hospital, Division of Biomedical Statistics and Informatics, Mayo Clinic, Division of Biomedical Statistics and Informatics, Mayo Clinic, Laboratoire Interuniversitaire des Systèmes Atmosphériques (LISA (UMR_7583)), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Boston University School of Medicine (BUSM), Boston University [Boston] (BU), Genetics, The University of Texas Health Science Center at Houston (UTHealth), Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University [New York], Perelman School of Medicine, University of Pennsylvania, INSERM Research Center for Epidemiology and Biostatistics (U897) Team Neuroepidemiology, Bordeaux, France College of Health Sciences, University of Bordeaux, Bordeaux, France, Systèmes et Applications des Technologies de l'Information et de l'Energie (SATIE), École normale supérieure - Cachan (ENS Cachan)-Université Paris-Sud - Paris 11 (UP11)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-École normale supérieure - Rennes (ENS Rennes)-Université de Cergy Pontoise (UCP), Université Paris-Seine-Université Paris-Seine-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Centre National de la Recherche Scientifique (CNRS), Université Lille Nord de France (COMUE), Department of neurology, Groupe d'Imagerie Neurofonctionnelle (GIN - UMR 5296), Service NEUROSPIN (NEUROSPIN), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), Dept of Psychology, Molecular Epidemiology, Harvard Medical School [Boston] (HMS), Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA, Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston]-Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Program in Translational NeuroPsychiatric Genomics, Brigham and Women's Hospital [Boston], Columbia Mailman School of Public Health, Laboratoire pharmaceutique Lilly France [Neuilly-sur-Seine], Institute of Molecular Biology & Biochemistry, Johns Hopkins University School of Medicine [Baltimore], Faculty of Medicine, University of Iceland [Reykjavik], The Icelandic Heart Association, Kopavogur, Iceland, Institutes for Community Medicine, Department of Epidemiology, University of Washington, Group Health Research Institute, Group Health Cooperative, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC), National University of Singapore (NUS), Université Grenoble Alpes - UFR Sciences de l'Homme et de la Société (UGA UFR SHS), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Université Grenoble Alpes - UFR Langage, lettres et arts du spectacle, information et communication - Dpt Sciences de l'information et de la communication (UGA UFR LLASIC SIC), Mayo Clinic [Rochester], Academic Unit of Inflammation and Tumour Targeting, Dept. of Oncology, University of Sheffield Medical School, East China University of Science and Technology, Medstar Research Institute, Institut de pharmacologie et de biologie structurale (IPBS), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Bioinformatics, GlaxoSmithKline, National Institutes of Health [Bethesda] (NIH), Institute of Clinical Chemistry and Laboratory Medicine, Universität Greifswald - University of Greifswald, Delft University of Technology (TU Delft), Cardiovascular Health Research Unit, University of Washington, Department of Medicine, University of Washington, Department of Health Services, University of Washington, Department of Biostatistics, University of Washington, Cedars-Sinai Medical Center, Dept of Neurology, Univ Medicine of Greifswald, Germany, Department of Physics [Stockholm], Stockholm University, University of Minnesota [Twin Cities] (UMN), University of Minnesota System, Kaiser Permanente, Broad Institute [Cambridge], Harvard University-Massachusetts Institute of Technology (MIT), Department of Medical Biochemistry and Microbiology, Uppsala University, Institute of Cardiovascular and Medical Sciences [Glasgow], University of Glasgow, King‘s College London, Institute of Molecular Biology and Biochemistry, Centre for Molecular Medicine, Medical University of Graz, Graz, Austria, Research Centre for Stroke & Dementia, St George 's Univ of London, Interuniversity Cardiology Institute Netherlands, SAC, Bush Estate, School Medicine, University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE)-Pennsylvania Commonwealth System of Higher Education (PCSHE), Framingham Heart Study, Boston University [Boston] (BU)-National Heart, Lung, and Blood Institute [Bethesda] (NHLBI), Singapore Eye Research Institute, Singapore National Eye Centre, University of Oslo (UiO), German Research Center for Neurodegenerative Diseases - Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Ninewells Hospital and Medical School, Biomedical Research Centre, University of Dundee, Dundee Technopole, CXR Biosciences Ltd, Department of Atmospheric, Oceanic, and Space Sciences [Ann Arbor] (AOSS), University of Michigan System-University of Michigan System, University of Miami [Coral Gables], Centre d'Immunologie de Marseille - Luminy (CIML), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Biospective [Montréal], Dept of Epidemiology & Public Health Sciences, Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement - U 1167 (RID-AGE), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), University of Mississippi Medical Center (UMMC), Department of Neurology and Center for Neuroscience, University of California at Davis, Sacramento, University of California [Davis] (UC Davis), University of California (UC)-University of California (UC), Center for Medical Systems Biology, Netherlands Genomics Initiative, Leiden University Medical Center, Leiden, The Netherlands, Austrian Institute of Technology [Vienna] (AIT), Donders Institute for Brain, Cognition and Behaviour, Radboud University [Nijmegen], Department of Psychiatry and Psychotherapy, HELIOS Klinikum Stralsund Hanseatic-Greifswald University Hospital, Human Genetics Center, University of Pennsylvania [Philadelphia], Université Paris-Seine-Université Paris-Seine-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Centre National de la Recherche Scientifique (CNRS), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Service NEUROSPIN (NEUROSPIN), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Memory Aging & Cognition Centre, National Univ of Singapore, Singapore, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, China, Centre National de la Recherche Scientifique (CNRS)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Harvard University [Cambridge]-Massachusetts Institute of Technology (MIT), National Heart, Lung, and Blood Institute [Bethesda] (NHLBI)-Boston University [Boston] (BU), Dept of Ophthalmology, National Univ of Singapore & National Univ Health System, Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille)-Université de Lille-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), University of California-University of California, Radboud university [Nijmegen], Epidemiology, Radiology & Nuclear Medicine, General Practice, Neurology, Medical Informatics, Clinical Genetics, Internal Medicine, Human genetics, NCA - neurodegeneration, Hal, GIN, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), and HESAM Université (HESAM)-HESAM Université (HESAM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Oncology, Male, single nucleotide, Pathology, Genome-wide association study, leukoencephalopathies, polymorphisms, single nucleotide, Chromosomes, Human, Genetics (clinical), Aged, 80 and over, education.field_of_study, Continental Population Groups, cerebrovascular disorders, Middle Aged, White Matter, 3. Good health, Stroke, genetics [Stroke], Female, cerebral small vessel diseases, Alzheimer's disease, Cardiology and Cardiovascular Medicine, medicine.medical_specialty, hypertension, Population, genetics [Chromosomes, Human], Article, Meta-Analysis as Topic, Internal medicine, Genetics, medicine, Dementia, Humans, ddc:610, 1000 Genomes Project, education, Genetic association, Aged, Intracerebral hemorrhage, genome-wide association study, Models, Genetic, business.industry, [SCCO.NEUR]Cognitive science/Neuroscience, [SCCO.NEUR] Cognitive science/Neuroscience, Racial Groups, medicine.disease, ethnology [Stroke], Hyperintensity, Genetic Loci, pathology [Stroke], business, polymorphisms, Genome-Wide Association Study
Abstract

Background— The burden of cerebral white matter hyperintensities (WMH) is associated with an increased risk of stroke, dementia, and death. WMH are highly heritable, but their genetic underpinnings are incompletely characterized. To identify novel genetic variants influencing WMH burden, we conducted a meta-analysis of multiethnic genome-wide association studies. Methods and Results— We included 21 079 middle-aged to elderly individuals from 29 population-based cohorts, who were free of dementia and stroke and were of European (n=17 936), African (n=1943), Hispanic (n=795), and Asian (n=405) descent. WMH burden was quantified on MRI either by a validated automated segmentation method or a validated visual grading scale. Genotype data in each study were imputed to the 1000 Genomes reference. Within each ethnic group, we investigated the relationship between each single-nucleotide polymorphism and WMH burden using a linear regression model adjusted for age, sex, intracranial volume, and principal components of ancestry. A meta-analysis was conducted for each ethnicity separately and for the combined sample. In the European descent samples, we confirmed a previously known locus on chr17q25 ( P =2.7×10 −19 ) and identified novel loci on chr10q24 ( P =1.6×10 −9 ) and chr2p21 ( P =4.4×10 −8 ). In the multiethnic meta-analysis, we identified 2 additional loci, on chr1q22 ( P =2.0×10 −8 ) and chr2p16 ( P =1.5×10 −8 ). The novel loci contained genes that have been implicated in Alzheimer disease (chr2p21 and chr10q24), intracerebral hemorrhage (chr1q22), neuroinflammatory diseases (chr2p21), and glioma (chr10q24 and chr2p16). Conclusions— We identified 4 novel genetic loci that implicate inflammatory and glial proliferative pathways in the development of WMH in addition to previously proposed ischemic mechanisms.

Published
2015

18. Single-Shot 3D Imaging Meta-Microscope.

Author

Hao H, Wang H, Wang X, Ding X, Zhang S, Pan CF, Rahman MA, Ling T, Li H, Tan J, Yang JKW, Lu W, Liu J, and Hu G

Abstract

Three-dimensional (3D) imaging enables high-precision and high-resolution axial positioning, which is crucial for biological imaging, semiconductor defect monitoring, and other applications. Conventional implementations rely on bulky optical elements or scanning mechanisms, resulting in low speed and complicated setups. Here, we generate the double-helix (DH) point spread function with an all-dielectric metasurface and thus innovate the 3D imaging microscope (hence dubbed meta-microscope), both in 4f and 2f imaging systems. The 4f-meta-microscope with a numerical aperture of 0.7 achieves an axial localization accuracy below 0.12 μm within a 15.47 μm detection range, while the 2f-DH meta-microscope with a numerical aperture of 0.3 shows a 1.12 μm accuracy within a 227.33 μm range. We also demonstrate single-shot and accurate 3D biological imaging of the mouse kidney tissue and peach anther, providing a comprehensive and efficient approach for 3D bioimaging and other applications through a single-shot 3D meta-microscope.

Published
2024
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19. Current research and future strategies for the management of vision-threatening diabetic retinopathy.

Author

Li H, Jia W, Vujosevic S, Sabanayagam C, Grauslund J, Sivaprasad S, and Wong TY

Abstract

Diabetic retinopathy (DR) is a major ocular complication of diabetes and the leading cause of blindness and visual impairment, particularly among adults of working-age adults. Although the medical and economic burden of DR is significant and its global prevalence is expected to increase, particularly in low- and middle-income countries, a large portion of vision loss caused by DR remains preventable through early detection and timely intervention. This perspective reviewed the latest developments in research and innovation in three areas, first novel biomarkers (including advanced imaging modalities, serum biomarkers, and artificial intelligence technology) to predict the incidence and progression of DR, second, screening and early detection of referable DR and vision-threatening DR (VTDR), and finally, novel therapeutic strategies for VTDR, including diabetic macular oedema (DME), with the goal of reducing diabetic blindness., (Copyright © 2024. Published by Elsevier Inc.)

Published
2024
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20. Biomechanical changes occur in myopic choroidal stroma and mirror those in the adjacent sclera.

Author

Ito K, Hoerig C, Dan YS, McFadden SA, Mamou J, and Hoang QV

Abstract

Retina-derived growth signals relayed from the choroid to the sclera cause remodeling of the extracellular scleral matrix, resulting in myopic ocular elongation. However, to the best of our knowledge, no studies have assessed changes in choroidal stromal biomechanical properties during myopia progression. Here we utilized 7 µm-resolution scanning acoustic microscopy (SAM) to assess biomechanical properties (bulk modulus (K) and mass density (rho)) of choroidal stroma from guinea pig eyes with form-deprivation (FD) induced myopia. The choroidal stroma had considerable intrinsic strength arising from its biomechanical properties and these were differentially affected by myopia in central and peripheral regions. Choroidal stromal biomechanical values were also highly correlated with those in adjacent scleral regions, and the choroidal stromal-scleral association was stronger in myopic eyes. Biomechanical changes observed in the choroidal stroma of myopic eyes were mirrored to those observed in the adjacent sclera. These findings suggest that choroidal stromal remodeling may accompany myopia and open the door to the source of the signals that cause scleral remodeling in myopia., (© 2024. The Author(s).)

Published
2024
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21. Key role for inflammation-related signaling in the pathogenesis of myopia based on evidence from proteomics analysis.

Author

Jiang L, Koh JHZ, Seah SHY, Dan YS, Wang Z, Chan X, Zhou L, Barathi VA, and Hoang QV

Subjects
Humans, Animals, Disease Models, Animal, Cytokines metabolism, Myopia metabolism, Myopia pathology, Signal Transduction, Proteomics methods, Inflammation metabolism
Abstract

The mechanisms underlying myopia pathogenesis are not well understood. Using publicly-available human and animal datasets, we expound on the roles of known, implicated proteins, and new myopia-related signaling pathways were hypothesized. Proteins identified from human serum or ocular fluids, and from ocular tissues in myopic animal models, were uploaded and analyzed with the QIAGEN Ingenuity Pathway Analysis (IPA) software (March 2023). With each IPA database update, more potentially-relevant proteins and signaling pathways previously unavailable during data acquisition are added, allowing extraction of novel conclusions from existing data. Canonical pathway analysis was used to analyze these data and calculate an IPA activation z-score-which indicates not only whether an association is significant, but also whether the pathway is likely activated or inhibited. Cellular immune response and cytokine signaling were frequently found to be affected in both human and animal myopia studies. Analysis of two publicly-available proteomic datasets highlighted a potential role of the innate immune system and inflammation in myopia development, detailing specific signaling pathways involved such as Granzyme A (GzmA) and S100 family signaling in the retina, and activation of myofibroblast trans-differentiation in the sclera. This perspective in myopia research may facilitate development of more effective and targeted therapeutic agents., (© 2024. The Author(s).)

Published
2024
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22. Effect of childhood atropine treatment on adult choroidal thickness using sequential deep learning-enabled segmentation.

Author

Li Y, Wong D, Sreng S, Chung J, Toh A, Yuan H, Eppenberger LS, Leow C, Ting D, Liu N, Schmetterer L, Saw SM, Jonas JB, Chia A, and Ang M

Abstract

Purpose: To describe choroidal thickness measurements using a sequential deep learning segmentation in adults who received childhood atropine treatment for myopia control., Design: Prospective, observational study., Methods: Choroidal thickness was measured by swept-source optical coherence tomography in adults who received childhood atropine, segmented using a sequential deep learning approach., Results: Of 422 eyes, 94 (22.3 %) had no previous exposure to atropine treatment, while 328 (77.7 %) had received topical atropine during childhood. After adjusting for age, sex, and axial length, childhood atropine exposure was associated with a thicker choroid by 32.1 μm (95 % CI, 9.2-55.0; P = 0.006) in the inner inferior, 23.5 μm (95 % CI, 1.9-45.1; P = 0.03) in the outer inferior, 21.8 μm (95 % CI, 0.76-42.9; P = 0.04) in the inner nasal, and 21.8 μm (95 % CI, 2.6-41.0; P = 0.03) in the outer nasal. Multivariable analysis, adjusted for age, sex, atropine use, and axial length, showed an independent association between central subfield choroidal thickness and the incidence of tessellated fundus (P < 0.001; OR, 0.97; 95 % CI, 0.96-0.98)., Conclusions: This study demonstrated that short-term (2-4 years) atropine treatment during childhood was associated with an increase in choroidal thickness of 20-40 μm in adulthood (10-20 years later), after adjusting for age, sex, and axial length. We also observed an independent association between eyes with thicker central choroidal measurements and reduced incidence of tessellated fundus. Our study suggests that childhood exposure to atropine treatment may affect choroidal thickness in adulthood., Competing Interests: Declaration of Competing Interest Dr Jost B. Jonas has disclosed European patent EP 3 271 392, JP 2021–119187, and US 2021 0340237 A1: Agents for use in the therapeutic or prophylactic treatment of myopia or hyperopia. Dr Audrey Chia has disclosed royalties from Myopine. Dr Leopold Schmetterer has disclosed consultancy fee from Thea Pharma., (Copyright © 2024. Published by Elsevier Inc.)

Published
2024
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23. Practice Patterns and Challenges in Managing Inherited Retinal Diseases across Asia-Pacific: A Survey from the APIED Network.

Author

Wong WM, Tham YC, Ayton LN, Britten-Jones AC, Edwards TL, Grigg J, Simunovic MP, Chen FK, Jin ZB, Shen RJ, Sui R, Yang L, Zhao C, Chen H, Li S, Ding X, Bhende M, Raman R, Sen P, Poornachandra B, Valen C, Manurung F, Sasongko MB, Ikeda H, Fujinami K, Woo SJ, Kim SJ, Bastion MC, Kamalden AT, Lott PP, Fong K, Shunmugam M, Lim A, Thapa R, Ibañez BMB, Koh A, Holder GE, Su X, Chan CM, Fenner BJ, Laude A, Ngo WK, Chen TC, Wang NK, Kang EY, Surawatsatien N, Pisuchpen P, Sujirakul T, Wongchaisuwat N, Apivatthakakul A, Kumaramanickavel G, Leroy B, Michaelides M, Pontikos N, Cheng CY, Pang CP, and Chen LJ

Abstract

Purpose: The objective of this paper is to shed light on the current landscape of genotyping practices, phenotyping practices and availability of essential vision rehabilitation management for inherited retinal diseases (IRD) in the Asia-Pacific (APAC) Region., Methods: The 62-item questionnaire was distributed electronically via email. The questions covered five domains: (1) structure of the IRD service and registry/database; (2) genotyping practices; (3) genetic counselling; (4) deep phenotyping practices; (5) low-vision rehabilitation services., Results: The survey was completed by 36 of 45 centres in twelve countries and regions in APAC. Among these centres, 42% reported managing more than 1000 patients. Notably, 39% of centres lack an IRD database or registry, and 44% of centres have tested less than one-quarter of their IRD patients. The majority of centres (67%) do not have genetic counsellors. While there was consistency in the imaging-based investigations, there was marked heterogeneity for functional testing using electrophysiology and formal perimetry. Only 34% of centres confirmed the availability of access to low-vision assistive devices., Conclusions: This study reveals several critical gaps in managing IRDs in the APAC region. These include the lack of IRD database/registry in one-third of centres, a substantial proportion of patients remaining genetically undiagnosed, and limited availability of genetic counsellors. The findings also underscore a need to harmonise investigations for evaluating retinal function and identify areas for improvement in the provision of low-vision rehabilitation services., (Copyright © 2024. Published by Elsevier Inc.)

Published
2024
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24. Anatomical compensation of retinal nerve fiber layer improves the detection of glaucoma between ethnicities.

Author

Chua J, Li C, Wong DWK, Chong RS, Husain R, Wong TT, Vass C, Cheng CY, Aung T, and Schmetterer L

Subjects
Humans, Male, Female, Middle Aged, Adult, Asian People, Retina diagnostic imaging, Retina pathology, India, Aged, Retinal Ganglion Cells pathology, China epidemiology, Ethnicity, Glaucoma diagnosis, Nerve Fibers pathology, Tomography, Optical Coherence methods
Abstract

The study aimed to evaluate the impact of compensating retinal nerve fiber layer (RNFL) thickness for demographic and anatomical factors on glaucoma detection in Chinese and Indian adults. A population-based study included 1995 healthy participants (1076 Chinese and 919 Indians) to construct a multivariable linear regression compensation model. This model was applied to 357 Chinese glaucoma patients, 357 healthy Chinese, and 357 healthy Indians using Cirrus spectral-domain optical coherence tomography (OCT). The compensated RNFL thickness considered age, refractive error, optic disc parameters, and retinal vessel density. Results showed that although the average RNFL thickness was significantly higher in Chinese participants compared to Indians, the compensation model reduced this difference to nonsignificance. Moreover, the compensation model significantly improved the area under the receiver operating characteristic curve (0.90 vs. 0.78; p<0.001), sensitivity (75% vs. 51%), and specificity (67% vs. 32%) in distinguishing Chinese glaucoma patients from healthy Indian individuals. The compensation model significantly enhanced the diagnostic accuracy of RNFL thickness in distinguishing glaucoma in the Chinese ethnic group compared to the OCT instrument's default values. These results suggest that modifying RNFL measurements based on individual characteristics can yield substantial benefits for glaucoma detection across ethnicities., (© 2024 The Author(s). Annals of the New York Academy of Sciences published by Wiley Periodicals LLC on behalf of The New York Academy of Sciences.)

Published
2024
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25. Predict and Protect: Evaluating the Double-Layer Sign in Age-Related Macular Degeneration.

Author

Sivaprasad S, Chandra S, Sadda S, Teo KYC, Thottarath S, de Cock E, Empeslidis T, and Esmaeelpour M

Abstract

Introduction: Advanced age-related macular degeneration (AMD) is a major cause of vision loss. Therefore, there is interest in precursor lesions that may predict or prevent the onset of advanced AMD. One such lesion is a shallow separation of the retinal pigment epithelium (RPE) and Bruch's membrane (BM), which is described by various terms, including double-layer sign (DLS)., Methods: In this article, we aim to examine and clarify the different terms referring to shallow separation of the RPE and BM. We also review current evidence on the outcomes associated with DLS: firstly, whether DLS is predictive of exudative neovascular AMD; and secondly, whether DLS has potential protective properties against geographic atrophy., Results: The range of terms used to describe a shallow separation of the RPE and BM reflects that DLS can present with different characteristics. While vascularised DLS appears to protect against atrophy but can progress to exudation, non-vascularised DLS is associated with an increased risk of atrophy. Optical coherence tomography (OCT) angiography (OCTA) is the principal method for identifying and differentiating various forms of DLS. If OCTA is unavailable or not practically possible, simplified classification of DLS as thick or thin, using OCT, enables the likelihood of vascularisation to be approximated. Research is ongoing to automate DLS detection by applying deep-learning algorithms to OCT scans., Conclusions: The term DLS remains applicable for describing shallow separation of the RPE and BM. Detection and classification of this feature provides valuable information regarding the risk of progression to advanced AMD. However, the appearance of DLS and its value in predicting AMD progression can vary between patients. With further research, individualised risks can be confirmed to inform appropriate treatment., (© 2024. The Author(s).)

Published
2024
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26. Chatbots Vs. Human Experts: Evaluating Diagnostic Performance of Chatbots in Uveitis and the Perspectives on AI Adoption in Ophthalmology.

Author

Rojas-Carabali W, Sen A, Agarwal A, Tan G, Cheung CY, Rousselot A, Agrawal R, Liu R, Cifuentes-González C, Elze T, Kempen JH, Sobrin L, Nguyen QD, de-la-Torre A, Lee B, Gupta V, and Agrawal R

Subjects
Humans, Male, Female, Middle Aged, Adult, Ophthalmologists, Diagnostic Techniques, Ophthalmological, Surveys and Questionnaires, Uveitis diagnosis, Artificial Intelligence, Ophthalmology
Abstract

Purpose: To assess the diagnostic performance of two chatbots, ChatGPT and Glass, in uveitis diagnosis compared to renowned uveitis specialists, and evaluate clinicians' perception about utilizing artificial intelligence (AI) in ophthalmology practice., Methods: Six cases were presented to uveitis experts, ChatGPT (version 3.5 and 4.0) and Glass 1.0, and diagnostic accuracy was analyzed. Additionally, a survey about the emotions, confidence in utilizing AI-based tools, and the likelihood of incorporating such tools in clinical practice was done., Results: Uveitis experts accurately diagnosed all cases (100%), while ChatGPT achieved a diagnostic success rate of 66% and Glass 1.0 achieved 33%. Most attendees felt excited or optimistic about utilizing AI in ophthalmology practice. Older age and high level of education were positively correlated with increased inclination to adopt AI-based tools., Conclusions: ChatGPT demonstrated promising diagnostic capabilities in uveitis cases and ophthalmologist showed enthusiasm for the integration of AI into clinical practice.

Published
2024
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27. Pathogenesis of Central Serous Chorioretinopathy and the Link Between Choroidal Hyperpermeability and Retinal Pigment Epithelium Pump Reversal.

Author

Fossataro F, Fossataro C, Abraham N, Fouad Y, Mrejen S, Tan ACS, Voichanski S, and Sarraf D

Subjects
Humans, Male, Female, Middle Aged, Adult, Multimodal Imaging, Acute Disease, Retrospective Studies, Central Serous Chorioretinopathy diagnosis, Central Serous Chorioretinopathy physiopathology, Retinal Pigment Epithelium pathology, Tomography, Optical Coherence, Fluorescein Angiography methods, Choroid pathology, Capillary Permeability, Indocyanine Green administration & dosage, Coloring Agents administration & dosage, Visual Acuity physiology, Laser Coagulation
Abstract

Purpose: To describe 6 cases of acute central serous chorioretinopathy (CSCR) and the response to laser treatment, focusing on the underlying pathogenic mechanism., Methods: Multimodal imaging from 6 eyes of 6 patients with acute and recurrent CSCR were reviewed, including fundus autofluorescence (FAF), fluorescein angiography (FA), indocyanine green angiography (ICGA), and optical coherence tomography (OCT) at baseline and after laser therapy., Results: In 3 of the 6 cases with acute CSCR, the hyporeflective lucency sign was identified with cross-sectional and en face OCT and co-localized with an intense active inkblot retinal pigment epithelium (RPE) leak on FA. The development of this sign was suggestive of active leakage into the subretinal space displacing overlying subretinal hyperreflective material (SHRM) and suggestive of a reversal of RPE pump function. All 6 cases were treated with focal laser to directly target the intense leakage points with remarkable resolution of the fluid due to destruction of the RPE cells mediating reversal of pump function., Conclusions: Unlike chronic CSCR in which degenerative changes of the RPE lead to oozing of fluid into the subretinal space, in acute forms of CSCR including bullous CSCR, there are focal leaks of the RPE that actively drive fluid into the subretinal space suggestive of RPE pump reversal. We propose that pachychoroid disease causes increased hydrostatic pressure and increased resistance to the RPE pump, thereby triggering a reversal in pump function. Understanding this concept can have therapeutic implications., (Published by Elsevier Inc.)

Published
2024
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28. Understanding the Prevalence and Risk Factor Profile of Olfactory Impairment and Its Impact on Patient Health Indicators and Economic Outcomes in Community-Dwelling Older Asian Adults.

Author

Man REK, Wong CMJ, Gupta P, Fenwick EK, Aravindhan A, Teo NWY, Charn TC, Forde C, and Lamoureux EL

Abstract

Background and Objectives: There is a paucity of data on the prevalence, risk factors, and impact of olfactory impairment (OI) on key health indicators and economic outcomes in Asian populations. We aimed to address these gaps in a population of community-dwelling older adults., Research Design and Methods: We included 2 101 participants (mean age ± standard deviation [ SD ]: 72.9 ± 8.1 years; 55.1% women) from the baseline assessment of the Population Health and Eye Disease Profile in Elderly Singaporeans (PIONEER) study (2017-2022). Any OI was based on a score of <11 on the 16-item identification segment of the Sniffin' Sticks test battery; subcategorized into hyposmia (score 9-10) and anosmia (score ≤8). Sociodemographic, clinical, and lifestyle risk determinants, health indicators (health-related quality of life, depressive symptoms, daily caloric intake, frailty, and cognitive impairment), and economic outcomes (healthcare expenditure, productivity loss) were assessed via standardized clinical testing and validated questionnaires. Multivariable logistic and linear regression models were utilized to explore the risk factor profile of OI across its severity spectrum and its impact on health indicators and economic outcomes., Results: The census-adjusted prevalence of any OI, hyposmia, and anosmia were 34.0%, 20.5%, and 13.5%, respectively. Older age and male gender were associated with increased likelihood of hyposmia and anosmia, while the presence of diabetes and >4 days/week alcohol consumption were associated with increased odds of having anosmia only (all p  < .05). Both hyposmia and anosmia were also associated with more than twofold increased odds of having CI., Discussion and Implications: Over a third of our community-dwelling older Singaporean population had OI, with 1-in-10 experiencing total olfaction loss. Those with OI had more than double the odds of having CI, regardless of its severity. Our results suggest the importance of community-based programs aimed at detecting and delaying the progression of OI in high-risk individuals., Competing Interests: None., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Gerontological Society of America.)

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2024
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29. Application of a deep-learning marker for morbidity and mortality prediction derived from retinal photographs: a cohort development and validation study.

Author

Nusinovici S, Rim TH, Li H, Yu M, Deshmukh M, Quek TC, Lee G, Chong CCY, Peng Q, Xue CC, Zhu Z, Chew EY, Sabanayagam C, Wong TY, Tham YC, and Cheng CY

Abstract

Background: Biological ageing markers are useful to risk stratify morbidity and mortality more precisely than chronological age. In this study, we aimed to develop a novel deep-learning-based biological ageing marker (referred to as RetiPhenoAge hereafter) using retinal images and PhenoAge, a composite biomarker of phenotypic age., Methods: We used retinal photographs from the UK Biobank dataset to train a deep-learning algorithm to predict the composite score of PhenoAge. We used a deep convolutional neural network architecture with multiple layers to develop our deep-learning-based biological ageing marker, as RetiPhenoAge, with the aim of identifying patterns and features in the retina associated with variations of blood biomarkers related to renal, immune, liver functions, inflammation, and energy metabolism, and chronological age. We determined the performance of this biological ageing marker for the prediction of morbidity (cardiovascular disease and cancer events) and mortality (all-cause, cardiovascular disease, and cancer) in three independent cohorts (UK Biobank, the Singapore Epidemiology of Eye Diseases [SEED], and the Age-Related Eye Disease Study [AREDS] from the USA). We also compared the performance of RetiPhenoAge with two other known ageing biomarkers (hand grip strength and adjusted leukocyte telomere length) and one lifestyle factor (physical activity) for risk stratification of mortality and morbidity. We explored the underlying biology of RetiPhenoAge by assessing its associations with different systemic characteristics (eg, diabetes or hypertension) and blood metabolite levels. We also did a genome-wide association study to identify genetic variants associated with RetiPhenoAge, followed by expression quantitative trait loci mapping, a gene-based analysis, and a gene-set analysis. Cox proportional hazards models were used to estimate the hazard ratios (HRs) and corresponding 95% CIs for the associations between RetiPhenoAge and the different morbidity and mortality outcomes., Findings: Retinal photographs for 34 061 UK Biobank participants were used to train the model, and data for 9429 participants from the SEED cohort and for 3986 participants from the AREDS cohort were included in the study. RetiPhenoAge was associated with all-cause mortality (HR 1·92 [95% CI 1·42-2·61]), cardiovascular disease mortality (1·97 [1·02-3·82]), cancer mortality (2·07 [1·29-3·33]), and cardiovascular disease events (1·70 [1·17-2·47]), independent of PhenoAge and other possible confounders. Similar findings were found in the two independent cohorts (HR 1·67 [1·21-2·31] for cardiovascular disease mortality in SEED and 2·07 [1·10-3·92] in AREDS). RetiPhenoAge had stronger associations with mortality and morbidity than did hand grip strength, telomere length, and physical activity. We identified two genetic variants that were significantly associated with RetiPhenoAge (single nucleotide polymorphisms rs3791224 and rs8001273), and were linked to expression quantitative trait locis in various tissues, including the heart, kidneys, and the brain., Interpretation: Our new deep-learning-derived biological ageing marker is a robust predictor of mortality and morbidity outcomes and could be used as a novel non-invasive method to measure ageing., Funding: Singapore National Medical Research Council and Agency for Science, Technology and Research, Singapore., Competing Interests: Declaration of interests THR and GL own stocks in MediWhale, to whom RetiAge was licensed. ZZ holds a National Health and Medical Research Council Investigator Grant (2010072) and owns two patents for biological age prediction from ocular images (AU2023903213A0 and CN114782361A). T-YW is a consultant for Aldropika Therapeutics, Bayer, Boehringer Ingelheim, Carl Zeiss, Genentech, Iveric Bio, Novartis, Oxurion, Plano, Roche, Sanofi, and Shanghai Henlius; is an inventor, holds patents, and is a co-founder of the start-up companies EyRiS and Visre; and has interests in, and develops digital solutions for, eye diseases, including diabetic retinopathy, outside of the submitted work. C-YC holds licences and receives consultation fees from MediWhale. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Published
2024
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30. A Competition for the Diagnosis of Myopic Maculopathy by Artificial Intelligence Algorithms.

Author

Qian B, Sheng B, Chen H, Wang X, Li T, Jin Y, Guan Z, Jiang Z, Wu Y, Wang J, Chen T, Guo Z, Chen X, Yang D, Hou J, Feng R, Xiao F, Li Y, El Habib Daho M, Lu L, Ding Y, Liu D, Yang B, Zhu W, Wang Y, Kim H, Nam H, Li H, Wu WC, Wu Q, Dai R, Li H, Ang M, Ting DSW, Cheung CY, Wang X, Cheng CY, Tan GSW, Ohno-Matsui K, Jonas JB, Zheng Y, Tham YC, Wong TY, and Wang YX

Abstract

Importance: Myopic maculopathy (MM) is a major cause of vision impairment globally. Artificial intelligence (AI) and deep learning (DL) algorithms for detecting MM from fundus images could potentially improve diagnosis and assist screening in a variety of health care settings., Objectives: To evaluate DL algorithms for MM classification and segmentation and compare their performance with that of ophthalmologists., Design, Setting, and Participants: The Myopic Maculopathy Analysis Challenge (MMAC) was an international competition to develop automated solutions for 3 tasks: (1) MM classification, (2) segmentation of MM plus lesions, and (3) spherical equivalent (SE) prediction. Participants were provided 3 subdatasets containing 2306, 294, and 2003 fundus images, respectively, with which to build algorithms. A group of 5 ophthalmologists evaluated the same test sets for tasks 1 and 2 to ascertain performance. Results from model ensembles, which combined outcomes from multiple algorithms submitted by MMAC participants, were compared with each individual submitted algorithm. This study was conducted from March 1, 2023, to March 30, 2024, and data were analyzed from January 15, 2024, to March 30, 2024., Exposure: DL algorithms submitted as part of the MMAC competition or ophthalmologist interpretation., Main Outcomes and Measures: MM classification was evaluated by quadratic-weighted κ (QWK), F1 score, sensitivity, and specificity. MM plus lesions segmentation was evaluated by dice similarity coefficient (DSC), and SE prediction was evaluated by R2 and mean absolute error (MAE)., Results: The 3 tasks were completed by 7, 4, and 4 teams, respectively. MM classification algorithms achieved a QWK range of 0.866 to 0.901, an F1 score range of 0.675 to 0.781, a sensitivity range of 0.667 to 0.778, and a specificity range of 0.931 to 0.945. MM plus lesions segmentation algorithms achieved a DSC range of 0.664 to 0.687 for lacquer cracks (LC), 0.579 to 0.673 for choroidal neovascularization, and 0.768 to 0.841 for Fuchs spot (FS). SE prediction algorithms achieved an R2 range of 0.791 to 0.874 and an MAE range of 0.708 to 0.943. Model ensemble results achieved the best performance compared to each submitted algorithms, and the model ensemble outperformed ophthalmologists at MM classification in sensitivity (0.801; 95% CI, 0.764-0.840 vs 0.727; 95% CI, 0.684-0.768; P = .006) and specificity (0.946; 95% CI, 0.939-0.954 vs 0.933; 95% CI, 0.925-0.941; P = .009), LC segmentation (DSC, 0.698; 95% CI, 0.649-0.745 vs DSC, 0.570; 95% CI, 0.515-0.625; P < .001), and FS segmentation (DSC, 0.863; 95% CI, 0.831-0.888 vs DSC, 0.790; 95% CI, 0.742-0.830; P < .001)., Conclusions and Relevance: In this diagnostic study, 15 AI models for MM classification and segmentation on a public dataset made available for the MMAC competition were validated and evaluated, with some models achieving better diagnostic performance than ophthalmologists.

Published
2024
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31. Review of emerging trends and projection of future developments in large language models research in ophthalmology.

Author

Wong M, Lim ZW, Pushpanathan K, Cheung CY, Wang YX, Chen D, and Tham YC

Subjects
Humans, Biomedical Research trends, Language, Ophthalmology trends
Abstract

Background: Large language models (LLMs) are fast emerging as potent tools in healthcare, including ophthalmology. This systematic review offers a twofold contribution: it summarises current trends in ophthalmology-related LLM research and projects future directions for this burgeoning field., Methods: We systematically searched across various databases (PubMed, Europe PMC, Scopus and Web of Science) for articles related to LLM use in ophthalmology, published between 1 January 2022 and 31 July 2023. Selected articles were summarised, and categorised by type (editorial, commentary, original research, etc) and their research focus (eg, evaluating ChatGPT's performance in ophthalmology examinations or clinical tasks)., Findings: We identified 32 articles meeting our criteria, published between January and July 2023, with a peak in June (n=12). Most were original research evaluating LLMs' proficiency in clinically related tasks (n=9). Studies demonstrated that ChatGPT-4.0 outperformed its predecessor, ChatGPT-3.5, in ophthalmology exams. Furthermore, ChatGPT excelled in constructing discharge notes (n=2), evaluating diagnoses (n=2) and answering general medical queries (n=6). However, it struggled with generating scientific articles or abstracts (n=3) and answering specific subdomain questions, especially those regarding specific treatment options (n=2). ChatGPT's performance relative to other LLMs (Google's Bard, Microsoft's Bing) varied by study design. Ethical concerns such as data hallucination (n=27), authorship (n=5) and data privacy (n=2) were frequently cited., Interpretation: While LLMs hold transformative potential for healthcare and ophthalmology, concerns over accountability, accuracy and data security remain. Future research should focus on application programming interface integration, comparative assessments of popular LLMs, their ability to interpret image-based data and the establishment of standardised evaluation frameworks., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

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2024
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32. Comparing generative and retrieval-based chatbots in answering patient questions regarding age-related macular degeneration and diabetic retinopathy.

Author

Cheong KX, Zhang C, Tan TE, Fenner BJ, Wong WM, Teo KY, Wang YX, Sivaprasad S, Keane PA, Lee CS, Lee AY, Cheung CMG, Wong TY, Cheong YG, Song SJ, and Tham YC

Subjects
Humans, Cross-Sectional Studies, Surveys and Questionnaires, Female, Male, Patient Education as Topic methods, Diabetic Retinopathy diagnosis, Macular Degeneration physiopathology
Abstract

Background/aims: To compare the performance of generative versus retrieval-based chatbots in answering patient inquiries regarding age-related macular degeneration (AMD) and diabetic retinopathy (DR)., Methods: We evaluated four chatbots: generative models (ChatGPT-4, ChatGPT-3.5 and Google Bard) and a retrieval-based model (OcularBERT) in a cross-sectional study. Their response accuracy to 45 questions (15 AMD, 15 DR and 15 others) was evaluated and compared. Three masked retinal specialists graded the responses using a three-point Likert scale: either 2 (good, error-free), 1 (borderline) or 0 (poor with significant inaccuracies). The scores were aggregated, ranging from 0 to 6. Based on majority consensus among the graders, the responses were also classified as 'Good', 'Borderline' or 'Poor' quality., Results: Overall, ChatGPT-4 and ChatGPT-3.5 outperformed the other chatbots, both achieving median scores (IQR) of 6 (1), compared with 4.5 (2) in Google Bard, and 2 (1) in OcularBERT (all p ≤8.4×10 -3 ). Based on the consensus approach, 83.3% of ChatGPT-4's responses and 86.7% of ChatGPT-3.5's were rated as 'Good', surpassing Google Bard (50%) and OcularBERT (10%) (all p ≤1.4×10 -2 ). ChatGPT-4 and ChatGPT-3.5 had no 'Poor' rated responses. Google Bard produced 6.7% Poor responses, and OcularBERT produced 20%. Across question types, ChatGPT-4 outperformed Google Bard only for AMD, and ChatGPT-3.5 outperformed Google Bard for DR and others., Conclusion: ChatGPT-4 and ChatGPT-3.5 demonstrated superior performance, followed by Google Bard and OcularBERT. Generative chatbots are potentially capable of answering domain-specific questions outside their original training. Further validation studies are still required prior to real-world implementation., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

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2024
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33. Pneumatic displacement of submacular haemorrhage secondary to neovascular age-related macular degeneration and polypoidal choroidal vasculopathy.

Author

Sim SS, Cheong KX, Chan HH, Choo JQH, Tsai ASH, Lee SY, Yeo IYS, Cheung CMG, and Teo KYC

Abstract

Background: To compare the visual and anatomical outcomes of pneumatic displacement (PD) combined with anti-vascular endothelial growth factor (VEGF) therapy versus anti-VEGF monotherapy in treatment-naive eyes with submacular haemorrhage (SMH) secondary to neovascular age-related macular degeneration and polypoidal choroidal vasculopathy., Methods: In a retrospective comparative interventional study of 57 eyes, the changes in logMAR visual acuity (VA), and SMH height and area at baseline at months 1, 3 and 12 were compared between the PD and non-PD groups., Results: There was no significant difference in mean VA in the PD versus non-PD group at month 12 (1.1 versus 0.7, p = 0.09). At baseline, the PD group, compared to the non-PD group, had significantly larger SMH area (35.9 versus 26.9 mm 2 , p = 0.04) and SMH height at the fovea (733.7 versus 503.6 µm, p < 0.01). The greatest reduction in SMH height and area occurred between baseline and month 1 in the PD group, which was faster than between month 1 and month 3 in the non-PD group, with similar findings in the matched pair analysis matched for SMH height and area. In the multivariable analysis, only baseline VA was associated with VA outcomes (month 1: β = -0.46, 95% [confidence interval] CI = -0.78 to -0.14, p = 0.006; month 3: β = -0.52, 95% CI = -0.86 to -0.18, p = 0.004; and month 12: β = -0.78, 95% CI = -1.16 to -0.39, p < 0.001)., Conclusions: The visual outcome of SMH at month 12 in nAMD and PCV is poor regardless of whether PD is performed in addition to anti-VEGF therapy, although a more rapid resolution of SMH can be expected., (© 2024. The Author(s), under exclusive licence to The Royal College of Ophthalmologists.)

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2024
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34. Generative artificial intelligence and ethical considerations in health care: a scoping review and ethics checklist.

Author

Ning Y, Teixayavong S, Shang Y, Savulescu J, Nagaraj V, Miao D, Mertens M, Ting DSW, Ong JCL, Liu M, Cao J, Dunn M, Vaughan R, Ong MEH, Sung JJ, Topol EJ, and Liu N

Abstract

The widespread use of Chat Generative Pre-trained Transformer (known as ChatGPT) and other emerging technology that is powered by generative artificial intelligence (GenAI) has drawn attention to the potential ethical issues they can cause, especially in high-stakes applications such as health care, but ethical discussions have not yet been translated into operationalisable solutions. Furthermore, ongoing ethical discussions often neglect other types of GenAI that have been used to synthesise data (eg, images) for research and practical purposes, which resolve some ethical issues and expose others. We did a scoping review of the ethical discussions on GenAI in health care to comprehensively analyse gaps in the research. To reduce the gaps, we have developed a checklist for comprehensive assessment and evaluation of ethical discussions in GenAI research. The checklist can be integrated into peer review and publication systems to enhance GenAI research and might be useful for ethics-related disclosures for GenAI-powered products and health-care applications of such products and beyond., Competing Interests: Declaration of interests NL reports funding from the Duke–NUS Signature Research Programme funded by the Ministry of Health, Singapore. JS reports funding from the Wellcome Trust and roles as a Bioethics Committee consultant for Bayer and as an advisory panel member for the Hevolution Foundation. DSWT reports funding from National Medical Research Council, Singapore, Duke–NUS Medical School, and Agency for Science, Technology, and Research; patents on deep learning systems for diabetic retinopathy, glaucoma, and age-related macular degeneration (co-inventor; 2017), a computer-implemented method for training an image classifier using weakly annotated training data (2019), and automatically extracting measurements from an image of a display of a measurement device (2020); has a leadership role (unpaid) as Chair of the AI and Digital Innovation Standing Committee and the Asia–Pacific Academy of Ophthalmology; and serves on the executive committees of the American Academy of Ophthalmology AI Committee, STARD-AI Steering Committee, Imperial College London, DECIDE-AI, and QUANDAS-AI. EJT reports funding from the National Institutes of Health (NIH) Grant and consulting fees as an adviser to Tempus Labs, Pheno.AI, and Abridge. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Published
2024
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35. Omega-3 Polyunsaturated Fatty Acids as a Protective Factor for Myopia.

Author

Xue CC, Li H, Dong XX, Yu M, Da Soh Z, Chong C, Jiang C, Choquet H, Zebardast N, Zekavat SM, Hysi PG, Saw SM, Fan Q, Tham YC, Pan CW, and Cheng CY

Abstract

Purpose: Animal models suggest omega-3 polyunsaturated fatty acids (PUFAs) may protect against myopia by modulating choroidal blood perfusion, but clinical evidence is scarce and mixed. We aimed to determine the causality between omega-3 PUFAs and myopia using Mendelian randomization (MR) analysis., Design: Two-sample MR analysis., Methods: Exposures are genetically predicted 18 fatty acids (FAs) related traits. Spherical equivalent refraction (SER) and axial length were used as measurements of myopia. Genome-wide association study summary data on blood levels of 18 FAs related traits (n=115,006), refractive spherical equivalent (n=351,091), axial length (n=69,945) and choroidal thickness (n=44,823) were sourced from the UK Biobank, the Genetic Epidemiology Research on Adult Health and Aging cohort, and the Consortium for Refractive Error and Myopia Study. We used five MR models and considered results statistically significant if the Bonferroni-corrected P-value was ≤2.78 × 10 -3 in at least 3 MR models. The beta represents the change in outcomes (SER in diopter; axial length in mm; choroidal thickness in standard deviation) per standard deviation unit increase in FAs levels., Results: At a Bonferroni-corrected significance, higher levels of omega-3 (Beta, 0.32-0.34), omega-3/total FAs ratio (Beta, 0.31-0.44), docosahexaenoic acid (DHA) (Beta, 0.36-0.46), DHA/total FAs ratio (Beta, 0.37-0.53), PUFAs/total FAs ratio (Beta, 0.07-1.003), and degree of unsaturation (Beta, 0.28-0.44) were associated with a more positive SER, suggesting a lower risk of myopia. Similar trends were observed for axial length albeit with borderline significance (P≤0.035 in ≥2 models). Higher levels of omega-3, DHA, DHA/total FAs ratio, PUFAs/total FAs ratio, PUFAs/monounsaturated FAs ratio, and degree of unsaturation were nominally associated with thicker choroidal thickness (Beta, 0.05-0.13; P≤0.045 in ≥2 models)., Conclusion: Our multiple MR models suggest a protective effect of omega-3 and DHA on myopia, potentially through modulation of choroidal blood perfusion. Further randomized clinical trials are needed to confirm the effectiveness and determine the optimal dose and duration., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

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2024
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36. Iris Morphological and Biomechanical Factors Influencing Angle Closure During Pupil Dilation.

Author

Tan RKY, Ng GY, Tun TA, Braeu FA, Nongpiur ME, Aung T, and Girard MJA

Subjects
Humans, Biomechanical Phenomena, Glaucoma, Angle-Closure physiopathology, Intraocular Pressure physiology, Anterior Chamber diagnostic imaging, Anterior Chamber anatomy & histology, Cornea physiology, Cornea anatomy & histology, Sclera, Iris anatomy & histology, Pupil physiology, Finite Element Analysis
Abstract

Purpose: To use finite element (FE) analysis to assess what morphologic and biomechanical factors of the iris and anterior chamber are more likely to influence angle narrowing during pupil dilation., Methods: The study consisted of 1344 FE models comprising the cornea, sclera, lens, and iris to simulate pupil dilation. For each model, we varied the following parameters: anterior chamber depth (ACD = 2-4 mm) and anterior chamber width (ACW = 10-12 mm), iris convexity (IC = 0-0.3 mm), iris thickness (IT = 0.3-0.5 mm), stiffness (E = 4-24 kPa), and Poisson's ratio (v = 0-0.3). We evaluated the change in (△∠) and the final dilated angles (∠f) from baseline to dilation for each parameter., Results: The final dilated angles decreased with a smaller ACD (∠f = 53.4° ± 12.3° to 21.3° ± 14.9°), smaller ACW (∠f = 48.2° ± 13.5° to 26.2° ± 18.2°), larger IT (∠f = 52.6° ± 12.3° to 24.4° ± 15.1°), larger IC (∠f = 45.0° ± 19.2° to 33.9° ± 16.5°), larger E (∠f = 40.3° ± 17.3° to 37.4° ± 19.2°), and larger v (∠f = 42.7° ± 17.7° to 34.2° ± 18.1°). The change in angles increased with larger ACD (△∠ = 9.37° ± 11.1° to 15.4° ± 9.3°), smaller ACW (△∠ = 7.4° ± 6.8° to 16.4° ± 11.5°), larger IT (△∠ = 5.3° ± 7.1° to 19.3° ± 10.2°), smaller IC (△∠ = 5.4° ± 8.2° to 19.5° ± 10.2°), larger E (△∠ = 10.9° ± 12.2° to 13.1° ± 8.8°), and larger v (△∠ = 8.1° ± 9.4° to 16.6° ± 10.4°)., Conclusions: The morphology of the iris (IT and IC) and its innate biomechanical behavior (E and v) were crucial in influencing the way the iris deformed during dilation, and angle closure was further exacerbated by decreased anterior chamber biometry (ACD and ACW).

Published
2024
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38. Effect of anti-VEGF on retinal blood flow in diabetic mice using laser speckle flowgraphy.

Author

Su ZZS, Ang BCH, Balne PK, Tun SBB, Htoon HM, Schmetterer L, Barathi VA, and Agrawal R

Subjects
Animals, Mice, Reproducibility of Results, Blood Flow Velocity physiology, Male, Intraocular Pressure physiology, Intraocular Pressure drug effects, Optic Disk blood supply, Receptors, Vascular Endothelial Growth Factor administration & dosage, Mice, Inbred C57BL, Intravitreal Injections, Retinal Vessels diagnostic imaging, Retinal Vessels physiopathology, Diabetic Retinopathy physiopathology, Diabetic Retinopathy drug therapy, Diabetic Retinopathy diagnosis, Recombinant Fusion Proteins administration & dosage, Diabetes Mellitus, Experimental physiopathology, Regional Blood Flow physiology, Laser-Doppler Flowmetry methods, Angiogenesis Inhibitors administration & dosage, Vascular Endothelial Growth Factor A antagonists & inhibitors
Abstract

Purpose: To assess intra- (repeatability) and inter-observer (reproducibility) variability of laser speckle flowgraphy (LSFG) for retinal blood flow (RBF) measurement in 20 eyes of wild type (C57BL/6J) mice and effect of intravitreal Aflibercept on RBF in optic nerve head (ONH) region of 10 eyes of Ins2 (Akita) diabetic mice., Methods: 'Mean blur rate (MBR)' was measured for all quadrants of tissue area (MT), vessel (MV) and total area (MA) of ONH region. Changes in MT were analysed at each timepoint. Repeatability was evaluated by measuring MBR variability without changing mouse head position, and reproducibility after resetting mouse head position by another operator. Coefficient of repeatability (CR) through Bland-Altman plot method coefficient of variation (COV) and Intraclass correlation coefficient (ICC) was calculated. Intravitreal Aflibercept (1 μg) was administered to Akita eyes and intraocular pressure (IOP) was measured using a tonometer at baseline, day 7, 14, 21 and 28 post-injection. Hurvich and Tsai's criterion was used., Results: Coefficient of repeatability values of repeatability and reproducibility for all quadrants were within limits of agreement. Reliability was excellent (ICC 0.98-0.99) and reproducibility was moderate to excellent (ICC 0.64-0.96). There was a non-significant IOP increase in all Akita eyes at Day 28 (p > 0.05), and significant increase in MT in all quadrants at Day 21 and superior, inferior and temporal quadrants at Day 28 (p < 0.05)., Conclusion: Laser speckle flowgraphy demonstrates excellent repeatability and moderate to excellent reproducibility in measuring RBF. Intravitreal Aflibercept injection results in a significant increase in MT up to 28 days post-injection without significant increase in IOP., (© 2024 The Authors. Acta Ophthalmologica published by John Wiley & Sons Ltd on behalf of Acta Ophthalmologica Scandinavica Foundation.)

Published
2024
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40. Optical coherence tomography angiography of the retina and choroid in systemic diseases.

Author

Chua J, Tan B, Wong D, Garhöfer G, Liew XW, Popa-Cherecheanu A, Loong Chin CW, Milea D, Li-Hsian Chen C, and Schmetterer L

Abstract

Optical coherence tomography angiography (OCTA) has transformed ocular vascular imaging, revealing microvascular changes linked to various systemic diseases. This review explores its applications in diabetes, hypertension, cardiovascular diseases, and neurodegenerative diseases. While OCTA provides a valuable window into the body's microvasculature, interpreting the findings can be complex. Additionally, challenges exist due to the relative non-specificity of its findings where changes observed in OCTA might not be unique to a specific disease, variations between OCTA machines, the lack of a standardized normative database for comparison, and potential image artifacts. Despite these limitations, OCTA holds immense potential for the future. The review highlights promising advancements like quantitative analysis of OCTA images, integration of artificial intelligence for faster and more accurate interpretation, and multi-modal imaging combining OCTA with other techniques for a more comprehensive characterization of the ocular vasculature. Furthermore, OCTA's potential future role in personalized medicine, enabling tailored treatment plans based on individual OCTA findings, community screening programs for early disease detection, and longitudinal studies tracking disease progression over time is also discussed. In conclusion, OCTA presents a significant opportunity to improve our understanding and management of systemic diseases. Addressing current limitations and pursuing these exciting future directions can solidify OCTA as an indispensable tool for diagnosis, monitoring disease progression, and potentially guiding treatment decisions across various systemic health conditions., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Published
2024
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42. The causal effect of adult height on late-life handgrip strength: The Singapore Chinese Health Study.

Author

Chang X, Chua KY, Shih CC, Chen J, Lee AS, Tan P, Wang L, Liu J, Heng CK, Yuan JM, Khor CC, Dorajoo R, and Koh WP

Abstract

Background: Adult height has been associated with handgrip strength, which is a surrogate marker of physical frailty. However, it is uncertain if this association is causative or due to confounding bias., Methods: We evaluated pairwise associations among handgrip strength, adult height and genetically determined height [using a polygenic score (PGS) for height in a mediation framework and a two-sample Mendelian randomisation approach] by means of multivariable regression model using a prospective cohort of Chinese living in Singapore. We additionally evaluated pathway enrichments of height-related genes in relation to increased handgrip strength to discover common biological mechanisms underlying associations of genetically determined height with handgrip strength., Results: Height PGS exhibited a positive association with handgrip strength at late life after adjusting for midlife body weight and other baseline exposures (cigarette smoking, education and physical activity status, P=1.2×10-9). Approximately 66.4% of the total effect of height PGS on handgrip strength was mediated through adult height (βindirect-effect=0.034, Pindirect-effect=1.4×10-40). Two-sample Mendelian randomisation evaluations showed a consistent causal relationship between increased height and increased handgrip strength in late life (P between 6.6×10-4 and 3.9×10-18), with insignificant horizontal pleiotropic effects (PMR-Egger  intercept=0.853). Pathway analyses of genes related to both increased adult height and handgrip strength revealed enrichment in ossification and adipogenesis pathways (Padj between 0.034 to 6.8×10-4)., Conclusions: The study highlights on a potentially causal effect between increased adult height and increased handgrip strength at late life, which may be explained by related biological processes underlying preservation of muscle mass and strength in ageing., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Published
2024
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43. Artificial intelligence in corneal diseases: A narrative review.

Author

Nguyen T, Ong J, Masalkhi M, Waisberg E, Zaman N, Sarker P, Aman S, Lin H, Luo M, Ambrosio R, Machado AP, Ting DSJ, Mehta JS, Tavakkoli A, and Lee AG

Abstract

Corneal diseases represent a growing public health burden, especially in resource-limited settings lacking access to specialized eye care. Artificial intelligence (AI) offers promising solutions for automating the diagnosis and management of corneal conditions. This narrative review examines the application of AI in corneal diseases, focusing on keratoconus, infectious keratitis, pterygium, dry eye disease, Fuchs endothelial corneal dystrophy, and corneal transplantation. AI models integrating diverse imaging modalities (e.g., corneal topography, slit-lamp, and anterior segment OCT images) and clinical data have demonstrated high diagnostic accuracy, often outperforming human experts. Emerging trends include the incorporation of biomechanical data to enhance keratoconus detection, leveraging in vivo confocal microscopy for diagnosing infectious keratitis, and employing multimodal approaches for comprehensive disease analysis. Additionally, AI has shown potential in predicting disease progression, treatment outcomes, and postoperative complications in corneal transplantation. While challenges remain such as population heterogeneity, limited external validation, and the "black box" nature of some models, ongoing advancement in explainable AI, data augmentation, and improved regulatory frameworks can serve to address these limitations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 British Contact Lens Association. Published by Elsevier Ltd. All rights reserved.)

Published
2024
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44. Housing status is protective of neuropsychiatric symptoms among dementia-free multi-ethnic Asian elderly.

Author

Zhang H, Wang Y, Zhang Y, Hilal S, Cheng CY, Wong TY, Chen C, Venketasubramanian N, and Xu X

Subjects
Humans, Male, Female, Aged, Singapore epidemiology, Aged, 80 and over, Independent Living, Housing, Neuropsychological Tests, Middle Aged, Cognitive Dysfunction epidemiology, Cognitive Dysfunction ethnology, Cognitive Dysfunction psychology, Dementia epidemiology, Dementia ethnology, Dementia psychology, Dementia prevention & control
Abstract

Background: Housing has been associated with dementia risk and disability, but associations of housing with differential patterns of neuropsychiatric symptoms (NPS) among dementia-free older adults remain to be explored. The present study sought to explore the contribution of housing status on NPS and subsyndromes associated with cognitive dysfunction in community-dwelling dementia-free elderly in Singapore., Methods: A total of 839 dementia-free elderly from the Epidemiology of Dementia in Singapore (EDIS) study aged ≥ 60 were enrolled in the current study. All participants underwent clinical, cognitive, and neuropsychiatric inventory (NPI) assessments. The housing status was divided into three categories according to housing type. Cognitive function was measured by a comprehensive neuropsychological battery. The NPS were assessed using 12-term NPI and were grouped into four clinical subsyndromes: psychosis, hyperactivity, affective, and apathy. Associations of housing with composite and domain-specific Z-scores, as well as NPI scores, were assessed using generalized linear models (GLM). Binary logistic regression models analysed the association of housing with the presence of NPS and significant NPS (NPI total scores ≥ 4)., Results: Better housing status (5-room executive apartments, condominium, or private housing) was associated with better NPS (OR = 0.49, 95%CI = 0.24 to 0.98, P < 0.05) and significant NPS profile (OR = 0.20, 95%CI = 0.08 to 0.46, P < 0.01), after controlling for demographics, risk factors, and cognitive performance. Compared with those living in 1-2 room apartments, older adults in better housing had lower total NPI scores (β=-0.50, 95%CI=-0.95 to -0.04, P = 0.032) and lower psychosis scores (β=-0.36, 95%CI=-0.66 to -0.05, P = 0.025), after controlling for socioeconomic status (SES) indexes. Subgroup analysis indicated a significant correlation between housing type and NPS in females, those of Malay ethnicity, the more educated, those with lower income, and those diagnosed with cognitive impairment, no dementia (CIND)., Conclusions: Our study showed a protective effect of better housing arrangements on NPS, especially psychosis in a multi-ethnic Asian geriatric population without dementia. The protective effect of housing on NPS was independent of SES and might have other pathogenic mechanisms. Improving housing could be an effective way to prevent neuropsychiatric disturbance among the elderly., (© 2024. The Author(s).)

Published
2024
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46. Comparing Optical Coherence Tomography Angiography Metrics in Healthy Chinese and Caucasian Adults.

Author

Bujor I, Chua J, Tan B, Iancu R, Pirvulescu R, Geamanu A, Bostan M, Toma E, Ionescu D, Schmetterer L, and Popa-Cherecheanu A

Abstract

Background: The goal of the present study was to identify differences in retinal microvasculature between healthy Caucasians and healthy Asians in order to provide a better understanding of the variability between different ethnic groups., Methods: In this cross-sectional study, 191 healthy Chinese and Caucasian participants were enrolled. They underwent optical coherence tomography angiography (OCTA) scans with Zeiss Cirrus HD-5000 Spectral-Domain with AngioPlex. Linear regression models were used to investigate the association of OCTA metrics with potential risk factors., Results: Whereas participants in both groups are comparable in age and sex, Chinese participants had a longer axial length, higher spherical equivalent, higher intraocular pressure ( p < 0.001), and a significantly higher perfusion density of large vessels in the superficial capillary plexus ( p < 0.001). Regarding the foveolar avascular area (FAZ), Chinese participants had a larger superficial FAZ, a wider superficial FAZ perimeter, and a more circular deep FAZ shape ( p < 0.001)., Conclusions: There are significant differences in the retinal vasculature between Caucasian and Asian eyes as measured using OCTA. This needs to be considered when developing normative databases. Whether such findings relate to inter-racial differences in the incidence of retinal vascular disease remains to be shown.

Published
2024
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47. A Deep Learning Approach for Accurate Discrimination Between Optic Disc Drusen and Papilledema on Fundus Photographs.

Author

Sathianvichitr K, Najjar RP, Zhiqun T, Fraser JA, Yau CWL, Girard MJA, Costello F, Lin MY, Lagrèze WA, Vignal-Clermont C, Fraser CL, Hamann S, Newman NJ, Biousse V, and Milea D

Abstract

Background: Optic disc drusen (ODD) represent an important differential diagnosis of papilledema caused by intracranial hypertension, but their distinction may be difficult in clinical practice. The aim of this study was to train, validate, and test a dedicated deep learning system (DLS) for binary classification of ODD vs papilledema (including various subgroups within each category), on conventional mydriatic digital ocular fundus photographs collected in a large international multiethnic population., Methods: This retrospective study included 4,508 color fundus images in 2,180 patients from 30 neuro-ophthalmology centers (19 countries) participating in the Brain and Optic Nerve Study with Artificial Intelligence (BONSAI) Group. For training and internal validation, we used 857 ODD images and 3,230 papilledema images, in 1,959 patients. External testing was performed on an independent data set (221 patients), including 207 images with ODD (96 visible and 111 buried), provided by 3 centers of the Optic Disc Drusen Studies Consortium, and 214 images of papilledema (92 mild-to-moderate and 122 severe) from a previously validated study., Results: The DLS could accurately distinguish between all ODD and papilledema (all severities included): area under the receiver operating characteristic curve (AUC) 0.97 (95% confidence interval [CI], 0.96-0.98), accuracy 90.5% (95% CI, 88.0%-92.9%), sensitivity 86.0% (95% CI, 82.1%-90.1%), and specificity 94.9% (95% CI, 92.3%-97.6%). The performance of the DLS remained high for discrimination of buried ODD from mild-to-moderate papilledema: AUC 0.93 (95% CI, 0.90-0.96), accuracy 84.2% (95% CI, 80.2%-88.6%), sensitivity 78.4% (95% CI, 72.2%-84.7%), and specificity 91.3% (95% CI, 87.0%-96.4%)., Conclusions: A dedicated DLS can accurately distinguish between ODD and papilledema caused by intracranial hypertension, even when considering buried ODD vs mild-to-moderate papilledema., Competing Interests: The authors report no conflicts of interest., (Copyright © 2024 by North American Neuro-Ophthalmology Society.)

Published
2024
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48. Evaluation of thickness of individual macular retinal layers in diabetic eyes from optical coherence tomography.

Author

Shah J, Tan B, Wong D, Abdul Gani NFB, Hu Q, Liu X, and Chua J

Subjects
Humans, Male, Female, Middle Aged, Aged, Retina diagnostic imaging, Retina pathology, Macular Edema diagnostic imaging, Macular Edema pathology, Macula Lutea diagnostic imaging, Macula Lutea pathology, Retinal Pigment Epithelium pathology, Retinal Pigment Epithelium diagnostic imaging, Retinal Ganglion Cells pathology, Tomography, Optical Coherence methods, Diabetic Retinopathy diagnostic imaging, Diabetic Retinopathy pathology
Abstract

The effect of diabetes mellitus (DM) on individual retinal layers remains incompletely understood. We evaluated the intra-retinal layer thickness alterations in 71 DM eyes with no diabetic retinopathy (DR), 90 with mild DR, and 63 with moderate DR without macular edema, using spectral-domain optical coherence tomography (SD-OCT) and the Iowa Reference Algorithm for automated retinal layer segmentation. The average thickness of 10 intra-retinal layers was then corrected for ocular magnification using axial length measurements, and pairwise comparisons were made using multivariable linear regression models adjusted for gender and race. In DM no DR eyes, significant thinning was evident in the ganglion cell layer (GCL; p < 0.001), inner nuclear layer (INL; p = 0.001), and retinal pigment epithelium (RPE; p = 0.014) compared to normal eyes. Additionally, mild DR eyes exhibited a thinner inner plexiform layer (IPL; p = 0.008) than DM no DR eyes. Conversely, moderate DR eyes displayed thickening in the INL, outer nuclear layer, IPL, and retinal nerve fiber layer (all p ≤ 0.002), with notably worse vision. These findings highlight distinctive patterns: early diabetic eyes experience thinning in specific retinal layers, while moderate DR eyes exhibit thickening of certain layers and slightly compromised visual acuity, despite the absence of macular edema. Understanding these structural changes is crucial for comprehending diabetic eye complications., (© 2024. The Author(s).)

Published
2024
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49. Artificial intelligence for diabetes care: current and future prospects.

Author

Sheng B, Pushpanathan K, Guan Z, Lim QH, Lim ZW, Yew SME, Goh JHL, Bee YM, Sabanayagam C, Sevdalis N, Lim CC, Lim CT, Shaw J, Jia W, Ekinci EI, Simó R, Lim LL, Li H, and Tham YC

Subjects
Humans, Artificial Intelligence trends, Diabetes Mellitus therapy, Diabetes Mellitus diagnosis
Abstract

Artificial intelligence (AI) use in diabetes care is increasingly being explored to personalise care for people with diabetes and adapt treatments for complex presentations. However, the rapid advancement of AI also introduces challenges such as potential biases, ethical considerations, and implementation challenges in ensuring that its deployment is equitable. Ensuring inclusive and ethical developments of AI technology can empower both health-care providers and people with diabetes in managing the condition. In this Review, we explore and summarise the current and future prospects of AI across the diabetes care continuum, from enhancing screening and diagnosis to optimising treatment and predicting and managing complications., Competing Interests: Declaration of interests NS is the director of London Safety and Training Solutions. HL is supported by the National Key Research and Development Program of China (2022YFA1004804), the Excellent Young Scientists Fund of the National Natural Science Foundation of China (82022012), and the innovative research team of high-level local universities in Shanghai (SHSMU-ZDCX20212700). Y-CT is supported by the National Medical Research Council of Singapore (NMRC/MOH/ HCSAINV21nov-0001)., (Copyright © 2024 Published by Elsevier Ltd. All rights reserved, including those for text and data mining, AI training, and similar technologies.)

Published
2024
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50. The prevalence patterns and risk factor profiles of poor muscle health and its associated components in multiethnic older Asians: The PIONEER study.

Author

Gupta P, Vu TA, Man REK, Fenwick EK, Tay L, Yee Sien N, Ng D, Frederick KHX, Yong EL, Chew STH, and Lamoureux EL

Subjects
Humans, Female, Male, Aged, Risk Factors, Prevalence, Singapore epidemiology, Asian People, Aged, 80 and over, Muscle Strength, Ethnicity statistics & numerical data, Middle Aged, Sarcopenia epidemiology, Sarcopenia ethnology
Abstract

Background: We aim to determine the multiethnic patterns of the prevalence and associated factors of poor muscle health and its associated components in older Chinese, Malays, and Indian Asian adults., Methods: We included 2199 participants (mean age ± SD: 72.9 ± 8.3 years; 54.3% female) from the baseline assessment of the Population Health and Eye Disease Profile in Elderly Singaporeans (PIONEER; 2017-2022) cohort study. Poor muscle health was defined as the presence of either low muscle mass (DEXA), or low muscle strength (handgrip strength), or low physical performance (gait speed). Its components include poor muscle function (low muscle strength and/or low physical performance without low muscle mass), pre-sarcopenia (low muscle mass only), and any sarcopenia (low muscle mass with low muscle strength and/or low physical performance). Sociodemographic, clinical, and lifestyle factors were assessed using biochemistry, clinical tests, and validated questionnaires. Regression models were utilized to evaluate the independent risk factors of poor muscle health and its components., Results: The national census-adjusted prevalence of poor muscle health (88%) was similar across the three ethnic groups. However, Chinese individuals had higher prevalence of pre-sarcopenia and any sarcopenia, and a lower prevalence of poor muscle function compared with Indians or Malays. We observed ethnic differences in modifiable risk factors (low physical activity, diabetes, osteoporosis, and obesity) of poor muscle health and its components. Although obesity was protective of pre-sarcopenia (RRR = 0.19, 95% CI: 0.11, 0.36) and any sarcopenia (RRR = 0.29, 95% CI: 0.18, 0.47) in the overall population and across ethnic groups, it was associated with 1.7 times (95% CI: 1.07, 2.67) the likelihood of poor muscle function in the entire population., Conclusions: Almost 90% of community dwelling Singaporean aged ≥60 years have poor muscle health across the three ethnic groups with ethnic disparities in modifiable risk factors, highlighting an urgent need for community-wide targeted interventions to promote muscle health., (© 2024 The Authors. Journal of Cachexia, Sarcopenia and Muscle published by Wiley Periodicals LLC.)

Published
2024
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