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2. Epilepsy: Mitochondrial Connections to the ‘Sacred’ Disease

Author

Moos, Walter H, Faller, Douglas V, Glavas, Ioannis P, Kanara, Iphigenia, Kodukula, Krishna, Pernokas, Julie, Pernokas, Mark, Pinkert, Carl A, Powers, Whitney R, Sampani, Konstantina, Steliou, Kosta, and Vavvas, Demetrios G

Subjects
Complementary and Integrative Health, Neurosciences, Nutrition, Brain Disorders, Neurodegenerative, Epilepsy, Aetiology, 2.1 Biological and endogenous factors, Neurological, Good Health and Well Being, Cuproptosis/copper, epilepsy, ferroptosis/iron, mitochondria, neurodegenerative disease, reactive oxygen species, seizure, Genetics, Biochemistry & Molecular Biology
Abstract

Over 65 million people suffer from recurrent, unprovoked seizures. The lack of validated biomarkers specific for myriad forms of epilepsy makes diagnosis challenging. Diagnosis and monitoring of childhood epilepsy add to the need for non-invasive biomarkers, especially when evaluating antiseizure medications. Although underlying mechanisms of epileptogenesis are not fully understood, evidence for mitochondrial involvement is substantial. Seizures affect 35%-60% of patients diagnosed with mitochondrial diseases. Mitochondrial dysfunction is pathophysiological in various epilepsies, including those of non-mitochondrial origin. Decreased ATP production caused by malfunctioning brain cell mitochondria leads to altered neuronal bioenergetics, metabolism and neurological complications, including seizures. Iron-dependent lipid peroxidation initiates ferroptosis, a cell death pathway that aligns with altered mitochondrial bioenergetics, metabolism and morphology found in neurodegenerative diseases (NDDs). Studies in mouse genetic models with seizure phenotypes where the function of an essential selenoprotein (GPX4) is targeted suggest roles for ferroptosis in epilepsy. GPX4 is pivotal in NDDs, where selenium protects interneurons from ferroptosis. Selenium is an essential central nervous system micronutrient and trace element. Low serum concentrations of selenium and other trace elements and minerals, including iron, are noted in diagnosing childhood epilepsy. Selenium supplements alleviate intractable seizures in children with reduced GPX activity. Copper and cuproptosis, like iron and ferroptosis, link to mitochondria and NDDs. Connecting these mechanistic pathways to selenoproteins provides new insights into treating seizures, pointing to using medicines including prodrugs of lipoic acid to treat epilepsy and to potential alternative therapeutic approaches including transcranial magnetic stimulation (transcranial), photobiomodulation and vagus nerve stimulation.

Published
2023

3. AOSLO-net: A deep learning-based method for automatic segmentation of retinal microaneurysms from adaptive optics scanning laser ophthalmoscope images

Author

Zhang, Qian, Sampani, Konstantina, Xu, Mengjia, Cai, Shengze, Deng, Yixiang, Li, He, Sun, Jennifer K., and Karniadakis, George Em

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Microaneurysms (MAs) are one of the earliest signs of diabetic retinopathy (DR), a frequent complication of diabetes that can lead to visual impairment and blindness. Adaptive optics scanning laser ophthalmoscopy (AOSLO) provides real-time retinal images with resolution down to 2 $\mu m$ and thus allows detection of the morphologies of individual MAs, a potential marker that might dictate MA pathology and affect the progression of DR. In contrast to the numerous automatic models developed for assessing the number of MAs on fundus photographs, currently there is no high throughput image protocol available for automatic analysis of AOSLO photographs. To address this urgency, we introduce AOSLO-net, a deep neural network framework with customized training policies to automatically segment MAs from AOSLO images. We evaluate the performance of AOSLO-net using 87 DR AOSLO images and our results demonstrate that the proposed model outperforms the state-of-the-art segmentation model both in accuracy and cost and enables correct MA morphological classification.

Published
2021

4. Pathogenic mitochondrial dysfunction and metabolic abnormalities

Author

Moos, Walter H, Faller, Douglas V, Glavas, Ioannis P, Harpp, David N, Kamperi, Natalia, Kanara, Iphigenia, Kodukula, Krishna, Mavrakis, Anastasios N, Pernokas, Julie, Pernokas, Mark, Pinkert, Carl A, Powers, Whitney R, Steliou, Kosta, Tamvakopoulos, Constantin, Vavvas, Demetrios G, Zamboni, Robert J, and Sampani, Konstantina

Subjects
Neurodegenerative, Nutrition, Genetics, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Animals, COVID-19, Diet, Healthy, Energy Metabolism, Humans, Metabolic Diseases, Mitochondria, Mitochondrial Diseases, Neurodegenerative Diseases, Oxidative Stress, Mitochondrial diseases, Disorders, Dysfunction, Metabolic abnormalities, Diseases, Homeostasis, Pathogenesis, Reprogramming, Biochemical pathways, Physiological networks, Pathogenesis and pathogenic drivers, Therapeutics, Biochemistry and Cell Biology, Pharmacology and Pharmaceutical Sciences, Pharmacology & Pharmacy
Abstract

Herein we trace links between biochemical pathways, pathogenesis, and metabolic diseases to set the stage for new therapeutic advances. Cellular and acellular microorganisms including bacteria and viruses are primary pathogenic drivers that cause disease. Missing from this statement are subcellular compartments, importantly mitochondria, which can be pathogenic by themselves, also serving as key metabolic disease intermediaries. The breakdown of food molecules provides chemical energy to power cellular processes, with mitochondria as powerhouses and ATP as the principal energy carrying molecule. Most animal cell ATP is produced by mitochondrial synthase; its central role in metabolism has been known for >80 years. Metabolic disorders involving many organ systems are prevalent in all age groups. Progressive pathogenic mitochondrial dysfunction is a hallmark of genetic mitochondrial diseases, the most common phenotypic expression of inherited metabolic disorders. Confluent genetic, metabolic, and mitochondrial axes surface in diabetes, heart failure, neurodegenerative disease, and even in the ongoing coronavirus pandemic.

Published
2021

5. Assessment of Baseline Ultrawidefield Fluorescein Angiographic Quantitative Leakage Parameters with Ultrawidefield Fundus Features and Clinical Parameters in Diabetic Retinopathy in Protocol AA

Author

Harara, Abla M., Palacios, Angela N., Berger, Brian B., Corak, Boris, Luong, Bianca, Jhaveri, Chirag D., Wilson, Daniela Mariel, Jonna, Gowtham, Gunderson, Ivana, Hosein, Kimberly, Reid, Ryan M., Chexal, Saradha, Moore, Tori, Seidu, Tina A., Gatavaski, Valerie, Ren, Yong, Stern, Bradley A., Benvenutti, Celia E., Oude-Reimerink, Dinah S., Shaheen, Jenny, Grybas, John, Vitale-Kuhn, Julianne, Staffne, Jessica L., Ventimiglia, Katie M., Allis, Megan, Monk, Mary K., Thomas, Marc E., Massu, Nicole M., Edwards, Paul Andrew, Troszak, Tracy A., Irons, Amber N., Rego, Brittany, Han, Dennis P., Dorsey, Eleanor, Nelson, Erika, Sheppard, Hannah, Beringer, Joseph R., Kim, Judy E., Keller, Kristy L., Packard, Krissa L., Altmann, Marriner L., Goldberg, Mara, Chen, Nickolas, Winter, Pat A., Bourgeois, Shay, Jacobo, Samantha, Moebius, Stephanie J., Connor, Thomas B., Barwick, Vicki, Williams, Vesper V., Wirostko, William J., Ghuman, A. Thomas, Leslie, Anita H., Sharma, Ashish G., Kiesel, Cheryl, Dyshanowitz, Danielle, Knips, Eileen, Wing, Glenn, Walker, Joseph P., Raskauskas, Paul A., Kiesel, Raymond K., Schlossman, Deborah K., Weimann, Elizabeth S., Sharuk, George S., Kwak, Hanna, Cavallerano, Jerry D., Rhee, Jae W., Sampani, Konstantina, Tran, Katie V., Bestourous, Leila, Miranda, Linette, Krigman, Michael N., Stockman, Margaret E., Arrigg, Paul G., Cavicchi, Robert W., Kirby, Rita K., Glynn, Shireen, Papaconstantinou, Steve L., Shah, Sabera T., Murtha, Timothy J., Carli, William, Finch, Autumn K., Gentile, Angella K., Price, Angela K., Murphy, Brittany A., Rowland, Beverly O., Fleming, Christina J., Mahr, Courtney, Shore, Carol A., Browning, David, McClain, Donna, Breglio, Erica, Lester, Gina M., Herby, Jenna T., Bratcher, Kayla A., Clark, Loraine M., Jackson, Lisa A., Watson, Lynn, McOwen, Michael D., Punjabi, Omar S., Bojaj, Swann J., Ennis, Sarah A., Fredenberg, Sherry L., Jones, Taylor S., Ragin, Teneisha A., Balasubramaniam, Uma M., Ornelas, Blanca, Rodriquez, Brenda, Edwards, Carla, Carns, Danielle R., Tonner, Eileen E., Woo, Kisung, Richine, Len, MacCumber, Mathew W., Merrill, Pauline Townsend, Kociborski, Sarah, Harless, Ashley M., Harris, Charlotte, White, Lorraine, Maturi, Raj K., Asher, Julie, Walsh, Justin, Wheeler, Jeff, Milstead, Katie, Oliver, Kristina, Lovelady, Lisa, Anderson, Nicholas G., Coppola, Patricia, Lince, Raul E., Shuler, R. Keith, Morris, Steve, Oelrich, Sarah M., Gardner, Brandon S., Moore, Bob, Cain, Dennis, Donohue, Deborah, Emmert, David, Adeyemo, Kemi, Levin, Lisa K., Frey, Mary, Rhoton, Nick, Bressler, Susan, Solomon, Sharon D., Ford, Amy L., Hughes, Ashley, Brewer, Alisha N., Booth, JoAnn T., Lunsford, Keven W., Ukleya, Lauren D., Burris, Russ, Kingsley, Ronald M., Almeida, Shannon R., Icks, Sonny, Shah, Vinay A., Bergman, Vanessa A., Castellarin, Alessandro A., Shook, Aimee H., Walker, Aimee, Pieramici, Dante J., Hong, Gina, Avery, Kelly, McKee, Kate M., Giust, Matthew, Munoz, Marco A., Fishbein, Sarah, Camp, Alecia B., Baker, Carl W., Baker, Jil D., Sedberry, Kylie S., Lambert, Lynnette F., Orr, Margaret J., Alcaraz, Sonya L., Kettler, Samantha, Caldwell, Tracey M., Miller, Abigail, Dorr, Christine M., Hampton, G. Robert, Brown, Jamin S., Barker, Jeffrey P., Rosenberg, Kevin I., Kwasniewski, Lynn M., Sienkiewycz, Laurie J., Spuches, Lisa, Manley, Michelle L., Robarge, Nicole E., DeSantis, Stefanie R., DeForge, Teresa M., Brucker, Alexander J., Kim, Benjamin J., Berger, Jim M., DuPont, Joan C., Drossner, Sheri, Freeman, Sara, Studebaker, Ashley, Payne, John F., Wells, John A., Spivey, Robbin, Ogbuewu, Tiffany N., Swinford, Tiffany R., Guillory, Adrienne, Hutson, Amy, Schefler, Amy C., Shah, Ankoor R., Almanza, Belinda A., Dives, Brenda, Richter, Beau A., Stoever, Cary A., Brown, David M., Foerster, Danee, Garcia, David, Rodriguez, Diana, Park, Daniel, Chen, Eric, Kegley, Eric N., Quellar, Elizabeth, Twining, Garret L., Koger-Grifaldo, Heather, Ortega, Ilsa, Carranza, Jolene, Major, James C., Williamson, Kimberly, Burt, Lindsay, Salinas, Luis R., Wolff, Lisa M., Benz, Matthew S., Estes, Maura A., James, Miranda F., Berry, Meredith, Vela, Melina, Landaverde, Nubia, Webb, Nina A., Fish, Richard H., Kim, Rosa Y., Yee, Rebecca, Karani, Sadia Y., Supapo, Stacy M., Dodel, Tamara L., McCoy, Tyneisha, Wong, Tien P., Sneed, Veronica A., Barnhart, Cassandra J., Cantrell, Debra, DuBose, Elizabeth L., Sharpe, Houston P., Ulrich, Jan Niklas, Bhansali, Kanika A., Esquejo, Rona Lyn, Garg, Seema, Grout, Sean, McKinney, Allen, Bobbitt, Brenda J., Wendel, Ceara L., Fagan, Damanda F., Andrews, Jacqueline, Holmes, Krystal Nikki, Seyez, Karen L., Williamson, Kimberly A., Moinfar, Nader, Walters, Paige N., Carlton, Steve, Rehling, Shannon M., Williams, Shana E., Reed, Tiara L., VandeVelde, Amber R., Yeager, Frank T., Fox, Gregory M., Batlle, Ivan R., Bruce, Kiersten, Pippin, Katherine, Ainley, Lexie R., Singh, Ravi S.J., Adamo, Ashley M., Guardado, Adrian, Patel, Apurva K., Puckett, Brian S., Hoerner, Christine, Ma, Colin, Clark, David J., Flato, Inessa M., Cohen, Joshua, Charpentier, Margaret E., Kopfer, Marcia, Peters, Mark A., Smith, Pualani, Tlucek, Paul S., Hobbs, Stephen, Ho, Stephanie L., Metzger, Ashley M., McCalla, Alesia K., Thompson, Amy, Ringrose, Christine, Sandler, Dallas R., Leder, Henry A., Belz, Jennifer L., Starr, JoAnn, Simmons, Jennifer L., Orr, Peggy R., Sotirakos, Peter, Singletary, Pamela V., Cain, Terri, Coffey, Teresa, Carter, Tiffany M., Robinson, Twyla J., Shah, Chirag P., Cammarata, Dominique, Kruger, Jennifer L., Colegrove, Lindsey, Graham, Margie, Gleason, Shane T., Noel, Bryan, Damron, Catherine, Holcomb, Diana M., Slade, Edward A., Van Arsdall, Jeanne, Bicknell, Lisa, Buck, Michelle, Stone, Thomas W., Farooq, Amina, Parsons, Brook, Singh, Harinderjit, Ivey, Ken, Foster, Lindsay Allison, Woodward, Michele, Ortiz, Siobhan O., Bailey, Thomas, Mynampati A, Bharani Krishna, White, Cheryl L., Hamdani, Ghulam Shabbir, Smith, Jazzmin N., Chalam, Kakarla V., Sambhav, Kumar, Babaria, Romesh, Grover, Sandeep, Carroll, Catherine, Chau, Felix Y., Lim, Jennifer I., Talasnik, Lauren A., Janowicz, Mark, Stankovic, Natasa, Berlatsky, Sarah L., Niec, Marcia, Sun, Jie, Johnson, Tametha, Ovando, Yesenia, Nakoski, Brenda, Mein, Calvin E., Wienecke, Christopher Sean, Castillo, Elaine, Baker, Jaynee, San Roman, Jonathan, Adams, Lydia, Kirschbaum, Lita, Chica, Moises A., Cloudt, Sara L., Moore, Tori R., Sabates, Felix N., Gallimore, Gary S., Chen, Yin C., Swann, Adrienne C., Cadwell, Deborah M., Diddie, Kenneth R., Boisvert, Taryn F., Tessau, Carrie D., Bowers, Jack, Nielsen, Jared S., Rostvold, Jay, Spillman, Jamie, Alliman, Kyle J., Boender, Lisa M., Johnson, Marilyn A., Parker, Marianne, Bix, Paula L., Ridgway, Spencer D., Woehl, Tami Jo, Stonewall, Whitney, Brown, Christopher M., Lema, Gareth M.C., Wiechelt, Luann, Yoganathan, Pradeepa, Boglione, Sandra L., Montesclaros, Chris A., Mangham, Cory, Karsaliya, Gopal, Le, Phillip V., Wong, Robert W., Godfrey, Anne Marie, Kuzmanovic, Aleksandra, Kirker, Andrew William, Harrison, Bryan, Forooghian, Farzin, Elvena, Garnet Louise, Hall, Laura J., Turhal, Bilgin, Brown, Ian, Kotei, Isaac A., Chen, Lina, Brent, Michael Henry, Moon, Michelle, Sutakovic, Olivera, Chang, Angela, Godfrey, Anne-Marie, Albiani, David, Maberley, David A.L., Navajas, Eduardo Vitor, Grant, Kelly, Tran, Khoi A., Jovanovic, Mira, Cao, Sijia, Wiens, Theresa, Kozbial, Andrzej, Orlin, Anton, Lenane, Courtney Nichole, Herder, Susan P., Kiss, Szilard, Reeves, Tom, Cruess, Alan F., Dean, Andrea, Hoskin-Mott, Ann, Morrison, Christine, Caldwell, Meggie D., Hynes, Mitzi, Gupta, R. Rishi, Durling, Stacey, MacDonnell, Trina, Beck, Roy W., Baptista, Alyssa, Beaulieu, Wesley T., Calhoun, Claire T., Constantine, Sharon R., Correia, Isabella, Dale, Brian B., Dupre, Simone S., Franklin, Crystal A., Galusic, Sandra, Huggins, Meagan, Hunter, Brenda L., Johnson, Paula A., Josic, Kristin, Kelly, Brittany, Maguire, Maureen G., Meadows, Britney, Stockdale, Cynthia R., Zokruah, Alice, Bhargava, Sangeeta, Barkmeier, Andrew J., Baskin, Darrell, Blodi, Barbra, Chew, Emily, Ferris, Frederick L., Jaffe, Glenn J., Bressler, Neil M., Lujan, Brandon, Tolls, Dorothy, Sheridan, Daniel, Pitoc, Cloyd M., Anne C Aquino, Lizzie, Salva, Claude Michael G., Lewis, Drew, Stainback, Jeffery, Makkena, Vijaya, Winter, Katrina, Mora, Adiel, Harrington, Chris, Vinh, Doc-Lap, Ehlers, Justis P., Yordi, Sari, Martin, Alison, Srivastava, Sunil K., and Sun, Jenifer K.

Published
2024
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6. Klotho Pathways, Myelination Disorders, Neurodegenerative Diseases, and Epigenetic Drugs

Author

Moos, Walter H, Faller, Douglas V, Glavas, Ioannis P, Harpp, David N, Kanara, Iphigenia, Mavrakis, Anastasios N, Pernokas, Julie, Pernokas, Mark, Pinkert, Carl A, Powers, Whitney R, Sampani, Konstantina, Steliou, Kosta, Vavvas, Demetrios G, Zamboni, Robert J, Kodukula, Krishna, and Chen, Xiaohong

Subjects
Biochemistry and Cell Biology, Biomedical and Clinical Sciences, Biological Sciences, Genetics, Brain Disorders, Neurodegenerative, Neurosciences, Generic health relevance, Neurological, amyotrophic lateral sclerosis, Klotho, mitochondria, multiple sclerosis, neurodegenerative disease, Biochemistry and cell biology, Biomedical engineering
Abstract

In this review we outline a rationale for identifying neuroprotectants aimed at inducing endogenous Klotho activity and expression, which is epigenetic action, by definition. Such an approach should promote remyelination and/or stimulate myelin repair by acting on mitochondrial function, thereby heralding a life-saving path forward for patients suffering from neuroinflammatory diseases. Disorders of myelin in the nervous system damage the transmission of signals, resulting in loss of vision, motion, sensation, and other functions depending on the affected nerves, currently with no effective treatment. Klotho genes and their single-pass transmembrane Klotho proteins are powerful governors of the threads of life and death, true to the origin of their name, Fates, in Greek mythology. Among its many important functions, Klotho is an obligatory co-receptor that binds, activates, and/or potentiates critical fibroblast growth factor activity. Since the discovery of Klotho a little over two decades ago, it has become ever more apparent that when Klotho pathways go awry, oxidative stress and mitochondrial dysfunction take over, and age-related chronic disorders are likely to follow. The physiological consequences can be wide ranging, potentially wreaking havoc on the brain, eye, kidney, muscle, and more. Central nervous system disorders, neurodegenerative in nature, and especially those affecting the myelin sheath, represent worthy targets for advancing therapies that act upon Klotho pathways. Current drugs for these diseases, even therapeutics that are disease modifying rather than treating only the symptoms, leave much room for improvement. It is thus no wonder that this topic has caught the attention of biomedical researchers around the world.

Published
2020

7. Klotho Pathways, Myelination Disorders, Neurodegenerative Diseases, and Epigenetic Drugs.

Author

Faller, Douglas, Glavas, Ioannis, Harpp, David, Kanara, Iphigenia, Mavrakis, Anastasios, Pernokas, Julie, Pernokas, Mark, Pinkert, Carl, Powers, Whitney, Sampani, Konstantina, Steliou, Kosta, Vavvas, Demetrios, Zamboni, Robert, Kodukula, Krishna, Chen, Xiaohong, and Moos, Walter

Subjects
Klotho, amyotrophic lateral sclerosis, mitochondria, multiple sclerosis, neurodegenerative disease
Abstract

In this review we outline a rationale for identifying neuroprotectants aimed at inducing endogenous Klotho activity and expression, which is epigenetic action, by definition. Such an approach should promote remyelination and/or stimulate myelin repair by acting on mitochondrial function, thereby heralding a life-saving path forward for patients suffering from neuroinflammatory diseases. Disorders of myelin in the nervous system damage the transmission of signals, resulting in loss of vision, motion, sensation, and other functions depending on the affected nerves, currently with no effective treatment. Klotho genes and their single-pass transmembrane Klotho proteins are powerful governors of the threads of life and death, true to the origin of their name, Fates, in Greek mythology. Among its many important functions, Klotho is an obligatory co-receptor that binds, activates, and/or potentiates critical fibroblast growth factor activity. Since the discovery of Klotho a little over two decades ago, it has become ever more apparent that when Klotho pathways go awry, oxidative stress and mitochondrial dysfunction take over, and age-related chronic disorders are likely to follow. The physiological consequences can be wide ranging, potentially wreaking havoc on the brain, eye, kidney, muscle, and more. Central nervous system disorders, neurodegenerative in nature, and especially those affecting the myelin sheath, represent worthy targets for advancing therapies that act upon Klotho pathways. Current drugs for these diseases, even therapeutics that are disease modifying rather than treating only the symptoms, leave much room for improvement. It is thus no wonder that this topic has caught the attention of biomedical researchers around the world.

Published
2020

9. Treatment and prevention of pathological mitochondrial dysfunction in retinal degeneration and in photoreceptor injury

Author

Moos, Walter H., Faller, Douglas V., Glavas, Ioannis P., Harpp, David N., Kamperi, Natalia, Kanara, Iphigenia, Kodukula, Krishna, Mavrakis, Anastasios N., Pernokas, Julie, Pernokas, Mark, Pinkert, Carl A., Powers, Whitney R., Sampani, Konstantina, Steliou, Kosta, Tamvakopoulos, Constantin, Vavvas, Demetrios G., Zamboni, Robert J., and Chen, Xiaohong

Published
2022
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10. Characterizing Vascular Wall and Lumen Caliber in Eyes with Diabetic Retinopathy Based on Adaptive Optics Scanning Laser Ophthalmoscopy.

Author

Sampani, Konstantina, Mujat, Mircea, Patel, Ankit H., Kang, Chaerim, Iftimia, Nicusor, Chatziralli, Irini, and Sun, Jennifer K.

Subjects
*SCANNING laser ophthalmoscopy, *TYPE 1 diabetes, *DIABETIC retinopathy, *ADAPTIVE optics, *RETINAL diseases, *RETINAL imaging
Abstract

(200/200) Purpose: Our aim was to evaluate structural alterations of retinal arterioles due to type 1 diabetes (T1D) and/or diabetic retinopathy (DR) under AOSLO imaging. Methods: Each study eye underwent mydriasis and AOSLO imaging in a single-visit study. The instrument's arrangement of four offset aperture images provided two orthogonal split-detector images and enabled isotropic analysis of the arteriolar boundaries. For each arteriole, we calculated the wall-to-lumen ratio (WLR), mean wall thickness, and luminal and external diameters. Results: In total, we enrolled 5 (20.8%) healthy control eyes and 19 eyes of patients with T1D. The DR distribution was: four (16.7%) no-DR, nine (37.5%%) mild or moderate nonproliferative DR (NPDR), and six (25%) severe NPDR or proliferative DR. Mean wall thickness increased significantly in eyes with T1D compared to healthy controls (p = 0.0006) and in eyes with more advanced DR (p = 0.0004). The WLR was significantly higher in eyes with T1D (p = 0.002) or more severe DR (p = 0.004). There was no significant relationship between T1D status or DR severity and any of the arteriolar diameters. Conclusions: In this preliminary study, there appeared to be increases in the WLR and mean wall thickness in eyes with T1D and more severe DR than in the controls and eyes with no/less severe DR. Future studies may further elucidate the relationship between the retinal arteriolar structure and physiologic alterations in DR. [ABSTRACT FROM AUTHOR]

Published
2024
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15. AOSLO-net: A Deep Learning-Based Method for Automatic Segmentation of Retinal Microaneurysms From Adaptive Optics Scanning Laser Ophthalmoscopy Images

Author

Zhang, Qian, Sampani, Konstantina, Xu, Mengjia, Cai, Shengze, Deng, Yixiang, Li, He, Sun, Jennifer K., and Karniadakis, George Em

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, Optics and Photonics, Diabetic Retinopathy, Computer Vision and Pattern Recognition (cs.CV), Lasers, Image and Video Processing (eess.IV), Computer Science - Computer Vision and Pattern Recognition, Biomedical Engineering, Electrical Engineering and Systems Science - Image and Video Processing, Microaneurysm, Machine Learning (cs.LG), Ophthalmoscopy, Ophthalmology, Deep Learning, FOS: Electrical engineering, electronic engineering, information engineering, Humans
Abstract

Accurate segmentation of microaneurysms (MAs) from adaptive optics scanning laser ophthalmoscopy (AOSLO) images is crucial for identifying MA morphologies and assessing the hemodynamics inside the MAs. Herein, we introduce AOSLO-net to perform automatic MA segmentation from AOSLO images of diabetic retinas.AOSLO-net is composed of a deep neural network based on UNet with a pretrained EfficientNet as the encoder. We have designed customized preprocessing and postprocessing policies for AOSLO images, including generation of multichannel images, de-noising, contrast enhancement, ensemble and union of model predictions, to optimize the MA segmentation. AOSLO-net is trained and tested using 87 MAs imaged from 28 eyes of 20 subjects with varying severity of diabetic retinopathy (DR), which is the largest available AOSLO dataset for MA detection. To avoid the overfitting in the model training process, we augment the training data by flipping, rotating, scaling the original image to increase the diversity of data available for model training.The validity of the model is demonstrated by the good agreement between the predictions of AOSLO-net and the MA masks generated by ophthalmologists and skillful trainees on 87 patient-specific MA images. Our results show that AOSLO-net outperforms the state-of-the-art segmentation model (nnUNet) both in accuracy (e.g., intersection over union and Dice scores), as well as computational cost.We demonstrate that AOSLO-net provides high-quality of MA segmentation from AOSLO images that enables correct MA morphological classification.As the first attempt to automatically segment retinal MAs from AOSLO images, AOSLO-net could facilitate the pathological study of DR and help ophthalmologists make disease prognoses.

Published
2022

17. Pathogenic mitochondrial dysfunction and metabolic abnormalities

Author

Moos, Walter H., primary, Faller, Douglas V., additional, Glavas, Ioannis P., additional, Harpp, David N., additional, Kamperi, Natalia, additional, Kanara, Iphigenia, additional, Kodukula, Krishna, additional, Mavrakis, Anastasios N., additional, Pernokas, Julie, additional, Pernokas, Mark, additional, Pinkert, Carl A., additional, Powers, Whitney R., additional, Steliou, Kosta, additional, Tamvakopoulos, Constantin, additional, Vavvas, Demetrios G., additional, Zamboni, Robert J., additional, and Sampani, Konstantina, additional

Published
2021
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18. Retinal Vascular Caliber Association with Nonperfusion and Diabetic Retinopathy Severity Depends on Vascular Caliber Measurement Location

Author

Ashraf, Mohamed, primary, Shokrollahi, Siamak, additional, Pisig, Alex U., additional, Sampani, Konstantina, additional, Abdelal, Omar, additional, Cavallerano, Jerry D., additional, Robertson, Gavin, additional, Fleming, Alan, additional, van Hemert, Jano, additional, Pitoc, Cloyd M., additional, Sun, Jennifer K., additional, Aiello, Lloyd Paul, additional, and Silva, Paolo S., additional

Published
2021
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20. Response to Letter to the Editor from Brunerova et al: “Association of Cognitive Function and Retinal Neural and Vascular Structure in Type 1 Diabetes”

Author

Fickweiler, Ward, primary, Wolfson, Emily A, additional, Paniagua, Samantha M, additional, Yu, Marc Gregory, additional, Adam, Atif, additional, Bahnam, Vanessa, additional, Sampani, Konstantina, additional, Wu, I-Hsien, additional, Musen, Gail, additional, Aiello, Lloyd P, additional, Shah, Hetal, additional, Sun, Jennifer K, additional, and King, George L, additional

Published
2021
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21. S1. Modeling platelet transport and aggregation using Force coupling method from Predictive modelling of thrombus formation in diabetic retinal microaneurysms

Author

Li, He, Sampani, Konstantina, Xiaoning Zheng, Papageorgiou, Dimitrios P., Alireza Yazdani, Bernabeu, Miguel O., Karniadakis, George E., and Sun, Jennifer K.

Subjects
body regions, musculoskeletal diseases, fungi, lipids (amino acids, peptides, and proteins), hormones, hormone substitutes, and hormone antagonists
Abstract

Microaneurysms (MAs) are one of the earliest clinically visible signs of diabetic retinopathy (DR). Vision can be reduced at any stage of DR by MAs, which may enlarge, rupture and leak fluid into the neural retina. Recent advances in ophthalmic imaging techniques enable reconstruction of the geometries of MAs and quantification of the corresponding hemodynamic metrics, such as shear rate and wall shear stress, but there is lack of computational models that can predict thrombus formation in individual MAs. In this study, we couple a particle model to a continuum model to simulate the platelet aggregation in MAs with different shapes. Our simulation results show that under a physiologically relevant blood flow rate, thrombosis is more pronounced in saccular-shaped MAs than fusiform-shaped MAs, in agreement with recent clinical findings. Our model predictions of the size and shape of the thrombi in MAs are consistent with experimental observations, suggesting that our model is capable of predicting the formation of thrombus for newly detected MAs. This is the first quantitative study of thrombosis in MAs through simulating platelet aggregation, and our results suggest that computational models can be used to predict initiation and development of intraluminal thrombus in MAs as well as provide insights into their role in the pathophysiology of DR.

Published
2020
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22. S3. Growth of thrombus with respect to time from Predictive modelling of thrombus formation in diabetic retinal microaneurysms

Author

Li, He, Sampani, Konstantina, Xiaoning Zheng, Papageorgiou, Dimitrios P., Alireza Yazdani, Bernabeu, Miguel O., Karniadakis, George E., and Sun, Jennifer K.

Subjects
body regions, musculoskeletal diseases, fungi, lipids (amino acids, peptides, and proteins), hormones, hormone substitutes, and hormone antagonists
Abstract

Microaneurysms (MAs) are one of the earliest clinically visible signs of diabetic retinopathy (DR). Vision can be reduced at any stage of DR by MAs, which may enlarge, rupture and leak fluid into the neural retina. Recent advances in ophthalmic imaging techniques enable reconstruction of the geometries of MAs and quantification of the corresponding hemodynamic metrics, such as shear rate and wall shear stress, but there is lack of computational models that can predict thrombus formation in individual MAs. In this study, we couple a particle model to a continuum model to simulate the platelet aggregation in MAs with different shapes. Our simulation results show that under a physiologically relevant blood flow rate, thrombosis is more pronounced in saccular-shaped MAs than fusiform-shaped MAs, in agreement with recent clinical findings. Our model predictions of the size and shape of the thrombi in MAs are consistent with experimental observations, suggesting that our model is capable of predicting the formation of thrombus for newly detected MAs. This is the first quantitative study of thrombosis in MAs through simulating platelet aggregation, and our results suggest that computational models can be used to predict initiation and development of intraluminal thrombus in MAs as well as provide insights into their role in the pathophysiology of DR.

Published
2020
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23. S2. Wall shear stress in microaneurysms from Predictive modelling of thrombus formation in diabetic retinal microaneurysms

Author

Li, He, Sampani, Konstantina, Xiaoning Zheng, Papageorgiou, Dimitrios P., Alireza Yazdani, Bernabeu, Miguel O., Karniadakis, George E., and Sun, Jennifer K.

Subjects
body regions, musculoskeletal diseases, fungi, lipids (amino acids, peptides, and proteins), hormones, hormone substitutes, and hormone antagonists
Abstract

Microaneurysms (MAs) are one of the earliest clinically visible signs of diabetic retinopathy (DR). Vision can be reduced at any stage of DR by MAs, which may enlarge, rupture and leak fluid into the neural retina. Recent advances in ophthalmic imaging techniques enable reconstruction of the geometries of MAs and quantification of the corresponding hemodynamic metrics, such as shear rate and wall shear stress, but there is lack of computational models that can predict thrombus formation in individual MAs. In this study, we couple a particle model to a continuum model to simulate the platelet aggregation in MAs with different shapes. Our simulation results show that under a physiologically relevant blood flow rate, thrombosis is more pronounced in saccular-shaped MAs than fusiform-shaped MAs, in agreement with recent clinical findings. Our model predictions of the size and shape of the thrombi in MAs are consistent with experimental observations, suggesting that our model is capable of predicting the formation of thrombus for newly detected MAs. This is the first quantitative study of thrombosis in MAs through simulating platelet aggregation, and our results suggest that computational models can be used to predict initiation and development of intraluminal thrombus in MAs as well as provide insights into their role in the pathophysiology of DR.

Published
2020
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24. Association of Cognitive Function and Retinal Neural and Vascular Structure in Type 1 Diabetes

Author

Fickweiler, Ward, primary, Wolfson, Emily A, additional, Paniagua, Samantha M, additional, Yu, Marc Gregory, additional, Adam, Atif, additional, Bahnam, Vanessa, additional, Sampani, Konstantina, additional, Wu, I-Hsien, additional, Musen, Gail, additional, Aiello, Lloyd P, additional, Shah, Hetal, additional, Sun, Jennifer K, additional, and King, George L, additional

Published
2020
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31. Disparity of microaneurysm count between ultrawide field colour imaging and ultrawide field fluorescein angiography in eyes with diabetic retinopathy

Author

Ashraf, Mohamed, primary, Sampani, Konstantina, additional, AbdelAl, Omar, additional, Fleming, Alan, additional, Cavallerano, Jerry, additional, Souka, Ahmed, additional, El Baha, Samir Mohamed, additional, Silva, Paolo S, additional, Sun, Jennifer, additional, and Aiello, Lloyd Paul, additional

Published
2020
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32. Epigenetic treatment of dermatologic disorders

Author

Moos, Walter H., primary, Faller, Douglas V., additional, Glavas, Ioannis P., additional, Harpp, David N., additional, Kanara, Iphigenia, additional, Pinkert, Carl A., additional, Powers, Whitney R., additional, Sampani, Konstantina, additional, Steliou, Kosta, additional, Vavvas, Demetrios G., additional, Kodukula, Krishna, additional, and Zamboni, Robert J., additional

Published
2019
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34. Association of Cognitive Function and Retinal Neural and Vascular Structure in Type 1 Diabetes.

Author

Fickweiler, Ward, Wolfson, Emily A., Paniagua, Samantha M., Yu, Marc Gregory, Adam, Atif, Bahnam, Vanessa, Sampani, Konstantina, Wu, I.-Hsien, Musen, Gail, Aiello, Lloyd P., Shah, Hetal, Sun, Jennifer K., and King, George L.

Subjects
TYPE 1 diabetes, COGNITIVE ability
Abstract

Context: Cognitive dysfunction is a growing and understudied public health issue in the aging type 1 diabetic population and is difficult and time-consuming to diagnose. Studies in long duration type 1 diabetes have reported the presence of proliferative diabetic retinopathy was associated with cognitive dysfunction.Objective: This study assessed whether structural and vascular abnormalities of the retina, representing an extension of the central nervous system, are associated with cognitive impairment and other complications of type 1 diabetes.Methods: An observational cross-sectional study of individuals with 50 or more years of type 1 diabetes (Joslin Medalist Study) was conducted at a university hospital in the United States. The study included 129 participants with complete cognitive testing. Validated cognitive testing measures included psychomotor speed, and immediate, and delayed memory. Optical coherence tomography (OCT) and OCT angiography (OCTA) were performed to obtain neural retinal layer thicknesses and vascular density for superficial (SCP) and deep retinal capillary plexus (DCP). Multivariable modeling was adjusted for potential confounders associated with outcomes in unadjusted analyses.Results: Decreased vessel density of the SCP and DCP was associated with worse delayed memory (DCP: P = .002) and dominant hand psychomotor speed (SCP: P = .01). Thinning of the retinal outer nuclear layer was associated with worse psychomotor speed both in nondominant and dominant hands (P = .01 and P = .05, respectively). Outer plexiform layer thickness was associated with delayed memory (P = .04).Conclusion: These findings suggest that noninvasive retinal imaging using OCT and OCTA may assist in estimating the risks for cognitive dysfunction in people with type 1 diabetes. [ABSTRACT FROM AUTHOR]

Published
2021
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35. Cardiac Enlargement in US Firefighters: Prevalence Estimates by Echocardiography, Cardiac Magnetic Resonance and Autopsies

Author

Maria Korre, Sampani, Konstantina, Porto, Luiz Guilherme G, Yang, Yustin, Christiani, David C, Christophi, Costas A, Lombardi, David A, Kovacs, Richard J, Mastouri, Ronald, Abbasi, Siddique, Steigner, Michael, Moffatt, Steven, Smith, Denise L, Kales, Stefanos N., FARIOLI, ANDREA, Maria Korre, Sampani, Konstantina, Porto, Luiz Guilherme G, Farioli, Andrea, Yang, Yustin, Christiani, David C, Christophi, Costas A, Lombardi, David A, Kovacs, Richard J, Mastouri, Ronald, Abbasi, Siddique, Steigner, Michael, Moffatt, Steven, Smith, Denise L, and Kales, Stefanos N

Subjects
Heart weight, Body surface area, medicine.medical_specialty, business.industry, Cardiac enlargement, Autopsy, 030204 cardiovascular system & hematology, Left ventricular hypertrophy, medicine.disease, Omics, Firefighter, Sudden Cardiac Death, 030210 environmental & occupational health, Surgery, Sudden cardiac death, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, cardiovascular system, Cardiology, Medicine, cardiovascular diseases, Cardiology and Cardiovascular Medicine, business, Cardiac magnetic resonance
Abstract

Background: Cardiovascular Disease (CVD) accounts for 45% of on-duty deaths in US fire service; cardiac enlargement is common among US firefighters; and plays a major role in firefighter Sudden Cardiac Death (SCD). Objective: To estimate the prevalence of cardiac enlargement in US Firefighters by autopsies, echocardiography (ECHO) and Cardiac Magnetic Resonance (CMR). Methods: In the present cross-sectional study, the prevalence of Left Ventricular Hypertrophy (LVH)/ cardiomegaly was a) estimated non-invasively among active career firefighters and b) examined by reviewing autopsies of firefighters who suffered a non-cardiac, on-duty fatality. Left ventricular mass (LVM) among active career firefighters was assessed by ECHO and CMR, and normalized (indexed) for body surface area (BSA) and height. Autopsy estimates were based on cardiac weights and other forensic parameters. Results: LVH prevalence estimates among active career firefighters presented a range from 3.3% to 32.8% among ECHO; and 0.0% to 5.3% among CMR criteria. LVH was present in 17.5% and 0.4% of the active firefighters as defined by LVM indexed to height 1.7 (by ECHO and CMR, respectively). LVM indexed to BSA as measured by CMR indicated zero prevalence of LVH. Among non-cardiac traumatic autopsies, prevalence estimates of cardiomegaly and LVH were 39.5% (95% CI 33.7–45.3) and 45.4% (95% CI 39.5–51.4) respectively, even after adjustment for age and BMI. Conclusions: The prevalence of cardiac enlargement varied widely depending on the imaging assessment, the cutoffs and the normalization techniques. For autopsy data, BMI was a major determinant of heart weight. Future CVD-outcome based studies are needed to provide evidence for the most accurate clinical cutoffs, while standardization of autopsies is needed across protocols and jurisdictions.

Published
2016

38. Assessment of Baseline Ultrawidefield Fluorescein Angiographic Quantitative Leakage Parameters with Ultrawidefield Fundus Features and Clinical Parameters in Diabetic Retinopathy in Protocol AA

Author

Ehlers, Justis P., Josic, Kristin, Yordi, Sari, Martin, Alison, Srivastava, Sunil K., Sun, Jenifer K., Harara, Abla M., Palacios, Angela N., Berger, Brian B., Corak, Boris, Luong, Bianca, Jhaveri, Chirag D., Wilson, Daniela Mariel, Jonna, Gowtham, Gunderson, Ivana, Hosein, Kimberly, Reid, Ryan M., Chexal, Saradha, Moore, Tori, Seidu, Tina A., Gatavaski, Valerie, Ren, Yong, Stern, Bradley A., Benvenutti, Celia E., Oude-Reimerink, Dinah S., Shaheen, Jenny, Grybas, John, Vitale-Kuhn, Julianne, Staffne, Jessica L., Ventimiglia, Katie M., Allis, Megan, Monk, Mary K., Thomas, Marc E., Massu, Nicole M., Edwards, Paul Andrew, Troszak, Tracy A., Irons, Amber N., Rego, Brittany, Han, Dennis P., Dorsey, Eleanor, Nelson, Erika, Sheppard, Hannah, Beringer, Joseph R., Kim, Judy E., Keller, Kristy L., Packard, Krissa L., Altmann, Marriner L., Goldberg, Mara, Chen, Nickolas, Winter, Pat A., Bourgeois, Shay, Jacobo, Samantha, Moebius, Stephanie J., Connor, Thomas B., Barwick, Vicki, Williams, Vesper V., Wirostko, William J., Ghuman, A. Thomas, Leslie, Anita H., Sharma, Ashish G., Kiesel, Cheryl, Dyshanowitz, Danielle, Knips, Eileen, Wing, Glenn, Walker, Joseph P., Raskauskas, Paul A., Kiesel, Raymond K., Schlossman, Deborah K., Weimann, Elizabeth S., Sharuk, George S., Kwak, Hanna, Cavallerano, Jerry D., Rhee, Jae W., Sampani, Konstantina, Tran, Katie V., Bestourous, Leila, Miranda, Linette, Krigman, Michael N., Stockman, Margaret E., Arrigg, Paul G., Cavicchi, Robert W., Kirby, Rita K., Glynn, Shireen, Papaconstantinou, Steve L., Shah, Sabera T., Murtha, Timothy J., Carli, William, Finch, Autumn K., Gentile, Angella K., Price, Angela K., Murphy, Brittany A., Rowland, Beverly O., Fleming, Christina J., Mahr, Courtney, Shore, Carol A., Browning, David, McClain, Donna, Breglio, Erica, Lester, Gina M., Herby, Jenna T., Bratcher, Kayla A., Clark, Loraine M., Jackson, Lisa A., Watson, Lynn, McOwen, Michael D., Punjabi, Omar S., Bojaj, Swann J., Ennis, Sarah A., Fredenberg, Sherry L., Jones, Taylor S., Ragin, Teneisha A., Balasubramaniam, Uma M., Ornelas, Blanca, Rodriquez, Brenda, Edwards, Carla, Carns, Danielle R., Tonner, Eileen E., Woo, Kisung, Richine, Len, MacCumber, Mathew W., Merrill, Pauline Townsend, Kociborski, Sarah, Harless, Ashley M., Harris, Charlotte, White, Lorraine, Maturi, Raj K., Asher, Julie, Walsh, Justin, Wheeler, Jeff, Milstead, Katie, Oliver, Kristina, Lovelady, Lisa, Anderson, Nicholas G., Coppola, Patricia, Lince, Raul E., Shuler, R. Keith, Morris, Steve, Oelrich, Sarah M., Gardner, Brandon S., Moore, Bob, Cain, Dennis, Donohue, Deborah, Emmert, David, Adeyemo, Kemi, Levin, Lisa K., Frey, Mary, Rhoton, Nick, Bressler, Susan, Solomon, Sharon D., Ford, Amy L., Hughes, Ashley, Brewer, Alisha N., Booth, JoAnn T., Lunsford, Keven W., Ukleya, Lauren D., Burris, Russ, Kingsley, Ronald M., Almeida, Shannon R., Icks, Sonny, Shah, Vinay A., Bergman, Vanessa A., Castellarin, Alessandro A., Shook, Aimee H., Walker, Aimee, Pieramici, Dante J., Hong, Gina, Avery, Kelly, McKee, Kate M., Giust, Matthew, Munoz, Marco A., Fishbein, Sarah, Camp, Alecia B., Baker, Carl W., Baker, Jil D., Sedberry, Kylie S., Lambert, Lynnette F., Orr, Margaret J., Alcaraz, Sonya L., Kettler, Samantha, Caldwell, Tracey M., Miller, Abigail, Dorr, Christine M., Hampton, G. Robert, Brown, Jamin S., Barker, Jeffrey P., Rosenberg, Kevin I., Kwasniewski, Lynn M., Sienkiewycz, Laurie J., Spuches, Lisa, Manley, Michelle L., Robarge, Nicole E., DeSantis, Stefanie R., DeForge, Teresa M., Brucker, Alexander J., Kim, Benjamin J., Berger, Jim M., DuPont, Joan C., Drossner, Sheri, Freeman, Sara, Studebaker, Ashley, Payne, John F., Wells, John A., Spivey, Robbin, Ogbuewu, Tiffany N., Swinford, Tiffany R., Guillory, Adrienne, Hutson, Amy, Schefler, Amy C., Shah, Ankoor R., Almanza, Belinda A., Dives, Brenda, Richter, Beau A., Stoever, Cary A., Brown, David M., Foerster, Danee, Garcia, David, Rodriguez, Diana, Park, Daniel, Chen, Eric, Kegley, Eric N., Quellar, Elizabeth, Twining, Garret L., Koger-Grifaldo, Heather, Ortega, Ilsa, Carranza, Jolene, Major, James C., Williamson, Kimberly, Burt, Lindsay, Salinas, Luis R., Wolff, Lisa M., Benz, Matthew S., Estes, Maura A., James, Miranda F., Berry, Meredith, Vela, Melina, Landaverde, Nubia, Webb, Nina A., Fish, Richard H., Kim, Rosa Y., Yee, Rebecca, Karani, Sadia Y., Supapo, Stacy M., Dodel, Tamara L., McCoy, Tyneisha, Wong, Tien P., Sneed, Veronica A., Barnhart, Cassandra J., Cantrell, Debra, DuBose, Elizabeth L., Sharpe, Houston P., Ulrich, Jan Niklas, Bhansali, Kanika A., Esquejo, Rona Lyn, Garg, Seema, Grout, Sean, McKinney, Allen, Bobbitt, Brenda J., Wendel, Ceara L., Fagan, Damanda F., Andrews, Jacqueline, Holmes, Krystal Nikki, Seyez, Karen L., Williamson, Kimberly A., Moinfar, Nader, Walters, Paige N., Carlton, Steve, Rehling, Shannon M., Williams, Shana E., Reed, Tiara L., VandeVelde, Amber R., Yeager, Frank T., Fox, Gregory M., Batlle, Ivan R., Bruce, Kiersten, Pippin, Katherine, Ainley, Lexie R., Singh, Ravi S.J., Adamo, Ashley M., Guardado, Adrian, Patel, Apurva K., Puckett, Brian S., Hoerner, Christine, Ma, Colin, Clark, David J., Flato, Inessa M., Cohen, Joshua, Charpentier, Margaret E., Kopfer, Marcia, Peters, Mark A., Smith, Pualani, Tlucek, Paul S., Hobbs, Stephen, Ho, Stephanie L., Metzger, Ashley M., McCalla, Alesia K., Thompson, Amy, Ringrose, Christine, Sandler, Dallas R., Leder, Henry A., Belz, Jennifer L., Starr, JoAnn, Simmons, Jennifer L., Orr, Peggy R., Sotirakos, Peter, Singletary, Pamela V., Cain, Terri, Coffey, Teresa, Carter, Tiffany M., Robinson, Twyla J., Shah, Chirag P., Cammarata, Dominique, Kruger, Jennifer L., Colegrove, Lindsey, Graham, Margie, Gleason, Shane T., Noel, Bryan, Damron, Catherine, Holcomb, Diana M., Slade, Edward A., Van Arsdall, Jeanne, Bicknell, Lisa, Buck, Michelle, Stone, Thomas W., Farooq, Amina, Parsons, Brook, Singh, Harinderjit, Ivey, Ken, Foster, Lindsay Allison, Woodward, Michele, Ortiz, Siobhan O., Bailey, Thomas, Mynampati A, Bharani Krishna, White, Cheryl L., Hamdani, Ghulam Shabbir, Smith, Jazzmin N., Chalam, Kakarla V., Sambhav, Kumar, Babaria, Romesh, Grover, Sandeep, Carroll, Catherine, Chau, Felix Y., Lim, Jennifer I., Talasnik, Lauren A., Janowicz, Mark, Stankovic, Natasa, Berlatsky, Sarah L., Niec, Marcia, Sun, Jie, Johnson, Tametha, Ovando, Yesenia, Nakoski, Brenda, Mein, Calvin E., Wienecke, Christopher Sean, Castillo, Elaine, Baker, Jaynee, San Roman, Jonathan, Adams, Lydia, Kirschbaum, Lita, Chica, Moises A., Cloudt, Sara L., Moore, Tori R., Sabates, Felix N., Gallimore, Gary S., Chen, Yin C., Swann, Adrienne C., Cadwell, Deborah M., Diddie, Kenneth R., Boisvert, Taryn F., Tessau, Carrie D., Bowers, Jack, Nielsen, Jared S., Rostvold, Jay, Spillman, Jamie, Alliman, Kyle J., Boender, Lisa M., Johnson, Marilyn A., Parker, Marianne, Bix, Paula L., Ridgway, Spencer D., Woehl, Tami Jo, Stonewall, Whitney, Brown, Christopher M., Lema, Gareth M.C., Wiechelt, Luann, Yoganathan, Pradeepa, Boglione, Sandra L., Montesclaros, Chris A., Mangham, Cory, Karsaliya, Gopal, Le, Phillip V., Wong, Robert W., Godfrey, Anne Marie, Kuzmanovic, Aleksandra, Kirker, Andrew William, Harrison, Bryan, Forooghian, Farzin, Elvena, Garnet Louise, Hall, Laura J., Turhal, Bilgin, Brown, Ian, Kotei, Isaac A., Chen, Lina, Brent, Michael Henry, Moon, Michelle, Sutakovic, Olivera, Chang, Angela, Godfrey, Anne-Marie, Kirker, Andrew William, Kuzmanovic, Aleksandra, Harrison, Bryan, Albiani, David, Maberley, David A.L., Navajas, Eduardo Vitor, Grant, Kelly, Tran, Khoi A., Hall, Laura J., Jovanovic, Mira, Cao, Sijia, Wiens, Theresa, Kozbial, Andrzej, Orlin, Anton, Lenane, Courtney Nichole, Herder, Susan P., Kiss, Szilard, Reeves, Tom, Cruess, Alan F., Dean, Andrea, Hoskin-Mott, Ann, Morrison, Christine, Caldwell, Meggie D., Hynes, Mitzi, Gupta, R. Rishi, Durling, Stacey, MacDonnell, Trina, Beck, Roy W., Baptista, Alyssa, Beaulieu, Wesley T., Calhoun, Claire T., Constantine, Sharon R., Correia, Isabella, Dale, Brian B., Dupre, Simone S., Franklin, Crystal A., Galusic, Sandra, Huggins, Meagan, Hunter, Brenda L., Johnson, Paula A., Josic, Kristin, Kelly, Brittany, Maguire, Maureen G., Meadows, Britney, Stockdale, Cynthia R., Zokruah, Alice, Bhargava, Sangeeta, Barkmeier, Andrew J., Baskin, Darrell, Blodi, Barbra, Chew, Emily, Ferris, Frederick L., Jaffe, Glenn J., Bressler, Neil M., Lujan, Brandon, Tolls, Dorothy, Sheridan, Daniel, Pitoc, Cloyd M., Anne C Aquino, Lizzie, Salva, Claude Michael G., Lewis, Drew, Stainback, Jeffery, Makkena, Vijaya, Winter, Katrina, Mora, Adiel, Harrington, Chris, and Vinh, Doc-Lap

Abstract

Evaluate quantitative leakage parameters on ultrawidefield fluorescein angiography (UWF-FA) images and explore their association with Diabetic Retinopathy Severity Scale (DRSS), predominantly peripheral lesions (PPLs), visual acuity, and clinical characteristics.

Published
2024
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40. 86-OR: Association of Cognitive Function with Retinal Neural Structure and Vasculature in Type 1 Diabetes.

Author

PANIAGUA, SAMANTHA M., FICKWEILER, WARD, BAHNAM, VANESSA, SAMPANI, KONSTANTINA, WU, I-HSIEN, SHAH, HETAL, MUSEN, GAIL, AIELLO, LLOYD P., SUN, JENNIFER K., and KING, GEORGE L.

Abstract

Early cognitive decline, a dreaded complication of diabetes, is difficult and time consuming to diagnose. The Joslin Medalist Study, comprising individuals with ≥50 years of type 1 diabetes (T1D), reported that cognitive dysfunction was greater in T1D patients as compared to age-matched nondiabetic controls and was associated with proliferative diabetic retinopathy (PDR). We examined a larger Medalist sample to determine whether cognitive dysfunction is correlated with specific structural and vascular abnormalities in the retina, which embryonically is an extension of the central nervous system. Retinal imaging techniques such as optical coherence tomography (OCT) and OCT angiography (OCTA) can quantitate structural changes in individual retinal layers and the superficial and deep capillary plexus of the retinal microvasculature. We assessed Medalists (n=110) who underwent cognitive testing consisting of 5 validated measures in the following domains: executive functioning (EF), motor skills (MS), and immediate (IM), delayed (DM) and working memory (WM). Thinning of the neuroretinal ganglion cell layer (β: 0.69, P: 0.02) and inner plexiform layer (β: 0.56, P: 0.01) was associated with worse EF. PDR was associated with worse cognitive function (MS, dominant hand: OR: 1.02, P: 0.01; MS, non-dominant hand: OR: 1.01, P: 0.02; EF: OR: 0.83, P: 0.03) and decreased superficial retinal capillary plexus density (p=0.001). Decreased vessel density of the deep capillary plexus was associated with worse cognitive function including DM (β: 0.10, P: 0.01), IM (β: 0.10, P: 0.02), MS (dominant β: -0.07, P: 0.01; non-dominant β: -0.04, P: 0.03), even after adjusting for DR severity, T1D duration and visual acuity. These findings suggest that noninvasive ocular imaging techniques have potential to identify T1D individuals with early cognitive impairment, and provide insights into pathophysiological connections between cognitive function, diabetes and microvascular complications. Disclosure: S.M. Paniagua: None. W. Fickweiler: None. V. Bahnam: None. K. Sampani: None. I. Wu: None. H. Shah: None. G. Musen: None. L.P. Aiello: Advisory Panel; Self; Novo Nordisk A/S. Consultant; Self; Decision Resources Group, KalVista Pharmaceuticals, Inc., Mingsight, Retinal Solutions. Stock/Shareholder; Self; KalVista Pharmaceuticals, Inc. Other Relationship; Self; Optos. J.K. Sun: Research Support; Self; Adaptive Sensory Technology, Boston Micromachines Corporation, Genentech, Inc., KalVista Pharmaceuticals, Inc., Optovue, Incorporated. Other Relationship; Self; Genentech, Inc., Novartis Pharmaceuticals Corporation, Novo Nordisk Inc. G.L. King: Research Support; Self; Sanofi. Funding: National Institute of Diabetes and Digestive and Kidney Diseases (P30DK036836, UL1RR025758-03, R24283DK083957-01, DP3DK094333-01, T32DK007260); JDRF (17-2013-310); Thomas J. Beatson, Jr. Foundation Inc. [ABSTRACT FROM AUTHOR]

Published
2019
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