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Retinal aging in 3× Tg-AD mice model of Alzheimer's disease

2022Journal article Open access
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dc.contributor.authorGuimarães, Pedro
dc.contributor.authorSerranho, Pedro
dc.contributor.authorMartins, João
dc.contributor.authorMoreira, Paula I.
dc.contributor.authorAmbrósio, António Francisco
dc.contributor.authorCastelo-Branco, Miguel
dc.contributor.authorBernardes, Rui
dc.date.accessioned2023-01-03T15:39:22Z
dc.date.available2023-01-03T15:39:22Z
dc.date.issued2022
dc.description.abstractThe retina, as part of the central nervous system (CNS), can be the perfect target for in vivo, in situ, and noninvasive neuropathology diagnosis and assessment of therapeutic efficacy. It has long been established that several age-related brain changes are more pronounced in Alzheimer’s disease (AD). Nevertheless, in the retina such link is still under-explored. This study investigates the differences in the aging of the CNS through the retina of 3×Tg-AD and wild-type mice. A dedicated optical coherence tomograph imaged mice’s retinas for 16 months. Two neural networks were developed to model independently each group’s ages and were then applied to an independent set containing images fromboth groups. Our analysis shows amean absolute error of 0.875±1.1×10−2 and 1.112 ± 1.4 × 10−2 months, depending on training group. Our deep learning approach appears to be a reliable retinal OCT aging marker. We show that retina aging is distinct in the two classes: the presence of the three mutated human genes in the mouse genome has an impact on the aging of the retina. For mice over 4 months-old, transgenic mice consistently present a negative retina age-gap when compared to wildtype mice, regardless of training set. This appears to contradict AD observations in the brain. However, the ‘black-box” nature of deep-learning implies that one cannot infer reasoning. We can only speculate that some healthy age-dependent neural adaptations may be altered in transgenic animals.pt_PT
dc.description.sponsorshipThis study was supported by The Portuguese Foundation for Science and Technology (FCT) through PTDC/EMD-EMD/28039/2017, UIDB/04950/2020, PestUID/NEU/04539/2019, and by FEDER-COMPETE through POCI-01-0145-FEDER-028039.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3389/fnagi.2022.832195pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.2/12927
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relationCoimbra Institute for Biomedical Imaging and Translational Research
dc.relationCNC. IBILI
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectAgingpt_PT
dc.subjectArtificial intelligencept_PT
dc.subjectAge-gappt_PT
dc.subjectAlzheimer’s diseasept_PT
dc.subjectDeep learningpt_PT
dc.subjectAnimal modelpt_PT
dc.subjectRetinapt_PT
dc.subjectOptical coherence tomographypt_PT
dc.titleRetinal aging in 3× Tg-AD mice model of Alzheimer's diseasept_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCoimbra Institute for Biomedical Imaging and Translational Research
oaire.awardTitleCNC. IBILI
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/9471 - RIDTI/PTDC%2FEMD-EMD%2F28039%2F2017/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04950%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FNEU%2F04539%2F2019/PT
oaire.citation.titleFrontiers in Aging Neurosciencept_PT
oaire.citation.volume14pt_PT
oaire.fundingStream9471 - RIDTI
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameSerranho
person.familyNameCastelo-Branco
person.familyNameDias Cortesão dos Santos Bernardes
person.givenNamePedro
person.givenNameMiguel
person.givenNameRui Manuel
person.identifierM-4231-2013
person.identifier.ciencia-id031F-5D62-E6EC
person.identifier.ciencia-id7A12-48FE-7B56
person.identifier.ciencia-idDB19-B18E-690C
person.identifier.orcid0000-0003-2176-3923
person.identifier.orcid0000-0003-4364-6373
person.identifier.orcid0000-0002-6677-2754
person.identifier.scopus-author-id7004634386
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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