Aging-related cognitive decline is associated with changes across different tissues and the gut microbiome, including dysfunction of the gut-brain axis. However, only few studies have linked multi-organ alterations to cognitive decline during aging. Here we report a multi-omics analysis integrating metabolomics, transcriptomics, DNA methylation, and metagenomics data from hippocampus, liver, colon, and fecal samples of mice, correlated with cognitive performance in the Barnes Maze spatial learning task across different age groups. We identified 734 molecular features associated with cognitive rank within individual data layers, of which 227 features remain when integrating all data layers with each other. Among the single-layer predictors, several host and microbial features were highlighted, with host-associated markers being predominant. Host features associated with cognitive function mainly belong to innate and adaptive inflammatory activity (inflammaging) and developmental processes. Our findings suggest that cognitive decline in aging is tightly coupled to systemic, age-associated inflammation, potentially initiated by microbiome-driven gastrointestinal inflammatory activity, emphasizing a link between peripheral tissue alterations and brain function.

Aging is accompanied by considerable changes in the gut microbiome, yet the molecular mechanisms driving aging and the role of the microbiome remain unclear. Here we combined metagenomics, transcriptomics and metabolomics from aging mice with metabolic modelling to characterize host-microbiome interactions during aging. Reconstructing integrated metabolic models of host and 181 mouse gut microorganisms, we show a complex dependency of host metabolism on known and previously undescribed microbial interactions. We observed a pronounced reduction in metabolic activity within the aging microbiome accompanied by reduced beneficial interactions between bacterial species. These changes coincided with increased systemic inflammation and the downregulation of essential host pathways, particularly in nucleotide metabolism, predicted to rely on the microbiota and critical for preserving intestinal barrier function, cellular replication and homeostasis. Our results elucidate microbiome-host interactions that potentially influence host aging processes. These pathways could serve as future targets for the development of microbiome-based anti-aging therapies.

Aging is the predominant cause of morbidity and mortality in industrialized countries. The specific molecular mechanisms that drive aging are poorly understood, especially the contribution of the microbiota in these processes. Here, we combined multi-omics with metabolic modeling in mice to comprehensively characterize host-microbiome interactions and how they are affected by aging. Our findings reveal a complex dependency of host metabolism on microbial functions, including previously known as well as novel interactions. We observed a pronounced reduction in metabolic activity within the aging microbiome, which we attribute to reduced beneficial interactions in the microbial community and a reduction in its metabolic output. These microbial changes coincided with a corresponding downregulation of key host pathways predicted by our model to be dependent on the microbiome that are crucial for maintaining intestinal barrier function, cellular replication, and homeostasis. Our results elucidate microbiome-host interactions that potentially influence host aging processes, focusing on microbial nucleotide metabolism as a pivotal factor in aging dynamics. These pathways could serve as future targets for the development of microbiome-based therapies against aging.

Acta OphthalmologicaVolume 100, Issue 6 p. e1354-e1355 Letter to the Editor Fluorescence lifetime and peak emission wavelength differ between AMD patients with soft drusen and sub-retinal drusenoid deposits Rowena Simon, Rowena Simon Department of Ophthalmology, University Hospital Jena, Jena, GermanySearch for more papers by this authorChristine A. Curcio, Christine A. Curcio Department of Ophthalmology and Visual Sciences, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USASearch for more papers by this authorSebastian Weber, Sebastian Weber Department of Ophthalmology, University Hospital Jena, Jena, GermanySearch for more papers by this authorDaniel Meller, Daniel Meller Department of Ophthalmology, University Hospital Jena, Jena, GermanySearch for more papers by this authorMartin Hammer, Corresponding Author Martin Hammer [email protected] orcid.org/0000-0001-9674-8096 Department of Ophthalmology, University Hospital Jena, Jena, Germany Center for Medical Optics and Photonics, University of Jena, Jena, Germany Correspondence: Martin Hammer, PhD Department of Ophthalmology University Hospital Jena Am Klinikum 1 07747 Jena Germany. Telephone: 03641 - 939 08 60 Fax: 03641 - 932 97 02 Email: [email protected]Search for more papers by this author Rowena Simon, Rowena Simon Department of Ophthalmology, University Hospital Jena, Jena, GermanySearch for more papers by this authorChristine A. Curcio, Christine A. Curcio Department of Ophthalmology and Visual Sciences, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USASearch for more papers by this authorSebastian Weber, Sebastian Weber Department of Ophthalmology, University Hospital Jena, Jena, GermanySearch for more papers by this authorDaniel Meller, Daniel Meller Department of Ophthalmology, University Hospital Jena, Jena, GermanySearch for more papers by this authorMartin Hammer, Corresponding Author Martin Hammer [email protected] orcid.org/0000-0001-9674-8096 Department of Ophthalmology, University Hospital Jena, Jena, Germany Center for Medical Optics and Photonics, University of Jena, Jena, Germany Correspondence: Martin Hammer, PhD Department of Ophthalmology University Hospital Jena Am Klinikum 1 07747 Jena Germany. Telephone: 03641 - 939 08 60 Fax: 03641 - 932 97 02 Email: [email protected]Search for more papers by this author First published: 21 January 2022 https://doi.org/10.1111/aos.15087Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume100, Issue6September 2022Pages e1354-e1355 RelatedInformation

Purpose:The purpose of this study was to investigate histologic autofluorescence lifetimes and spectra of retinal pigment epithelium (RPE) on the transition from normal aging to RPE activation and migration in age-related macular degeneration (AMD).Methods:Autofluorescence lifetimes and spectra of 9 donor eyes were analyzed in cryosections by means of 2-photon excited fluorescence at 960 nm. Spectra were detected at 483 to 665 nm. Lifetimes were measured using time-correlated single photon counting in 2 spectral channels: 500 to 550 nm (short-wavelength spectral channel [SSC]) and 550 to 700 nm (long-wavelength spectral channel [LSC]). Fluorescence decays over time were approximated by a series of three exponential functions. The amplitude-weighted mean fluorescence lifetime was determined. Markers for retinoid activity (RPE65) and immune function (CD68) were immunolocalized in selected neighboring sections.Results:We identified 9 RPE morphology phenotypes resulting in 399 regions of interest (ROIs) for spectral and 497 ROIs for lifetime measurements. RPE dysmorphia results in a shorter wavelength peak of spectral emission: normal aging versus RPE migrated into the retina (intraELM) = 601.7 (9.5) nm versus 581.6 (7.3) nm, P < 0.001, whereas autofluorescence lifetimes increase: normal aging versus intraELM: SSC 180 (44) picosecond (ps) versus 320 (86) ps, P < 0.001; and LSC 250 (55) ps versus 441 (76) ps, P < 0.001. Ectopic RPE within the neurosensory retina is strongly CD68 positive and RPE65 negative.Conclusions:In the process of RPE degeneration, comprising different steps of dysmorphia and migration, lengthening of autofluorescence lifetimes and a hypsochromic shift of emission spectra can be observed. These autofluorescence changes might provide early biomarkers for AMD progression and contribute to our understanding of RPE-driven pathology.

PURPOSE:To observe fundus autofluorescence (FAF) lifetimes and peak emission wavelength (PEW) of drusen with respect to the pathology of the overlying RPE in the follow-up of AMD-patients.METHODS:Forty eyes of 38 patients (age: 75.1 ± 7.1 years) with intermediate AMD were included. FAF lifetimes and PEW were recorded by fluorescence lifetime imaging ophthalmoscopy (FLIO). Twenty-six eyes had a follow-up investigation between months 12 and 36, and 10 at months 37-72. AMD progression was retrieved from color fundus photography (CFP) and OCT. Drusen were classified with respect to changes in the overlying RPE into groups no, questionable or faint, and apparent hyperpigmentation based on CFP.RESULTS:Among the 210 hyperautofluorescent drusen found at baseline, those with hyperpigmentation had longer lifetimes and shorter PEW than those without. Drusen without hyperpigmentation had shorter lifetimes and PEW than neighboring RPE (all p < 0.001) at baseline, but drusen lifetimes increased, and PEW shortened further over follow-up. Eyes, showing AMD progression, had significantly longer FAF lifetimes at baseline than non-progressing eyes: 282 ± 102 ps versus 245 ± 98 ps, p < 0.001 and 365 ± 44 ps vs. 336 ± 48 ps, p = 0.025 for short and long wavelength FLIO channel, respectively.CONCLUSIONS:Depending on hyperpigmentation properties, drusen show lifetimes and PEW different from that of adjacent RPE which change over the natural history of AMD. This difference and change, however, might reflect progressive dysmorphia of the RPE rather than representing fluorescence of drusen material itself. Nevertheless, the observed FAF changes could make FLIO a useful tool for the early detection of AMD progression risk.

Purpose To investigate the haemoglobin concentration and oxygenation in the optic disc in glaucoma patients vs. controls. Methods Thirty-one eyes of primary open angle glaucoma patients (mean age: 64.9 ± 2.1 years) and 31 eyes of 31 healthy controls (65.5 ± 2.0 years) were included. Perimetry, optical coherence tomography (OCT), and OCT angiography were performed. Multispectral imaging was used to record the optic disc reflectance at wavelengths 522 nm, 548 nm, 555 nm, 586 nm, and 610 nm, and haemoglobin concentration and oxygenation (SO 2 ) were calculated from these measures. This was done in the rest and under stimulation of neuronal activity by flicker light. Results The haemoglobin concentration was significantly lower ( p < 0.001) in the rim (40.0 ± 6.3) and the excavation (35.7 ± 8.0) of the glaucoma patients’ discs than in controls (45.7 ± 7.5). SO 2 was not different in general, but lower in a subgroup of 18 glaucoma patients with ischaemic disc rims than in non-ischaemic ones (median 26.8%, interquartile range (IQR): 29.5% vs. 51.9%, IQR 32.0%, p = 0.02) as well as in controls (41.0%, IQR 30.6%, p = 0.01). Flicker light stimulation significantly increased the haemoglobin concentration in the controls (+ 1.3 ± 3.6, p = 0.048) as well as in the rim of glaucoma discs (+ 2.6 ± 5.0, p = 0.006) and SO 2 in the controls only (+ 15.4 ± 23.6%, p = 0.001). The haemoglobin concentration was significantly correlated with the perimetric mean defect, retinal nerve fibre layer (RNFL) thickness and para-papillary perfusion density. Conclusions The optic disc haemoglobin concentration and oxygenation are quantifiable from multispectral imaging and reduced in glaucoma. The correlation of haemoglobin concentration with perfusion density, RNFL thickness and visual field loss indicates its implication in glaucoma pathology.

PURPOSE. To measure fundus autofluorescence (FAF) lifetimes and peak emission wavelengths (PEW) of subretinal drusenoid deposits (SDD) in age-related macular degeneration (AMD) and their development over time. METHODS. Fluorescence lifetime imaging ophthalmoscopy (FLIO) was performed in 30 eyes with optical coherence tomography (OCT)-confirmed early or intermediate AMD and SDD. Contrasts of mean lifetimes in short- (SSC) and long-wavelength channels (LSC), PEW, and relative fluorescence intensity were determined as differences of the respective measures at individual SDD and their environment. Measurements were made at baseline and at follow-up intervals 1 (13-36 months) and 2 (37-72 months), respectively. RESULTS. Of 423 SDD found at baseline, 259, 47, and 117 were hypoautofluorescent, isoautofluorescent, and hyperautofluorescent, respectively. FAF lifetimes of SDD were significantly longer than those of their environment by 14.5 ps (SSC, 95% confidence interval [CI], 13.3-15.7 ps) and 3.9 ps (LSC, 3.1-4.7 ps). PEW was shorter by 1.53 nm (1.071.98 nm, all contrasts P < 0.001) with higher contrasts for hyperfluorescent SDD. Over follow-up, SDD tended to hyperautofluorescence (relative intensities increased by 3.4% [95% CI, 2.9%-4.1%; P < 0.001] in follow-up 2). Hyperautofluorescence was associated with disruption of the ellipsoid zone on OCT. Disease progression to late-stage AMD was associated with higher lifetime contrast in SSC (15.9ps [14.2-17.6 ps] vs. 11.7 ps [9.9-13.5 ps], P < 0.001) at baseline. CONCLUSIONS. SDD show longer FAF lifetimes and shorter PEW than their environments. A high lifetime contrast of SDD in SSC might predict disease progression to late-stage AMD.

Fluorescence lifetime imaging ophthalmoscopy (FLIO) provides information on fluorescence lifetimes in two spectral channels as well as the peak emission wavelength (PEW) of the fluorescence. Here, we combine these measures in an integral three-dimensional lifetime-PEW metric vector and determine a normal range for this vector from measurements in young healthy subjects. While for these control subjects 97 (±8) % (median (interquartile range)) of all para-macular pixels were covered by this normal vector range, it was 67 (±55) % for the elderly healthy, 38 (±43) % for age-related macular degeneration (AMD)-suspect subjects, and only 6 (±4) % for AMD patients. The vectors were significantly different for retinal pigment epithelium (RPE) lesions in AMD patients from that of non-affected tissue (p < 0.001). Lifetime- PEW plots allowed to identify possibly pathologic fundus areas by fluorescence parameters outside a 95% quantile per subject. In a patient follow-up, changes in fluorescence parameters could be traced in the lifetime-PEW metric, showing their change over disease progression.