A Data Mining Metabolomics Exploration of Glaucoma.

Glaucoma is an age related disease characterized by the progressive loss of retinal ganglion cells, which are the neurons that transduce the visual information from the retina to the brain. It is the leading cause of irreversible blindness worldwide. To gain further insights into primary open-angle glaucoma (POAG) pathophysiology, we performed a non-targeted metabolomics analysis on the plasma from POAG patients (n = 34) and age- and sex-matched controls (n = 30). We investigated the differential signature of POAG plasma compared to controls, using liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS). A data mining strategy, combining a filtering method with threshold criterion, a wrapper method with iterative selection, and an embedded method with penalization constraint, was used. These strategies are most often used separately in metabolomics studies, with each of them having their own limitations. We opted for a synergistic approach as a mean to unravel the most relevant metabolomics signature. We identified a set of nine metabolites, namely: nicotinamide, hypoxanthine, xanthine, and 1-methyl-6,7-dihydroxy-1,2,3,4-tetrahydroisoquinoline with decreased concentrations and N-acetyl-L-Leucine, arginine, RAC-glycerol 1-myristate, 1-oleoyl-RAC-glycerol, cystathionine with increased concentrations in POAG; the modification of nicotinamide, N-acetyl-L-Leucine, and arginine concentrations being the most discriminant. Our findings open up therapeutic perspectives for the diagnosis and treatment of POAG.

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

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.

A Plasma Metabolomic Signature Involving Purine Metabolism in Human Optic Atrophy 1 (OPA1)-Related Disorders.

Purpose: Dominant optic atrophy (DOA; MIM [Mendelian Inheritance in Man] 165500), resulting in retinal ganglion cell degeneration, is mainly caused by mutations in the optic atrophy 1 (OPA1) gene, which encodes a dynamin guanosine triphosphate (GTP)ase involved in mitochondrial membrane processing. This work aimed at determining whether plasma from OPA1 pathogenic variant carriers displays a specific metabolic signature. Methods: We applied a nontargeted clinical metabolomics pipeline based on ultra-high-pressure liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS) allowing the exploration of 500 polar metabolites in plasma. We compared the plasma metabolic profiles of 25 patients with various OPA1 pathogenic variants and phenotypes to those of 20 healthy controls. Statistical analyses were performed using univariate and multivariate (principal component analysis [PCA], orthogonal partial least-squares discriminant analysis [OPLS-DA]) methods and a machine learning approach, the Biosigner algorithm. Results: A robust and relevant predictive model characterizing OPA1 individuals was obtained, based on a complex panel of metabolites with altered concentrations. An impairment of the purine metabolism, including significant differences in xanthine, hypoxanthine, and inosine concentrations, was at the foreground of this signature. In addition, the signature was characterized by differences in urocanate, choline, phosphocholine, glycerate, 1-oleoyl-rac-glycerol, rac-glycerol-1-myristate, aspartate, glutamate, and cystine concentrations. Conclusions: This first metabolic signature reported in the plasma of patient carrying OPA1 pathogenic variants highlights the unexpected involvement of purine metabolism in the pathophysiology of DOA.

Blue light-filtering intraocular lenses and post-operative mood: a pilot clinical study.

The purpose of the study was to determine if implantation of blue-filtering intraocular lenses (IOLs) affects post-operative mood, inducing more depression, compared to patients undergoing implantation with conventional IOLs. The study was conducted at the Angers University Hospital, France. This was a prospective with a lowercase pilot study, including consecutive patients planned to undergo cataract surgery in both eyes within 1 week. The same type of IOL was used in both eyes of each patient. The choice of IOL was not randomized but driven by the habits and experience of each participating surgeon. Cognitively healthy patients (an MMSE score higher than 25) were assessed before and after surgery, using the 30-item geriatric depression scale (GDS) to seek symptoms of depression. Univariate and multiple logistic regressions were used to examine the association between the type of IOL and the 30-item GDS score improvement during the 3 months after lens implantation, while adjusting for participants' characteristics (age, visual acuity). Blue-filtering IOLs were used in 16 patients (mean ± standard deviation, 75.6 ± 7.5 years; 75 % female), and untinted IOLs in 18 patients (77.3 ± 6.9 years; 77.8 %female). Pre-operatively visual acuity and GDS scores were comparable in the two groups. The post-operative GDS score was improved by 1.91 ± 3.10 points in the whole sample (P = 0.002), as well as in each subgroup of patients. Three months after surgery, the mean change in GDS score did not differ between groups (P = 0.365), nor did the mean visual acuity (P = 0.198).