Inherited retinal degeneration (RD) leads to the impairment or loss of vision in millions of individuals worldwide, most frequently due to the loss of photoreceptor (PR) cells. Animal models, particularly the laboratory mouse, have been used to understand the pathogenic mechanisms that underlie PR cell loss and to explore therapies that may prevent, delay, or reverse RD. Here, we reviewed entries in the Mouse Genome Informatics and PubMed databases to compile a comprehensive list of monogenic mouse models in which PR cell loss is demonstrated. The progression of PR cell loss with postnatal age was documented in mutant alleles of genes grouped by biological function. As anticipated, a wide range in the onset and rate of cell loss was observed among the reported models. The analysis underscored relationships between RD genes and ciliary function, transcription-coupled DNA damage repair, and cellular chloride homeostasis. Comparing the mouse gene list to human RD genes identified in the RetNet database revealed that mouse models are available for 40% of the known human diseases, suggesting opportunities for future research. This work may provide insight into the molecular players and pathways through which PR degenerative disease occurs and may be useful for planning translational studies.

It is well known that obesity/high body mass index (BMI) plays a key role in the evolution of insulin resistance and type-2 diabetes mellitus (T2DM). However, the exact mechanism underlying its contribution is still not fully understood. This work focuses on an NMR-based metabolomic investigation of the serum profiles of diabetic, obese South Indian Asian subjects. ¹H 1D and 2D NMR experiments were performed to profile the altered metabolic patterns of obese diabetic subjects and multivariate statistical methods were used to identify metabolites that contributed significantly to the differences in the samples of four different subject groups: diabetic and non-diabetic with low and high BMIs. Our analysis revealed that the T2DM-high BMI group has higher concentrations of saturated fatty acids, certain amino acids (leucine, isoleucine, lysine, proline, threonine, valine, glutamine, phenylalanine, histidine), lactic acid, 3-hydroxybutyric acid, choline, 3,7-dimethyluric acid, pantothenic acid, myoinositol, sorbitol, glycerol, and glucose, as compared to the non-diabetic-low BMI (control) group. Of these 19 identified significant metabolites, the levels of saturated fatty acids, lactate, valine, isoleucine, and phenylalanine are also higher in obese non-diabetic subjects as compared to control subjects, implying that this set of metabolites could be identified as potential biomarkers for the onset of diabetes in subjects with a high BMI. Our work validates the utility of NMR-based metabolomics in conjunction with multivariate statistical analysis to provide insights into the underlying metabolic pathways that are perturbed in diabetic subjects with a high BMI.

We utilized an NMR-based metabolomic approach to profile the metabolites in Drosophila melanogaster that cycle with a daily rhythm. ¹H 1D and 2D NMR experiments were performed on whole-body extracts sampled from flies that experienced strong time cues in the form of both light and temperature cycles. Multivariate and univariate statistical analysis was used to identify those metabolites whose concentrations oscillate diurnally. We compared metabolite levels at two time points twelve hours apart, one close to the end of the day and the other close to the end of the night, and identified metabolites that differed significantly in their relative concentrations. We were able to identify 14 such metabolites whose concentrations differed significantly between the two time points. The concentrations of metabolites such as sterols, fatty acids, amino acids such as leucine, valine, isoleucine, alanine and lysine as well as other metabolites such as creatine, glucose, AMP and NAD were higher close to the end of the night, whereas the levels of lactic acid, and a few amino acids such as histidine and tryptophan were higher close to the end of the day. We compared signal intensities across 12 equally spaced time points for these 14 metabolites, in order to profile the changes in their levels across the day, since the NMR metabolite peak intensity is directly proportional to its molar concentration. Through this report we establish NMR-based metabolomics combined with multivariate statistical analysis as a useful method for future studies on the interactions between circadian clocks and metabolic processes.