Quantitative metabolomics of photoreceptor degeneration and the effects of stem cell-derived retinal pigment epithelium transplantation

Development of microflow ultra high performance liquid chromatography-mass spectrometry metabolomic assays for analysis of mammalian biofluids

INTRODUCTION AND OBJECTIVES

The application of untargeted metabolomics assays using ultra high performance liquid chromatography-mass spectrometry (UHPLC-MS) to study metabolism in biological systems including humans is rapidly increasing. In some of these studies there is a requirement to collect and analyse low sample volumes of biofluids (e.g. tear fluid) or low cell and tissue mass samples (e.g. tissue needle biopsies). The application of microflow, capillary or nano liquid chromatography (≤ 1.0 mm column internal diameter (i.d.)) theoretically should accomplish a higher assay sensitivity compared to analytical liquid chromatography (2.1-5.0 mm column internal diameter). To date, there has been limited research into microflow UHPLC-MS assays that can be applied to study samples of low volume or mass.

METHODS

This paper presents three complementary UHPLC-MS assays (aqueous C18 reversed-phase, lipidomics C18 reversed-phase and Hydrophilic Interaction Liquid Chromatography (HILIC)) applying 1.0 mm internal diameter columns for untargeted metabolomics. Human plasma and urine samples were applied for the method development, with porcine plasma, urine and tear fluid used for method assessment. Data were collected and compared for columns of the same length, stationary phase and stationary phase particle size but with two different column internal diameters (2.1 mm and 1.0 mm).

RESULTS AND CONCLUSIONS

All three assays showed an increase in peak areas and peak widths when applying the 1.0 mm i.d. assays. HILIC assays provide an advantage at lower sample dilutions whereas for reversed phase (RP) assays there was no benefit added. This can be seen in the validation study where a much higher number of compounds were detected in the HILIC assay. RP assays were still appropriate for small volume samples with hundreds of compounds being detected. In summary, the 1.0 mm i.d. column assays are applicable for small volume samples where dilution is required during sample preparation.

Metabolomics studies in common multifactorial eye disorders: a review of biomarker discovery for age-related macular degeneration, glaucoma, diabetic retinopathy and myopia

Introduction

Multifactorial Eye disorders are a significant public health concern and have a huge impact on quality of life. The pathophysiological mechanisms underlying these eye disorders were not completely understood since functional and low-throughput biological tests were used. By identifying biomarkers linked to eye disorders, metabolomics enables early identification, tracking of the course of the disease, and personalized treatment.

Methods

The electronic databases of PubMed, Scopus, PsycINFO, and Web of Science were searched for research related to Age-Related macular degeneration (AMD), glaucoma, myopia, and diabetic retinopathy (DR). The search was conducted in August 2023. The number of cases and controls, the study's design, the analytical methods used, and the results of the metabolomics analysis were all extracted. Using the QUADOMICS tool, the quality of the studies included was evaluated, and metabolic pathways were examined for distinct metabolic profiles. We used MetaboAnalyst 5.0 to undertake pathway analysis of differential metabolites.

Results

Metabolomics studies included in this review consisted of 36 human studies (5 Age-related macular degeneration, 10 Glaucoma, 13 Diabetic retinopathy, and 8 Myopia). The most networked metabolites in AMD include glycine and adenosine monophosphate, while methionine, lysine, alanine, glyoxylic acid, and cysteine were identified in glaucoma. Furthermore, in myopia, glycerol, glutamic acid, pyruvic acid, glycine, cysteine, and oxoglutaric acid constituted significant metabolites, while glycerol, glutamic acid, lysine, citric acid, alanine, and serotonin are highly networked metabolites in cases of diabetic retinopathy. The common top metabolic pathways significantly enriched and associated with AMD, glaucoma, DR, and myopia were arginine and proline metabolism, methionine metabolism, glycine and serine metabolism, urea cycle metabolism, and purine metabolism.

Conclusion

This review recapitulates potential metabolic biomarkers, networks and pathways in AMD, glaucoma, DR, and myopia, providing new clues to elucidate disease mechanisms and therapeutic targets. The emergence of advanced metabolomics techniques has significantly enhanced the capability of metabolic profiling and provides novel perspectives on the metabolism and underlying pathogenesis of these multifactorial eye conditions. The advancement of metabolomics is anticipated to foster a deeper comprehension of disease etiology, facilitate the identification of novel therapeutic targets, and usher in an era of personalized medicine in eye research.

Metabolomics facilitates differential diagnosis in common inherited retinal degenerations by exploring their profiles of serum metabolites

The diagnosis of inherited retinal degeneration (IRD) is challenging owing to its phenotypic and genotypic complexity. Clinical information is important before a genetic diagnosis is made. Metabolomics studies the entire picture of bioproducts, which are determined using genetic codes and biological reactions. We demonstrated that the common diagnoses of IRD, including retinitis pigmentosa (RP), cone-rod dystrophy (CRD), Stargardt disease (STGD), and Bietti's crystalline dystrophy (BCD), could be differentiated based on their metabolite heatmaps. Hundreds of metabolites were identified in the volcano plot compared with that of the control group in every IRD except BCD, considered as potential diagnosing markers. The phenotypes of CRD and STGD overlapped but could be differentiated by their metabolomic features with the assistance of a machine learning model with 100% accuracy. Moreover, EYS-, USH2A-associated, and other RP, sharing considerable similar characteristics in clinical findings, could also be diagnosed using the machine learning model with 85.7% accuracy. Further study would be needed to validate the results in an external dataset. By incorporating mass spectrometry and machine learning, a metabolomics-based diagnostic workflow for the clinical and molecular diagnoses of IRD was proposed in our study.

Uncontrolled Oxygen Levels in Cultures of Retinal Pigment Epithelium: Have We Missed the Obvious?

Retinal pigment epithelium (RPE) is the outermost layer of retina located between the photoreceptor cells and the choroid. This highly-polarized monolayer provides critical support for the functioning of the other parts of the retina, especially photoreceptors. Methods of culturing RPE have been under development since its establishment in 1920s. Despite considering various factors, oxygen (O₂) levels in RPE microenvironments during culture preparation and experimental procedure have been overlooked. O₂ is a crucial parameter in the cultures, and therefore, maintaining RPE cells at O₂ levels different from their native environment (70-90 mm Hg of O₂) could have unintended consequences. Owing to the importance of the topic, lack of sufficient discussion in the literature and to encourage future research, this paper will focus on uncontrolled O₂ level in cultures of RPE cells.

Metabolomics in Retinal Diseases: An Update

Retinal diseases are a leading cause of visual loss and blindness, affecting a significant proportion of the population worldwide and having a detrimental impact on quality of life, with consequent economic burden. The retina is highly metabolically active, and a number of retinal diseases are associated with metabolic dysfunction. To better understand the pathogenesis underlying such retinopathies, new technology has been developed to elucidate the mechanism behind retinal diseases. Metabolomics is a relatively new "omics" technology, which has developed subsequent to genomics, transcriptomics, and proteomics. This new technology can provide qualitative and quantitative information about low-molecular-weight metabolites (M.W. < 1500 Da) in a given biological system, which shed light on the physiological or pathological state of a cell or tissue sample at a particular time point. In this article we provide an extensive review of the application of metabolomics to retinal diseases, with focus on age-related macular degeneration (AMD), diabetic retinopathy (DR), retinopathy of prematurity (ROP), glaucoma, and retinitis pigmentosa (RP).

Metabolomics in Age-Related Macular Degeneration: A Systematic Review

Purpose

Age-related macular degeneration (AMD) is one of the leading causes of blindness among the elderly, and the exact pathogenesis of the AMD remains unclear. The purpose of this review is to summarize potential metabolic biomarkers and pathways of AMD that might facilitate risk predictions and clinical diagnoses of AMD.

Methods

We obtained relevant publications of metabolomics studies of human beings by systematically searching the MEDLINE (PubMed) database before June 2020. Studies were included if they performed mass spectrometry-based or nuclear magnetic resonance-based metabolomics approach for humans. In addition, AMD was assessed from fundus photographs based on standardized protocols. The metabolic pathway analysis was performed using MetaboAnalyst 3.0.

Results

Thirteen studies were included in this review. Repeatedly identified metabolites including phenylalanine, adenosine, hypoxanthine, tyrosine, creatine, citrate, carnitine, proline, and maltose have the possibility of being biomarkers of AMD. Validation of the biomarker panels was observed in one study. Dysregulation of metabolic pathways involves lipid metabolism, carbohydrate metabolism, nucleotide metabolism, amino acid metabolism, and translation, which might play important roles in the development and progression of AMD.

Conclusions

This review summarizes the potential metabolic biomarkers and pathways related to AMD, providing opportunities for the construction of diagnostic or predictive models for AMD and the discovery of new therapeutic targets.

Metabolomic analysis in ophthalmology

Modern science takes into account phenotype complexity and establishes approaches to track changes on every possible level. Many "omics" studies have been developed over the last decade. Metabolomic analysis enables dynamic measurement of the metabolic response of a living system to a variety of stimuli or genetic modifications. Important targets of metabolomics is biomarker development and translation to the clinic for personalized diagnosis and a greater understanding of disease pathogenesis. The current review highlights the major aspects of metabolomic analysis and its applications for the identification of relevant predictive, diagnostic and prognostic biomarkers for some ocular diseases including dry eye, keratoconus, retinal diseases, macular degeneration, and glaucoma. To date, possible biomarker candidates for dry eye disease are lipid metabolites and androgens, for keratoconus cytokeratins, urea, citrate cycle, and oxidative stress metabolites. Palmitoylcarnitine, sphingolipids, vitamin D related metabolites, and steroid precursors may be used for distinguishing glaucoma patients from healthy controls. Dysregulation of amino acid and carnitine metabolism is critical in the development and progression of diabetic retinopathy. Further work is needed to discover and validate metabolic biomarkers as a powerful tool for understanding the molecular mechanisms of ocular diseases, to provide knowledge on their etiology and pathophysiology and opportunities for personalized clinical intervention at an early stage.

Immunological Considerations for Retinal Stem Cell Therapy

There is an increasing effort toward generating replacement cells for neuronal application due to the nonregenerative nature of these tissues. While much progress has been made toward developing methodologies to generate these cells, there have been limited improvements in functional restoration. Some of these are linked to the degenerative and often nonreceptive microenvironment that the new cells need to integrate into. In this chapter, we will focus on the status and role of the immune microenvironment of the retina during homeostasis and disease states. We will review changes in both innate and adaptive immunity as well as the role of immune rejection in stem cell replacement therapies. The chapter will end with a discussion of immune-modulatory strategies that have helped to ameliorate these effects and could potentially improve functional outcome for cell replacement therapies for the eye.

Metabolomics and Age-Related Macular Degeneration

Age-related macular degeneration (AMD) leads to irreversible visual loss, therefore, early intervention is desirable, but due to its multifactorial nature, diagnosis of early disease might be challenging. Identification of early markers for disease development and progression is key for disease diagnosis. Suitable biomarkers can potentially provide opportunities for clinical intervention at a stage of the disease when irreversible changes are yet to take place. One of the most metabolically active tissues in the human body is the retina, making the use of hypothesis-free techniques, like metabolomics, to measure molecular changes in AMD appealing. Indeed, there is increasing evidence that metabolic dysfunction has an important role in the development and progression of AMD. Therefore, metabolomics appears to be an appropriate platform to investigate disease-associated biomarkers. In this review, we explored what is known about metabolic changes in the retina, in conjunction with the emerging literature in AMD metabolomics research. Methods for metabolic biomarker identification in the eye have also been discussed, including the use of tears, vitreous, and aqueous humor, as well as imaging methods, like fluorescence lifetime imaging, that could be translated into a clinical diagnostic tool with molecular level resolution.

CRISPR-Cas9 genome engineering: Treating inherited retinal degeneration

Gene correction is a valuable strategy for treating inherited retinal degenerative diseases, a major cause of irreversible blindness worldwide. Single gene defects cause the majority of these retinal dystrophies. Gene augmentation holds great promise if delivered early in the course of the disease, however, many patients carry mutations in genes too large to be packaged into adeno-associated viral vectors and some, when overexpressed via heterologous promoters, induce retinal toxicity. In addition to the aforementioned challenges, some patients have sustained significant photoreceptor cell loss at the time of diagnosis, rendering gene replacement therapy insufficient to treat the disease. These patients will require cell replacement to restore useful vision. Fortunately, the advent of induced pluripotent stem cell and CRISPR-Cas9 gene editing technologies affords researchers and clinicians a powerful means by which to develop strategies to treat patients with inherited retinal dystrophies. In this review we will discuss the current developments in CRISPR-Cas9 gene editing in vivo in animal models and in vitro in patient-derived cells to study and treat inherited retinal degenerative diseases.

A new perspective on lipid research in age-related macular degeneration

There is an urgency to find new treatment strategies that could prevent or delay the onset or progression of AMD. Different classes of lipids and lipoproteins metabolism genes have been associated with AMD in a multiple ways, but despite the ever-increasing knowledge base, we still do not understand fully how circulating lipids or local lipid metabolism contribute to AMD. It is essential to clarify whether dietary lipids, systemic or local lipoprotein metabolismtrafficking of lipids in the retina should be targeted in the disease. In this article, we critically evaluate what has been reported in the literature and identify new directions needed to bring about a significant advance in our understanding of the role for lipids in AMD. This may help to develop potential new treatment strategies through targeting the lipid homeostasis.

Regenerative medicine in the retina: from stem cells to cell replacement therapy

Following the fast pace of the growing field of stem cell research, retinal cell replacement is finally emerging as a feasible mean to be explored for clinical application. Although neuroprotective treatments are able to slow the progression of retinal degeneration caused by diseases such as age-related macular degeneration and glaucoma, they are insufficient to fully halt disease progression and unable to recover previously lost vision. Comprehensive, technological and intellectual advances over the past years, including the in vitro differentiation of retinal cells at manufacturing scale from embryonic stem (ES) cell and induced pluripotent stem (iPS) cell cultures, progress within the area of retinal disease modeling, and the first clinical trials have started to shape the way towards addressing this treatment gap and translating retinal cell replacement to the clinic. Here, summarize the most recent advances within retinal cell replacement from both a scientific and clinical perspective, and discuss the remaining challenges towards the delivery of the first retinal cell products.

Plasma metabolomic study in Chinese patients with wet age-related macular degeneration

BACKGROUND

Age-related macular degeneration (AMD) is a leading disease associated with blindness. It has a high incidence and complex pathogenesis. We aimed to study the metabolomic characteristics in Chinese patients with wet AMD by analyzing the morning plasma of 20 healthy controls and 20 wet AMD patients for metabolic differences.

METHODS

We used ultra-high-pressure liquid chromatography and quadrupole-time-of-flight mass spectrometry for this analysis. The relationship of these differences with AMD pathophysiology was also assessed. Remaining data were normalized using Pareto scaling, and then valid data were handled using multivariate data analysis with MetaboAnalysis software, including unsupervised principal component analysis and supervised partial least squares-discriminate analysis. The purpose of the present work was to identify significant metabolites for the analyses. Hierarchical clustering was conducted to identify metabolites that differed between the two groups. Significant metabolites were then identified using the established database, and features were mapped on the Kyoto Encyclopedia of Genes and Genomes.

RESULTS

A total of 5443 ion peaks were detected, all of them attributable to the same 10 metabolites. These included some amino acids, isomaltose, hydrocortisone, and biliverdin. The heights of these peaks differed significantly between the two groups. The biosynthesis of amino acids pathways also differed profoundly between patients with wet AMD and controls.

CONCLUSIONS

These findings suggested that metabolic profiles and and pathways differed between wet AMD and controls and may provide promising new targets for AMD-directed therapeutics and diagnostics.