Genomic-Metabolomic Associations Support the Role of LIPC and Glycerophospholipids in Age-Related Macular Degeneration

Functional genomics in age-related macular degeneration: From genetic associations to understanding disease mechanisms

Genome-wide association studies have been remarkably successful in identifying genetic variants associated with age-related macular degeneration (AMD), demonstrating a strong genetic component largely driven by common variants. However, progress in translating these genetic findings into a deeper understanding of disease mechanisms and new therapies has been slow. Slow progress in this area can be attributed to limited knowledge of the functional impact of AMD-associated non-coding variants on gene function, the molecular mechanisms and cell types underlying disease. This review offers a comprehensive overview of functional genomics approaches to uncover the genetic, epigenetic, cellular and molecular mechanisms underlying AMD and outlines future directions for research.

Unraveling the genetic and epigenetic landscape governing intramuscular fat deposition in rabbits: Insights and implications

Intramuscular fat (IMF) content is a predominant factor recognized to affect rabbit meat quality, directly impacting flavor, juiciness, and consumer preference. Despite its significance, the major interplay of genetic and epigenetic factors regulating IMF in rabbits remains largely unexplored. This review sheds light on this critical knowledge gap, offering valuable insights and future directions. We delve into the potential role of established candidate genes from other livestock (e.g. PPARγ, FABP4, and SCD) in rabbits, while exploring the identified novel genes of IMF in rabbits. Furthermore, we explored the quantitative trait loci studies in rabbit IMF and genomic selection approaches for improving IMF content in rabbits. Beyond genetics, this review unveils the exciting realm of epigenetic mechanisms modulating IMF deposition. We explored the potential of DNA methylation patterns, histone modifications, and non-coding RNA-mediation as fingerprints for selecting rabbits with desirable IMF levels. Additionally, we explored the possibility of manipulating the epigenetic landscape through nutraceuticals interventions to promote favorable IMF depositions. By comprehensively deciphering the genomic and epigenetic terrain of rabbit intramuscular fat regulation, this study aims to assess the existing knowledge regarding the genetic and epigenetic factors that control the deposition of intramuscular fat in rabbits. By doing so, we identified gaps in the current research, and suggested potential areas for further investigation that would enhance the quality of rabbit meat. This can enable breeders to develop targeted breeding strategies, optimize nutrition, and create innovative interventions to enhance the quality of rabbit meat, meet consumer demands and increase market competitiveness.

Epigenome-metabolism nexus in the retina: implications for aging and disease

Intimate links between epigenome modifications and metabolites allude to a crucial role of cellular metabolism in transcriptional regulation. Retina, being a highly metabolic tissue, adapts by integrating inputs from genetic, epigenetic, and extracellular signals. Precise global epigenomic signatures guide development and homeostasis of the intricate retinal structure and function. Epigenomic and metabolic realignment are hallmarks of aging and highlight a link of the epigenome-metabolism nexus with aging-associated multifactorial traits affecting the retina, including age-related macular degeneration and glaucoma. Here, we focus on emerging principles of epigenomic and metabolic control of retinal gene regulation, with emphasis on their contribution to human disease. In addition, we discuss potential mitigation strategies involving lifestyle changes that target the epigenome-metabolome relationship for maintaining retinal function.

Unveiling Statins and Genetics in Age-Related Macular Degeneration: The Coimbra Eye Study-Report 9

Purpose

To assess the association of age-related macular degeneration (AMD) progression and statins, connected with AMD genetic risk, and if there is an interplay between statins and genetics.

Methods

In this analysis, 682 subjects made two visits (6.5-year follow-up) of the Coimbra Eye Study. Subjects who started taking statins at any time point between the two visits were considered. Progressors were defined as not having AMD at baseline and having any AMD at follow-up. Genetic risk scores (GRSs) were calculated individually with 52 independent variants associated with AMD. Time to progression was estimated using unadjusted Kaplan-Meier curves. An extended Cox model was used for the association between statins and GRS with the risk for AMD progression. Multiplicative and additive interactions were assessed.

Results

Median survival time was 7.50 years for subjects not taking statins and 7.62 for subjects taking statins (P < 0.001). Statin intake reduced the risk for progression to AMD in 48%, adjusting for age, sex, body mass index, smoking, and diabetes (model 1) and GRS (model 2). The combined effects of not taking statins and having high GRS increased the progression risk fourfold compared to taking statins and having low GRS (hazard ratio [HR] = 4.25; 95% confidence interval [CI], 1.62-11.16; P = 0.003). For subjects not taking statins, an increased risk of progression was found for those subjects with high GRS compared to subjects with low GRS (HR = 1.80; 95% CI, 1.13-2.85; P = 0.013). No statistically significant multiplicative or additive interactions were found.

Conclusions

Statins seem to be protective against AMD progression, and genetics may play a role in treatment response.

Workshop report - interdisciplinary metabolomic epidemiology: the pathway to clinical translation

Metabolomic epidemiology studies are complex and require a broad array of domain expertise. Although many metabolite-phenotype associations have been identified; to date, few findings have been translated to the clinic. Bridging this gap requires understanding of both the underlying biology of these associations and their potential clinical implications, necessitating an interdisciplinary team approach. To address this need in metabolomic epidemiology, a workshop was held at Metabolomics 2023 in Niagara Falls, Ontario, Canada that highlighted the domain expertise needed to effectively conduct these studies -- biochemistry, clinical science, epidemiology, and assay development for biomarker validation -- and emphasized the role of interdisciplinary teams to move findings towards clinical translation.

Metabolites and Cognitive Decline in a Puerto Rican Cohort

Background

Recent studies have identified plasma metabolites associated with cognitive decline and Alzheimer's disease; however, little research on this topic has been conducted in Latinos, especially Puerto Ricans.

Objective

This study aims to add to the growing body of metabolomics research in Latinos to better understand and improve the health of this population.

Methods

We assessed the association between plasma metabolites and global cognition over 12 years of follow-up in 736 participants of the Boston Puerto Rican Health Study (BPRHS). Metabolites were measured with untargeted metabolomic profiling (Metabolon, Inc) at baseline. We used covariable adjusted linear mixed models (LMM) with a metabolite * time interaction term to identify metabolites (of 621 measured) associated with ∼12 years cognitive trajectory.

Results

We observed strong inverse associations between medium-chain fatty acids, caproic acid, and the dicarboxylic acids, azelaic and sebacic acid, and global cognition. N-formylphenylalanine, a tyrosine pathway metabolite, was associated with improvement in cognitive trajectory.

Conclusions

The metabolites identified in this study are generally consistent with prior literature and highlight a role medium chain fatty acid and tyrosine metabolism in cognitive decline.

Integrating genetics and metabolomics from multi-ethnic and multi-fluid data reveals putative mechanisms for age-related macular degeneration

Age-related macular degeneration (AMD) is a leading cause of blindness in older adults. Investigating shared genetic components between metabolites and AMD can enhance our understanding of its pathogenesis. We conduct metabolite genome-wide association studies (mGWASs) using multi-ethnic genetic and metabolomic data from up to 28,000 participants. With bidirectional Mendelian randomization analysis involving 16,144 advanced AMD cases and 17,832 controls, we identify 108 putatively causal relationships between plasma metabolites and advanced AMD. These metabolites are enriched in glycerophospholipid metabolism, lysophospholipid, triradylcglycerol, and long chain polyunsaturated fatty acid pathways. Bayesian genetic colocalization analysis and a customized metabolome-wide association approach prioritize putative causal AMD-associated metabolites. We find limited evidence linking urine metabolites to AMD risk. Our study emphasizes the contribution of plasma metabolites, particularly lipid-related pathways and genes, to AMD risk and uncovers numerous putative causal associations between metabolites and AMD risk.

Systemic Metabolomics in a Framework of Genetics and Lifestyle in Age-Related Macular Degeneration

Insights into the pathogenesis of age-related macular degeneration (AMD), a leading cause of blindness, point towards a complex interplay of genetic and lifestyle factors triggering various systemic pathways. This study aimed to characterize metabolomic profiles for AMD and to evaluate their position in the trias with genetics and lifestyle. This study included 5923 individuals from five European studies. Blood metabolomics were assessed using a nuclear magnetic resonance platform of 146 metabolites. Associations were studied using regression analyses. A genetic risk score (GRS) was calculated using β-values of 49 AMD variants, a lifestyle risk score (LRS) using smoking and diet data, and a metabolite risk score (MRS) using metabolite values. We identified 61 metabolites associated with early-intermediate AMD, of which 94% were lipid-related, with higher levels of HDL-subparticles and apolipoprotein-A1, and lower levels of VLDL-subparticles, triglycerides, and fatty acids (false discovery rate (FDR) p-value < 1.4 × 10^-2). Late AMD was associated with lower levels of the amino acids histidine, leucine, valine, tyrosine, and phenylalanine, and higher levels of the ketone bodies acetoacetate and 3-hydroxybutyrate (FDR p-value < 1.5 × 10^-3). A favorable lifestyle characterized by a healthy diet was associated with higher levels of amino acids and lower levels of ketone bodies, while an unfavorable lifestyle, including smoking, showed opposite effects (FDR p-value < 2.7 × 10^-2). The MRS mediated 5% of the effect of the GRS and 20% of that of the LRS on late AMD. Our findings show that metabolomic profiles differ between AMD stages and show that blood metabolites mostly reflect lifestyle. The severity-specific profiles spur further interest into the systemic effects related to disease conversion.

Integrating transcriptomics, metabolomics, and GWAS helps reveal molecular mechanisms for metabolite levels and disease risk

Transcriptomics data have been integrated with genome-wide association studies (GWASs) to help understand disease/trait molecular mechanisms. The utility of metabolomics, integrated with transcriptomics and disease GWASs, to understand molecular mechanisms for metabolite levels or diseases has not been thoroughly evaluated. We performed probabilistic transcriptome-wide association and locus-level colocalization analyses to integrate transcriptomics results for 49 tissues in 706 individuals from the GTEx project, metabolomics results for 1,391 plasma metabolites in 6,136 Finnish men from the METSIM study, and GWAS results for 2,861 disease traits in 260,405 Finnish individuals from the FinnGen study. We found that genetic variants that regulate metabolite levels were more likely to influence gene expression and disease risk compared to the ones that do not. Integrating transcriptomics with metabolomics results prioritized 397 genes for 521 metabolites, including 496 previously identified gene-metabolite pairs with strong functional connections and suggested 33.3% of such gene-metabolite pairs shared the same causal variants with genetic associations of gene expression. Integrating transcriptomics and metabolomics individually with FinnGen GWAS results identified 1,597 genes for 790 disease traits. Integrating transcriptomics and metabolomics jointly with FinnGen GWAS results helped pinpoint metabolic pathways from genes to diseases. We identified putative causal effects of UGT1A1/UGT1A4 expression on gallbladder disorders through regulating plasma (E,E)-bilirubin levels, of SLC22A5 expression on nasal polyps and plasma carnitine levels through distinct pathways, and of LIPC expression on age-related macular degeneration through glycerophospholipid metabolic pathways. Our study highlights the power of integrating multiple sets of molecular traits and GWAS results to deepen understanding of disease pathophysiology.

Neuroprotection for Age-Related Macular Degeneration

Age-related macular degeneration (AMD) is a leading cause of blindness worldwide. Early to intermediate AMD is characterized by the accumulation of lipid- and protein-rich drusen. Late stages of the disease are characterized by the development of choroidal neovascularization, termed "exudative" or "neovascular AMD," or retinal pigment epithelium (RPE) cell and photoreceptor death, termed "geographic atrophy" (GA) in advanced nonexudative AMD. Although we have effective treatments for exudative AMD in the form of anti-VEGF agents, they have no role for patients with GA. Neuroprotection strategies have emerged as a possible way to slow photoreceptor degeneration and vision loss in patients with GA. These approaches include reduction of oxidative stress, modulation of the visual cycle, reduction of toxic molecules, inhibition of pathologic protein activity, prevention of cellular apoptosis or programmed necrosis (necroptosis), inhibition of inflammation, direct activation of neurotrophic factors, delivery of umbilical tissue-derived cells, and RPE replacement. Despite active investigation in this area and significant promise based on preclinical studies, many clinical studies have not yielded successful results. We discuss selected past and current neuroprotection trials for AMD, highlight the lessons learned from these past studies, and discuss our perspective regarding remaining questions that must be answered before neuroprotection can be successfully applied in the field of AMD research.

AMD Genomics: Non-Coding RNAs as Biomarkers and Therapeutic Targets

Age-related macular degeneration (AMD) is a progressive neurodegenerative disease that is the world’s leading cause of blindness in the aging population. Although the clinical stages and forms of AMD have been elucidated, more specific prognostic tools are required to determine when patients with early and intermediate AMD will progress into the advanced stages of AMD. Another challenge in the field has been the appropriate development of therapies for intermediate AMD and advanced atrophic AMD. After numerous negative clinical trials, an anti-C5 agent and anti-C3 agent have recently shown promising results in phase 3 clinical trials, in terms of slowing the growth of geographic atrophy, an advanced form of AMD. Interestingly, both drugs appear to be associated with an increased incidence of wet AMD, another advanced form of the disease, and will require frequent intravitreal injections. Certainly, there remains a need for other therapeutic agents with the potential to prevent progression to advanced stages of the disease. Investigation of the role and clinical utility of non-coding RNAs (ncRNAs) is a major advancement in biology that has only been minimally applied to AMD. In the following review, we discuss the clinical relevance of ncRNAs in AMD as both biomarkers and therapeutic targets.

Urinary Mass Spectrometry Profiles in Age-Related Macular Degeneration

We and others have shown that patients with different severity stages of age-related macular degeneration (AMD) have distinct plasma metabolomic profiles compared to controls. Urine is a biofluid that can be obtained non-invasively and, in other fields, urine metabolomics has been proposed as a feasible alternative to plasma biomarkers. However, no studies have applied urinary mass spectrometry (MS) metabolomics to AMD. This study aimed to assess urinary metabolomic profiles of patients with different stages of AMD and a control group. We included two prospectively designed, multicenter, cross-sectional study cohorts: Boston, US (n = 185) and Coimbra, Portugal (n = 299). We collected fasting urine samples, which were used for metabolomic profiling (Ultrahigh Performance Liquid chromatography—Mass Spectrometry). Multivariable logistic and ordinal logistic regression models were used for analysis, accounting for gender, age, body mass index and use of AREDS supplementation. Results from both cohorts were then meta-analyzed. No significant differences in urine metabolites were seen when comparing patients with AMD and controls. When disease severity was considered as an outcome, six urinary metabolites differed significantly (p < 0.01). In particular, two of the metabolites identified have been previously shown by our group to also differ in the plasma of patients of AMD compared to controls and across severity stages. While there are fewer urinary metabolites associated with AMD than plasma metabolites, this study identified some differences across stages of disease that support previous work performed with plasma, thus highlighting the potential of these metabolites as future biomarkers for AMD.

Plasma Metabolomics of Intermediate and Neovascular Age-Related Macular Degeneration Patients

To characterize metabolites and metabolic pathways altered in intermediate and neovascular age-related macular degeneration (IAMD and NVAMD), high resolution untargeted metabolomics was performed via liquid chromatography-mass spectrometry on plasma samples obtained from 91 IAMD patients, 100 NVAMD patients, and 195 controls. Plasma metabolite levels were compared between: AMD patients and controls, IAMD patients and controls, and NVAMD and IAMD patients. Partial least-squares discriminant analysis and linear regression were used to identify discriminatory metabolites. Pathway analysis was performed to determine metabolic pathways altered in AMD. Among the comparisons, we identified 435 unique discriminatory metabolic features. Using computational methods and tandem mass spectrometry, we identified 11 metabolic features whose molecular identities had been previously verified and confirmed the molecular identities of three additional discriminatory features. Included among the discriminatory metabolites were acylcarnitines, phospholipids, amino acids, and steroid metabolites. Pathway analysis revealed that lipid, amino acid, and vitamin metabolism pathways were altered in NVAMD, IAMD, or AMD in general, including the carnitine shuttle pathway which was significantly altered in all comparisons. Finally, few discriminatory features were identified between IAMD patients and controls, suggesting that plasma metabolic profiles of IAMD patients are more similar to controls than to NVAMD patients.