Integrated Analysis of Metabolomics and Lipidomics in Plasma of T2DM Patients with Diabetic Retinopathy

Update in the molecular mechanism and biomarkers of diabetic retinopathy

Diabetic retinopathy (DR) is a serious complication of diabetes caused by long-term hyperglycemia that leads to microvascular and neuronal damage in the retina. The molecular mechanisms of DR involve oxidative stress, inflammatory responses, neurodegenerative changes, and vascular dysfunction triggered by hyperglycemia. Oxidative stress activates multiple metabolic pathways, such as the polyol, hexosamine, and protein kinase C (PKC) pathways, resulting in the production of, which in turn promote the formation of advanced glycation end products (AGEs). These pathways exacerbate vascular endothelial damage and the release of inflammatory factors, activating inflammatory signaling pathways such as the NF-κB pathway, leading to retinal cell damage and apoptosis. Additionally, DR involves neurodegenerative changes, including the activation of glial cells, neuronal dysfunction, and cell death. Research on the multiomics molecular markers of DR has revealed complex mechanisms at the genetic, epigenetic, and transcriptional levels. Genome-wide association studies (GWASs) have identified multiple genetic loci associated with DR that are involved in metabolic and inflammatory pathways. Noncoding RNAs, such as miRNAs, circRNAs, and lncRNAs, participate in the development of DR by regulating gene expression. Proteomic, metabolomic and lipidomic analyses have revealed specific proteins, metabolites and lipid changes associated with DR, providing potential biomarkers for the early diagnosis and treatment of this disease. This review provides a comprehensive perspective for understanding the molecular network of DR and facilitates the exploration of innovative therapeutic approaches.

Advances in molecular epidemiology of diabetic retinopathy: from genomics to gut microbiomics

Diabetic retinopathy (DR) remains a prevalent complication of diabetes mellitus and a leading cause of blindness worldwide. The growing global diabetic population underscores the urgency to deepen our understanding of DR pathogenesis and develop effective prevention strategies. This review synthesizes recent advancements in molecular epidemiology, spanning genomics, epigenomics, transcriptomics, proteomics, metabolomics, and gut microbiomics, elucidating genetic underpinnings, epigenetic modifications, transcriptional alterations, protein biomarkers, metabolic disruptions, and gut microbiota dysbiosis associated with DR. Highlighted are key findings from genome-wide association studies (GWAS), Mendelian randomization (MR) studies, candidate gene association studies, and advancements in epigenetic mechanisms, revealing intricate disease pathways and potential therapeutic targets. Additionally, insights into altered metabolic profiles and gut microbiota compositions in DR underscore their emerging roles in disease progression and complications. Challenges and future directions in molecular epidemiological research are discussed to accelerate the translation of these findings into clinical applications for personalized DR management. The integration of multi-omics research findings may provide novel perspectives for facilitating rapid and accurate disease diagnosis, enabling dynamic disease monitoring, and advancing targeted therapeutic strategies.

Causal role of plasma liposome in diabetic retinopathy: mendelian randomization (MR) study

BACKGROUND

Research indicates that there may be an association between plasma lipidome levels and the incidence of diabetic retinopathy (DR) in patients. However, the potential causality of this relationship is yet to be determined. To investigate this matter further, we employed a two-sample Mendelian randomization (MR) analysis to comprehensively assess the causality between lipidome levels and DR.

METHODS

Summary statistics for lipid levels and DR were obtained from the Genome-Wide Association Studies (GWAS) Catalog database and the FinnGen Consortium, respectively. We conducted a two-sample MR analysis, and statistical analysis were performed using the inverse variance weighted (IVW) with the addition of the MR-Egger, weighted median (WM), constrained maximum likelihood and model averaging (cML-MA) to test for causal associations between lipid levels and DR. Heterogeneity was checked using Cochran's Q statistic. The MR Pleiotropy Residual Sum and Outlier (MR-PRESSO) global test and the MR-Egger regression were used to detect horizontal pleiotropy. The robustness of our findings was assessed using leave-one-out and funnel plots. To further assess the reliability of the results, linkage disequilibrium score regressions, colocalization analysis and reverse MR analysis were also performed.

RESULTS

Analysis of the pooled MR results and after correction for the false discovery rate (FDR) revealed that five lipid levels were associated with DR risk. Phosphatidylcholine (16:0_16:0) levels [OR = 0.869 (0.810 to 0.933), Pfdr = 0.006], phosphatidylcholine (16:0_20:2) levels [OR = 0.893 (0.834 to 0.956), Pfdr = 0.043] and phosphatidylethanolamine (18:0_20:4) levels [OR = 0.906 (0.863 to 0.951), Pfdr = 0.006] were protective against DR, whereas sphingomyelin (d36:1) levels [OR = 1.120 (1.061 to 1.183), Pfdr = 0.006], and sphingomyelin (d40:1) levels [OR = 1.081 (1.031 to 1.134), Pfdr = 0.043] were associated with a greater risk of DR. Further sensitivity analysis did not reveal heterogeneity or horizontal pleiotropy.

CONCLUSION

In summary, genetic evidence suggests a causal relationship between the levels of specific lipid levels and DR. These findings may provide valuable insights into the causal relationships between lipid levels and DR, potentially informing future prevention and treatment strategies.

Plasma Metabolomics Identifies Key Metabolites and Improves Prediction of Diabetic Retinopathy: Development and Validation across Multinational Cohorts

PURPOSE

To identify longitudinal metabolomic fingerprints of diabetic retinopathy (DR) and to evaluate their usefulness in predicting DR development and progression.

DESIGN

Multicenter, multiethnic cohort study.

PARTICIPANTS

This study included 17 675 participants from the UK Biobank (UKB) who had baseline prediabetes or diabetes, identified in accordance with the 2021 American Diabetes Association guidelines, and were free of baseline DR and an additional 638 participants with type 2 diabetes mellitus from the Guangzhou Diabetic Eye Study (GDES) for external validation. Diabetic retinopathy was determined by ICD-10 codes in the UKB cohort and revised ETDRS grading criteria in the GDES cohort.

METHODS

Longitudinal DR metabolomic fingerprints were identified through nuclear magnetic resonance (NMR) assay in UKB participants. The predictive value of these fingerprints for predicting DR development were assessed in a fully withheld test set. External validation and extrapolation analyses of DR progression and microvascular damage were conducted in the GDES cohort using NMR technology. Model assessments included the concordance (C) statistic, net classification improvement (NRI), integrated discrimination improvement (IDI), calibration, and clinical usefulness in both cohorts.

MAIN OUTCOME MEASURES

DR development and progression and retinal microvascular damage.

RESULTS

Of 168 metabolites, 118 were identified as candidate metabolomic fingerprints for future DR development. These fingerprints significantly improved the predictability for DR development beyond traditional indicators (C statistic, 0.802 [95% confidence interval (CI), 0.760-0.843] vs. 0.751 [95% CI, 0.706-0.796]; P = 5.56 × 10-4). Glucose, lactate, and citrate were among the fingerprints validated in the GDES cohort. Using these parsimonious and replicable fingerprints yielded similar improvements for predicting DR development (C statistic, 0.807 [95% CI, 0.711-0.903] vs. 0.617 [95% CI, 0.494-0.740]; P = 1.68 × 10-4) and progression (C statistic, 0.797 [95% CI, 0.712-0.882] vs. 0.665 [95% CI, 0.545-0.784]; P = 0.003) in the external GDES cohort. Improvements in NRIs, IDIs, and clinical usefulness also were evident in both cohorts (all P < 0.05). In addition, lactate and citrate were associated with microvascular damage across macular and optic nerve head regions among Chinese GDES (all P < 0.05).

CONCLUSIONS

Metabolomic profiling may be effective in identifying robust fingerprints for predicting future DR development and progression, providing novel insights into the early and advanced stages of DR pathophysiology.

FINANCIAL DISCLOSURE(S)

The author(s) have no proprietary or commercial interest in any materials discussed in this article.

Identification of genes related to fatty acid metabolism in type 2 diabetes mellitus

Aim

Fatty acid metabolism is pivotal for lipid synthesis, cellular signaling, and maintaining cell membrane integrity. However, its diagnostic significance in type 2 diabetes mellitus (T2DM) remains unclear.

Materials and methods

Three datasets and fatty acid metabolism-related genes were retrieved. Differential expression analysis, WGCNA, machine learning algorithms, diagnostic analysis, and validation were employed to identify key feature genes. Functional analysis, ceRNA network construction, immune microenvironment assessment, and drug prediction were conducted to explore the underlying molecular mechanisms.

Results

Six feature genes were identified with strong diagnostic performance and were involved in processes such as ribosome function and fatty acid metabolism. Immune cells, including dendritic cells, eosinophils, and neutrophils, may play a role in the progression of T2DM. ceRNA and drug-target network analysis revealed potential interactions, such as RP11-miR-29a-YTHDF3 and BPA-MSANTD1. The expression patterns of the feature genes, except for YTHDF3, were consistently upregulated in T2DM, aligning with trends observed in the training set.

Conclusion

This study investigated the potential molecular mechanisms of six fatty acid metabolism-related genes in T2DM, offering valuable insights that may guide future research and therapeutic development.

The association between plasma lipidome and diabetic microangiopathy: a mendelian randomization study

BACKGROUND

Current studies have identified severe lipid metabolism diseases in diabetic microangiopathy patients, especially in diabetic kidney disease (DKD), diabetic retinopathy (DR) and diabetic neuropathy (DN), with unclear causal relationships.

METHODS

We employed a large-scale dataset containing 179 lipid species as the exposure and large-scale public summary-level datasets of DKD, DR and DN as the outcome. We applied Mendelian randomization (MR) approach to explore causal associations between circulating liposomes and diabetic microangiopathy. A sequence of sensitivity tests was conducted to verify the stability of the MR analysis.

RESULTS

We manifest that diacylglycerol (18:1_18:3) (OR = 0.716, 95%CI = 0.559-0.917, P = 0.008), triacylglycerol (OR:0.741-0.763, P < 0.05) and phosphatidylcholine (OR:0.620-1.247, P < 0.05) have a potential association with DKD. And there is a nominal causal effect of phosphatidylinositol (16:0_18:2) (OR = 0.617, 95%CI = 0.401-0.948, P = 0.028), phosphatidylcholine (OR:0.499-0.672, P < 0.05) and sphingomyelin (OR:0.652-1.850, P < 0.05) to DR. In addition, phosphatidylethanolamine (18:1_0:0) (OR = 0.616, 95%CI = 0.405-0.935, P = 0.023), diacylglycerol (16:0_18:1) (OR = 0.675, 95%CI = 0.463-0.984, P = 0.041) and phosphatidylcholine (OR = 0.720-1.619, P < 0.05) nominally associate with DN. It is noteworthy that plasma lipidome of different structures show different effects.

CONCLUSION

We establish a possible causal connection between certain plasma lipidome and major diabetic microangiopathies. Implementing intervention strategies targeting different lipid molecules may provide novel approaches for preventing and treating diabetic microangiopathies.

Comparative Proteomic Analysis of Type 2 Diabetic versus Non-Diabetic Vitreous Fluids

BACKGROUND

Diabetic retinopathy (DR) is a leading cause of vision loss, with complex mechanisms. The study aimed to comprehensively explore vitreous humor of diabetic and non-diabetic individuals, paving the way for identifying the potential molecular mechanisms underlying DR.

METHODS

Vitreous samples from type 2 diabetic and non-diabetic subjects, collected post-mortem, were analyzed using liquid chromatography-mass spectrometry. Pathway enrichment and gene ontology analyses were conducted to identify dysregulated pathways and characterize protein functions.

RESULTS

Pathway analysis revealed dysregulation in multiple metabolic and signaling pathways associated with diabetes, including glycerolipid metabolism, histidine metabolism, and Wnt signaling. Gene ontology analysis identified proteins involved in inflammation, immune response dysregulation, and calcium signaling. Notably, proteins such as Inositol 1,4,5-trisphosphate receptor type 2 (ITPR2), Calcium homeostasis endoplasmic reticulum protein (CHERP), and Coronin-1A (CORO1A) were markedly upregulated in diabetic vitreous, implicating aberrant calcium signaling, inflammatory responses, and cytoskeletal reorganization in DR.

CONCLUSIONS

Our study provides valuable insights into the intricate mechanisms underlying DR and highlights the significance of inflammation, immune dysregulation, and metabolic disturbances in disease progression. Identification of specific proteins as potential biomarkers underscores the multifactorial nature of DR. Future research in this area is vital for advancing therapeutic interventions and translating findings into clinical practice.

Pharmacodynamic and targeted amino acid metabolomics researches on the improvement of diabetic retinopathy with Fufang Xueshuantong component compatibility

The Fufang Xueshuantong capsule (FXT) has significant preventive and therapeutic effects on diabetic retinopathy(DR), but the compatibility of its active components remains to be thoroughly explored. In this study, a zebrafish diabetic retinopathy model was established using high-mixed sugars, and the optimal ratios of notoginseng total saponins, total salvianolic acid, astragaloside, and harpagide were selected through orthogonal experiments. Furthermore, we used UPLC-QqQ/MS to detect the changes in amino acid content of DR zebrafish tissues after administration of FXT and its compatible formula to analyze the effects of FXT and its compatible formula on amino acid metabolites. The results showed that the final compatibility ratios of the components were 8: 5: 1: 6.6 by comprehensive evaluation of the indicators. FXT and its compatibility formula had beneficial effects on retinal vasodilatation, lipid accumulation in the liver, total glucose, and VEGF levels in DR zebrafish, and all of them could call back some amino acid levels in DR zebrafish. In this research, we determined the compatible formulation of the active ingredients in the FXT and investigated their efficacy in DR zebrafish for further clinical applications.

Lipidome characterisation and sex-specific differences in type 1 and type 2 diabetes mellitus

BACKGROUND

In this study, we evaluated the lipidome alterations caused by type 1 diabetes (T1D) and type 2 diabetes (T2D), by determining lipids significantly associated with diabetes overall and in both sexes, and lipids associated with the glycaemic state.

METHODS

An untargeted lipidomic analysis was performed to measure the lipid profiles of 360 subjects (91 T1D, 91 T2D, 74 with prediabetes and 104 controls (CT)) without cardiovascular and/or chronic kidney disease. Ultra-high performance liquid chromatography-electrospray ionization mass spectrometry (UHPLC-ESI-MS) was conducted in two ion modes (positive and negative). We used multiple linear regression models to (1) assess the association between each lipid feature and each condition, (2) determine sex-specific differences related to diabetes, and (3) identify lipids associated with the glycaemic state by considering the prediabetes stage. The models were adjusted by sex, age, hypertension, dyslipidaemia, body mass index, glucose, smoking, systolic blood pressure, triglycerides, HDL cholesterol, LDL cholesterol, alternate Mediterranean diet score (aMED) and estimated glomerular filtration rate (eGFR); diabetes duration and glycated haemoglobin (HbA1c) were also included in the comparison between T1D and T2D.

RESULTS

A total of 54 unique lipid subspecies from 15 unique lipid classes were annotated. Lysophosphatidylcholines (LPC) and ceramides (Cer) showed opposite effects in subjects with T1D and subjects with T2D, LPCs being mainly up-regulated in T1D and down-regulated in T2D, and Cer being up-regulated in T2D and down-regulated in T1D. Also, Phosphatidylcholines were clearly down-regulated in subjects with T1D. Regarding sex-specific differences, ceramides and phosphatidylcholines exhibited important diabetes-associated differences due to sex. Concerning the glycaemic state, we found a gradual increase of a panel of 1-deoxyceramides from normoglycemia to prediabetes to T2D.

CONCLUSIONS

Our findings revealed an extensive disruption of lipid metabolism in both T1D and T2D. Additionally, we found sex-specific lipidome changes associated with diabetes, and lipids associated with the glycaemic state that can be linked to previously described molecular mechanisms in diabetes.

Relationship between circulating metabolites and diabetic retinopathy: a two-sample Mendelian randomization analysis

Diabetic retinopathy (DR) is the most frequent microvascular complication of diabetes mellitus, however, its underlying biological mechanisms remain poorly understood. We examined single nucleotide polymorphisms linked to 486 blood metabolites through extensive genome-wide association studies conducted on individuals of European ancestry. The FinnGen Biobank database served as a reference to define DR. Two-sample MR analysis was conducted to reveal the association between the levels of genetically predicted circulating metabolites and the susceptibility to DR. To validate the robustness of the obtained findings, sensitivity analyses with weighted median, weighted mode, and MR-Egger were conducted. 1-oleoylglycerophosphoethanolamine (odds ratio [OR] (OR per one standard deviation [SD] increase) = 0.414; 95% confidence interval [CI] 0.292-0.587; P = 7.613E-07, PFDR = 6.849E-06), pyroglutamine (OR per one SD increase = 0.414; 95% confidence interval [CI] 0.292-0.587; P = 8.31E-04, PFDR = 0.007), phenyllactate (PLA) (OR per one SD increase = 0.591; 95% confidence interval [CI] 0.418-0.836; P = 0.003, PFDR = 0.026), metoprolol acid metabolite (OR per one SD increase = 0.978; 95% confidence interval [CI] 0.962-0.993; P = 0.005, PFDR = 0.042), 10-undecenoate (OR per one SD increase = 0.788; 95% confidence interval [CI] 0.667-0.932; P = 0.005, PFDR = 0.049), erythritol (OR per one SD increase = 0.691; 95% confidence interval [CI] 0.513-0.932; P = 0.015, PFDR = 0.034), 1-stearoylglycerophosphoethanolamine (OR per one SD increase = 0.636; 95% confidence interval [CI] 0.431-0.937; P = 0.022, PFDR = 0.099), 1-arachidonoylglycerophosphoethanolamine (OR per one SD increase = 0.636; 95% confidence interval [CI] 0.431-0.937; P = 0.030, PFDR = 0.099) showed a significant causal relationship with DR and could have protective effects. stachydrine (OR per one SD increase = 1.146; 95% confidence interval [CI] 1.066-1.233; P = 2.270E-04, PFDR = 0.002), butyrylcarnitine (OR per one SD increase = 1.117; 95% confidence interval [CI] 1.023-1.219; P = 0.014, PFDR = 0.062), 5-oxoproline (OR per one SD increase = 1.569; 95% confidence interval [CI] 1.056-2.335; P = 0.026, PFDR = 0.082), and kynurenine (OR = 1.623; 95% CI 1.042-2.526; P = 0.041, PFDR = 0.097) were significantly associated with an increased risk of DR. This study identified metabolites have the potential to be considered prospective compounds for investigating the underlying mechanisms of DR and for selecting appropriate drug targets.

Integrating serum pharmacochemistry and network pharmacology to reveal the mechanism of chickpea in improving insulin resistance

Although chickpea have great potential in the treatment of obesity and diabetes, the bioactive components and therapeutic targets of chickpea to prevent insulin resistance (IR) are still unclear. The purpose of this study was to investigate the chemical and pharmacological characteristics of chickpea on IR through serum pharmacochemistry and network pharmacology. The results revealed that compared with other polar fractions, the ethyl acetate extract of chickpea (CE) had the definitive performance on enhancing the capacities of glucose consumption and glycogen synthesis. In addition, we analyzed the components of CE in vivo and in vitro based on UPLC-Q-Orbitrap HRMS technology. There were 28 kinds of in vitro chemical components, among which the isoflavones included biochanin A, formononetin, ononin, sissotrin, and astragalin, etc. Concerningly, the chief prototype components of CE absorbed into the blood were biochanin A, formononetin, loliolide, and lenticin, etc. Furthermore, a total of 209 common targets between IR and active components of CE were screened out by network pharmacology, among which the key targets involved PI3K p85, NF-κB p65 and estrogen receptor 1, etc. Specifically, KEGG pathway analysis indicated that PI3K-AKT signaling pathway, HIF-1 signaling pathway, and AGE-RAGE signaling pathway may play critical roles in the IR remission by CE. Finally, the in vitro validation experiments disclosed that CE significantly balanced the oxidative stress state of IR-HepG2 cells and inhibited expressions of inflammatory cytokines. In conclusion, the present study will be an important reference for clarifying the pharmacodynamic substance basis and underlying mechanism of chickpea to alleviate IR.

Integration of systematic review, lipidomics with experiment verification reveals abnormal sphingolipids facilitate diabetic retinopathy by inducing oxidative stress on RMECs

OBJECTIVE

This study aims to explore the potential biomarkers in the development of diabetes mellitus (DM) into diabetic retinopathy (DR).

METHODS

Systematic review of diabetic metabolomics was used to screen the differential metabolites and related pathways during the development of DM. Non-targeted lipidomics of rat plasma was performed to explore the differential metabolites in the development of DM into DR in vivo. To verify the effects of differential metabolites in inducing retinal microvascular endothelial cells (RMECs) injury by increasing oxidative stress, high glucose medium containing differential metabolites was used to induce rat RMECs injury and cell viability, malondialdehyde (MDA) contents, superoxide dismutase (SOD) activities, reactive oxygen species (ROS) levels and mitochondrial membrane potential (MMP) were evaluated in vitro. Network pharmacology was performed to explore the potential mechanism of differential metabolites in inducing DR.

RESULTS

Through the systematic review, 148 differential metabolites were obtained and the sphingolipid metabolic pathway attracted our attention. Plasma non-targeted lipidomics found that sphingolipids were accompanied by the development of DM into DR. In vitro experiments showed sphinganine and sphingosine-1-phosphate aggravated rat RMECs injury induced by high glucose, further increased MDA and ROS levels, and further decreased SOD activities and MMP. Network pharmacology revealed sphinganine and sphingosine-1-phosphate may induce DR by regulating the AGE-RAGE and HIF-1 signaling pathways.

CONCLUSIONS

Integrated systematic review, lipidomics and experiment verification reveal that abnormal sphingolipid metabolism facilitates DR by inducing oxidative stress on RMECs. Our study could provide the experimental basis for finding potential biomarkers for the diagnosis and treatment of DR.

Manganese overexposure induces Parkinson-like symptoms, altered lipid signature and oxidative stress in C57BL/6 J mouse

Although adequate intake of manganese (Mn) is essential to humans, Mn in excess is neurotoxic. Exposure to extremely high doses of Mn results in "manganism", a condition that exhibits Parkinson-like symptoms. However, the mechanisms underlying its neurotoxic effects in Mn-induced parkinsonism pathogenesis are unclear. In this study, 8-week-old male C57BL/6 J mice were injected intraperitoneally with saline and 50 mg/kg MnCl2 respectively once daily for 14 days to produce an acute Mn neurotoxicity model. Accumulation of Mn in the midbrain, motor dysfunction and loss of dopaminergic neurons in the substantia nigra evidenced Mn neurotoxicity. Untargeted lipidomic analysis demonstrated that Mn overexposure altered lipidome profiles. A significant modulation of 12 lipid subclasses belonging to 5 different categories were found in the midbrain and among the most abundant lipids were sphingolipids, glycerophospholipids, and glycerides. The levels of sphingomyelin (SM) were significantly decreased after Mn treatment. The expression of SM biosynthesis genes was decreased dramatically while sphingomyelinase was up-regulated. In addition, we observed oxidative stress in both the midbrain of mice and MN9D cells, indicated by the increase of MDA level, the decrease of reduced GSH level and the inhibition of SOD and GPx enzyme activities. There was a correlation between these changes and motor dysfunctions. Overall, our study is the first to use lipidomics techniques to explore the pathogenesis of Mn-induced parkinsonism in C57BL/6 J mice. Mn induced molecular events in the midbrain, such as lipid metabolism disorders, oxidative stress and dopaminergic neurons injury, may mechanistically play important roles in the pathogenesis of Parkinson-like symptoms. Moreover, these findings emphasize the necessity for reducing the health risk of environmental neurotoxic pollutants in relation to parkinsonism.

Recent Advances and Perspectives in Relation to the Metabolomics-Based Study of Diabetic Retinopathy

Diabetic retinopathy (DR), a prevalent microvascular complication of diabetes, is a major cause of acquired blindness in adults. Currently, a clinical diagnosis of DR primarily relies on fundus fluorescein angiography, with a limited availability of effective biomarkers. Metabolomics, a discipline dedicated to scrutinizing the response of various metabolites within living organisms, has shown noteworthy advancements in uncovering metabolic disorders and identifying key metabolites associated with DR in recent years. Consequently, this review aims to present the latest advancements in metabolomics techniques and comprehensively discuss the principal metabolic outcomes derived from analyzing blood, vitreous humor, aqueous humor, urine, and fecal samples.

Untargeted Multiomics Approach Coupling Lipidomics and Metabolomics Profiling Reveals New Insights in Diabetic Retinopathy

Diabetic retinopathy (DR) is a microvascular complication of diabetes mellitus (DM) which is the main cause of vision loss in the working-age population. Currently known risk factors such as age, disease duration, and hemoglobin A1c lack sufficient efficiency to distinguish patients with early stages of DR. A total of 194 plasma samples were collected from patients with type 2 DM and DR (moderate to proliferative (PDR) or control (no or mild DR) matched for age, gender, diabetes duration, HbA1c, and hypertension. Untargeted lipidomic and metabolomic approaches were performed. Partial-least square methods were used to analyze the datasets. Levels of 69 metabolites and 85 lipid species were found to be significantly different in the plasma of DR patients versus controls. Metabolite set enrichment analysis indicated that pathways such as metabolism of branched-chain amino acids (methylglutaryl carnitine p = 0.004), the kynurenine pathway (tryptophan p < 0.001), and microbiota metabolism (p-Cresol sulfate p = 0.004) were among the most enriched deregulated pathways in the DR group. Moreover, Glucose-6-phosphate (p = 0.001) and N-methyl-glutamate (p < 0.001) were upregulated in DR. Subgroup analyses identified a specific signature associated with PDR, macular oedema, and DR associated with chronic kidney disease. Phosphatidylcholines (PCs) were dysregulated, with an increase of alkyl-PCs (PC O-42:5 p < 0.001) in DR, while non-ether PCs (PC 14:0-16:1, p < 0.001; PC 18:2-14:0, p < 0.001) were decreased in the DR group. Through an unbiased multiomics approach, we identified metabolites and lipid species that interestingly discriminate patients with or without DR. These features could be a research basis to identify new potential plasma biomarkers to promote 3P medicine.