WAMD long-chain acyl carnitine detection method based on targeted metabonomics

Abstract

The invention discloses a wAMD long-chain acyl carnitine detection method based on targeted metabonomics, and relates to the field of medical detection. Comprising the following steps: collecting aqueous humor samples of a wAMD patient and a cataract control group; performing qualitative and quantitative detection on the long-chain acyl carnitine LCACs in an aqueous humor sample by using a targeted metabonomics technology; the method comprises the following steps: screening differentially expressed LCCs molecules through data analysis, respectively collecting 10 samples of a wAMD patient and a cataract control group, collecting the samples of the wAMD group during anti-VEGF treatment, and collecting the samples of the cataract group during cataract surgery. The method can directly and efficiently detect the change of the LCADs in the aqueous humor of a wAMD patient, reveals the association between the LCADs and the wAMD pathology, and the identified key LCADs molecule can be used as a potential biomarker or a therapeutic target, and has important theoretical value and conversion prospect.

Description

A wAMD long-chain acylcarnitine detection method based on targeted metabolomics Technical Field

[0001] This invention relates to the field of medical testing, and more particularly to a wAMD long-chain acylcarnitine detection method based on targeted metabolomics. Background Technology

[0002] Wet age-related macular degeneration (wAMD) is the leading cause of irreversible central vision loss in older adults worldwide, with its core pathological feature being the formation and exudation of choroidal neovascularization (CNV). Although anti-vascular endothelial growth factor (VEGF) therapy has become the standard treatment, some patients respond poorly, develop resistance, or require long-term, repeated injections, suggesting that the development and progression of wAMD involves a complex, VEGF-independent regulatory network. Therefore, a deeper understanding of its pathogenesis and the identification of new intervention targets are of significant clinical and scientific importance.

[0003] In recent years, metabolic reprogramming has been confirmed as a key driver of various chronic diseases. Metabolomics refers to the qualitative and quantitative measurement of a biological system's metabolic response to physiological and pathological stimuli and gene alterations, thereby describing changes in endogenous metabolites and their response to internal and external factors. The eye possesses a blood-aqueous humor barrier and a blood-retinal barrier, providing it with a unique metabolic environment. While large molecules cannot cross these barriers and are therefore undetectable, some small metabolites can be detected. This makes it possible to use metabolomics to study metabolites in body fluid samples from AMD patients, thereby revealing its pathogenesis. The retina, as one of the most metabolically active tissues in the human body, is highly dependent on precise metabolic homeostasis for its function. Long-chain acylcarnitines (LCACs) are key carrier molecules for fatty acid β-oxidation, participating not only in energy metabolism but also acting as important signaling molecules, regulating processes such as oxidative stress, inflammatory responses, and apoptosis. Existing studies have suggested that systemic lipid metabolism disorders are associated with the risk of wAMD, and mitochondrial dysfunction has been observed in the retina of wAMD patients. However, the specific changes of LCACs in the local microenvironment of wAMD (especially the aqueous humor), their direct association with core pathological processes of wAMD (such as CNV formation and blood-retinal barrier disruption), and their downstream molecular mechanisms currently lack direct evidence from clinical samples and in-depth functional explanations.

[0004] Therefore, this invention provides a method for directly detecting LCACs in the aqueous humor of wAMD patients based on targeted metabolomics technology, in order to solve the above-mentioned problems. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a wAMD long-chain acylcarnitine detection method based on targeted metabolomics.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a method for detecting long-chain acylcarnitine (LCACs) in wAMD based on targeted metabolomics, comprising the following steps: S1: collecting aqueous humor samples from wAMD patients and cataract control groups; S2: using targeted metabolomics technology to perform qualitative and quantitative detection of long-chain acylcarnitine (LCACs) in aqueous humor samples; S3: screening differentially expressed LCACs molecules through data analysis.

[0007] Preferably, 10 samples were collected from each of the wAMD patients and the cataract control group. The wAMD group samples were collected during anti-VEGF treatment, and the cataract group samples were collected during cataract surgery.

[0008] Preferably, the inclusion criteria for wAMD patients are: meeting the clinical diagnostic criteria for wAMD based on fundus examination, OCT and FFA / ICGA evidence, being ≥50 years old, and not having received anti-VEGF treatment or having stopped treatment for ≥3 months.

[0009] Preferably, the inclusion criteria for the cataract control group are: age-related cataract patients aged ≥50 years, and without a history of retinal diseases, glaucoma, uveitis, or other eye diseases.

[0010] Preferably, the exclusion criteria for sample collection include: coexisting retinal diseases, history of previous intraocular surgery, intraocular inflammation, history of infection or trauma, systemic metabolic diseases, long-term use of drugs that may affect the metabolome, insufficient sample size or failed collection.

[0011] Preferably, the targeted metabolomics technology employs liquid chromatography-mass spectrometry (LC-MS).

[0012] Preferably, the long-chain acylcarnitine includes 4-hydroxydodecanoic acid carnitine and 3-hydroxytetradec-4-ene carnitine.

[0013] Preferably, the data analysis includes calculating the variable importance projection (VIP), p-value, Q-value, and Fold Change, where VIP > 1 and p < 0.05 are considered significant differences.

[0014] Preferably, it also includes identifying metabolic pathways associated with wAMD through KEGG bioinformatics analysis.

[0015] Preferably, the metabolic pathway includes the glycerophospholipid metabolic pathway.

[0016] The beneficial effects of this invention are as follows: 1. This invention can directly and efficiently detect changes in LCACs in the aqueous humor of wAMD patients, reveal their association with wAMD pathology, and the identified key LCACs molecules can serve as potential biomarkers or therapeutic targets, which have important theoretical value and translational prospects. Attached Figure Description

[0017] Figure 1 shows the experimental results of significant upregulation of fatty acid metabolites in an example of the wAMD long-chain acylcarnitine detection method based on targeted metabolomics proposed in this invention; Figures 2 and 3 show the experimental results of upregulation of long-chain acylcarnitine in an example of the wAMD long-chain acylcarnitine detection method based on targeted metabolomics proposed in this invention; Figures 4 and 5 show the experimental results of enrichment and upregulation of glycerophospholipid metabolic pathways in an example of the wAMD long-chain acylcarnitine detection method based on targeted metabolomics proposed in this invention. Detailed Implementation

[0018] The technical solution of the present invention will be further described in detail below with reference to specific embodiments.

[0019] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "setting" should be interpreted broadly. For example, they can refer to a fixed connection or setting, a detachable connection or setting, or an integral connection or setting. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0020] Example 1: Sample Collection and Grouping Experimental Group: Aqueous humor samples were collected from 10 patients who met the clinical diagnostic criteria for wet age-related macular degeneration (wAMD) (based on fundus examination, OCT, and FFA / ICGA evidence). All patients were ≥50 years old and had not received anti-VEGF treatment or had discontinued treatment for ≥3 months. Samples were collected when patients first received anti-VEGF drug treatment.

[0021] Control group: Aqueous humor samples were collected from 10 age-matched (all ≥50 years old) age-related cataract patients as controls. All controls had no history of retinal disease, glaucoma, uveitis, or other ocular conditions. Samples were collected during cataract surgery.

[0022] Exclusion criteria: To eliminate interference, individuals with other retinal diseases (such as diabetic retinopathy, retinal vein occlusion, etc.), a history of intraocular surgery (excluding cataract surgery in the control group), a history of intraocular inflammation, infection or trauma, systemic metabolic diseases such as diabetes, long-term use of drugs that may affect the metabolome such as statins or carnitine supplements, as well as those with insufficient sample size or failed collection.

[0023] Sample pretreatment: Collected aqueous humor samples were immediately stored at -80°C for analysis. Before detection, 100 μL of aqueous humor sample was taken and 400 μL of pre-cooled methanol:acetonitrile (1:1, v / v) solution was added for protein precipitation. After vortexing for 3 minutes, the sample was centrifuged at 4°C and 12,000 rpm for 15 minutes. The supernatant was carefully collected and evaporated to dryness in a vacuum centrifuge. Before targeted metabolomics analysis, the sample was reconstituted with 100 μL of acetonitrile:water (1:1, v / v) solution, vortexed for 2 minutes, centrifuged, and the supernatant was used for analysis.

[0024] Targeted metabolomics detection instrument platform: Analysis was performed using an ultra-high performance liquid chromatography-triple quadrupole mass spectrometry (UPLC-MS / MS) system.

[0025] Chromatographic conditions: The column was an ACQUITY UPLC HSS T3 column (2.1 mm × 100 mm, 1.8 μm). Mobile phase A was water (containing 0.1% formic acid), and mobile phase B was acetonitrile (containing 0.1% formic acid). The gradient elution program was as follows: 0–2 min, 5% B; 2–4 min, 5%–30% B; 4–8 min, 30%–60% B; 8–12 min, 60%–95% B; 12–14 min, 95% B; 14–14.1 min, 95%–5% B; 14.1–16 min, 5% B. The flow rate was 0.35 mL / min, the column temperature was 40°C, and the injection volume was 2 μL.

[0026] Mass spectrometry conditions: Electrospray ionization (ESI) was used with multiple reaction monitoring (MRM) in positive ion mode. Ion source parameters were set as follows: ion source temperature 150°C, desolvation gas temperature 500°C, desolvation gas flow rate 1000 L / h, cone gas flow rate 150 L / h, and collision gas flow rate 0.15 mL / min. MRM ion pairs, cone voltage, and collision energy were optimized for target long-chain acylcarnitines (such as 4-hydroxydodecanoic acid carnitine, 3-hydroxytetradec-4-enedicarnitine, etc.).

[0027] Data analysis and result determination involve importing the obtained raw mass spectrometry data into analysis software (such as Skyline) for integration, calibration, and quantification.

[0028] Multivariate statistical analysis, including partial least squares-discriminant analysis (PLS-DA), was performed using SIMCA-P software. The screening criteria for differentially expressed metabolites were variable importance projection (VIP) > 1 and univariate analysis p-value < 0.05 (calculated using Student's t-test).

[0029] Results: As shown in the results table in the disclosure document, several fatty acid metabolites, including capric acid (VIP=2.4, P=0.046, FC=2.8), were significantly upregulated. In particular, 4-hydroxydodecanoic acid carnitine (12 carbons) and 3-hydroxytetradec-4-enecarnitine (14 carbons) among long-chain acylcarnitines were identified as significantly upregulated in both the volcano plot and the matchstick plot, satisfying the conditions of VIP>1 and P<0.05.

[0030] Pathway analysis: The differentially metabolites were imported into the KEGG database for pathway enrichment analysis. The results showed that the glycerophospholipid metabolism pathway (hsa00564) was enriched. This pathway was annotated with differentially metabolites such as choline and triethanolamine, and its DAScore was positive, indicating that the activity of this pathway was enhanced in wAMD.

[0031] In conclusion, this embodiment successfully applied targeted metabolomics to detect a significant upregulation of specific long-chain acylcarnitine molecules (such as 4-hydroxydodecanoylcarnitine and 3-hydroxytetradec-4-enedicarnitine) in the aqueous humor of wAMD patients. This method exhibits good reproducibility and high specificity, providing a reliable detection method for elucidating the role of LCACs in wAMD. The identified differentially expressed LCACs have value as potential biomarkers for wAMD.

[0032] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for detecting wAMD long-chain acylcarnitine based on targeted metabolomics, characterized in that, Includes the following steps: S1: Collect aqueous humor samples from wAMD patients and cataract control groups; S2: Use targeted metabolomics technology to qualitatively and quantitatively detect long-chain acylcarnitine (LCACs) in aqueous humor samples; S3: Screen differentially expressed LCACs molecules through data analysis.

2. The wAMD long-chain acylcarnitine detection method based on targeted metabolomics according to claim 1, characterized in that, Ten samples were collected from each of the wAMD patients and the cataract control group. Samples from the wAMD group were collected during anti-VEGF treatment, and samples from the cataract group were collected during cataract surgery.

3. The wAMD long-chain acylcarnitine detection method based on targeted metabolomics according to claim 1, characterized in that, The inclusion criteria for wAMD patients were: meeting the clinical diagnostic criteria for wAMD based on fundus examination, OCT and FFA / ICGA evidence, being ≥50 years old, and not having received anti-VEGF treatment or having stopped treatment for ≥3 months.

4. The wAMD long-chain acylcarnitine detection method based on targeted metabolomics according to claim 1, characterized in that, The inclusion criteria for the cataract control group were: age-related cataract patients aged ≥50 years with no history of retinal disease, glaucoma, uveitis or other eye diseases.

5. The wAMD long-chain acylcarnitine detection method based on targeted metabolomics according to claim 1, characterized in that, The exclusion criteria for sample collection include: coexisting retinal diseases, history of previous intraocular surgery, intraocular inflammation, history of infection or trauma, systemic metabolic diseases, long-term use of drugs that may affect the metabolome, insufficient sample size or failed collection.

6. The wAMD long-chain acylcarnitine detection method based on targeted metabolomics according to claim 1, characterized in that, The targeted metabolomics technology employs a liquid chromatography-mass spectrometry (LC-MS) method.

7. The wAMD long-chain acylcarnitine detection method based on targeted metabolomics according to claim 1, characterized in that, The long-chain acylcarnitines include 4-hydroxydodecanoic acid carnitine and 3-hydroxytetradec-4-ene carnitine.

8. The wAMD long-chain acylcarnitine detection method based on targeted metabolomics according to claim 1, characterized in that, The data analysis includes calculating variable importance projection (VIP), p-value, Q-value, and Fold Change, where VIP > 1 and p < 0.05 are considered significant differences.

9. The wAMD long-chain acylcarnitine detection method based on targeted metabolomics according to claim 1, characterized in that, It also includes identifying metabolic pathways associated with wAMD through KEGG bioinformatics analysis.

10. The wAMD long-chain acylcarnitine detection method based on targeted metabolomics according to claim 9, characterized in that, The metabolic pathways include the glycerophospholipid metabolic pathway.

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