Combination of molecular markers for early diagnosis of HIV-associated neurocognitive impairment and use thereof

Abstract

The application discloses a molecular marker combination for early diagnosis of HIV-associated neurocognitive impairment (HAND), which comprises core markers and auxiliary markers; the core markers comprise TNFRSF9, MDGA1 and NBL1, and the auxiliary markers comprise one or more of CRTAM, BMP-4, EDA2R, CCL25, SLAMF1 and CD6. The molecular marker combination has the following advantages: (1) based on differential expression data, an explicit relative ratio is derived to solve the core protection requirement of the material composition; (2) high specificity and accuracy, and an accurate ratio relationship can accurately distinguish pathological stages; (3) the marker combination is significantly related to neurocognitive function, and can accurately reflect the early molecular mechanism of HAND; (4) convenient detection, no need for invasive operation, and good tolerance of subjects. Through the molecular marker combination, ANI, PWND and HC can be accurately distinguished, the defects that the existing scale diagnosis is highly subjective, time-consuming and cannot identify subclinical impairment are solved, and key technical support is provided for early intervention of HAND.

Description

Technical Field

[0001] This invention relates to the field of medical diagnostic technology, specifically to a combination of molecular markers for the early diagnosis of HIV-related neurocognitive impairment and their applications. Background Technology

[0002] With the widespread use of combined antiretroviral therapy (cART), AIDS has evolved into a chronic disease. However, about half of people living with HIV (PLWH) will gradually experience cognitive and motor function loss, eventually leading to HIV-related cognitive impairment (HAND). HAND is the most common central nervous system complication of HIV infection, severely impacting patients' quality of life and treatment adherence. Cognitive impairment persists even with viral suppression and immune recovery.

[0003] Asymptomatic neurocognitive impairment (ANI), as an early stage of hallucination disorder (HAND), is also the most common type of HAND. It is characterized by performance in ≥2 cognitive domains below the mean of the demographically adjusted canonical score by at least one standard deviation, but without a decline in daily living functions. ANI represents a critical and reversible period for HAND prevention and intervention. Timely identification and intervention of ANI can effectively prevent the disease from progressing to symptomatic mild neurocognitive impairment (MND) or HIV-related dementia (HAD). However, early identification of ANI faces significant challenges: current clinical diagnosis mainly relies on neurocognitive scale screening, including the Activities of Daily Living (ADL) scale, the Hamilton Depression Rating Scale (HAMD), and neuropsychological examinations covering six cognitive domains. However, scale diagnosis suffers from limitations such as time consumption, high subjectivity, low thresholds, and inability to identify subclinical impairments. It cannot accurately distinguish between ANI patients and those without cognitive impairment (PWND), thus failing to meet the needs for early clinical warning.

[0004] Immune dysfunction and neuroinflammation are key factors in the pathophysiology of HAND (Hyperactive Neuropathic Disorder). Following HIV infection, the virus can enter the central nervous system via the "free virus hypothesis" or the "Trojan horse hypothesis," infecting microglia, astrocytes, and macrophages, inducing the release of viral proteins, neurotoxins, cytokines, and chemokines. This indirectly damages neurons through neuroimmune activation and inflammation. Simultaneously, alterations in transcriptomics can reflect global changes in gene expression, providing crucial insights into the molecular pathways of HAND. Traditional single biomarkers (such as neurofilament light chain protein NfL and the inflammatory factor IL-6) suffer from insufficient specificity and sensitivity. Multi-omics combined analysis can leverage the complementarity of immunomics and transcriptomics to comprehensively elucidate the molecular mechanisms of HAND at the protein and gene levels, screening for more precise diagnostic biomarkers.

[0005] Olink proteomics, a groundbreaking high-throughput detection technology, enables highly sensitive micro-quantity detection of immune and neurological proteins in body fluids, while whole-transcriptome sequencing comprehensively captures differentially expressed genes. Based on this, this invention integrates Olink immunomics and PBMC whole-transcriptome data to screen for combinations of molecular markers with specific relative expression characteristics, achieving precise differentiation between ANI and PWND, filling a gap in existing diagnostic technologies. Summary of the Invention

[0006] To address the aforementioned technical problems, this invention provides a combination of molecular biomarkers for the early diagnosis of HIV-related neurocognitive impairment and their applications.

[0007] In one aspect, this invention provides a combination of molecular markers for the early diagnosis of HIV-related neurocognitive impairment (HAND), including core markers and auxiliary markers; The core biomarkers include TNFRSF9 (tumor necrosis factor receptor superfamily member 9), MDGA1 (containing MAM domain glycerophosphoinositol anchor 1), and NBL1 (DAN family BMP antagonist). The auxiliary biomarkers include one or more of CRTAM (cytotoxic and regulatory T cell molecule), BMP-4 (human bone morphogenetic protein 4), EDA2R (extracellular dysplastic A2 receptor), CCL25 (CC motif chemokine ligand 25), SLAMF1 (signaling lymphocyte activation molecule family member 1), and CD6.

[0008] Furthermore, compared with the healthy control group: In patients without cognitive impairment, the relative expression levels of TNFRSF9, MDGA1, CCL25, CRTAM, BMP-4, and EDA2R were all elevated. In patients with asymptomatic neurocognitive impairment, the relative expression levels of NBL1, CCL25, and SLAMF1 were all elevated.

[0009] Furthermore, compared with the patients without cognitive impairment, the relative expression level of CD6 was reduced in the patients with asymptomatic neurocognitive impairment.

[0010] Further, taking the abundance of the corresponding biomarker in the healthy control group as 1: Among the patients without cognitive impairment, the relative expression levels of TNFRSF9 were 2.2 or higher, MDGA1 were 2.8 or higher, CCL25 were 2.1 or higher, CRTAM were 2.0 or higher, BMP-4 were 2.1 or higher, and EDA2R were 2.0 or higher. In the asymptomatic neurocognitive impairment patients, the relative expression level of NBL1 was 3.5 or higher, the relative expression level of CCL25 was 2.0 or higher, and the relative expression level of SLAMF1 was 2.0 or higher. With the abundance of CD6 in the patients without cognitive impairment being 1, the relative expression level of CD6 in the asymptomatic neurocognitive impairment patients is 0.55 or lower.

[0011] Further, taking the abundance of the corresponding biomarker in the healthy control group as 1: In the patients without cognitive impairment, the relative expression levels of TNFRSF9 were 2.2–2.4, MDGA1 were 2.8–3.0, CCL25 were 2.1–2.3, CRTAM were 2.0–2.2, BMP-4 were 2.1–2.3, and EDA2R were 2.0–2.2. In the asymptomatic neurocognitive impairment patients, the relative expression levels of NBL1 were 3.5–3.7, CCL25 were 2.0–2.2, and SLAMF1 were 2.0–2.2. With the abundance of CD6 in the patients without cognitive impairment as 1, the relative expression level of CD6 in the asymptomatic neurocognitive impairment patients is 0.45~0.55.

[0012] Further, taking the abundance of the corresponding biomarker in the healthy control group as 1: In the patients without cognitive impairment, the relative expression levels of TNFRSF9 were 2.33, MDGA1 was 2.95, CCL25 was 2.17, CRTAM was 2.05, BMP-4 was 2.21, and EDA2R was 2.13. In patients with asymptomatic neurocognitive impairment, the relative expression levels of NBL1 were 3.63, CCL25 2.10, and SLAMF1 2.07. With the abundance of CD6 in the patients without cognitive impairment as 1, the relative expression level of CD6 in the patients with asymptomatic neurocognitive impairment is 0.51.

[0013] In another aspect, the present invention provides the application of the above-mentioned combination of molecular markers in the preparation of reagents or kits for the early diagnosis of HIV-related neurocognitive impairment.

[0014] Furthermore, the reagent or the kit is used for qualitative and quantitative detection of the biomarker combination.

[0015] A third aspect of the present invention provides a kit for the early diagnosis of HIV-related neurocognitive impairment, comprising a detection reagent for detecting the combination of the above-mentioned biomarkers.

[0016] Furthermore, the detection reagent includes specific amplification primers for the core biomarker and specific antibodies for the auxiliary biomarker.

[0017] The beneficial effects of this invention are as follows: The molecular marker combination provided by this invention for the early diagnosis of HIV-related neurocognitive impairment (HAND) has the following advantages: (1) Clear ratio: The relative ratio is derived based on differential expression data, which solves the core protective needs of the material composition; (2) High specificity: CD6 is the only significantly different protein between ANI and PWND, and NBL1 is a gene specifically upregulated by ANI. The precise ratio relationship can accurately distinguish the pathological stage; (3) Strong correlation: The marker combination is significantly correlated with neurocognitive functions (attention, memory and language functions), reflecting the early molecular mechanism of HAND; (4) Convenient detection: Only peripheral blood samples are required, no invasive operation is required, and the subjects tolerate it well. The kit using this molecular marker combination can accurately distinguish between ANI, PWND, and HC by detecting the expression level and relative characteristics of the combination in the peripheral blood of the subjects. It solves the defects of existing diagnostic methods, such as strong subjectivity, time consumption, and inability to identify subclinical damage. It provides key technical support for the early intervention of HAND and has important clinical application value. Attached Figure Description

[0018] One or more embodiments are illustrated by way of example with reference to the accompanying drawings, and these illustrative examples are not intended to limit the embodiments. The term "illustrative" as used herein means "serving as an example, embodiment, or illustration." Any embodiment illustrated herein as "illustrative" is not necessarily to be construed as superior to or better than other embodiments.

[0019] Figure 1 The brain regions with significant differences in functional connectivity (FC) are shown in the PWND, ANI, and HC groups. In the diagram: A represents the differential FC connectivity between the PWND and HC groups; B represents the differential FC connectivity between the ANI and HC groups; and C represents the differential FC connectivity between the ANI and PWND groups.

[0020] Figure 2This is a scatter plot showing the distribution of NPX (relative quantitative units of protein expression on the Olink platform) for sample quality control results. A represents the NPX distribution of the Olink neurogenic protein detection group, and B represents the NPX distribution of the Olink inflammatory and immune-related protein detection group. The horizontal axis represents the mean NPX of the samples (the two vertical lines represent the mean ± 3 standard deviations), and the vertical axis represents the interquartile range (IQR) of the NPX of the samples (the two horizontal lines represent the mean IQR ± 3 standard deviations of IQR). Blue represents qualified samples, red represents unqualified samples, and light blue represents warning samples.

[0021] Figure 3 The image shows a volcano plot of differential protein expression between the PWND and HC groups. In this plot: A compares the expression of neurotransmitter-related proteins between the PWND and HC groups; B compares the expression of inflammation-related proteins between the PWND and HC groups; red indicates upregulated proteins, blue indicates downregulated proteins, and gray indicates proteins with no significant difference.

[0022] Figure 4 The volcano plot shows the differential protein expression between the ANI and HC groups. In the A group, A represents the comparison of expression of nerve-related proteins between the ANI and HC groups; B represents the comparison of expression of inflammation-related proteins between the ANI and HC groups. Red represents upregulated proteins, blue represents downregulated proteins, and gray represents proteins with no significant difference.

[0023] Figure 5 The image shows a volcano plot of differential protein expression between the ANI and PWND groups. In the image: A represents the comparison of expression of neurotransmitter-related proteins between the ANI and PWND groups; B represents the comparison of expression of inflammation-related proteins between the ANI and PWND groups; red represents upregulated proteins, blue represents downregulated proteins, and gray represents proteins with no significant difference.

[0024] Figure 6 The heatmaps show the cluster analysis of differentially expressed neural proteins (DEPs) among the PWND, ANI, and HC groups. Specifically: A represents the cluster analysis heatmap of Olink neural protein detection groups in the HC and PWND groups; B represents the cluster analysis heatmap of Olink neural protein detection groups in the PWND and ANI groups; and C represents the cluster analysis heatmap of Olink neural protein detection groups in the HC and ANI groups. The color intensity represents the expression level after Z-score normalization: red indicates upregulation, blue indicates downregulation, and gray indicates no quantitative information.

[0025] Figure 7The heatmaps show the cluster analysis of differentially expressed inflammatory immune-related proteins (DEPs) among the PWND, ANI, and HC groups. Specifically: A is the heatmap of cluster analysis of Olink inflammatory immune-related protein detection groups for the HC and PWND groups; B is the heatmap of cluster analysis of Olink inflammatory immune-related protein detection groups for the HC and ANI groups; and C is the heatmap of cluster analysis of Olink inflammatory immune-related protein detection groups for the ANI and PWND groups. The color intensity represents the expression level after Z-score normalization: red indicates upregulation, blue indicates downregulation, and gray indicates no quantitative information.

[0026] Figure 8 The graphs show the functional enrichment analysis of DEPs gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) between the PWND and HC groups. In the graphs: A is a bar chart of GO enrichment analysis for the PWND and HC groups; B is a bubble chart of KEGG enrichment analysis for the PWND and HC groups. The bubble size represents the number of enriched proteins, and the color from green to red indicates an increasing enrichment fraction.

[0027] Figure 9 The graphs show the functional enrichment analysis of DEPs gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) between the ANI and HC groups. In the graphs: A is a bar chart of GO enrichment analysis for the ANI and HC groups; B is a bubble chart of KEGG enrichment analysis for the ANI and HC groups. The bubble size represents the number of enriched proteins, and the color from green to red indicates an increasing enrichment score.

[0028] Figure 10 The graphs show the functional enrichment analysis of DEPs gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) between the ANI and PWND groups. In the graphs: A is a bar chart of GO enrichment analysis for the ANI and PWND groups; B is a bubble chart of KEGG enrichment analysis for the ANI and PWND groups. The bubble size represents the number of enriched proteins, and the color from green to red indicates an increasing enrichment score.

[0029] Figure 11 The bar chart and genome circle diagram show the differentially expressed genes (DEGs) among the three sample groups: PWND, ANI, and HC. In the diagram: A is the bar chart of mRNA DEGs in the three sample groups; B is the bar chart of incRNA DEGs in the three sample groups; red indicates upregulation and green indicates downregulation.

[0030] Figure 12 Genome diagrams of differentially expressed genes (DEGs) among the three sample groups: PWND, ANI, and HC.

[0031] Figure 13The diagrams show the Venn diagrams of mRNA and lncRNA DEGs among the three sample groups: PWND, ANI, and HC. In the diagrams, A is the Venn diagram of mRNA DEGs for the three sample groups; B is the Venn diagram of lncRNA DEGs for the three sample groups; and the overlapping circles represent the DEGs common to all groups.

[0032] Figure 14 Venn diagrams were used to integrate the DEPs and DEGs of the three sample groups: PWND, ANI, and HC. In the diagrams, A represents the common DEPs / DEGs of the PWND and HC groups; B represents the common DEPs / DEGs of the ANI and HC groups; and C represents the common DEPs / DEGs of the ANI and PWND groups. All_protein represents proteomic quantifiable proteins, All_Gene represents transcriptomic quantifiable genes, DE_Protein represents differentially expressed proteins, and DE_Gene represents differentially expressed genes.

[0033] Figure 15 Scatter plots showing the correlation between core biomarkers and functional connectivity (FC) are shown below: A is a scatter plot showing the correlation between MDGA1 expression level and FC in PWND; B is a scatter plot showing the correlation between TNFRSF9 expression level and FC in PWND; and C is a scatter plot showing the correlation between NBL1 expression level and FC in ANI. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] Furthermore, to better illustrate the present invention, numerous specific details are set forth in the following detailed embodiments. Those skilled in the art will understand that the present invention can still be practiced even without certain specific details. In some embodiments, materials, elements, methods, and means well known to those skilled in the art are not described in detail in order to highlight the spirit of the invention.

[0036] Unless otherwise expressly stated, throughout the specification and claims, the term "comprising" or its variations such as "including" or "comprises" shall be understood to include the stated elements or components without excluding other elements or other components.

[0037] Unless otherwise specified, all test materials used in the following examples are available through conventional commercial channels.

[0038] Example This invention is based on a prospective study, which performed non-targeted metabolomics analysis and metagenomic sequencing on plasma samples from 49 HIV-infected individuals (18 ANI patients and 31 PWND patients) and 23 healthy controls (HC). Differential biomarkers were screened through systematic statistical analysis, and the quantitative proportions of each biomarker were derived based on inter-group abundance differences, as detailed below: 1. Study subject selection and baseline data Study Design: This was a prospective study approved by the Ethics Committee of Beijing You'an Hospital, Capital Medical University (Ethics No.: LL-2023-070-K). All participants signed written informed consent forms, which complied with the requirements of the Declaration of Helsinki.

[0039] 1.1 Inclusion criteria (1) HIV-infected individuals: Chinese men aged 20-50 who are male homosexual and HIV-infected, right-handed, and whose HIV infection is confirmed by immunoblotting or PCR. (2) HC: 20-50 years old, right-handed, no complaints of cognitive decline, normal standardized cognitive function test results, no history of neurological diseases or positive imaging findings.

[0040] 1.2 Exclusion Criteria (1) The presence of neurological diseases such as brain tumors, infections, strokes, and epilepsy that can cause cognitive impairment; (2) Mental illnesses such as depression and anxiety (HAMD score ≥ 7); (3) History of drug abuse, alcoholism, or drug use; (4) Having claustrophobia or contraindications for MRI examination; (5) Severe visual, hearing and reading difficulties, unable to cooperate with the examination.

[0041] 1.3 Baseline Data The study ultimately included 31 patients with post-WND, 18 patients with ANI, and 23 patients with HC. There were no significant differences in demographic data (age, years of education) among the three groups (p>0.05). Compared with PWND, the ANI group had significantly lower t-scores in all six cognitive domains (p<0.001). Specific data are shown in Table 3-1 (Table 3-1 of the paper). The diagnosis of ANI strictly followed the Frascati criteria: (1) performance in ≥2 cognitive domains below the mean of the demographically adjusted normative score by at least one standard deviation; (2) no decline in daily living function; (3) impairment that does not meet the criteria for delirium or dementia; and (4) no evidence that ANI was caused by other factors.

[0042] The brain regions showing significant differences in FC (functional connectivity) indices among the three groups of subjects are shown in the following diagram. Figure 1As shown in the figure, A represents the differential FC connectivity between the PWND and HC groups, showing 81 differential connections, all of which are weakened, with the most significant weakening observed in the connection between the right transverse temporal gyrus and the left middle temporal gyrus; B represents the differential FC connectivity between the ANI and HC groups, showing 145 differential connections, all of which are weakened, with the most significant weakening observed in the connection between the right middle temporal gyrus and the left middle frontal gyrus; C represents the differential FC connectivity between the ANI and PWND groups, showing 8 differential connections, all of which are weakened, with the most significant weakening observed in the connection between the right thalamus and the right middle temporal gyrus. This demonstrates that after HIV infection, regardless of the presence of cognitive symptoms, the strength of brain functional connectivity is abnormally weakened, with the degree of abnormality being higher in the ANI group than in the PWND group. This provides direct evidence of objective brain functional impairment in the early stages of HAND. Furthermore, the brain functional abnormalities shown in this figure are significantly correlated with the molecular markers of this invention (see below). Figure 15 This confirms the correlation between the combination of biomarkers and the pathological process of the disease, providing support for the scientific nature of the diagnosis.

[0043] 2. Sample Collection and Processing 2.1 Peripheral blood collection All subjects fasted for 12 hours. The next morning, 10 mL of peripheral venous blood was collected, aliquoted into EDTA anticoagulant tubes, and gently inverted 5-10 times to mix the anticoagulant with the blood. The tubes were then temporarily stored at 4°C and pre-processed within 4 hours of sampling.

[0044] 2.2 Plasma separation Centrifuge whole blood at 1900g / min for 10 minutes at 4°C, transfer 200μL of supernatant (plasma) to a 300μL nuclease-free EP tube, aliquot and transfer to a cryovial for storage at -80°C for Olink immunomics analysis, and prepare two backup samples.

[0045] 2.3 PBMC Separation PBMCs were isolated using the Ficoll-Paque density gradient centrifugation method. After centrifuging 10 mL of whole blood, the supernatant serum was discarded, and culture medium was added to fill the centrifuge tube, which was then gently mixed. 5 mL of lymphocyte separation medium was added to a new tube, and the diluted blood cells were slowly transferred onto the lymphocyte separation medium using a dropper. The tube was centrifuged at 2200 rpm for 25 min. 5 mL of basic culture medium was added to a new centrifuge tube, and the PBMC layer was transferred to culture medium. Culture medium was added to fill the centrifuge tube, and the tube was centrifuged at 1000 g / min for 5 min. The supernatant was discarded, the residue was aspirated, and 2 mL of cryopreservation solution was added. The cell pellet was pipetted, and the cell suspension was divided equally into two tubes. The tubes were placed in a temperature-programmed cooling box and stored at -80°C overnight. Afterward, the tubes were transferred to a cryopreservation box and stored at -80°C, avoiding repeated freeze-thaw cycles.

[0046] 3. Marker detection and proportion verification 3.1 Olink Immunomics Detection (Auxiliary Biomarkers) The expression levels of CRTAM, BMP-4, EDA2R, CCL25, SLAMF1, and CD6 in plasma were detected using the Olink® Target 96 Neurology Panel and Inflammation Panel.

[0047] Technical principle: Based on the adjacent extension analysis (PEA) technique, a pair of antibodies that specifically recognize the target protein are designed. A nucleotide sequence is attached to the end of the antibody. When the two antibodies correctly recognize the target protein, the nucleotides carried by the antibodies perform base complementary pairing to form a double strand. Subsequently, the target protein is quantitatively analyzed by PCR amplification and qPCR detection. The experimental procedure includes three stages: incubation (antibody binding to target protein), extension (DNA fragment amplification and enrichment), and detection (qPCR detection and data collection), as detailed below: (1) Incubation stage (antibody binding to target protein): Take the subject's EDTA anticoagulated plasma sample, thaw it on ice, centrifuge at 4℃ and 1600g for 5 minutes to remove the precipitate; take the supernatant and perform a 400-fold serial dilution using the kit's diluent; take 4μL of the diluted plasma sample and add it to a 96-well detection plate, then add 4μL of the target protein-pairing antibody-oligonucleotide probe mixture, seal it and place it in a constant temperature mixer, shake at 37℃ and 500rpm for 60 minutes to complete the specific binding of the antibody to the target protein and the complementary pairing of the probe.

[0048] (2) Extension stage (DNA fragment amplification and enrichment): After incubation, add 80 μL of the kit-matched extension reaction premix (containing high-fidelity DNA polymerase, dNTPs, and reaction buffer) to each well; seal and place in a PCR instrument, incubate at 37°C for 10 minutes to complete DNA chain extension and specific template amplification and enrichment, then heat at 95°C for 5 minutes to terminate the reaction, and store the reaction product at 4°C in the dark.

[0049] (3) Detection stage (qPCR detection and data collection): Take 5 μL of extension reaction product, add it to 20 μL of qPCR amplification reaction system, and place it on the Fruda qPCR platform to complete the detection; the amplification program is set as follows: 95℃ pre-denaturation for 2 minutes; 95℃ denaturation for 15 seconds, 60℃ annealing extension for 1 minute, for a total of 45 cycles; in the melting curve verification stage, the fluorescence signal is collected by gradient temperature increase from 60℃ to 95℃. After the reaction, the Ct value is converted into a standardized NPX value using Olink NPX manager software. After completing the batch effect correction within and between plates, the quantitative expression data of each target protein is obtained.

[0050] Quality control verification: The intra-plate CV of the neural panel was 5%, and the protein detection rate was 85%; the intra-plate CV of the inflammatory panel was 4%, and the protein detection rate was 97%.

[0051] The NPX distribution scatter plot of the sample quality control results is shown below. Figure 2 As shown, A represents the sample NPX distribution of the Olink Neurology Panel, and B represents the sample NPX distribution of the Inflammation Panel; the horizontal axis represents the sample NPX mean (the two vertical lines represent the mean ± 3 standard deviations), and the vertical axis represents the sample NPX interquartile range (IQR) (the two horizontal lines represent the IQR mean ± 3 standard deviations); blue represents acceptable samples, red represents unacceptable samples, and light blue represents warning samples. Figure 2 As can be seen, the qualified sample rate in this experiment reached over 95%, and all detection data were within a reasonable quality control range. This indicates that the NPX distribution of the samples met the quality control requirements, ensuring the authenticity and accuracy of subsequent derivation of molecular marker expression levels and relative characteristics, and laying a data foundation for the feasibility of the entire technical solution.

[0052] 3.2 Whole transcriptome sequencing detection (core biomarkers) RNA was extracted from PBMCs using Thermo Fisher Scientific TRIzol. The A260 / A280 absorbance ratio of the RNA samples was detected by Nanodrop ND-2000 (1.8~2.0), and the RIN value of the RNA was determined by Agilent 2100 Bioanalyzer (≥7.0). After passing the quality control, library construction and sequencing were performed.

[0053] Library construction: Ribosomal RNA was removed using the Epicentre Ribo-Zero™ rRNA Removal Kit. After ion-fractured RNA, the first strand of cDNA was synthesized using RNA as a template. The second strand of cDNA was synthesized after degrading the RNA strand (dUTP was used to replace dTTP). The double-stranded cDNA was purified, its ends were repaired, an "A" base was introduced at the 3' end and a sequencing adapter was ligated. USER enzyme was added to degrade the second strand of cDNA containing U. cDNA of about 400-500 bp was screened for PCR amplification and purification to obtain the library. Sequencing and analysis: Sequencing was performed using the Illumina sequencing platform. After filtering the raw data, high-quality sequences (Clean Data) were obtained and aligned to the human reference genome (hg38). The DESeq2 software package was used to perform differential analysis on gene expression data. The screening criteria were |log2FoldChange|>1 and p-value<0.05. The expression levels of TNFRSF9, MDGA1, and NBL1 were detected.

[0054] Figure 11 The bar charts show the DEGs among the three sample groups: PWND, ANI, and HC. In the charts, A represents the mRNA DEGs of the three sample groups, and B represents the incRNA DEGs of the three sample groups. Red indicates upregulation and green indicates downregulation. Figure 12 The figure shows the mRNA genome diagrams for the three groups of samples. The outermost circle represents chromosome bands, and the distribution of differentially expressed mRNAs in each group is shown from the outside in. Red indicates upregulation, green indicates downregulation, and gray indicates indifferential genes. As can be seen from the figure, the number of lncRNA DEGs is much higher than that of mRNAs, and the gene expression patterns of the HC group and the PWND / ANI group are similar. This figure presents the distribution characteristics of differentially expressed genes at the whole transcriptome level. The core markers (TNFRSF9, MDGA1, NBL1) are all mRNA-differential genes located in key chromosomal regions, indicating that they are representative differentially expressed genes screened from the whole genome, rather than localized or accidental expression differences, supporting the representativeness and reliability of the core markers.

[0055] Figure 13 The diagrams show the Venn diagrams of mRNA and lncRNA DEGs among the three groups of samples. In A, the Venn diagram of mRNA DEGs among the three groups of samples shows that there are a total of 142 DEGs between HC and ANI and between HC and PWND, and there is a total of 1 DEG (BTNL3) among the three groups. In B, the Venn diagram of lncRNA DEGs among the three groups of samples shows that there are a total of 1234 DEGs between HC and ANI and between HC and PWND, and there are a total of 17 DEGs among the three groups. Therefore, it can be seen that the core biomarkers of this invention (TNFRSF9, MDGA1, and NBL1) are not located in the DEGs shared by all groups: TNFRSF9 and MDGA1 only show significant differences in the DEGs of PWND and HC, and NBL1 only shows significant differences in the DEGs of ANI and HC. Combined with the feature that there is only one DEG shared by the three groups, it shows that the core biomarkers are "specific characteristic genes" of a specific cognitive state (PWND / ANI), rather than differentially expressed genes generalized after HIV infection. This verifies the diagnostic specificity of the biomarkers from the perspective of group specificity, rather than simply relying on the number of differentially expressed genes.

[0056] 3.3 Derivation and Verification of Proportional Relationships The differential protein expression among the groups was detected and analyzed, and the results are as follows: Figures 3-5 As shown. Figure 3In the figures, A shows the comparison of expression of neurotransmitter-related proteins between the PWND and HC groups, with upregulated proteins in red including CRTAM, BMP-4, and EDA2R; B shows the comparison of expression of inflammation-related proteins between the PWND and HC groups, with upregulated proteins in red including CCL25 and TNFRSF9. Figure 4 In the table, A represents a comparison of the expression of neurotransmitter-related proteins between the ANI and HC groups, with upregulated proteins in red including CRTAM and BMP-4; B represents a comparison of the expression of neurotransmitter-related proteins between the ANI and HC groups, with upregulated proteins in red including CCL25 and SLAMF1. Figure 5 In the diagram, A represents a comparison of the expression of neurotransmitter-related proteins between the ANI and PWND groups, with PDGF-R-alpha being downregulated in blue; B represents a comparison of the expression of neurotransmitter-related proteins between the ANI and PWND groups, with CD6 being downregulated in blue. Differentially expressed proteins were screened using a dual criterion of "fold change (x-axis) + reliability of difference (y-axis)". The selected red / blue differentially expressed proteins are the auxiliary biomarkers of this invention, ensuring that the biomarker combination is based on objective difference screening rather than random selection, thus supporting the specificity and scientific validity of the biomarker combination.

[0057] An integrated analysis was performed on DEPs (differentially expressed proteins) and DEGs (differentially expressed genes) among the samples in each group, such as... Figure 14 As shown, A shows that the common DEPs / DEGs of the PWND and HC groups are TNFRSF9 and MDGA1; B shows that the common DEPs / DEGs of the ANI and HC groups are NBL1; C shows that the ANI and PWND groups have no common DEPs / DEGs; All_protein represents proteomic quantifiable proteins, All_Gene represents transcriptomic quantifiable genes, DE_Protein represents differentially expressed proteins, and DE_Gene represents differentially expressed genes. Figure 14 The results showed that the core biomarkers exhibited significant differences at both the protein level (DEPs) and the gene level (DEGs), achieving dual verification of "gene-protein". This indicates that the differential expression of the biomarkers is a coherent biological change from transcription to translation, rather than a random error at a single level, which significantly improves the reliability and diagnostic confidence of the biomarker combination.

[0058] DEPs GO functional enrichment analysis and KEGG analysis among samples in each group are as follows: Figure 8As shown, A shows that DEPs in the PWND and HC groups are enriched in the endogenous cellular response; B shows that DEPs in the PWND and HC groups are enriched in the calcium signaling pathway; C shows that DEPs in the ANI and HC groups are enriched in the nerve growth factor stimulation response; D shows that DEPs in the ANI and HC groups are enriched in the neurotrophic factor signaling pathway; E shows that DEPs in the ANI and PWND groups are enriched in the T cell receptor complex; F shows that DEPs in the ANI and PWND groups are enriched in the gap junction pathway. The size of the bubbles represents the number of enriched proteins, and the color from green to red indicates an increasing enrichment fraction. This figure reveals that the biomarker combination of the present invention mainly participates in biological processes and pathways such as neuroinflammation, cellular stress response, and neurotrophic factor signal transduction, all of which are core pathological mechanisms already clearly defined in HAND. This indicates that the biomarker combination is not simply a collection of randomly differentially expressed proteins, but rather key molecules deeply involved in the occurrence and development of diseases, significantly improving the specificity and mechanistic correlation of diagnosis.

[0059] Based on the above differential expression analysis results, using the biomarker expression level of HC as a baseline (set as 1), the relative expression ratio was calculated using the log2FoldChange value: PWND group: TNFRSF9 (log2FoldChange=1.23) was converted to 2.3±0.1 times HC, MDGA1 (log2FoldChange=1.56) was converted to 2.9±0.1 times HC, CCL25 (log2FoldChange=1.12) was converted to 2.2±0.1 times HC, CRTAM (log2FoldChange=1.02) was converted to 2.1±0.1 times HC, BMP-4 (log2FoldChange=1.14) was converted to 2.2±0.1 times HC, and EDA2R (log2FoldChange=1.09) was converted to 2.1±0.1 times HC. ANI group: NBL1 (log2FoldChange=1.89) is equivalent to 3.6±0.1 times HC, CCL25 (log2FoldChange=1.07) is equivalent to 2.1±0.1 times HC, SLAMF1 (log2FoldChange=1.05) is equivalent to 2.1±0.1 times HC, and CD6 (log2FoldChange=-0.97 relative to PWND) is equivalent to 0.5±0.05 times PWND.

[0060] 4. Combinatorial validity verification 4.1 Cluster Analysis Validation Hierarchical clustering analysis (Euclidean distance algorithm + Average linkage connection method) was performed on the marker combination, and the results are as follows: Figure 6 and Figure 7 As shown, the HC, PWND, and ANI samples each clustered into one class, with high similarity in expression patterns within each group and significant differences between groups. This indicates that the expression patterns based on the biomarker combination of this invention can effectively distinguish between healthy individuals, HIV-positive individuals without cognitive impairment, and individuals in the early stages of HAND, directly confirming the classification efficacy of the biomarker combination and providing key experimental evidence for its application in clinical diagnosis.

[0061] 4.2 Validation of the correlation between neurocognitive function The correlation between DEPs / DEGs and FC among the three groups of samples (PWND, ANI, and HC) is as follows: Figure 15 As shown in the figure, the data points are sample test values, the regression line is the correlation trend, and the shaded area is the confidence interval, verifying the association between the biomarker and brain function abnormalities. In the above diagram, A is a scatter plot showing the correlation between MDGA1 expression level and FC in PWND, which shows that MDGA1 expression level and corresponding differential FC are positively correlated to varying degrees (p<0.05). The brain networks to which the correlated differential FC belong mainly involve the Default Mode Network (DMN) and the Limbic Network (LIM). B is a scatter plot showing the correlation between TNFRSF9 expression level and FC in PWND, which shows that TNFRSF9 expression level and corresponding differential FC are positively correlated to varying degrees (p<0.05). The brain networks to which the correlated differential FC belong mainly are located in the Limbic Network (LIM). C is a scatter plot showing the correlation between NBL1 expression level and FC in ANI, which shows that NBL1 expression level and corresponding differential FC are negatively correlated to varying degrees (p<0.05). The brain networks to which the correlated differential FC belong mainly are located in the Visual Network (VIS).

[0062] Spearman correlation analysis was performed on the expression levels and proportions of biomarkers with neuropsychological test scores in six cognitive domains. The results showed that: TNFRSF9 was negatively correlated with attention and working memory scores (r=-0.198, p=0.032). MDGA1 was negatively correlated with verbal and language scores (r=-0.215, p=0.024). NBL1 was negatively correlated with memory (learning and recognition) scores (r=-0.237, p=0.016). CD6 was positively correlated with scores on abstract and executive functions (r=0.205, p=0.028). This confirms that the proportional relationship of this combination is closely related to neurocognitive function.

[0063] This figure quantifies the correlation between the molecular biomarkers of this invention and brain dysfunction (FC index): the biomarker expression level changes regularly with the abnormality of brain functional connectivity strength, indicating that the biomarkers can not only distinguish different populations, but also quantify the degree of pathological damage of the disease; it further confirms the direct association between the biomarker combination and the pathological process of HAND, providing functional support for its use as a diagnostic indicator, and improving the accuracy and application value of diagnosis.

[0064] 5. Diagnostic criteria The relative expression levels and proportions of each biomarker in the subjects were compared with the standard proportions defined in this invention: (1) Compared with HC, the relative expression levels of TNFRSF9, MDGA1, CCL25, CRTAM, BMP-4, and EDA2R were 2.3±0.1 times that of HC, 2.9±0.1 times that of HC, 2.2±0.1 times that of HC, 2.1±0.1 times that of HC, 2.2±0.1 times that of HC, and 2.1±0.1 times that of HC. (2) Compared with HC, the relative expression level of NBL1 was 3.6±0.1 times that of HC, the relative expression level of CCL25 was 2.1±0.1 times that of HC, and the relative expression level of SLAMF1 was 2.1±0.1 times that of HC; (3) Among the subjects who met (2), the relative expression level of CD6 was 0.5 ± 0.05 times that of the subjects who met (1).

[0065] If a subject's biomarkers meet the criteria in (1) above, the subject is considered a suspected PWND patient; if a subject's biomarkers meet both (2) and (3) above, the subject is considered a suspected ANI patient. All of the above determinations must be further confirmed in conjunction with clinical symptoms and neuropsychological testing to ensure the reliability of the diagnosis.

[0066] 6. Summary In summary, this invention, based on the pathophysiological mechanisms of HIV-related neurocognitive impairment, screened a combination of molecular markers consisting of core markers (TNFRSF9, MDGA1, NBL1) and auxiliary markers (CRTAM, BMP-4, EDA2R, CCL25, SLAMF1, CD6) through prospective cohort Olink immunomics and PBMC whole transcriptome sequencing analysis. The relative expression characteristics in each group were then deduced based on differential expression data. This invention overcomes the shortcomings of traditional scale-based diagnoses, such as high subjectivity, time consumption, and inability to identify subclinical lesions. It requires only peripheral blood samples for non-invasive testing, providing an objective and reliable technical means for early intervention and disease monitoring of HAND (Hearing-Onset Disease). Simultaneously, it provides a protein-gene level basis for the molecular mechanism research of HAND, possessing significant clinical application value and scientific research significance.

[0067] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A combination of molecular biomarkers for early diagnosis of HIV-related neurocognitive impairment, characterized in that, Includes core and auxiliary symbols; The core biomarkers include TNFRSF9, MDGA1, and NBL1. The auxiliary markers include one or more of CRTAM, BMP-4, EDA2R, CCL25, SLAMF1, and CD6.

2. The molecular marker combination according to claim 1, characterized in that, Compared with the healthy control group: In patients without cognitive impairment, the relative expression levels of TNFRSF9, MDGA1, CCL25, CRTAM, BMP-4, and EDA2R were all elevated. In patients with asymptomatic neurocognitive impairment, the relative expression levels of NBL1, CCL25, and SLAMF1 were all elevated.

3. The molecular marker combination according to claim 2, characterized in that, Compared with patients without cognitive impairment, the relative expression level of CD6 was reduced in patients with asymptomatic neurocognitive impairment.

4. The molecular marker combination according to claim 3, characterized in that, With the abundance of the corresponding biomarker in the healthy control group defined as 1: Among the patients without cognitive impairment, the relative expression levels of TNFRSF9 were 2.2 or higher, MDGA1 were 2.8 or higher, CCL25 were 2.1 or higher, CRTAM were 2.0 or higher, BMP-4 were 2.1 or higher, and EDA2R were 2.0 or higher. In the asymptomatic neurocognitive impairment patients, the relative expression level of NBL1 was 3.5 or higher, the relative expression level of CCL25 was 2.0 or higher, and the relative expression level of SLAMF1 was 2.0 or higher. With the abundance of CD6 in the patients without cognitive impairment being 1, the relative expression level of CD6 in the asymptomatic neurocognitive impairment patients is 0.55 or lower.

5. The molecular marker combination according to claim 4, characterized in that, With the abundance of the corresponding biomarker in the healthy control group defined as 1: In the patients without cognitive impairment, the relative expression levels of TNFRSF9 were 2.2–2.4, MDGA1 were 2.8–3.0, CCL25 were 2.1–2.3, CRTAM were 2.0–2.2, BMP-4 were 2.1–2.3, and EDA2R were 2.0–2.

2. In the asymptomatic neurocognitive impairment patients, the relative expression levels of NBL1 were 3.5–3.7, CCL25 were 2.0–2.2, and SLAMF1 were 2.0–2.

2. With the abundance of CD6 in the patients without cognitive impairment as 1, the relative expression level of CD6 in the asymptomatic neurocognitive impairment patients is 0.45~0.

55.

6. The molecular marker combination according to claim 5, characterized in that, With the abundance of the corresponding biomarker in the healthy control group defined as 1: In the patients without cognitive impairment, the relative expression levels of TNFRSF9 were 2.33, MDGA1 was 2.95, CCL25 was 2.17, CRTAM was 2.05, BMP-4 was 2.21, and EDA2R was 2.

13. In patients with asymptomatic neurocognitive impairment, the relative expression levels of NBL1 were 3.63, CCL25 2.10, and SLAMF1 2.

07. With the abundance of CD6 in the patients without cognitive impairment as 1, the relative expression level of CD6 in the patients with asymptomatic neurocognitive impairment is 0.

51.

7. The use of the combination of molecular markers according to any one of claims 1 to 6 in the preparation of reagents or kits for the early diagnosis of HIV-related neurocognitive impairment.

8. The application according to claim 7, characterized in that, The reagent or kit is used for qualitative and quantitative detection of the biomarker combination.

9. A kit for early diagnosis of HIV-related neurocognitive impairment, characterized in that, Includes a detection reagent for detecting the combination of markers according to any one of claims 1 to 6.

10. The reagent kit according to claim 9, characterized in that, The detection reagent includes specific amplification primers for the core biomarker and specific antibodies for the auxiliary biomarker.

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