107 results about "Healthy control" patented technology

The invention relates to a metabolic marker for diagnosing diabetic secondary osteoporosis and application of the metabolic marker, and belongs to the technical field of biological medicine. The method comprises the following steps: firstly, screening out obviously different metabolites between osteoporosis (DOP) and osteoporosis-free groups (DM) in diabetic patients; and secondly, screening out significant difference metabolites between the primary osteoporosis patient and the healthy control group, and excluding the intersection of the two groups of difference metabolites to obtain metabolites which exclude the influence of the primary osteoporosis. Metabolic markers, namely cytosine nucleotide, ketoglutaric acid and triethylamine, are obtained through further screening, and when the three metabolic markers are independently used, AUCgt; the AUC during combined use is 0.99, so that the limitation that the sensitivity of the traditional bone mineral density detection on the osteoporosis recognition in the diabetic population is insufficient is effectively made up.

The invention discloses an esophageal adenocarcinoma plasma circulation microbial marker combination, a reagent, a kit, a risk prediction model and application thereof, and belongs to the cross technical field of liquid biopsy and microbiomics. The esophageal adenocarcinoma plasma circulating microbial marker combination disclosed by the invention comprises enterobacteriaceae, cilia, prevotella, ackermania, lactobacillus fermentum and streptococcus. When the esophageal adenocarcinoma plasma circulating microbial marker combination is used for verifying esophageal adenocarcinoma patients and healthy controls, the AUC is 0.952, the sensitivity is 100%, the specificity is 80.00%, the accuracy is 91.43%, the positive predictive value is 86.96%, and the negative predictive value is 100%; the esophageal adenocarcinoma plasma circulating microbial marker combination can effectively distinguish esophageal adenocarcinoma patients from healthy people, is suitable for early screening of esophageal adenocarcinoma, and has remarkable clinical screening application value.

The invention discloses a novel tRNA (transfer ribonucleic acid) derived small RNA biomarker tRF5-23-GlyTCC-2 and application thereof, and relates to the technical field of biological medicines. The nucleotide sequence of the biomarker tRF5-23-GlyTCC-2 disclosed by the invention is as shown in SEQ ID NO. 1, and the nucleotide sequence of the biomarker tRF5-23-GlyTCC-2 is as shown in SEQ ID NO. Results of embodiments show that the gene has significant low expression in colorectal cancer tissues and serum, when the gene is independently used for colorectal cancer diagnosis, AUC for distinguishing a patient from a healthy control reaches 0.8628, the sensitivity is 74%, the specificity is 92%, and the AUC, the sensitivity and the specificity are both superior to CEA; the AUC is improved to 0.9077 and the sensitivity reaches 90% when the compound is used in combination with CEA (Carcino Embryonic Acid). Meanwhile, low expression of the marker is related to poor prognosis characteristics such as late T staging and low differentiation of a patient, and the marker can be used for prognosis evaluation. Functional experiments prove that overexpression can inhibit colorectal cancer cell proliferation and tumor growth, and a new scheme is provided for colorectal cancer diagnosis and treatment.

The present application relates to the field of biological medicine, and particularly relates to biomarkers for migraine diagnosis, kits and application thereof. The biomarkers related to migraine disease according to the present application include COL4A2, and also include any one or a combination of multiple of MMP-14, LCAT, ADAMTS13 and CPXM2. The present application is based on proteomic data of clinical healthy controls and migraine patients, and uses bioinformatics analysis and machine learning methods to deeply mine protein combinations with the most early warning value for migraine disease diagnosis, and to verify in a clinical cohort with expanded samples, to provide a good prospect for clinical transformation of newly discovered biomarkers, and also to lay a foundation for subsequent mechanism research.

The application discloses a Bifidobacterium longum subsp.longum strain for relieving pathological characteristics of mice with chronic kidney disease induced by adenine, and belongs to the technical fields of microorganisms and medicines.The application provides a biomarker combination related to end-stage renal disease of peritoneal dialysis, wherein the corresponding species abundance in the biomarker combination presents significant difference in matched healthy control population and peritoneal dialysis population, can effectively distinguish the end-stage renal disease population of peritoneal dialysis and the healthy population, and has high sensitivity and specificity.The application also provides a Bifidobacterium longum subsp.longum strain CCFM1375 capable of delaying the progression of renal failure, which can be used for preparing products for improving chronic kidney disease.

This invention relates to the field of chemical or physical testing technology, specifically to a method for detecting multiple SNARE-related proteins in children with ADHD. The method includes: identifying the best-matching capture antibody for a target protein; mixing the matching capture antibodies for various target proteins with a blood sample, and detecting the initial response value of the target protein in the mixed blood sample; identifying a combination of target proteins with spectral spillover interference by utilizing the correlation between the initial response values ​​of any two target proteins; determining the compensated response value and reference weight of the interfered protein by using the initial response value of the interfered protein in the target protein combination and the corresponding mean response value in the healthy control group; and obtaining the weighted total response value of all target proteins and the expression characteristics of the SNARE complex based on the compensated response value and reference weight. The technical solution of this invention can comprehensively, accurately, and conveniently reflect the overall functional state of the SNARE protein complex expression.

The invention discloses an AI intervention analysis method for diabetic renal interstitial fibrosis, and relates to the technical field of biologication.The method comprises the following specific steps of sample collection and multi-omics data acquisition, specifically, kidney tissue samples of diabetic renal interstitial fibrosis patients before and after the diabetic renal interstitial fibrosis patients use glucose kidney health intervention and kidney tissue samples of healthy contrasts are collected; respectively acquiring epigenetic data and single-cell gene expression data, preprocessing, and integrating to construct a comprehensive data set; by combining the AI technology and the high-throughput epigenetic detection technology, the epigenetic modification change on a TGF-beta1 / Smads signal path in the process of intervening diabetic renal interstitial fibrosis by the Sushenkang can be deeply analyzed; a brand-new perspective is provided for understanding the occurrence mechanism of the diabetic renal interstitial fibrosis disease and the drug action mechanism of the TGF-beta1 / Smads pathway, epigenetic data is deeply mined through AI, and the specific mechanism of the TGF-beta1 / Smads pathway related gene expression affected by the TGF-beta1 / Smads pathway through epigenetic regulation is shown.

The present application relates to a kind of molecular markers for early diagnosis of glaucoma, the molecular marker is tsRNA, the tsRNA is selected from one or more of tsRNA-5009b-ValCAC and tsRNA-5003c-GlyGCC.The present application finds that relative to healthy control group, the expression of tsRNA-5009b-ValCAC in POAG group patient is significantly down-regulated, its AUC value in ROC curve is 0.717, and diagnosis performance is good, indicating that the tsRNAs can be used as early diagnosis of POAG molecular marker and applied to clinical.

The invention discloses a screening method of a biomarker for auxiliary diagnosis of small cell lung cancer, and relates to the technical field of biomedicine. The method comprises: acquiring multiple groups of samples; the plurality of groups of samples comprise exosome RNA transcriptome sequencing data of a plurality of SCLC patients and a plurality of healthy controls; each piece of exosome RNA transcriptome sequencing data comprises a plurality of RNA characteristics; carrying out technical quality filtering on RNA characteristics in all exosome RNA transcriptome sequencing data, carrying out differential expression analysis on the filtered characteristics, and determining candidate RNA sets of the SCLC patient and the healthy contrast; performing feature selection on the candidate RNA set through three complementary feature selection modes, and screening an optimal exosome RNA marker combination from different quantities of RNA feature combinations through 20 times of iteration and 10-fold nested cross validation; and the optimal exosome RNA marker combination comprises LINC00989, CXCL5, MAP3K7CL and TUBB1 (Tumor Umbrella Blanket B1). The optimal exosome RNA marker combination screened by the method is beneficial to diagnosis of small cell lung cancer.

The present invention relates to a biomarker for diagnosing pediatric atopic dermatitis and use thereof. As result of comparing immune phenotypes of a healthy control group with those of pediatric atopic dermatitis patients, it has been identified that Th1, Th2, Th17 and Th22 cells or expression of STAT1, CD6 and ALCAM genes are increased or decreased. In addition, in the present invention, it has been identified that the frequencies of monocytes, plasmacytoid dendritic cells, CD4 central memory T cells, and CD4 effector memory T cells are related to the severity of pediatric atopic dermatitis. Therefore, the present invention can ensure an efficient treatment strategy for pediatric atopic dermatitis by accurately diagnosing pediatric atopic dermatitis and the severity thereof.

This invention discloses a method for identifying intrahepatic cholangiocarcinoma (ICC) based on serum peptide characteristics and its application. The invention collects serum samples from three groups: individuals with ICC, those with benign liver disease, and healthy controls. Peptide characteristic peaks associated with ICC are screened, and a model is constructed using a logistic regression algorithm. This model demonstrates excellent discriminative ability on both the training and independent test sets, with AUCs reaching 0.986 and 0.963, respectively, significantly outperforming traditional tumor markers CA19-9 and CEA. The peptide characteristic peak combination and the discriminative model constructed based on it can be used for early detection of ICC, differentiation between benign and malignant cases, and screening of high-risk populations. It offers advantages such as rapid detection, standardized procedures, strong early ICC identification capability, and low false positive rate, providing a highly sensitive, specific, and widely applicable non-invasive screening tool for clinical use.

The application discloses application of a reagent for detecting a biomarker in preparation of a product for predicting ulcerative colitis disease activity or a product for diagnosing ulcerative colitis disease, and relates to the technical field of serological markers of inflammatory bowel disease. The serum CD105 of a UC patient is significantly higher than that of a healthy control group, and CD105 has a very high effect of diagnosing ulcerative colitis disease, and CD105 can distinguish disease activity from remission. Therefore, the application provides a novel serum marker which is convenient to sample, has good repeatability and can objectively reflect the colon mucosa inflammation load, and is expected to provide more accurate marker selection for UC disease activity prediction and UC diagnosis.

The application discloses application of a killer cell lectin-like receptor G1 (KLRG1) gene as a marker in preparation of a systemic lupus erythematosus (SLE) secondary hemophagocytic lymphohistiocytosis (HLH) detection preparation, and the preparation is used for detecting the expression level of the KLRG1 gene in a biological sample. Research finds that the expression level of the KLRG1 gene in SLE secondary HLH patients is significantly lower than that of healthy control groups and SLE patients, and has good diagnostic sensitivity and specificity. The application also discloses a preparation for detecting the expression level of the KLRG1 gene in a biological sample of a patient, the preparation contains a primer pair for detecting the mRNA level of the KLRG1 gene expression, or contains an antibody for detecting the protein level of the KLRG1 gene expression, and only needs to extract peripheral blood mononuclear cells (PBMC) after blood drawing to detect whether SLE patients are secondary to HLH, and the preparation is simple, rapid, and accurate in result.

The invention relates to a methylation site marker for assisting in early diagnosis of esophageal squamous cell carcinoma and application of the methylation site marker, and belongs to the technical field of biomedicine. The methylation site marker is one or a combination of human peripheral blood mononuclear cell methylation sites cg05064044, cg03395511 and cg21548813, and the nucleotide sequence of the methylation site marker is as shown in SEQ ID NO. 1-3. According to the present invention, the methylation chip detection results show that the methylation levels of the cg05064044, the cg03395511 and the cg21548813 in the peripheral blood mononuclear cells of the esophageal squamous cell carcinoma patient are significantly increased compared to the health control group; the methylation levels of cg05064044, cg03395511 and cg21548813 sites in PBMC of esophageal squamous cell carcinoma patients in a training queue and a verification queue are all obviously higher than those of a healthy control group through further analysis. Finally, through ROC curve analysis, it is determined that the three methylation sites cg05064044, cg03395511 and cg21548813 have good specificity and sensitivity, have high diagnosis efficiency when being independently or jointly used for esophageal squamous cell carcinoma diagnosis and can be used as potential molecular markers for esophageal squamous cell carcinoma diagnosis.

The invention discloses a multi-modal CWP staging prediction method based on CT images and clinical biochemical data. The method comprises the following steps: S1, data acquisition: acquiring CT images and clinical biochemical data of a healthy control group and CWP different staging patients; s2, data pre-processing: performing different data pre-processing methods on the CT image and the clinical biochemical data to obtain heterogeneous data; s3, constructing a CWP staging prediction model based on a single mode of the CT image: selecting a plurality of deep learning models which are different in model architecture and are relatively wide in application degree in the medical field; s4, constructing a multi-modal staging prediction model: adopting two parallel feature extraction and feature level fusion architecture designs including an image feature extraction branch of the CT image and a biochemical feature extraction branch of the clinical biochemical data; and S5, multi-modal model CWP staging prediction: inputting the heterogeneous data preprocessed in the step S2 into the multi-modal staging prediction model constructed in the step S4 to carry out CWP staging prediction. According to the invention, accurate and comprehensive CWP staging prediction can be realized.

A system for early warning of coronary heart disease. A computer device comprises a memory, a processor, and a computer program stored on the memory. The processor executes the computer program to implement the following steps: receiving methylation level data of a DNA methylation marker combination of a potential coronary heart disease patient and a healthy control sample, establishing a mathematical model, and determining a threshold; and inputting methylation level data of the DNA methylation marker combination of a subject to be tested and substituting same into the mathematical model to obtain a detection index, and comparing the detection index with the threshold to obtain a conclusion of whether a sample to be tested belongs to the potential coronary heart disease patient or the healthy control. The present invention has important scientific significance and clinical application value in early warning of coronary heart disease and diagnosis and treatment of coronary heart disease.

The invention discloses a young coronary heart disease marker HTRA1 and application thereof, and belongs to the technical field of biomarkers. The expression level of the HTRA1 in serum of young coronary heart disease patients is obviously increased, the ROC value of the HTRA1 in the young coronary heart disease patients is high, healthy control and young coronary heart disease groups can be effectively distinguished, it is prompted that the HTRA1 has high value for predicting and diagnosing the young coronary heart disease, and the HTRA1 can be used for developing corresponding diagnostic reagents and kits and has good application prospects. The kit is used for detecting the content of HTRA1 in a human body sample, so that auxiliary diagnosis of the young coronary heart disease is realized. The diagnostic reagent and the kit have the advantages of being high in specificity, high in sensitivity, easy and convenient to operate and the like, and important reference bases can be provided for early discovery and treatment of the young coronary heart disease.

This invention discloses a set of biomarkers, reagents, kits, and applications for predicting alcoholic liver disease (ALD), belonging to the field of biomarker technology. The key technical points are: This invention uses non-target metabolomics to analyze plasma from ALD patients and healthy controls to identify potential biomarkers and related metabolic pathways in the plasma of ALD patients. Through human fecal metagenomic sequencing, potential biomarkers in the microbiome of ALD patients are identified, providing a scientific basis for the pathogenesis and early screening of ALD. Furthermore, this invention evaluates the therapeutic effect of L-threonine on ALD and explores its molecular mechanism, providing solid preclinical evidence and theoretical basis for L-threonine as a safe and effective natural metabolite-derived drug for the treatment of ALD, opening new directions for the development of innovative ALD therapies.

The invention belongs to the technical field of biological medicines, and particularly relates to an oral microbial gene marker for noninvasive diagnosis of esophageal cancer patients and application of the oral microbial gene marker. The invention provides an oral microbial gene marker for distinguishing esophageal cancer patients from healthy people, which consists of six microbial genes as shown in SEQ ID NO: 1-6, and the microbial genes are enriched in the oral cavity of a human body. The microbial gene distinguishing model disclosed by the invention has good distinguishing ability in esophageal cancer patients and healthy control people, and the feasibility, applicability and universality of the microbial gene distinguishing model in the esophageal cancer patients are proved.

The invention discloses an infant AML prognosis model constructed by integrating transcriptomics and machine learning and a construction method of the infant AML prognosis model. The method comprises the following steps: collecting clinical data and whole genome transcriptome data of an infant AML patient; identifying difference up-regulation expression genes of infant AML relative to healthy control and old children AML in the discovery set, and screening intersection genes of the genes and an external verification set; carrying out model construction on the obtained gene by taking the progression-free lifetime of the patient as an outcome, generating a plurality of algorithm combinations based on a machine learning algorithm, and calculating a C-index index of each combination; determining a model with the highest C-index mean value in the internal verification set and the external verification set as an optimal model, calculating a risk score IPScore of each patient by using the model, and performing evaluation in the verification set; and dividing the patients into a low-risk group and a high-risk group according to IPScore by utilizing the optimal cutoff value 0.42, namely an IPGroup model. The model can accurately and effectively predict the prognosis of the infant AML patient, and has good clinical practicability.

The present application relates to the technical field of biological medicine, in particular to a lipid metabolite combination for early diagnosis of VKH and application thereof, by obtaining plasma samples of patients with initial acute stage (early stage) VKH syndrome and healthy controls, and constructing sample-full lipid quantitative expression matrix, screening differential lipids through PCA unsupervised analysis and OPLS-DA supervised model, further screening lipids with high diagnostic performance by using elastic net logistic regression model, finally obtaining a diagnostic marker combination composed of 25 lipid metabolites, solving the technical problems of existing VKH diagnosis technology, such as invasiveness, insufficient sensitivity and stability of protein marker detection, limited diagnostic efficiency, lack of systematicness and standardized process in lipidomics research, achieving the effect of non-invasive, efficient, high sensitivity and high specificity of early auxiliary diagnosis of VKH syndrome, and providing objective and reliable technical means for precise identification of atypical cases and large-scale clinical screening.

The application belongs to the field of medical image pattern recognition, and provides a knee osteoarthritis injury prediction method based on CT images, which comprises the following steps: step one, acquiring a group of healthy controls and a group of CT images of subjects with different degrees of knee joint damage; step two, pre-processing the X-ray images, cropping out the knee joint region, and converting the gray-scale images to L, a and b channels by using the LAB color model; step three, performing image enhancement on the images in the L channel by using adaptive histogram equalization; step four, integrating the three channels of L, a and b after enhancement; step five, performing denoising on the enhanced images; step six, marking the images of the healthy controls as 0, and marking the images of the patients with knee osteoarthritis as 1, 2, 3 and 4 according to the severity; and step seven, performing feature extraction by using a discriminative autoencoder; the method can reduce artificial errors, is an effective supplement for clinicians to judge knee osteoarthritis, and is expected to realize accurate prediction of knee osteoarthritis in areas where professional medical personnel are lacking.

The invention provides a biomarker composition and application of the biomarker composition in breast cancer diagnosis. The biomarker composition is composed of an anti-HSPA4 autoantibody, an anti-PRPF19 autoantibody, an anti-ENO1 autoantibody, an anti-PRDX6 autoantibody and an anti-MMP14 autoantibody. The biomarker composition for detecting the breast cancer is obtained through research, and compared with a healthy control, the expression level of the biomarker composition in a breast cancer patient is remarkably improved, and the biomarker composition can be used as a potential diagnostic marker. Further, ROC curve analysis results show that when the biomarker composition is used for breast cancer diagnosis, the AUC reaches up to 0.97, the AUC in a verification queue also reaches up to 0.88, and the diagnosis efficiency is obviously superior to that of a single autoantibody in the biomarker composition. Therefore, the biomarker composition disclosed by the invention can be used as a specific marker for breast cancer diagnosis, and has relatively high detection sensitivity, specificity and accuracy.

The invention belongs to the technical field of biomedical signal processing, and particularly relates to a surface electromyogram signal-based upper limb movement function evaluation method for a stroke patient. The method comprises the steps of subject selection, electrode arrangement and signal acquisition, experimental normal form design, surface electromyographic signal preprocessing, macroscopic electromyographic feature extraction and microscopic electromyographic feature extraction. The method comprises the following steps: collecting surface electromyogram signals under a plurality of specific gestures, extracting eight macroscopic features and two microcosmic features, and constructing a model for Brunnstrom stage classification and upper limb Fugl-Meyer scoring prediction by using a K nearest neighbor algorithm; through systematic comparison of an affected side, an uninjured side and a healthy control group of a stroke patient, accurate quantification of the degree of stroke dyskinesia is realized, and objectivity, fineness and clinical practicability of evaluation are improved; manual evaluation deviation and time consumption can be greatly reduced, and an objective and real-time evaluation basis is provided for formulating a personalized rehabilitation scheme.

The invention belongs to the technical field of gene detection, and particularly relates to a brand new application of a DDX42 gene or an expression product thereof as an acute myelogenous leukemia (AML) diagnosis and prognosis biomarker. Specific high expression of DDX42 in bone marrow and peripheral blood samples of AML patients is revealed for the first time, the expression level of DDX42 is remarkably different from that of a healthy control group, and DDX42 can be detected through real-time fluorescent quantitative PCR, western blot and other methods and is used for diagnosis, differential diagnosis, disease state evaluation or risk stratification of AML. Meanwhile, the invention clarifies a molecular mechanism that DDX42 promotes AML cell proliferation and inhibits apoptosis and differentiation through PLK1 and LIMK1-CREB-DNMT1 signal axes, and verifies that a transcription factor ERG is an upstream forward regulatory factor for the first time. Based on the discovery, the invention not only provides a novel high-sensitivity molecular diagnosis marker for AML, but also lays a solid experimental foundation for developing a novel AML treatment strategy and a drug screening system targeting DDX42 and related signal channels thereof. The method has the advantages of mature detection method, high marker relevance, clear application prospect and the like.

The invention discloses application of neurogranular protein in diagnosis and treatment of spinal cerebellar ataxia type 3, and belongs to the technical field of biology. Research finds that SCA3 patients and healthy control can be well distinguished by detecting the concentration of the nerve granule protein in plasma, and the diagnosis efficiency of the nerve granule protein in the SCA3 is proved. Furthermore, by overexpressing the neurogranular protein in an SCA3 mouse model, it is proved that the neurogranular protein can be used as a therapeutic target to treat SCA3. According to the invention, a new biomarker and a treatment target are provided for diagnosis and treatment of SCA3, and a technical support and a theoretical basis are provided for precise diagnosis and treatment of SCA3 and in-depth research of pathogenesis of SCA3.

The application discloses an axSpA diagnosis biomarker combination and application thereof in judging axSpA diagnosis effect, relates to the biomedical field, and comprises the following four plasma proteins: LIM and SH3 domain protein 1 (LASP1), calponin binding protein 2 (CNN2), neuron protein kinase C and tyrosine protein kinase substrate 2 (PACSIN2) and tropomyosin 4 (TPM4). The expression levels of the four proteins in the plasma of axSpA light / severe group patients are all up-regulated relative to a healthy control group, and there is a significant difference between the severe group and the light group. Through deep proteomics, multi-algorithm statistics, machine learning models and independent queue immunological verification, the protein combination composed of LASP1, CNN2, PACSIN2 and TPM4 is first systematically identified and verified as an excellent performance of axSpA diagnosis biomarker.

The application belongs to the technical field of biological medicine, and relates to application of TNFR2 (tumor necrosis factor receptor 2) in diagnosis and / or prognosis evaluation of heart failure, a kit and a use method; in particular to application of a reagent for detecting a biomarker, i.e., TNFR2, in a product for diagnosis and / or prognosis evaluation of heart failure; the application proves that TNFR2 is significantly increased in plasma of heart failure patients, and has a significant statistical difference (P<0.0001) compared with a healthy control group through proteomics screening and multi-center clinical cohort verification; research shows that the AUC value of TNFR2 for diagnosing heart failure is excellent in a discovery cohort and a verification cohort; meanwhile, TNFR2 is an independent risk factor for all-cause death of heart failure, and has prediction robustness in medium and long-term prognosis prediction capability; the kit for detecting TNFR2 and the use method provided by the application are simple to detect, have good sensitivity and specificity, and have high clinical popularization and application value.

The application discloses an intestinal microbial marker combination for cirrhosis diagnosis and application thereof, which is composed of 8 specific intestinal bacterial species. The application accurately identifies the core combination from 181 differential characteristics by performing metagenomic sequencing on fecal samples of cirrhosis patients and healthy controls, and combining random forest, LASSO regression and recursive feature elimination algorithms. The random forest diagnosis model based on the 8 markers realizes an excellent performance of area under curve (AUC) 0.841, sensitivity 84.3% and specificity 83.7% on a completely independent test set, and the performance does not decrease compared with the full feature model in the case of reducing the number of characteristics by 86.9%. The marker combination provided by the application is highly simplified and has strong discrimination, and provides a clear and efficient microbiological basis and technical scheme for developing a cirrhosis non-invasive diagnosis kit, a gene chip and other products based on intestinal flora.

The invention discloses application of CTSB as a congenital maxillofacial deformity diagnostic marker in preparation of a diagnostic reagent, and relates to the technical field of biomedicine.Early auxiliary diagnosis of congenital maxillofacial deformity is achieved by detecting the mRNA expression level or protein expression level of CTSB in a biological sample, and when the expression level is higher than that of a healthy control by two times or above, the CTSB can be used as the diagnostic marker for the congenital maxillofacial deformity. And the congenital maxillofacial deformity risk is prompted. The biological sample comprises blood, saliva, amniotic fluid or a palate embryo mesenchymal cell tissue sample. Early auxiliary diagnosis of congenital maxillofacial deformity can be realized by detecting the expression level of CTSB in a biological sample, and targeted therapeutic drugs can be developed by inhibiting the activity or expression of CTSB. The problems that in the prior art, congenital maxillofacial deformity diagnosis lags behind, and treatment lacks specificity are solved, and a new theoretical basis and a new technical means are provided for prevention and treatment of congenital maxillofacial deformity.