CN113970606B

CN113970606B - Metabolic markers for diagnosing attention deficit hyperactivity disorder syndrome in urine of children

Info

Publication number: CN113970606B
Application number: CN202111217681.3A
Authority: CN
Inventors: 田晓怡; 宋文琪
Original assignee: Beijing Childrens Hospital
Current assignee: Beijing Childrens Hospital
Priority date: 2021-10-19
Filing date: 2021-10-19
Publication date: 2022-06-14
Anticipated expiration: 2041-10-19
Also published as: CN113970606A

Abstract

The invention discloses application of a group of metabolic markers in preparing products for screening and diagnosing early stages of attention deficit hyperactivity disorder, wherein the metabolic markers comprise one or more of FAPy-adenine, 3-methylazelaic acid and phenylacetylglutamine; the metabolic marker of the invention is used for early screening and diagnosing attention deficit hyperactivity disorder, has high specificity and sensitivity, and has guiding significance for the development of subsequent clinical application research.

Description

Metabolic markers for diagnosing attention deficit hyperactivity disorder syndrome in urine of children

Technical Field

The invention relates to the field of biological detection, in particular to a metabolic marker for diagnosing attention deficit hyperactivity disorder syndrome in urine of children.

Background

Attention Deficit Hyperactivity Disorder (ADHD), also known as hyperkinetic, is one of the most common neurodevelopmental disorders in children and adolescents.

ADHD is a behavioral disorder characterized by attention deficit, impulsivity, and hyperactivity that are inappropriate for child development, associated with immature brain function development [ 1; 2]. The current prevalence of ADHD in children and adolescents worldwide is around 5% (1), and recent population-based cross-sectional survey studies in the United states have shown a continuing upward trend in ADHD prevalence in the last two decades [3 ]. Meta analysis of ADHD of children in China reports that the total prevalence rate is as high as 5.6% [4] to 6.26% [5], and the prevalence rate of boys is obviously higher than that of girls.

ADHD disease can cause a series of problems in children, including insufficient concentration in class, poor learning performance, interpersonal interaction problems, and ADHD often incorporates other psychologic diseases such as sleep problems, learning difficulties, depression, anxiety, tics, etc. [ 1; 2] have long-term influence on physical and mental health of the sick children, cause huge psychological burden on parents and bring inconvenience to teachers and students in schools. Studies have also found that ADHD, with nearly 50% of childhood diagnoses, may persist into adults with a prevalence of 2% to 5% [6], ADHD may cause post-adult work problems, drug abuse, low self-esteem, social disability, antisocial personality disorders, and increased criminal behavior [1 ]. ADHD is no longer currently considered to be the only disease affecting children, but has become a global, chronic public health problem. The early accurate diagnosis of ADHD can provide early treatment opportunity for children patients, improve symptoms and improve learning score and confidence.

ADHD diagnosis is mainly performed by using a Diagnostic and Statistical Manual of Mental Disorders (5 th Edition), DSM-5, psychologists observing the symptoms of children, inquiring about the parents 'medical history (symptoms, onset age, course, impaired social function, performance in school, and discharge diagnosis), combining the results of various scales filled by parents, such as SNAP-IV Scale, ADHD Rating Scale fourth Edition (ADHD Rating Scale-IV), Vanderbilt Diagnostic Scale (VARS), and Conners' parental symptoms questionnaire, and performing continuous task tests (CPT) on children, and performing joint tests of Revern test type, etc. [7 ]. ADHD was classified according to DSM-5 into three clinical subtypes, attention deficit as major, hyperactivity/impulsivity as major and mixed phenotype [8 ]. In summary, the ADHD diagnosis method is highly subjective, a certain proportion of misdiagnosis and missed diagnosis can occur, and at present, no one or more accurately quantifiable biomarkers can be used for diagnosing ADHD clinically. Researchers in the relevant industry are keenly concerned with objective biomarkers associated with ADHD, and their discovery will help standardize disease diagnosis, optimize diagnostic evaluation procedures, and explore understanding the molecular mechanisms of disease [9 ].

Metabolites are intermediate products or end products of metabolic reactions of the body, driving essential biological functions of the human body. Measurement of these markers may reflect the health status of an individual, and may help understand the effects of diet, drugs and disease states on the metabolism of the body. Metabolomics is a research approach to find small molecule metabolites within biological samples by mass spectrometry. Metabonomic strategies have been widely used to study the specific phenotypes of psychiatric disorders and the like (e.g., schizophrenia, bipolar disorder, autism spectrum disorder [10-12]), and to screen and identify some small molecule metabolites in body fluids (blood or urine) as diagnostic markers. There are researchers who found some differentially expressed metabolites associated with ADHD disease in plasma [13], but there is currently no study on urine metabolomics of ADHD children patients, and metabolic markers in urine remain to be further explored.

[1]Faraone S V,Asherson P,Banaschewski T,et al.Attention-deficit/hyperactivity disorder[J].Nature Reviews Disease Primers,2015,1:1-23.

[2]Thapar A,Cooper M.Attention deficit hyperactivity disorder[J].The Lancet,2016,387(10024):1240-1250.

[3]Xu G,Strathearn L,Liu B,et al.Twenty-Year Trends in Diagnosed Attention-Deficit/Hyperactivity Disorder Among US Children and Adolescents,1997-2016[J].JAMA network open,2018,1(4):e181471-e181471.

[4] Li Shiming, von is Fang, et al, China child attention deficit hyperactivity disorder prevalence Meta analysis [ J ]. China epidemiology journal, 2018,39(7): 993-.

[5]Wang T,Liu K,Li Z,et al.Prevalence of attention deficit/hyperactivity disorder among children and adolescents in China:a systematic review and meta-analysis[J].BMC psychiatry,2017,17(1):32-32.

[6]Ramos-Quiroga J A,Nasillo V,Fernández-Aranda F,et al.Addressing the lack of studies in attention-deficit/hyperactivity disorder in adults[J].Expert Review of Neurotherapeutics,2014,14(5):553-567.

[7]Society B P.Attention Deficit Hyperactivity Disorder:Diagnosis and Management of ADHD in Children,Young People and Adults.[M].National Collaborating Centre for Mental Health(UK).2018.

[8]Association A P.Diagnostic and statistical manual of mental disorders

[M].American Psychiatric Pub,2013.

[9]Faraone S V,Bonvicini C,Scassellati C.Biomarkers in the Diagnosis of ADHD–Promising Directions[J].Current Psychiatry Reports,2014,16(497):1-20.

[10]Gevi F,Zolla L,Gabriele S,Persico AM.Urinary metabolomics of young Italian autistic children supports abnormal tryptophan and purine metabolism.Molecular Autism.2016；7:47.

[11]Glinton KE,Elsea SH.Untargeted Metabolomics for Autism Spectrum Disorders:Current Status and Future Directions.Front Psychiatry.2019；10:647.

[12]Yang J,Yan B,Zhao B,Fan Y,He X,Yang L,Ma Q,Zheng J,Wang W,Bai L et al.2020.Assessing the Causal Effects of Human Serum Metabolites on 5Major Psychiatric Disorders.Schizophrenia bulletin.46(4):804-813.

[13]Wang L-J,Chou W-J,Tsai C-S,Lee M-J,Lee S-Y,Hsu C-W,Hsueh P-C,Wu C-C.2021.Novel plasma metabolite markers of attention-deficit/hyperactivity disorder identified using high-performance chemical isotope labelling-based liquid chromatography-mass spectrometry.The World Journal of Biological Psychiatry.22(2):139-148.

Disclosure of Invention

The invention aims to screen a group of metabolic markers which can better distinguish normal healthy children (contrast) from ADHD children through a metabonomics method in urine based on the existing liquid chromatogram tandem mass spectrum technology, and provide a high-efficiency early diagnosis molecular marker for the diagnosis of ADHD diseases. The invention provides application of an identification reagent of ADHD disease-related metabolic markers in urine in preparation of products for ADHD diagnosis.

In order to realize the purpose, the specific technical scheme of the invention is as follows:

the invention provides application of a group of metabolic markers in preparing products for screening and diagnosing early stages of attention deficit hyperactivity disorder, wherein the metabolic markers comprise one or more of FAPy-adenine, 3-methyl azelaic acid and phenyl acetyl glutamine.

Preferably, the metabolic marker is a FAPy-adenine, 3-methyl azelaic acid and phenyl acetyl glutamine combined metabolic marker.

Compared with a normal healthy child control, the content of the FAPy-adenine in the sample of the child suffering from attention deficit hyperactivity disorder is obviously reduced, and the content of the 3-methylazelaic acid and the content of the phenylacetylglutamine in the sample of the child suffering from attention deficit hyperactivity disorder are respectively and obviously increased.

Preferably, the sample comprises urine.

In one embodiment of the present invention, the step of screening and diagnosing attention deficit hyperactivity disorder using the metabolic markers comprises: (1) obtaining a urine sample of a subject; (2) detecting the amount of the one or more metabolic markers in the sample from the subject; (3) indicating that the subject has attention deficit hyperactivity disorder if the FAPy-adenine metabolic marker level is decreased and the 3-methylazelaic acid and phenylacetylglutamine metabolite levels are respectively increased, as compared to a healthy control.

In a preferred embodiment of the present invention, the step of screening and diagnosing attention deficit hyperactivity disorder using the metabolic markers comprises: (1) obtaining a urine sample of a subject; (2) detecting the content of FAPy-adenine, 3-methyl azelaic acid and phenylacetyl glutamine metabolism markers in a sample of a subject; (3) if the FAPy-adenine metabolic marker level is decreased, the levels of 3-methylazelaic acid and phenylacetylglutamine metabolites, respectively, are increased, as compared to a healthy control, indicating that the subject has attention deficit hyperactivity disorder.

Preferably, the method for detecting the amount of said one or more metabolic markers in the sample of the subject comprises mass spectrometry, nuclear magnetic resonance analysis, enzymatic methods.

Preferably, the method for detecting the amount of said one or more metabolic markers in the sample of the subject is mass spectrometry, preferably, the mass spectrometry is liquid chromatography-high resolution mass spectrometry.

Preferably, when mass spectrometry is used to determine metabolite levels, a metabolite extraction, protein removal step may also be included after the step of obtaining a urine sample.

Preferably, the early screening and diagnostic product comprises a diagnostic formulation, kit or chip.

The invention provides a kit for early diagnosis of attention deficit hyperactivity disorder, which comprises a reagent for detecting the content of FAPy-adenine, 3-methylazelaic acid and phenylacetylglutamine metabolic markers.

Based on the technical scheme, the invention has the following beneficial effects:

the invention discloses a metabolic marker related to attention deficit hyperactivity disorder, and further proves that the metabolite can be used as a metabolic marker for diagnosing attention deficit hyperactivity disorder. The metabolic marker of the invention is used for early screening and diagnosing attention deficit hyperactivity disorder, has high specificity and sensitivity, and has guiding significance for the development of subsequent clinical application research.

Drawings

FIG. 1 shows a scatter plot of the PCA model of the metabolic differences between ADHD infants and normal healthy children.

FIG. 2 shows OPLS-DA scattergrams of the metabolic differences between the ADHD group and the healthy control group.

FIG. 3 is a ROC curve for the panel of three metabolite combinations for ADHD diagnosis with an area under the curve (AUC) of 0.918, a sensitivity of 0.87, and a specificity of 0.84.

FIG. 4 is a ROC curve for the validation set of the three metabolite combinations for ADHD diagnosis with an area under the curve (AUC) of 0.96 and a 95% confidence interval of 0.82 to 1.

Detailed Description

The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention. Unless otherwise specified, the technical means used in the examples are conventional means well known to those skilled in the art.

The experimental procedures used in the following examples are all conventional procedures unless otherwise specified.

All materials, reagents and the like in the following examples are commercially available unless otherwise specified.

Example 1 screening and identification of ADHD-related metabolites in urine of Children

The inventor uses liquid chromatography-high resolution mass spectrometry (LC-MS) to detect metabolites in urine through a full-scan mode, and screens the metabolites related to ADHD through multivariate statistical analysis. The identification of metabolic markers is performed by matching or resolving secondary fragments using secondary targeting analysis methods.

1. Materials and reagents

1) The instrument comprises the following steps: waters H-class liquid chromatograph (Waters Corp.) LTQ-Orbitrap pro Mass spectrometer (Thermofeisher Scientific Corp.).

2) The main reagents are as follows: acetonitrile (Thermofisher Scientific); c18 reverse phase chromatography column (3.0 mm. times.100 mm, C18,1.7 μm, Waters Co.).

3) Sample preparation: 31 ADHD children and 46 age, gender matched healthy children established a test group (training set), 13 ADHD children and 17 age, gender matched healthy children established a verification group (validation set), the children of the group were all from Beijing Children hospital affiliated to capital medical university.

2. Human urine sample collection

Collecting morning urine of children, centrifuging at 5000g for 30min, and removing precipitate.

3. Metabolite extraction

Taking 200 mu l urine supernatant, adding 200 mu l acetonitrile, whirling, standing for 30min at 4 ℃, centrifuging for 10min at 14000g, taking the supernatant, centrifuging, concentrating, vacuum-pumping, redissolving by 200 mu l 2% acetonitrile water, centrifuging for 10min at 14000g, removing small molecular proteins by a 10kD filter membrane, and taking 10 mu l for sample injection.

4. Liquid phase analysis

Waters H-class high performance liquid chromatograph

And (3) chromatographic column: waters HSS C18(3.0mm X100mm,1.7 μm), column temperature 45 ℃; the mobile phase A is 0.1% formic acid water, and the mobile phase B is acetonitrile; the analytical gradient was: 0-1min, 2% B; 1-8min, 2% -98% B; 8-8.1min, 98% -100% B; 8.1-12min, 100% B; 12-12.1min, 100% -2% B; 12.1-17min, 2% B; the flow rate is 0.5 ml/min; the injection volume was 10. mu.l.

5. Mass spectrometric analysis

Ultra Performance Liquid Chromatography (UPLC) tandem LTQ-Orbitrap (Thermo Fisher Scientific, san jose, CA, USA) mass spectrometry, using electrospray (electrospray) ion source positive ion mode; the sheath gas is nitrogen and auxiliary gas, and the flow rates are respectively 45 and 10 arbitrary units (arbitrary units); the mass spectrum scanning range is 100-1000 m/z; the electrospray voltage (spray voltages) was set to 4.2 KV; the ion transfer tube temperature was 350 ℃. The data is obtained by adopting a high-resolution Fourier Transform (FT) mode, and the first-level resolution is 60000; the secondary resolution is 15000.

6. Mass spectrometric data analysis

Raw data obtained from UPLC-LTQ orbitrap were processed using the commercial analysis software Progenesis QI from Waters corporation (Waters, Milford, MA, USA). The software can automatically complete the pretreatment procedures of peak alignment, peak identification, peak correction and the like, and finally output a three-dimensional matrix, namely a spectral peak index variable consisting of retention time and accurate mass-to-charge ratio, a sample name and peak intensity/area.

The obtained data matrix is imported into multivariate statistical software SIMCA-P software 14.0(Umetrics AB, Umea, Sweden) for PCA analysis, and the change trend among groups is visualized. And (3) screening the difference variable between groups by using a VIP value obtained by an OPLS-DA model, wherein the VIP value is more than 1, the non-reference test p value is less than 0.05, and the variable with the fold change of more than 1.5 is considered as the significant difference variable between groups and is screened as the ADHD potential diagnosis molecular marker.

And (3) performing secondary fragmentation on the screened differential variables, and selecting 20, 40, 60 or 80eV energy according to specific metabolites by adopting an HCD (high dilution fragmentation) fragmentation mode. Deconvoluting the secondary fragment by Progenetics QI software, searching HMDB (human METABOLOME DATABASE) database, and determining the structure of the differential metabolite.

7. Metabonomics analysis in urine to distinguish ADHD from healthy controls

The non-supervised Principal Component Analysis (PCA) score plot of the experimental group (training set) shows (fig. 1) that the ADHD group and the healthy control group exhibit a certain degree of discrimination in the direction of the horizontal axis, the ADHD samples are mainly gathered in the upper right corner, and the healthy controls are mainly in the lower left corner. Further, a supervised OPLS-DA was used to construct the model, with the two groups differentiated more clearly (fig. 2), mainly along the horizontal axis, ADHD mainly clustered on the left side, and healthy control samples mainly on the right side. The inventors screened 34 different metabolites. And further evaluating the prediction accuracy of the differential metabolites on the ADHD by using the ROC curve in the screened differential metabolites. As a result, the area under the curve (AUC) of FAPy-adenine (FAPy-adenine), 3-methylazelaic acid (3-methylazelaic acid) and phenylacetylglutamine (phenylacetylglutamine) metabolites (Table 1) is greater than 0.7, which indicates that the FAPy-adenine, the 3-methylazelaic acid and the phenylacetylglutamine have good prediction values. Compared with a normal healthy human control, the content of FAPy-adenine is reduced, and the content of 3-methyl azelaic acid and phenyl acetyl glutamine is increased.

Table 1: effect of three metabolites alone in ADHD diagnosis

Note: negative sign in fold change indicates down-regulation in the disease group, positive values represent up-regulation.

Studies have shown that the combined use of multiple metabolites may lead to a better diagnosis of disease. The inventor finally obtains that the combined diagnosis of the three metabolites can achieve better diagnosis effect by adopting a Logistic regression algorithm optimization model, and the area under the curve (AUC) value of the diagnosis of the three metabolites on ADHD is 0.946; the AUC value of ten-fold cross-validation (10-fold cross-validation) was 0.918 (FIG. 3), and the sensitivity (sensitivity) and specificity (specificity) are shown in Table 2. The effect of the combined diagnosis is clearly superior to that of the individual metabolites (table 1).

Table 2: area under ROC Curve (AUC), sensitivity and specificity for the diagnosis of ADHD by combination of three metabolites

Example 2 verification group

The inventor collects urine of 13 ADHD children and 17 healthy children, detects the content of FAPy-adenine, 3-methylazelaic acid and phenylacetylglutamine metabolites in a sample by a full-scanning mode through liquid chromatography-high resolution mass spectrometry (LC-MS), and evaluates the diagnosis effect of the three metabolite combinations on ADHD by adopting an ROC curve. The results showed that the AUC values for the three metabolite combinations diagnosis were 0.96 (95% CI, 0.82 to 1) (fig. 4), and further, it was confirmed that the three metabolites had good diagnostic effects.

Although the invention has been described in detail with respect to the general description and the specific embodiments thereof, it will be apparent to those skilled in the art that modifications and improvements can be made based on the invention. Accordingly, it is intended that all such modifications and alterations be included within the scope of this invention as defined in the appended claims.

Claims

1. Use of a set of metabolic markers comprising one or more of FAPy-adenine, 3-methylazelaic acid, phenylacetylglutamine for the manufacture of a product for the early screening and diagnosis of attention deficit hyperactivity disorder.

2. The use according to claim 1, wherein the metabolic marker is a FAPy-adenine, 3-methylazelaic acid, phenylacetylglutamine combined metabolic marker.

3. The use of claim 1, wherein said FAPy-adenine is present in a significantly reduced amount in a sample from a child suffering from attention deficit hyperactivity disorder, and wherein said 3-methylazelaic acid and phenylacetylglutamine are present in a significantly increased amount in a sample from a child suffering from attention deficit hyperactivity disorder, respectively, relative to a normal healthy child control.

4. The use of claim 3, wherein said sample comprises urine.

5. The use as claimed in any one of claims 1 to 3 wherein the step of screening and diagnosing attention deficit hyperactivity disorder using said metabolic markers comprises: (1) obtaining a urine sample of a subject; (2) detecting the amount of the one or more metabolic markers in the sample from the subject; (3) indicating that the subject has attention deficit hyperactivity disorder if the FAPy-adenine metabolic marker level is decreased and the 3-methylazelaic acid and phenylacetylglutamine metabolite levels are respectively increased, as compared to a healthy control.

6. The use of claim 5, wherein the means for detecting the amount of said one or more metabolic markers in the sample from the subject comprises mass spectrometry, nuclear magnetic resonance analysis, and enzymatic methods.

7. The use of claim 6, wherein the method of detecting the amount of said one or more metabolic markers in a sample from a subject is mass spectrometry, and said mass spectrometry is liquid chromatography-high resolution mass spectrometry.

8. The use of claim 7, wherein when mass spectrometry is used to determine metabolite content, the step of obtaining a urine sample is followed by a metabolite extraction, protein removal step.

9. The use of claim 1, wherein the early screening and diagnostic product comprises a diagnostic formulation, kit or chip.

10. A kit for early diagnosis of attention deficit hyperactivity disorder is characterized by comprising a reagent for detecting the content of FAPy-adenine, 3-methyl azelaic acid and phenylacetyl glutamine metabolism markers.