Application of oral microorganisms in diagnosis of severe depressive disorder with sleep disorder

Abstract

The invention discloses application of oral microorganisms in diagnosis of severe depressive disorder with sleep disorder, and belongs to the field of microbiomics and mental disease diagnosis. Specifically, the application comprises the application of the oral microorganism detection reagent in the preparation of the kit for diagnosing the severe depressive disorder with the sleep disorder, and the oral microorganisms comprise Solobacterium, Granulicatela, Campylobacter and Haemophilus. The invention further discloses the application of the oral microorganism detection reagent in the preparation of the kit for diagnosing the severe depressive disorder with the sleep disorder, and the oral microorganisms comprise Solobacterium, Granulicatela, Campylobacter and Haemophilus. Particularly, the Haemophilus has relatively high specificity and relatively excellent performance of a working characteristic curve (ROC) of a subject in diagnosis. The relative abundance of the bacteria is used as a biomarker for auxiliary diagnosis of MDD, and the capability of distinguishing depression from healthy people can be remarkably improved. The invention provides a new microecological approach for rapid and non-invasive diagnosis of depression diagnosis.

Description

Technical Field

[0001] The present invention relates to the fields of microbiomics and mental disease diagnosis, and particularly to the application of oral microorganisms in the diagnosis of major depressive disorder with sleep disorder. Background Art

[0002] Major Depressive Disorder (MDD) is a common and severe mental disease, and it is expected to become the leading cause of the global disease burden by 2030. Its main clinical features include persistent low mood, anhedonia, and prevalent sleep disorder. Research shows that about 60% to 90% of MDD patients are accompanied by sleep disorder to varying degrees, which is not only a significant clinical manifestation but also may be an important risk factor for the occurrence and development of MDD.

[0003] Currently, it is considered that MDD and sleep disorder may share a common biological basis, such as the dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis and the inflammatory response in the central nervous system (i.e., neuroinflammation). In recent years, research on the gut microbiota has revealed the important role of microbiota imbalance in depression and sleep disorder. Microorganisms deeply intervene in the host's neuropsychiatric state by synthesizing neurotransmitters (such as serotonin) and their metabolites, regulating inflammatory factors, and interfering with the endocrine axis. Stress state and circadian rhythm disorder can also, in turn, disrupt the microbiota homeostasis, triggering systemic inflammation and nerve dysfunction. However, so far, no single mechanism can fully explain the complex interaction between MDD and sleep disorder.

[0004] Clinically, the current treatment of MDD with sleep disorder mainly relies on drug interventions such as selective serotonin reuptake inhibitors (SSRIs), norepinephrine-serotonin reuptake inhibitors (SNRIs), or benzodiazepines. However, due to the significant individual differences in drug efficacy and the lack of objective efficacy evaluation indicators, there are great challenges in clinical practice.

[0005] On the other hand, as the second largest microbial ecosystem in the human body after the gut, the oral cavity has potential effects on regulating neuroimmune response, hormone levels, and central signal transduction. Existing research shows that the oral microbiota can intervene in the occurrence and development process of mood disorder by affecting salivary cortisol levels, C-reactive protein expression, and blood-brain barrier permeability. For example, depressive symptoms in adolescents are closely related to specific oral genera (such as Spirochaetaceae, Actinomyces, Treponema pallidum, and Fusobacterium), and animal studies have also found significant oral microecological imbalance in mice with depressive-like behavior. At the same time, there are also obvious differences in the oral microbiota composition and metabolic pathways between patients with obstructive sleep apnea syndrome (OSA) and healthy people.

[0006] Although the role of the oral microbiota in various brain dysfunctions has received increasing attention, there is currently no study systematically exploring its expression characteristics and mechanisms in depressive disorders accompanied by sleep disorders. The lack of specific, quantifiable, non-invasive, and specific microbial markers for this group remains an important bottleneck in the accurate diagnosis of current depressive disorders.

[0007] Therefore, there is an urgent need to explore the expression characteristics of oral microorganisms in patients with MDD accompanied by sleep disorders and their potential application value in disease diagnosis, providing a theoretical basis and technical support for the establishment of a more objective and quantifiable diagnostic tool. Summary of the Invention

[0008] In view of the deficiencies of the prior art, the present invention proposes the application of oral microorganisms in the diagnosis of major depressive disorder accompanied by sleep disorders.

[0009] The object of the present invention can be achieved by the following technical solutions:

[0010] In a first aspect of the present invention, it relates to the application of an oral microbiota detection reagent in the preparation of a kit for diagnosing major depressive disorder accompanied by sleep disorders, and the oral microbiota includes one or more of Solobacterium, Granulicatella, Campylobacter, and Haemophilus.

[0011] In a second aspect of the present invention, it relates to a kit for diagnosing major depressive disorder accompanied by sleep disorders, including an oral microbiota detection reagent, and the oral microbiota includes one or more of Solobacterium, Granulicatella, Campylobacter, and Haemophilus.

[0012] In a third aspect of the present invention, it relates to a diagnostic device for diagnosing major depressive disorder accompanied by sleep disorders, including:

[0013] a sample collection module for collecting an oral sample of a diagnostic object:

[0014] and a detection module for detecting the relative abundance of oral microbiota in the collected sample, and the oral microbiota includes one or more of Solobacterium, Granulicatella, Campylobacter, and Haemophilus.

[0015] Optionally, the sample collection module includes an oral microbiota DNA extraction kit.

[0016] Optionally, the detection module includes a microbiome detection kit based on 16S rRNA amplification and sequencing.

[0017] Optionally, the microbiome detection reagent based on 16S rRNA amplification and sequencing includes amplification primers: 338F and 806R, with nucleotide sequences ACTCCTACGGGAGGCAGCAG (SEQ ID NO.1) and GGACTACHVGGGTWTCTAAT (SEQ ID NO.2), respectively.

[0018] The composition includes a detection reagent for detecting the relative abundance of at least one target genus of oral microorganisms, and the target genus is selected from Solobacterium, Granulicatella, Campylobacter, and Haemophilus.

[0019] Among them, the increased relative abundance of Haemophilus is used as a diagnostic indicator for MDD, with an AUC value of 0.724 and a specificity of 89.47%.

[0020] A method for diagnosing depressive disorder using the relative abundance of oral genera includes collecting oral samples from a subject, detecting the relative abundances of Haemophilus, Campylobacter, Solobacterium, and Granulicatella genera, and determining whether there is a risk of MDD based on the expression patterns of at least one genus.

[0021] Advantages of the present invention:

[0022] 1. High non-invasiveness and repeatability: The present invention is based on oral sample collection, with the characteristics of simple operation and high subject compliance, and is suitable for large-scale clinical promotion and application;

[0023] 2. High specificity: There are significant differential expressions of specific genera in the oral cavity (Solobacterium, Granulicatella, Campylobacter

[0024] and Haemophilus) between MDD patients and healthy control groups, and the genus Haemophilus is significantly increased in MDD patients.

[0025] 3. Good diagnostic performance: ROC curve analysis shows that Haemophilus has good recognition ability, with AUC > 0.7; the other genera (Solobacterium, Campylobacter, Granulicatella) also have auxiliary diagnostic value with AUC > 0.6. Description of the Drawings

[0026] The present invention will be further described below with reference to the drawings.

[0027] Figure 1Abundance levels of four oral bacteria genera, Solobacterium, Granulicatella, Campylobacter, and Haemophilus, in MDD patients and healthy controls;

[0028] Figure 2 Schematic diagram of the diagnostic efficacy of four oral bacteria genera in identifying MDD patients with sleep disorders. Detailed implementation manners

[0029] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0030] I. Subject inclusion and grouping

[0031] A total of 68 subjects, including depression patients and healthy controls, were collected from the outpatient and inpatient departments of the psychiatry department. Among them, 38 were patients with major depressive disorder (MDD) who met the criteria of the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) and had definite sleep disorders, and 30 were healthy controls (HCs) without a history of mental disorders and with good sleep quality.

[0032] All MDD patients had not used any antidepressant drugs before sample collection, or had stopped taking drugs for more than four weeks. Exclusion criteria included: severe somatic diseases, organic lesions of the nervous system, pregnancy, lactation, and a history of obstructive sleep apnea, etc.

[0033] II. Sample collection and processing

[0034] All participants collected oral samples in the early morning. They were not allowed to eat, drink, or brush their teeth for at least 2 hours before sampling. The middle area of the dorsal tongue was gently scraped with a sterile cotton swab and immediately placed into a sterile centrifuge tube containing 1.5 mL of Tris-EDTA buffer and stored at -80 °C for further testing.

[0035] III. Extraction and amplification of oral microbiota DNA

[0036] Total DNA was extracted using a commercial oral microbial DNA extraction kit (Mabio, Guangzhou, China). The DNA concentration and integrity were evaluated by a NanoDrop spectrophotometer and 1% agarose gel electrophoresis.

[0037] The hypervariable regions V3-V4 of the bacterial 16S rRNA gene were amplified using a T100 thermal cycler (BIO-RAD, USA). The primer pair used was 338F (5'-ACTCCTACGGGAGGCAGCAG-3') and 806R (5'-GGACTACHVGGGTWTCTAAT-3'), and the primers were synthesized by Shanghai Sangon Biotech Co., Ltd. The PCR amplification products were purified, quantified, and mixed in equimolar amounts, and paired-end 300bp sequencing was performed using the Illumina NextSeq2000 platform.

[0038] IV. Sequence analysis and calculation of genus abundance

[0039] The original sequences were quality-controlled using the fastp software and assembled using the FLASH software. The optimized high-quality sequences were clustered into OTUs with 97% similarity, and species annotation was performed using the QIIME and SILVA databases. The relative abundances of each genus in each sample were finally obtained.

[0040] V. Biostatistics and evaluation of diagnostic models

[0041] The Mann-Whitney U test was used to compare the relative abundances of the target genera (Solobacterium, Granulicatella, Campylobacter, Haemophilus) in the MDD and HC groups. ROC curves were plotted to evaluate the efficacy of each genus in the auxiliary diagnosis of MDD.

[0042] VI. Application example of the diagnostic process

[0043] 1. Sampling: Dorsal tongue samples were collected after the subjects completed questionnaire assessments (such as HAMD-24, PSQI).

[0044] 2. Detection: DNA was extracted and 16S rRNA sequencing was performed.

[0045] 3. Judgment: If Haemophilus is significantly elevated, Campylobacter is elevated, and Solobacterium

[0046] and Granulicatella are decreased, it indicates a higher possibility of MDD.

[0047] Combined with the results of ROC curve analysis, the Youden index method (Youden Index = sensitivity + specificity - 1) was used to determine the optimal diagnostic ability cut-off point for each genus, as a reference for clinical auxiliary judgment. The diagnostic performance of each genus is as follows:

[0048] Haemophilus: AUC = 0.724, sensitivity is 56.67%, specificity is 89.47%, Youden index is 0.462, indicating that this genus shows the best performance in specific diagnosis.

[0049] Campylobacter: AUC = 0.637, sensitivity is 90.00%, specificity is 39.47%, Youden index is 0.295, and the diagnosis is biased towards high-sensitivity screening and is suitable for early risk warning.

[0050] Solobacterium: AUC = 0.658, sensitivity is 83.33%, specificity is 52.63%, Youden index is 0.359, and the diagnostic performance is medium, which can be used as a supplementary auxiliary index.

[0051] Granulicatella: AUC = 0.694, sensitivity is 70.00%, specificity is 73.68%, Youden index is 0.437, with both good sensitivity and specificity, and can be used in combination with Haemophilus to optimize the diagnostic model.

[0052] As Figure 1 shown, from the test results of patients with major depressive disorder with sleep disorder and healthy control group, it can be seen that the contents of Haemophilus, Campylobacter, Solobacterium and Granulicatella in the oral cavity are all different. Among them, the content of Haemophilus in the MDD group increased significantly, and the content of Granulicatella decreased significantly. Figure 1 The results imply that Haemophilus, Campylobacter, Solobacterium and Granulicatella can be applied to the diagnosis of patients with major depressive disorder with sleep disorder, and Haemophilus and Granulicatell have relatively greater application value.

[0053] As Figure 2 shown, the results show that in the MDD group: the contents of Haemophilus and Campylobacter increased significantly; the contents of Solobacterium and Granulicatella decreased significantly; among them, Haemophilus showed the best performance in the diagnosis of MDD with sleep disorder, with an AUC value of 0.724 and a specificity of 89.47%.

[0054] It should be noted that this application discloses that Haemophilus, Campylobacter, Solobacterium, and Granulicatella can be applied to the auxiliary diagnosis of major depressive disorder with sleep disorder. However, those skilled in the art should be aware that the above microbial abundance indicators of this application can also be combined with other known major depressive disorder diagnostic markers. Among them, the known biomarker can be a biological sample collected from a patient, such as peripheral blood. It can also be a depression diagnostic assessment scale. In short, after the microbial biomarker of this application is combined with the known major depressive disorder diagnostic marker, better accuracy and specificity can be obtained.

[0055] In the description of this specification, the description referring to terms such as "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0056] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art of this industry should understand that the present invention is not limited by the above embodiments. The above embodiments and the descriptions in the specification only illustrate the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed.

Claims

1. Use of an oral microbial detection reagent in the preparation of a kit for diagnosing major depressive disorder with sleep disorder, characterized in that, The oral microorganisms include one or more of Solobacterium, Granulicatella, Campylobacter, and Haemophilus.

2. Use of the oral microbiological detection reagent according to claim 1 in the preparation of a kit for diagnosing major depressive disorder with sleep disorder, characterized in that, The kit includes an oral microorganism DNA extraction reagent and a microbiome detection reagent based on 16S rRNA amplification and sequencing.

3. Use of the oral microbial detection reagent according to claim 2 in the preparation of a kit for diagnosing major depressive disorder with sleep disorder, characterized in that, The microbiome detection reagent based on 16S rRNA amplification and sequencing includes amplification primers: 338F and 806R, with nucleotide sequences ACTCCTACGGGAGGCAGCAG and GGACTACHVGGGTWTCTAAT respectively.

4. A kit for diagnosing major depressive disorder with sleep disorder, comprising oral microbiological detection reagents, and the oral microbiology includes: One or more of Solobacterium, Granulicatella, Campylobacter, and Haemophilus.

5. The kit for diagnosing major depressive disorder with sleep disorder according to claim 4, characterized in that, The kit includes an oral microorganism DNA extraction reagent and a microbiome detection reagent based on 16S rRNA amplification and sequencing.

6. The kit for diagnosing major depressive disorder with sleep disorder according to claim 5, wherein The microbiome detection reagent based on 16S rRNA amplification and sequencing includes amplification primers: 338F and 806R, with nucleotide sequences ACTCCTACGGGAGGCAGCAG and GGACTACHVGGGTWTCTAAT respectively.

7. A diagnostic device for diagnosing major depressive disorder with sleep disorder, comprising: A sample collection module that collects an oral sample of a diagnostic subject: And a detection module for detecting the relative abundance of oral microorganisms in the collected sample, wherein the oral microorganisms include; one or more of Solobacterium, Granulicatella, Campylobacter, and Haemophilus.

8. The diagnostic device for major depressive disorder with sleep disorder according to claim 7, wherein Comprising: The sample collection module includes an oral microorganism DNA extraction kit.

9. The diagnostic device for severe depressive disorder with sleep disorder according to claim 7, characterized in that, The detection module includes a microbiome detection kit based on 16S rRNA amplification and sequencing.

10. The diagnostic device for major depressive disorder with sleep disorder according to claim 9, characterized in that, The microbiome detection reagent based on 16S rRNA amplification and sequencing includes amplification primers: 338F and 806R, with nucleotide sequences ACTCCTACGGGAGGCAGCAG and GGACTACHVGGGTWTCTAAT respectively.

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