Differential diagnosis of bipolar versus unipolar disorder in patients during depressive phases using A-to-I RNA editing of the ZNF267 gene

Abstract

The present invention relates to a method for the differential diagnosis of bipolar versus unipolar disorder in a human patient during a depressive phase from a biological sample of the patient, comprising determining the relative proportions of RNA editing variants of at least the A-to-I-edited RNA ZNF267 gene. The present invention also relates to a method for monitoring the treatment of a depressed patient exhibiting bipolar or unipolar disorder. Finally, the present invention provides a kit for the differential diagnosis of bipolar versus unipolar disorder in a patient during a depressive phase.

Description

[Technical Field]

[0001] The present invention relates to a method for differentially diagnosing bipolar versus unipolar disorder in a human patient during a depressive phase, comprising determining the relative proportions of RNA editing variants of at least the A-to-I-edited RNA ZNF267 gene from a biological sample of the patient. The present invention also relates to a method for monitoring the treatment of a depressed patient exhibiting bipolar or unipolar disorder. Finally, the present invention provides a kit for differentially diagnosing bipolar versus unipolar disorder in a patient during a depressive phase.

[0002] Depression is one of the most common mental disorders, affecting nearly 10% of men and 20% of women worldwide, and is associated with a significant increase in mortality, primarily due to suicidal behavior. The Diagnostic and Statistical Manual of Mental Disorders characterizes a major depressive episode using a combination of five or more distinct symptoms, such as depressed mood, anhedonia, sleep dysregulation, fatigue, or indecisiveness. Among mood disorders, bipolar disorder (BD) is one of the most frequent and disabling, affecting 1% of the world's population. It is characterized by manic and hypomanic episodes and alternating or intertwined depressive episodes. In primary care clinics, 21% of patients treated for depression screened positive for BD, and two-thirds of them were never diagnosed with bipolar disorder. In fact, Judd et al. showed that patients were manic or hypomanic less than 10% of the time and were symptom-free approximately half the time, meaning they were depressed 40% of the time. [1] As a result, the average interval between the onset of BD symptoms and appropriate diagnosis is estimated to be approximately 7 years, delaying appropriate treatment and care management and increasing the risk of suicide. Various clinical interview-based instruments, including assessment of manic symptoms with the Young Mania Rating Scale (YMRS), Altman Self-Rating Scale (ASRM), or Mood Disorder Questionnaire (MDQ), are available and routinely used by psychiatrists to diagnose BD. Biological markers for demarcating different subtypes of depression are lacking, and a major research goal is to identify reliable and clinically useful biomarkers for distinguishing BD from unipolar depression.

[0003] Recent studies have demonstrated a link between depression and RNA alterations mediated by epitranscriptomic mechanisms [2], including RNA methylation [3], microRNAs [4], and RNA editing [5-7]. One of the most studied processes occurring at the RNA level is the conversion of adenosine (A) to inosine (I), mediated by ADARs (Adenosine deaminase acting on RNA), which bind to the stem-loop of double-stranded RNA (dsRNA) and modify A to I by deamination. Due to their similar chemical characteristics, inosine is interpreted as guanosine by the cellular machinery. Therefore, RNA editing can induce single amino acid substitutions in coding regions, leading to new start or stop codons or splice site modifications. Furthermore, it can affect RNA stability by modifying untranslated regions (UTRs) and can also influence the formation of various microRNA isoforms. Significant differences in RNA editing have already been reported in neurological or immunological disorders, among other pathologies. In the central nervous system (CNS), RNA editing has been found to alter ion channel permeability and response to excitatory neurotransmitters. Recently, we identified modifications in mRNA editing of 5-HTR2c (5-hydroxytryptamine receptor 2c) [8] and PDE8A (phosphodiesterase 8A) [9] in the anterior cingulate cortex (Brodmann area 24) of depressed suicide victims. Interestingly, phosphodiesterase, a key modulator of downstream signaling of 5-HTR2c, is involved in inflammatory cell activation, memory, and cognition. The diagnostic value of PDE8A mRNA editing in depression has also been demonstrated in blood from HCV patients treated with interferon-α

[10] and blood from depressed patients and suicide attempters compared with age- and sex-matched healthy controls

[11] .

[0004] More recently, Salvetat et al.

[12] described a study focusing on transcriptome-wide RNA editing modifications detected by RNA sequencing (RNA-Seq) to identify novel genes with differential A-to-I RNA editing in blood samples from depressed patients compared with healthy controls (n = 57, discovery cohort). The diagnostic potential of this panel of edited RNAs was validated by ultra-deep next-generation sequencing (NGS) on 410 samples (validation cohort) from either healthy controls (n = 143) or depressed patients (n = 267). By dichotomizing depressed patients into unipolar (n = 160) or bipolar (n = 95) patients, the same approach was applied to identify specific RNA editing sites or RNA editing isoforms (called biomarkers) on specific RNA sequences (gene targets). The diagnostic performance of these combinations was evaluated using a machine learning approach to distinguish between unipolar and BD patients (see also WO 2021 / 089865 and WO 2021 / 089866, published May 14, 2021).

[0005] The current COVID-19 pandemic has forced people into lockdown, the demographic and social impacts of which are still being assessed. Health restrictions have already taken a toll on the psychiatric field, with anxiety and depression rising sharply. Indeed, recent studies have shown a significant increase in the prevalence of depression since the COVID pandemic began [13, 14]. Furthermore, the spread and significant mortality of COVID-19 may exacerbate the risk of mental health problems and intensify existing psychiatric symptoms in certain individuals at risk for anxiety, depression, stress, and violence.

[0006] It is an object of the present invention to overcome at least one drawback of the prior art. It is a further object of the present invention to provide an improved method for the analysis of molecular biomarkers as a diagnostic, prognostic and / or predictive aid in the management of depressed patients. It is a further object of the present invention to provide an improved, highly sensitive and robust method that allows for earlier differential diagnosis of bipolar versus unipolar disorders in patients during depression, and optionally allows for reliable prediction of treatment resistance or response, improving the likelihood of treatment success.

[0007] Therefore, the need for reliable and accurate differential diagnosis to enable appropriate treatment of these conditions will become crucial in the coming years.

[0008] Strikingly, zinc finger protein 267 (ZNF267) has been identified as an A to I RNA biomarker, exhibiting two major variant types (A-to-G and T-to-C variants) and presenting sites whose editing may differ specifically between unipolar and bipolar disorder, controls versus depression, and controls versus bipolar disorder (see Table 1).

[0009] The inventors have also demonstrated that using these specific ZNF267 RNA editing sites, isoforms, and first patterns, or combinations thereof, preferably in combination / association with other A to I edited RNA genes of interest such as GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA, and PRKCB genes, high diagnostic performance (AUC ROC curve, sensitivity and specificity) was obtained in an internal validation cohort (study) and, for the first time, an independent cohort (external validation cohort / replication study) for the differential diagnosis of bipolar vs. unipolar patients during depressive phases.

[0010] Zinc finger protein 267 (ZNF267) is a member of the Kruppel-like transcription factor family, which regulates various biological processes, including cell proliferation and differentiation. It was first characterized as a transcriptional repressor of MMP-10, which is upregulated during the activation process of human hepatic stellate cells

[15] . Zinc finger protein 267 is upregulated in hepatocellular carcinoma and is induced by reactive oxygen species (ROS). Loss- and gain-of-function analyses have revealed that ZNF267 promotes tumor cell proliferation and HCC cell migration in vitro

[16] . Similarly, ZNF267 expression was found to be significantly upregulated in tissue specimens from patients with nonalcoholic fatty liver disease (NAFLD) compared with normal liver tissue. Incubation of primary human hepatocytes with palmitic acid induced ZNF267 in a dose-dependent manner in vitro, which correlated with lipid accumulation and ROS formation

[17] . A similar oncogenic role for ZNF267 has been suggested in acute lymphoblastic lymphoma (ALL) and has been shown to be regulated by miRNA-23a / b

[18] . ZNF267 has been found to be hypomethylated in patients with osteoporosis, but its role in bone metabolism remains unknown

[19] . ZNF267 has also been reported to be significantly upregulated during amyloid processing and inflammation

[20] , and ZNF267 has previously been associated with dementia. ZNF267 was selected as one of the 10 most predictive genes used in a blood-based transcriptome panel for AD diagnosis

[21] . Recently, ZNF267 has been shown to be a key transcription factor in the pathogenesis of cognitive impairment and neuroinflammation, produced by 1,2-diacetylbenzene (DAB) and targeted by curcumin

[22] .

[0011] This is the object of the present invention.

[0012] These objects have been solved by the aspects of the present invention specified below.

[0013] In a first aspect, the present invention provides a method for analyzing expression of a biomarker RNA molecule, comprising: A. isolating RNA from a blood sample obtained from the subject, determining the expression of at least one biomarker RNA molecule in the isolated RNA, and providing an expression profile based on the results, wherein the biomarker is the relative rate of RNA editing at at least a given editing site and / or isoform and / or pattern, or a combination of a given site and / or isoform and / or pattern, that may be edited on the ZNF267 gene; B. From the same isolated RNA, determining the expression of at least one additional biomarker RNA molecule in the isolated RNA and providing an expression profile based on the results, wherein the biomarker is the relative proportion of RNA editing at at least a given editing site and / or isoform and / or pattern, or a combination of a given site and / or isoform and / or pattern, that may be edited on another A to I edited RNA gene; C. performing a combined analysis of the results using the expression profiles determined in steps A and B.

[0014] In a preferred embodiment of the method, in step B, the additional A-to-I-edited RNA gene is selected from the group of A-to-I-edited RNA genes consisting of GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA, and PRKCB A-to-I-edited RNA genes.

[0015] In a also preferred embodiment of the method, in step A, the blood sample is taken from the patient during a depressive phase, preferably during a moderate or severe depressive phase.

[0016] In a also preferred embodiment of the present invention, a combined analysis of the results is provided, in which the expression profiles determined in steps A and B of the method of the present invention are used to obtain valuable information that allows for the differential diagnosis of bipolar versus unipolar disorder in patients during depression, preferably during a moderate or severe depressive phase of the patient.

[0017] As demonstrated by the examples, the combined analysis of the expression profiles of biomarkers of the A-to-I-edited RNA genes improves the prognostic and predictive value of the results obtained and can provide valuable diagnostic, prognostic and / or predictive information, in particular for the differential diagnosis of bipolar versus unipolar disorder in patients during depression, preferably during a moderate or severe depressive phase of the patient.

[0018] Thus, the in vitro method of the present invention can be used as an improved diagnostic, prognostic and / or predictive aid in the management of depressed patients, not only to support diagnosis, prognosis, but also to select the most appropriate treatment for depressed patients.

[0019] In a second aspect, the present invention relates to a method for the in vitro differential diagnosis of bipolar versus unipolar disorder in patients during a depressive phase, preferably in patients during a moderate or severe depressive phase, comprising determining in a patient sample the relative rates of RNA editing at at least a given editing site and / or isoform and / or pattern, or a combination of given sites and / or isoforms and / or patterns, that may be edited on the ZNF267 gene.

[0020] By definition, the relative proportion of RNA editing at a given editing "site" represents the sum of the editing modifications measured at this unique genomic coordinate. Conversely, edited mRNA isoforms are unique molecules that may or may not contain multiple editing modifications on the same transcript. For example, for a given transcript, edited mRNA isoform BC contains A-to-I modifications at both site B and site C within the same transcript. An editing pattern is one combination of editing events that occur at target sites in a transcript. By definition, given a list of target sites, a transcript has as many editing patterns as possible combinations. For example, for a given transcript with target sites ABC, the pattern analyzed is [A, B, C, AB, BC, AC, ABC].

[0021] The term "biomarker" refers to an editing site or isoform or pattern of RNA that contains one or more positions that are differentially edited, particularly in the comparison of bipolar versus unipolar disorder.

[0022] In a preferred embodiment, the method comprises at least determining in a patient sample at least the relative proportion of RNA editing of a given pattern or combination of patterns that may be edited on the ZNF267 gene.

[0023] In a preferred embodiment, the method of the invention further comprises determining the relative rates of RNA editing at at least a given editing site and / or isoform and / or pattern, or a combination of given sites and / or isoforms and / or patterns, that may be edited on another A-to-I-edited RNA gene selected from the group comprising the A-to-I-edited RNAs of GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA, and PRKCB, more preferably on at least two, three, four, five, or six of these genes.

[0024] Also in a preferred embodiment, the method comprises determining at least the relative proportion of RNA editing of a given pattern or combination of patterns that may be edited on the A-to-I-edited RNA genes of GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA or PRKCB in a patient sample.

[0025] More preferably, in the methods of the invention, the determination of the relative proportions of RNA editing at a given editing site and / or isoform and / or pattern, or a combination of a given site and / or isoform and / or pattern, on the A-to-I ZNF267 gene and on an A-to-I-edited RNA gene selected from the group comprising the A-to-I-edited RNA genes of GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA and PRKCB is performed on the same patient sample.

[0026] In a preferred embodiment, the method of the present invention further comprised determining the relative rates of RNA editing at a given editing site, and / or isoform, and / or pattern, or combination of a given site, and / or isoform, and / or pattern, that may be edited on the A-to-I-edited RNA genes of GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA, and PRKCB.

[0027] In a preferred embodiment, PCR products of the gene regions of interest of selected A-to-I edited RNA biomarkers are sequenced by NGS.

[0028] In a preferred embodiment, the primer pair used to obtain a PCR product of the ZNF267 gene of interest is: ZNF267 MPx_F2 GGCTGAGGTGGTCTTGGATG (SEQ ID NO: 1) ZNF267 MPx_R1 CCTCGCCTTCCACTGTGATT (SEQ ID NO: 2) (See Table 2).

[0029] In a preferred embodiment, the primer pairs used to obtain PCR products of the GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA and PRKCB genes of interest are listed in Table 7.

[0030] In a preferred embodiment, the method can also be used for the in vitro diagnosis of bipolar disorder in moderately or severely depressed patients.

[0031] In another preferred embodiment, the method can be used for the in vitro diagnosis of unipolar depression in moderately or severely depressed patients.

[0032] In another preferred embodiment, the method is a method for the in vitro diagnosis of bipolar versus unipolar patients.

[0033] The criteria for bipolar disorder, depressive disorder, moderate or severe depression, and MDD are well known to those skilled in the art and are described, for example, in the American Psychiatric Association's DSM-5™ book (2013, DSM-V, pp. 123-154).

[0034] The diagnoses included in this chapter are bipolar I disorder, bipolar II disorder, cyclothymic disorder, substance / medication-induced bipolar disorder and related disorders, bipolar disorder and related disorders due to another medical condition, other specified bipolar disorder and related disorders, and bipolar disorder and related disorders not otherwise specified. However, the majority of individuals whose symptoms meet the criteria for a fully symptomatic manic episode also experience major depressive episodes over the course of their lives. Bipolar II disorder is no longer considered a "milder" condition than bipolar I disorder because it requires the lifetime experience of at least one major depressive episode and at least one hypomanic episode, and because individuals with this condition experience longer periods of depression and the mood instability experienced by individuals with bipolar II disorder is typically accompanied by severe impairments in work and social functioning. A diagnosis of cyclothymic disorder is made in adults who experience periods of both hypomania and depression for at least two years (one full year for children) without ever meeting the criteria for a manic, hypomanic, or major depressive episode.

[0035] Criteria symptoms of unipolar depression are also well known to those skilled in the art and are described, for example, in the American Psychiatric Association's DSM-5™ book (2013, pp. 155-188). Depressive disorders include major mood dysregulation disorder, major depressive disorder (including major depressive episodes), persistent depressive disorder (dysthymia), premenstrual dysphoric disorder, substance / medication-induced depressive disorder, depressive disorder due to another medical condition, other specified depressive disorder, and unspecified depressive disorder.

[0036] In another aspect of the present invention, there is provided a method for in vitro differential diagnosis of bipolar versus unipolar disorder in a patient during a depressive phase of the present invention, comprising: a) determining in a sample from a patient being tested the relative proportion of RNA editing at at least a given editing site and / or isoform and / or pattern, or a combination of given sites and / or isoforms and / or patterns, that may be edited on the ZNF267 mRNA gene and optionally on at least another one of the A-to-I edited mRNA genes of GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA and PRKCB, preferably 2, 3, 4, 5, 6 or 7 of these genes; b) determining the value obtained from the ratio obtained in step a); c) comparing the result value obtained in step b) with control values ​​obtained for bipolar and / or unipolar patients and then classifying the patient as bipolar or unipolar, wherein the control values ​​have been determined in a manner comparable to that of the result value obtained in step b).

[0037] In a preferred embodiment, in step c) of the method of the present invention, The result value obtained for the patient being tested is compared to a threshold value (e.g., but not limited to, a cutoff or probability) associated with the disorder desired to be identified, and if the result value is approximately the selected threshold value, the patient is classified as a bipolar or unipolar patient according to the selected threshold value.

[0038] In a preferred embodiment, the patient sample is a biological sample, preferably blood, serum, urine, saliva, tears or plasma, more preferably a blood sample, serum, even more preferably the patient sample is a blood sample, even more preferably a whole blood sample.

[0039] In yet another preferred embodiment of the present invention, the method is carried out in vitro or ex vivo.

[0040] For example, but not limited to, in the differential diagnosis method of the present invention, the threshold, cutoff, or probability may be, but is not limited to: It may be a Z-score calculated for unipolar or bipolar patients during a depressive phase for a study cohort.

[0041] As used herein, the terms gene or target have the same meaning and can be used interchangeably.

[0042] In a preferred embodiment, in the in vitro method for differential diagnosis of bipolar versus unipolar patients during a depressive phase of the present invention, a combination of at least two biomarkers is determined to be statistically significant between patients with bipolar or unipolar disorder, e.g., a p-value <10 -4 is selected for whether

[0043] Also preferred is an in vitro method for differential diagnosis of bipolar versus unipolar patients during a depressive phase according to the invention, wherein in step b) the result value is calculated by an algorithm implementing a multivariate method, said algorithm comprising: The mROC program, in particular, identifies linear combinations that maximize the AUC (area under the curve) ROC, and provides the equation for each combination, which can be used as a new virtual marker Z as follows: Z = a (biomarker 1) + b (biomarker 2) + i (biomarker i) + n (biomarker n) where i is the calculated coefficient and (biomarker i) is the level of the biomarker being considered (i.e., the level of the RNA editing site or isoform for a given target / biomarker), an mROC program, and / or A random forest (RF) approach is applied to evaluate combinations of RNA editing sites and / or isoforms, in particular to rank the importance of RNA editing sites and / or isoforms and to combine the best RNA editing sites and / or isoforms, and / or optionally Multivariate analysis can be applied to evaluate combinations of RNA editing sites and / or isoforms for diagnosis, and the multivariate analysis can include, for example, Logistic regression models applied to univariate and multivariate analyses to estimate the relative risk of patients with different levels of RNA editing site or isoform values. A CART (Classification and Regression Tree) approach applied to evaluate combinations of RNA editing sites and / or isoforms; and / or Support Vector Machine (SVM) approach, Artificial Neural Network (ANN) approach, Bayesian network approach, WKNN (weighted k nearest neighbor) approach, Partial least squares discriminant analysis (PLS-DA), Linear and Quadratic Discriminant Analysis (LDA / QDA), and Extra Tree Algorithm (8), Any other mathematical method of combining biomarkers.

[0044] Preferably, the result value is calculated by an extra-tree algorithm.

[0045] It is preferred to select additional biomarkers (in addition to the ZNF267 biomarker) whose result value in step b) is statistically / specifically different from the control result value obtained at p<0.05.

[0046] Also, the biomarker or combination of biomarkers selected in step a) meets the following criteria: Coverage > 30, AUC>0.6, more preferably AUC>0.8, even more preferably AUC>0.890; 0.95 > Fold Change > 1.05, and The method of the present invention is preferred, provided that p<0.05 is satisfied.

[0047] Also preferred is a method of the invention, wherein the algorithm or formula allowing the calculation of the result value or depression score Z is selected from the Z formulas listed in the examples, preferably wherein the formula implements the A to I edited RNA biomarker combination of the following eight biomarkers: ZNF267, GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA and PR KCB.

[0048] Also preferred is a method of the invention, wherein in step a) the relative proportion of RNA editing in a given editing and / or isoform is measured in said biological sample by NGS.

[0049] Also preferred is a method of the invention, wherein in step a) the amplicon / nucleic acid sequence used for detecting the RNA editing site and / or RNA transcript isoform of the biomarker in question is obtained or obtainable using the set of primers listed in Table 2 and Table 7 for each of the selected biomarkers.

[0050] According to another aspect, there is provided a method for determining the effectiveness of a treatment in a subject or for predicting or monitoring a response to a treatment in a patient, comprising: I. Analyzing the expression of biomarker RNA molecules according to the methods of the invention before and / or during and / or after treatment of the patient; II. performing a combined analysis of the results using the determined expression profile.

[0051] In another aspect, the present invention provides a method for monitoring treatment of bipolar or unipolar disorder in a human patient during a depressive phase from a biological sample from the patient, comprising: A) differentially diagnosing bipolar versus unipolar disorder in said human by the methods of the invention prior to initiation of treatment for which monitoring is desired; B) repeating steps (a) through (c) of the method after a period during which the patient has received the desired treatment for the diagnosed bipolar or unipolar disorder to obtain a post-treatment outcome value; C) comparing the post-treatment outcome value from step (c) with the outcome value obtained before treatment.

[0052] In another aspect, the present invention provides a method for determining from a biological sample whether a patient during a depressive phase is a responder to a treatment for a bipolar disorder that can bring the patient into a state of manic-depressive remission (a state of normal mood), comprising: A) differentially diagnosing bipolar versus unipolar disorder in said human by the methods of the invention prior to initiation of treatment for which monitoring is desired; B) repeating steps (a) through (c) of the method of the invention after a period during which the patient has received the desired treatment for the diagnosed bipolar or unipolar disorder to obtain a post-treatment outcome value; C) The post-treatment outcome values ​​from step (c), Outcome values ​​obtained before treatment, and compared with known or obtained outcome values ​​for control patients with bipolar or unipolar disorder in manic-depressive remission, classifying the patient as a responder to treatment if the post-treatment outcome value obtained in step B) is closer to the outcome value for the bipolar remission state than the outcome value obtained before treatment.

[0053] In another aspect, the present invention provides a kit for the differential diagnosis of bipolar versus unipolar disorder in a human patient during a moderate or severe depressive phase, comprising: 1) optionally, instructions for applying the method for the differential diagnosis of bipolar versus unipolar disorder in a human patient during a depressive phase to obtain a result value, the analysis of which determines whether the depressed patient exhibits bipolar disorder or unipolar disorder; and 2) a) a primer pair having the sequences of SEQ ID NOs: 1 and 2, and b) A kit comprising at least one pair, preferably two, three, four, five, six or seven pairs of primers selected from the group of primer pairs having the sequences of SEQ ID NOs: 3 and 4, 5 and 6, 7 and 8, 9 and 10, 11 and 12, 13 and 14, and 15 and 16, more preferably seven pairs of primers having the sequences of SEQ ID NOs: 3 and 4, 5 and 6, 7 and 8, 9 and 10, 11 and 12, 13 and 14, and 15 and 16.

[0054] In a preferred embodiment, the present invention provides a kit for the differential diagnosis of bipolar versus unipolar disorder in a human patient during a moderate or severe depressive phase, comprising: 1) optionally, instructions for applying the method for the differential diagnosis of bipolar versus unipolar disorder in a human patient during a depressive phase to obtain a result value, the analysis of which determines whether the depressed patient exhibits bipolar disorder or unipolar disorder; and 2) a) a primer pair that includes an amplicon obtainable by a primer pair having the sequences of SEQ ID NOs: 1 and 2, or that can obtain an amplicon identical thereto; and b) A kit comprising at least one, preferably two, three, four, five, six or seven pairs of primers comprising an amplicon obtainable by a primer pair selected from the group of primer pairs having the sequences SEQ ID NOs: 3 and 4, 5 and 6, 7 and 8, 9 and 10, 11 and 12, 13 and 14, and 15 and 16, or capable of obtaining an amplicon identical thereto, preferably seven amplicons obtainable by seven pairs of primers having the sequences SEQ ID NOs: 3 and 4, 5 and 6, 7 and 8, 9 and 10, 11 and 12, 13 and 14, and 15 and 16, or seven pairs of primers capable of obtaining seven amplicons identical thereto.

[0055] In another preferred embodiment, the present invention provides a kit for the differential diagnosis of bipolar versus unipolar disorder in a human patient during a moderate or severe depressive phase, comprising: 1) optionally, instructions for applying the method for the differential diagnosis of bipolar versus unipolar disorder in a human patient during a depressive phase to obtain a result value, the analysis of which determines whether the depressed patient exhibits bipolar disorder or unipolar disorder; and 2) a) a primer pair capable of obtaining an amplicon containing at least all given editing sites and / or isoforms that can be edited on the ZNF267 mRNA gene, wherein each primer of the pair has a length of less than 40, preferably 35, 30 or 25 nucleotides, and comprises at least 10, preferably 12 or 15 consecutive nucleotides of the primers having the sequences of SEQ ID NOs: 1 and 2; and b) comprising at least one pair of primers, preferably 2, 3, 4, 5, 6 or 7 pairs of primers capable of obtaining an amplicon comprising at least all given editing sites and / or isoforms that can be edited on an mRNA gene selected from the group consisting of IFNAR1, LYN, PRKCB, MDM2, GAB2, IL17RA and PTPRC mRNA genes, wherein for each selected mRNA gene, the corresponding pair of primers has a length of less than 40, preferably 35, 30 or 25 nucleotides, and comprises at least 10, preferably 12 or 15 consecutive nucleotides of paired primers having the sequences of SEQ ID NOs: 3 and 4, 5 and 6, 7 and 8, 9 and 10, 11 and 12, 13 and 14, and 15 and 16; Preferably, the kit comprises seven pairs of primers capable of obtaining seven amplicons for each amplicon, the seven amplicons comprising at least all given editing sites and / or isoforms that can be edited on the corresponding mRNA gene, wherein the primers of the seven pairs of primers have a length of less than 40, preferably 35, 30 or 25 nucleotides, and comprise at least 10, preferably 12 or 15 consecutive nucleotides of corresponding pairs of primers having the sequences of SEQ ID NOs: 3 and 4, 5 and 6, 7 and 8, 9 and 10, 11 and 12, 13 and 14, and 15 and 16.

[0056] The following examples and the figures and legends below have been chosen to provide a complete description to those skilled in the art to enable them to make and use the invention. These examples are not intended to limit the scope of what the inventors regard as their invention, nor are they intended to represent that only the experiments described below were performed.

[0057] Other features and advantages of the present invention will become apparent in the remainder of the description, using the examples, figures and tables whose legends are set forth below. [Brief explanation of the drawings]

[0058] [Figure 1] STARD flow diagram for Montpellier participants (Studies 1 and 2). [Figure 2] STARD flow diagram for LesToises participants (Study 3). [Figure 3A] Overview of our AI RNA editing analysis: A) Overview of the workflow for RNA-Seq and editome analysis, B) Overview of the bioinformatics workflow for targeted next-generation sequencing. [Figure 3B] Overview of our AI RNA editing analysis: A) Overview of the workflow for RNA-Seq and editome analysis, B) Overview of the bioinformatics workflow for targeted next-generation sequencing. [Figure 4] Receiver operating characteristic curves and diagnostic performance for bipolar depression in both studies for model #154. [Figure 5]Receiver operating characteristic curves and diagnostic performance for bipolar depression in both studies for model #284. The probability of correct responses for the tested set is plotted using a case-specific trained random forest model (Extra-Trees model #284). The test dataset for Study 2 included 70 patients from the unipolar group and 28 from the bipolar group. The replication dataset for Study 3 included 67 patients from the unipolar group and 28 from the bipolar group. The number of targets used was 8 (GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA, ZNF267, and PRKCB), and the number of RNA editing variants used was 22 (Extra-Trees model #284). [Figure 6] It is an artificial intelligence procedure.

[0059] Example 1: Cohort 1.1. Subjects and Clinical Evaluation Study 1 (Exploratory, CHU Montpellier, France) Depressed patients (DEP) were recruited among outpatients at the Emergency Psychiatry and Post-Emergency Care (CHRU of Montpellier) in accordance with the principles of the 1975 Declaration of Helsinki and its subsequent updates, from September 2016 to January 2019. The study was approved by the French local ethics committee (CPP Sud-Mantel IV in Mediterranee, CPP No. A01978-41) and registered under the reference identification number NCT02855918.

[0060] The first exploratory cohort (n = 57) of patients with depression (n = 26) and controls (n = 31) was used for RNA-Seq experiments and biomarker discovery. Of the depressed patients, 12 were bipolar.

[0061] Study 2 (Validation, Montpellier University Hospital, France) A second validation cohort of 245 Caucasian depressed patients (155 unipolar and 90 bipolar) was recruited from outpatient settings in the emergency psychiatry and post-acute care department (Montpellier Regional University Hospital, Clinicaltrials.gov identification number: NCT02855918). The study was approved by the French local ethics committee (CPP Sud-Mantel IV in Mediterranee, CPP No. A01978-41). All participants, aged 18 to 65 years, understood and signed written informed consent before participating in the study. Diagnoses of unipolar depression and bipolar disorder were made by psychiatrists. During a standardized interview, psychiatrists scored depression using the French version of the Montgomery-Asberg Depression Rating Scale (MADRS) and the 30-item Inventory of Depressive Symptomatology, Clinician Rated (IDS-C30). The severity levels of depression, i.e., mild, moderate, and severe, were defined by 7 ≤ MADRS ≤ 19 and / or 12 ≤ IDSC-30 ≤ 23, 20 ≤ MADRS ≤ 34 and / or 24 ≤ IDSC-30 ≤ 36, and MADRS ≥ 35 and / or IDSC-30 ≥ 37, respectively. Manic symptoms were assessed using the Young Mania Rating Scale (YMRS). The presence of bipolar disorder was assessed by the clinician's expertise. All patients received treatments classified into these five categories: anxiolytics, hypnotics and sedatives, antidepressants, antipsychotics, and antiepileptics. A complete flow diagram of patients through the study is shown in Figure 1 (Figure 1: STARD Flow Diagram of Montpellier Participants (Studies 1 and 2)).

[0062] Study 3 (Replication, Les Toises Center, Switzerland) A second cohort of 94 Caucasian depressed patients (67 unipolar and 28 bipolar) was recruited at the Les Toises-Psychiatry and psychotherapy center in Lausanne, Switzerland.

[0063] All participants aged 18 years or older understood and signed written informed consent before participating in the study. Diagnoses of unipolar depression and bipolar disorder were made by psychiatrists. Depression severity levels, i.e., mild, moderate, and severe, were defined by a MADRS score of 7 ≤ ≤ 19, 20 ≤ ≤ 34, and MADRS ≥ 35, respectively. Manic symptoms were assessed using the Young Mania Rating Scale (YMRS). The presence of bipolar disorder was assessed by the clinician's expertise. All patients received treatments classified into five categories: anxiolytics, hypnotics and sedatives, antidepressants, antipsychotics, and antiepileptics. A complete flow diagram of patients through the study is shown in Figure 2 (Figure 2: STARD Flow Diagram of LesToises Participants (Study 3)).

[0064] 1.2.Inclusion criteria Tests 1 and 2 All subjects must meet the following inclusion criteria: For those aged 18-65 Subjects who signed informed consent Understand the nature, purpose and methodology of testing Able to understand and perform clinical and neuropsychological assessments. Subjects whose primary psychiatric diagnosis is a major depressive episode according to DSM-5 criteria (the presence of psychiatric comorbidity is not an exclusion criterion). A woman who is not pregnant.

[0065] Test 3 All subjects must meet the following inclusion criteria: For ages 18 and over Subjects who signed informed consent Understand the nature, purpose and methodology of testing Able to understand and perform clinical and neuropsychological assessments. Subjects with a history of harmful substance use will not be considered. Subjects whose primary psychiatric diagnosis is a major depressive episode according to DSM-5 criteria (the presence of psychiatric comorbidity is not an exclusion criterion).

[0066] We chose to include only patients with moderate and severe levels of depression severity (MADRS>20 and / or IDSC-30>24) in both studies to avoid "borderline" patients, e.g., patients with low depression scores or patients defined as depressed on one depression scale and healthy on the other.

[0067] 1.3. Biological Samples Patients enrolled in both studies received blood samples including a standard laboratory test (complete blood count) and two whole blood samples in PAXgene tubes™ to allow for extraction of total RNA from blood cells and measurement of targeted RNA editing.

[0068] Example 2: Methodological approach This description of process analysis is described in detail below and in Salvetat et al., Translational Psychiatry (2022) 12:182

[12] .

[0069] 2.1. RNA Extraction and Qualification from Whole Blood Samples were collected in PAXgene™ Blood RNA tubes, randomly distributed among different extraction sets, and isolated using a MagNA Pure 96 instrument (Roche) (Life Sciences) according to the manufacturer's protocol. Total RNA concentration and quality level were determined using a Qubit fluorometer (Invitrogen) and a LabChip (PerkinElmer, HT RNA Reagent Kit) instrument, respectively.

[0070] 2.2. Library preparation for RNA sequencing in the discovery cohort For RNA-Seq libraries, we used the TruSeq Stranded Total RNA Library Kit (Illumina), specifically adapted for blood samples, according to the manufacturer's instructions. Briefly, 300 ng of total RNA was depleted of rRNA and globin mRNA (Ribo-Zero Globin), purified, and fragmented to an average of 250 bp. First-strand cDNA was synthesized using Superscript II reverse transcriptase (Thermo Fisher Scientific, random primers), and second-strand cDNA was synthesized using DNA polymerase I and RNase H (UTP incorporation). DNA fragments were selectively enriched to obtain libraries, which were then normalized, denatured (0.1 M NaOH), and sequenced on an Illumina NextSeq 500 (high throughput, 2 × 75 bp read length). Approximately 70 million reads were obtained per sample.

[0071] 2.3. Targeted Next-Generation Sequencing Library Preparation and Sequencing The region of interest for each gene was amplified using validated primers in a Peqstar 96x thermocycler with Q5 Hot Start High Fidelity enzyme (New England Biolabs) according to the manufacturer's guidelines. Amplicon purity was determined using a nucleic acid analyzer (LabChipGx, PerkinElmer), and PCR products were quantified using the fluorescence-based Qubit method (ThermoFisher Scientific) to confirm quality control. PCR products were purified with magnetic beads (High Prep PCR MAGbio system, Mokascience) and then quantified (Qubit system) to calculate purification yield. After indexing the samples (Q5 Hot Start High Fidelity PCR enzyme, Illumina Nextera XT Index Kit), they were pooled and purified (Magbio PCR cleanup system). The resulting libraries were denatured (0.1 M NaOH), spiked with PhiX Control V3 (Illumina), loaded onto sequencing cartridges (Illumina MiSeq Reagent Kit V3 or Illumina NextSeq 500 / 550 Mid-Output) according to Illumina guidelines, and sequenced at standard density using ultra-deep sequencing (1 × 150 bp read length). Approximately 1 million reads were obtained per sample.

[0072] 2.4. Bioinformatics analysis of A-to-I RNA editome data Paired-end reads generated by an Illumina NextSeq 500 were demultiplexed using bcl2fastq (version 2.17.1.14, Illumina). Sequencing quality control was performed using FastQC (version 0.11.7) and MultiQC software. Identification and quantification of A-to-I editing events were performed using RNAEditor (version 1.0) with default parameters. RNAEditor accepts FASTQ files as input and executes a fully automated workflow, including mapping by BWA using the human genome version (GRCh38 release-83), followed by PCR duplicate removal, local realignment, and base quality score recalibration using the Genome Analysis Toolkit (GATK4). For RNA editing event detection, we used the GATK4 Unified Genotyper, followed by several refinement steps to reduce the number of false positives (excluding known SNPs, eliminating variants at splice sites, and removing variants at homopolymers), and finally, annotating RNA editing events. For further analysis, we used high-confidence editing filtering criteria (base quality >25, mapping quality >20, mean / median coverage >30x, minimum edited reads ≥2, editing degree change ≥10%, removal of edits with 100% editing degree, and Wilcoxon p-value <0.05). Functional annotation of edited events was then performed using ANNOVAR, RepeatMasker (http: / / repeatmasker.org), and REDIportal. Alu editing index (AEI) was performed according to the methodology described in Bazak et al. A flowchart of our A-to-I RNA editome analysis is shown in Figure 3A.

[0073] 2.5. Bioinformatics analysis of targeted sequencing data Sequencing data were downloaded from an Illumina NextSeq 500. Sequencing quality control was performed using FastQC software (version 0.11.7, https: / / github.com / s-andrews / FastQC / ). A minimum sequencing depth of 10,000 reads for each sample was considered for further analysis. A preprocessing step consisted of removing adapter sequences and filtering sequences according to length and quality score. Short reads (<100 nt) and reads with an average QC <20 were removed. The Flexible Read Trimming and Filtering Tool for Illumina NGS Data (fastp version) was used to improve the quality of the sequence alignment. After the preprocessing step, additional quality control was performed on each cleaned fastq file before further analysis. Alignment of the processed reads was performed using bowtie2 (version 2.2.9) in end-to-end high-sensitivity mode. Alignment was performed against the reference human genome sequence GRCh38. Non-uniquely aligned reads, unaligned reads, or reads containing insertions / deletions (INDELs) were removed from downstream analysis by SAMtools software (version 1.7). SAMtools mpileup was used for SVN calls. Edited positions in the alignment were identified by counting the number of different nucleotides at each genomic position using an in-house script. For each position, the script calculated the percentage of reads with a "G" [number of "G" reads / (number of "G" reads + number of "A" reads)]. *The script automatically detects genomic locations with an "A" criterion where the percentage of "G" reads exceeds 0.1 and is considered an "A-to-I editing site." In the final step, the percentages of all possible isoforms and / or patterns for each transcript are calculated. By definition, the relative proportion of RNA editing at a given editing "site" represents the sum of the editing modifications measured at this unique genomic coordinate. Conversely, edited mRNA isoforms are unique molecules that may or may not contain multiple editing modifications on the same transcript. For example, for a given transcript, edited mRNA isoform BC contains A-to-I modifications at both site B and site C within the same transcript. An editing pattern is a combination of editing events occurring at sites of interest in a transcript. By definition, given a list of sites of interest, a transcript has as many editing patterns as there are possible combinations. For example, for a given transcript with sites of interest ABC, the patterns analyzed are [A, B, C, AB, BC, AC, ABC]. A relative ratio of at least 0.1% was set as the threshold for inclusion in the analysis. A flowchart of our A-to-I RNA targeted next-generation sequencing pipeline is shown in Figure 3B (Figures 3A and 3B: Overview of our AI RNA editing analysis. A) Overview of the workflow for RNA-Seq and editome analysis. B) Overview of the bioinformatics workflow for targeted next-generation sequencing).

[0074] 2.6. Statistical analysis of data All statistics and figures were calculated using the R / Bioconductor statistical open-source software. BMK (i.e., RNA editing sites in target genes and edited isoforms / patterns) values ​​are usually presented as mean ± standard error of the mean (SEM). To ensure normal data distribution, each biomarker data was transformed in each dataset (Study 2 and Study 3) using the recipe package v0.2.0 (using the step_nzv, step_BoxCox, and step_normalize parameters). Differential analysis was performed using the most appropriate test: Mann-Whitney rank sum test, Student's t-test, or Welch's t-test, depending on the normality and sample variance distribution in each cohort. Significantly highly correlated variables were removed using the findCorrelation function in the Caret package. Significant variables with a coefficient of variation (CV) greater than 30% from the repeatability and reproducibility analysis were also removed.

[0075] All selected RNA editing variants were combined with age, gender, psychiatric treatment, and addiction using the ExtraTree algorithm, one of the most recent machine learning algorithms for classification. The ExtraTree method

[23] is derived from random forests and requires the use of a training set used to build a model and a test set to validate it. We allocated our dataset, using approximately 60% of the dataset for the learning phase and 40% for the testing phase. This allocation was randomized to respect the initial proportion of various states in each sample. We used a grid learning approach for each individual tree, specifying a specific maximum parameter set (ntree = 1000, mtree = (1, 20), splitrule = "extratrees", and min.node.size = (1, 15)). Subtrees were trained using classical cross-validation. RF results are shown for the test dataset from Study 2 (N = 98 samples), which was not included in the algorithm and replication dataset from Study 3. The implementation was performed using the R ranger package (version 0.13.1) and the R caret package (version 6.0-90).

[0076] Example 3: Results 3.1 ZNF267 in the exploratory cohort (Study 1, editome analysis) Using our RNA editome pipeline, we identified 40,398 A-to-I edited positions with high confidence in at least one sample (see Methods and Figure 3A). Two major variant types (A-to-G and T-to-C variants) were identified, accounting for 72.6% of RNA variants. Most A-to-I edited sites showed moderate editing, with the largest proportion exhibiting 10-30% editing. This RNA editing was primarily found in introns and 3' untranslated regions (UTRs) and Alu repeat regions, and was evenly distributed throughout the genome. We then performed differential analysis to identify sites where editing may differ specifically between unipolar and bipolar disorder, between controls and depression, and between controls and bipolar disorder.

[0077] To select genes of interest, we used strict statistical criteria (coverage > 50, p-value < 0.05, AUC > 0.750, FoldChange > 0.833 > 1.2). ZNF267 was the only biomarker selected for its diagnostic performance (Table 1).

[0078] 3.2 ZNF267 in the validation cohort (Study 2, targeted sequencing analysis) Analysis of the RNA editing amplicon of ZN267 in clinical samples (Study 2) was performed using our RNA editing measurement platform based on ultra-deep targeted sequencing. Indeed, NGS technology offers a unique opportunity to deeply examine RNA editing events. Our platform measures adenosine to inosine (A to I) modifications. The biological process is standard, with RNA extraction followed by two steps of PCR sequencing library preparation. In the bioinformatics pipeline, we use our AI RNA editing targeted NGS pipeline. The bioinformatics pipeline is fully automated and parallelized (Figure 3B).

[0079] 3.2.1 ZNF267 primers used for detection of RNA editing sites Use validated primers to amplify the region of interest, purify the PCR product, and sequence it by NGS (see Table 2).

[0080] 3.2.2 Quality control of sequencing data All quality criteria and requirements for applying our algorithm are met: Coverage per biomarker after filtering must be greater than 10,000 reads. The percentage of correctly sequenced sequences after filtering (Q25) is greater than 80%.

[0081] 3.2.3 Differential biomarkers of ZNF267 in Cohort 2 UN vs. BP In this study, the term "biomarker" refers to an editing site or isoform or pattern of RNA that contains one or more positions that are differentially edited in the UN vs. BD comparison.

[0082] A differential analysis of all detected RNA editing biomarkers was performed on a larger cohort of 245 participants for the ZNF267 amplicon. 58 biomarkers were found to be statistically significant between unipolar versus bipolar depression in the validation cohort with an adjusted p-value of <0.05 (Table 3).

[0083] 3.2.4 mROC combination of ZNF267 biomarkers in Cohort 2 UN vs. BP To evaluate the diagnostic performance of significant biomarkers of ZNF267 in Cohort 2, we used the mROC approach, a dedicated program for identifying linear combinations that maximize the AUC (area under the curve) ROC. The top five best combinations obtained are shown in Table 4.

[0084] 3.3 ZNF267 in association with other biomarkers of interest (Studies 2 and 3, targeted sequencing analysis) In addition to the ZNF267 biomarker, we selected seven targets of interest for the diagnosis of unipolar versus bipolar depression based on our previous results (Salvetat et al., Transl Psychiatry 2020 and WO 2021089866(A1)). These targets are IFNAR1, GAB2, IL17RA, LYN, MDM2, PRKCB, and PTPRC. We applied the same AI RNA editing targeted NGS pipeline as for ZNF267.

[0085] To combine all A-to-I RNA editing biomarkers, we developed a clinical decision algorithm using a machine learning approach (ExtraTree, R caret and ranger packages).

[0086] The performance of the top five best algorithms using eight targets is shown in Table 5.

[0087] Using the same approach, the performance of the best algorithms using seven targets without ZNF267 is shown in Table 6. As can be seen, the best performance is obtained with ZNF267 (see Table 5).

[0088] In Example 1, the Extra Trees algorithm model #154 provided an AUC ROC curve (see Figure 4) of 0.896 (CI 95%: [0.835-0.956]) with a sensitivity of 82.1% and a specificity of 80.0%, clearly distinguishing between unipolar and bipolar patients in the test dataset (internal validation) of Study 2. The same model (#154) provided an AUC ROC curve (see Figure 4) of 0.887 (CI 95%: [0.811-0.952]) with a sensitivity of 85.7% and a specificity of 81.8% in the replication dataset (external validation) of Study 3, confirming the diagnostic performance of Study 2 in an independent cohort (Figure 4: Receiver operating characteristic curves and diagnostic performance for model #154 for bipolar depression in both studies).

[0089] A case-specific trained random forest model (Extra Trees model #154) was used to plot the probability of correct responses for the tested set. The test dataset for Study 2 (internal validation) included 70 patients from the unipolar group and 28 from the bipolar group. The replication dataset for Study 3 (external validation) included 67 patients from the unipolar group and 28 from the bipolar group. The number of targets used: 8 (GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA, ZNF267, and PRKCB) and the number of RNA editing variants used: 22 (Extra Trees model #154).

[0090] In Example 2, the Extra Trees algorithm model #284 provided a sensitivity of 80.6%, a specificity of 85.1%, and an AUC ROC curve of 0.901 (CI 95%: [0.840-0.959]) (see Figure 5), clearly distinguishing unipolar and bipolar patients in the test dataset (internal validation) of Study 2. The same model (#284) provided a sensitivity of 85.7% and a specificity of 80.3% in the replication dataset (external validation) of Study 3, providing an AUC ROC curve of 0.906 (CI 95%: [0.832-0.964]) (see Figure 5), confirming the diagnostic performance of Study 2 in an independent cohort.

[0091] Figure 5: Receiver operating characteristic curves and diagnostic performance for bipolar depression in both studies for model #284.

[0092] A case-specific trained random forest model (Extra Trees Model #284) was used to plot the probability of correct responses for the tested set. The test dataset for Study 2 (internal validation) included 70 patients from the unipolar group and 28 from the bipolar group. The replication dataset for Study 3 (external validation) included 67 patients from the unipolar group and 28 from the bipolar group. The number of targets used: 8 (GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA, ZNF267, and PRKCB) and the number of RNA editing variants used: 22 (Extra Trees Model #284).

[0093] References: 1.Judd LL, Akiskal HS, Schettler PJ, Endicott J, Maser J, Solomon DA, et al.The longterm natural history of the weekly symptomatic status of bipolar I disorder.Arch Gen Psychiatry.2002;59:530-7. 2.Jung Y, Goldman D.Role of RNA modifications in brain and behavior.Genes Brain Behav.2018;17:e12444. 3.Shelton RC.The molecular neurobiology of depression.Psychiatr Clin North Am.2007.30:1-11. 4.Lee SY,Lu RB,Wang LJ,Chang CH,Lu T,Wang TY,et al.Serum miRNA as a possible biomarker in the diagnosis of bipolar II disorder.Sci Rep.2020;10:1131. 5.Giacopuzzi E,Gennarelli M,Sacco C,Filippini A,Mingardi J,Magri C,et al.Genome-wide analysis of consistently RNA edited sites in human blood reveals interactions with mRNA processing genes and suggests correlations with cell types and biological variables.BMC Genomics.2018;19:963。 6.Yang W,Wang Q,Kanes SJ,Murray JM,Nishikura K.Altered RNA editing of serotonin 5-HT2C receptor induced by interferon:implications for depression associated with cytokine therapy.Brain Res Mol Brain Res.2004;124:70-8。 7.Lyddon R,Dwork AJ,Keddache M,Siever LJ,Dracheva S.Serotonin 2c receptor RNA editing in major depression and suicide.World J Biol Psychiatry.2013;14:590-601。 8.Weissmann D,van der Laan S,Underwood MD,Salvetat N,Cavarec L,Vincent L,et al.Region-specific alterations of A-to-I RNA editing of serotonin 2c receptor in the cortex of suicides with major depression.Transl Psychiatry.2016;6:e878。 9. Chimienti F, Cavarec L, Vincent L, Salvetat N, Arango V, Underwood MD, et al. Brain region-specific alterations of RNA editing in PDE8A mRNA in suicide decedents. Transl Psychiatry. 2019;9, 91. 10. Salvetat N, Van der Laan S, Vire B, Chimienti F, Cleophax S, Bronowicki JP, et al. RNA editing blood biomarkers for predicting mood alterations in HCV patients. J. Neurovirol. 2019;25:825 - 36. 11. Salvetat N, Chimienti F, Cayzac C, Dubuc B, Checa-Robles F, Dupre P, et al. Phosphodiesterase 8A to discriminate in blood samples depressed patients and suicide attempters from healthy controls based on A-to-I RNA editing modifications. Transl Psychiatry. 2021;11:255. 12. Salvetat N, Checa-Robles FJ, Patel V, Cayzac C, Dubuc B, Chimienti F, Abraham JD, Dupre P, Vetter D, Mereuze S, Lang JP, Kupfer DJ, Courtet P, Weissmann D. A game changer for bipolar disorder diagnosis using RNA editing-based biomarkers. Transl Psychiatry. May 4, 2022;12(1):182. 13.Bueno-Notivol J,Gracia-Garcia P,Olaya B,Lasheras I,Lopez-Anton R,Santabarbara J.Prevalence of depression during the COVID-19 outbreak:a metaanalysis of community-based studies.Int J Clin Health Psychol.2021;21:100196。 14.Wu T,Jia X,Shi H,Niu J,Yin X,Xie J,et al.Prevalence of mental health problems during the COVID-19 pandemic:A systematic review and meta-analysis.J.Affect Disord.2021;281:91-98。 15.Schnabl B,Hu K,Muhlbauer M,Hellerbrand C,Stefanovic B,Brenner DA,et al.(2005):Zinc finger protein 267 is up-regulated during the activation process of human hepatic stellate cells and functions as a negative transcriptional regulator of MMP-10.Biochemical and biophysical research communications.335:87-96。 16.Schnabl B,Valletta D,Kirovski G,Hellerbrand C(2011):Zinc finger protein 267 is up-regulated in hepatocellular carcinoma and promotes tumor cell proliferation and migration.Experimental and molecular pathology.91:695-701。 17.Schnabl B,Czech B,Valletta D,Weiss TS,Kirovski G,Hellerbrand C(2011):Increased expression of zinc finger protein 267 in non-alcoholic fatty liver disease.International journal of clinical and experimental pathology.4:661-666。 18.Lu L,Chen XM,Tao HM,et al.(2015)Regulation of the expression of zinc finger protein genes by microRNAs enriched within acute lymphoblastic leukemia-derived microvesicles.Genet.Mol.Res.14(4):11884-1189。 19.Cheishvili D,Parashar S,Mahmood N,Arakelian A,Kremer R,Goltzman D,et al.(2018):Identification of an Epigenetic Signature of Osteoporosis in Blood DNA of Postmenopausal Women.Journal of bone and mineral research :the official journal of the American Society for Bone and Mineral Research.33:1980-1989。 20.Patel S,Howard D,Chowdhury N,et al.(2021)Characterization of human genes modulated by por-phyromonas gingivalis highlights the ribosome,hypothalamus,and cholinergic neurons.Front Immunol.12:646259。 21. Fehlbaum - Beurdeley P, Sol O, Desire L, Touchon J, Dantoine T, Vercelletto M, et al. (2012) Validation of AclarusDxTM, A Blood - Based Transcriptomic Signature for the Diagnosis of Alzheimer’s Disease. J Alzheimers Dis. 32:169 - 81. 22. Nguyen HD, Jo WH, Hoang NHM, Kim MS. Curcumin - Attenuated TREM - 1 / DAP12 / NLRP3 / Caspase - 1 / IL1B, TLR4 / NF - κB Pathways, and Tau Hyperphosphorylation Induced by 1,2 - Diacetyl Benzene: An in Vitro and in Silico Study. Neurotox Res. 2022 Oct;40(5):1272 - 1291. 23. Pierre Geurts, Danien Ernst, Louis Wehenkel. Extremely randomized trees. Mach Learn(2006)63:3 - 42 DOI 10.1007 / s10994 - 006 - 6226 - 1.

[0094] [Table 1]

[0095] [Table 2]

[0096] [Table 3 - 1]

[0097] [Table 3 - 2]

[0098] [Table 3-3]

[0099] [Table 4]

[0100] [Table 5]

[0101] [Table 6] * Target list: GAB2, IFNAR1, LYN, MDM2, PTPRC, and PRKCB

[0102] [Table 7]

Claims

1. 1. An in vitro method for analyzing expression of biomarker RNA molecules, comprising: A. isolating RNA from a blood sample obtained from a subject, determining the expression of at least one biomarker RNA molecule in the isolated RNA, and providing an expression profile based on the results, wherein the biomarker is the relative rate of RNA editing at at least a given editing site and / or isoform and / or pattern, or a combination of a given site and / or isoform and / or pattern, that may be edited on the ZNF267 gene; B. From the same isolated RNA, determining the expression of at least one additional biomarker RNA molecule in the isolated RNA and providing an expression profile based on the results, wherein the biomarker is the relative proportion of RNA editing at at least a given editing site and / or isoform and / or pattern, or a combination of a given site and / or isoform and / or pattern, that may be edited on another A to I edited RNA gene; C. performing a combined analysis of the results using the expression profiles determined in steps A and B.

2. 2. The method of claim 1, wherein in step B, the additional A-to-I-edited RNA gene is selected from the group of A-to-I-edited RNA genes consisting of GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA, and PRKCB A-to-I-edited RNA genes.

3. 3. The method according to claim 1 or 2, wherein in step A, the blood sample is taken from the patient during a depressive phase, preferably during a moderate or severe depressive phase.

4. 1. A method for in vitro differential diagnosis of bipolar versus unipolar disorder in patients during a moderate or severe depressive phase, comprising determining in a sample from said patient the relative proportions of RNA editing at at least a given editing site and / or isoform and / or pattern, or a combination of a given site and / or isoform and / or pattern, that may be edited on the ZNF267 gene.

5. 5. The method of claim 4, further comprising determining the relative proportion of RNA editing at at least a given editing site and / or isoform and / or pattern, or a combination of given sites and / or isoforms and / or patterns, which may be edited on another A-to-I edited RNA gene selected from the group comprising the A-to-I edited RNA biomarkers GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA and PRKCB, more preferably on at least 2, 3, 4, 5 or 6 of these genes, preferably in the same sample.

6. 6. The method of claim 4 or 5, further comprising determining the relative rates of RNA editing at at least a given editing site and / or isoform and / or pattern, or a combination of a given site and / or isoform and / or pattern, that may be edited on the A-to-I edited RNA genes of GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA and PR KCB.

7. The method of any one of claims 1 to 6, wherein the PCR products of the gene regions of interest of the selected A-to-I edited RNA genes are sequenced by NGS.

8. a) The primer pair used to obtain the PCR product of the ZNF267 gene of interest is ZNF267 MPx_F2 GGCTGAGGTGGTCTTGGATG (SEQ ID NO: 1) ZNF267 MPx_R1 CCTCGCCTTCCACTGTGATT (SEQ ID NO: 2) and, b) The primer pairs used to obtain PCR products of the IFNAR1, LYN, PRKCB, MDM2, GAB2, IL17RA and PTPRC genes of interest are listed in Table 7 (SEQ ID NOs: 3-16), respectively; The method according to any one of claims 1 to 7.

9. 9. A method for in vitro differential diagnosis of bipolar versus unipolar disorders in patients during a moderate or severe depressive phase according to any one of claims 4 to 8, comprising: a) determining in a sample of the patient being tested the relative proportion of RNA editing at at least a given editing site and / or isoform and / or pattern, or a combination of given sites and / or isoforms and / or patterns, which may be edited on the ZNF267 mRNA gene and optionally on at least another one of the A-to-I edited RNA genes GAB2, IFNAR1, LYN, MDM2, PTPRC, IL17RA and PRKCB, preferably 2, 3, 4, 5, 6 or 7 of these genes; b) determining the value obtained from the ratio obtained in step a); c) comparing the result value obtained in step b) with control values ​​obtained for bipolar and / or unipolar patients and then classifying the patient as bipolar or unipolar, wherein the control values ​​have been determined in a manner comparable to that of the result value obtained in step b).

10. 10. The method of claim 9, wherein in step c) the result value obtained for the patient being tested is compared with a threshold value (such as, but not limited to, a cutoff or probability) associated with the disorder whose discrimination is desired, and if the result value is approximately the threshold value, the patient is classified as a bipolar or unipolar patient according to the selected threshold value.

11. The method of any one of claims 1 to 10, wherein the patient sample is a biological sample, preferably a blood, serum, urine, saliva, tear or plasma sample, more preferably a blood sample, serum, even more preferably the patient sample is a blood sample, even more preferably a whole blood sample.

12. 1. A method for determining the effectiveness of a treatment in a subject or for predicting or monitoring a response to a treatment in a patient, comprising: I. analyzing the expression of biomarker RNA molecules according to the method of any one of claims 1 to 3 before and / or during and / or after treatment of said patient; II. performing a combined analysis of the results using the expression profile determined in step C for each of the analyses.

13. 1. A method for monitoring treatment of bipolar or unipolar disorder in a human patient during a moderate or severe depressive phase from a biological sample of said patient, comprising: A) differentially diagnosing bipolar versus unipolar disorder in said human by the method of any one of claims 9 and 10 prior to initiation of treatment for which monitoring is desired; B) repeating steps (a) through (c) of the method after a period during which the patient has received the desired treatment for the diagnosed bipolar or unipolar disorder to obtain a post-treatment outcome value; C) comparing the post-treatment outcome value from step (c) with the outcome value obtained before treatment.

14. 1. A method for determining from a biological sample whether a patient during a depressive phase is a responder to a treatment for bipolar or unipolar disorder that can bring said patient into a state of manic-depressive remission (a state of normal mood), comprising: A) differentially diagnosing bipolar versus unipolar disorder in said human by the method of any one of claims 9-10 prior to the initiation of treatment for which monitoring is desired; B) repeating steps (a) through (c) of the method of the present invention after a period during which the patient has received the desired treatment for the diagnosed bipolar or unipolar disorder to obtain a post-treatment outcome value; C) The post-treatment outcome values ​​from step (c) Outcome values ​​obtained before treatment, and compared with known or obtained outcome values ​​for control patients with bipolar or unipolar disorder in manic-depressive remission, classifying the patient as a responder to treatment if the post-treatment outcome value obtained in step B) is closer to the outcome value for the bipolar remission state than the outcome value obtained before the treatment.

15. 1. A kit for the differential diagnosis of bipolar versus unipolar disorder in a human patient during a moderate or severe depressive phase, comprising: 1) optionally, instructions for applying the method for the differential diagnosis of bipolar versus unipolar disorder in a human patient during a depressive phase to obtain a result value, the analysis of which determines whether the depressed patient exhibits bipolar disorder or unipolar disorder; and 2) a) a primer pair having the sequences of SEQ ID NOs: 1 and 2; and b) A kit comprising at least one pair, preferably 2, 3, 4, 5, 6 or 7 pairs of primers selected from the group of primer pairs having the sequences of SEQ ID NOs: 3 to 16, more preferably 7 pairs of primers having the sequences of SEQ ID NOs: 3 to 16.

16. 1. A kit for the differential diagnosis of bipolar versus unipolar disorder in a human patient during a moderate or severe depressive phase, comprising: 1) optionally, instructions for applying the method for the differential diagnosis of bipolar versus unipolar disorder in a human patient during a depressive phase to obtain a result value, the analysis of which determines whether the depressed patient exhibits bipolar disorder or unipolar disorder; and 2) a) a primer pair that includes an amplicon obtainable by a primer pair having the sequences of SEQ ID NOs: 1 and 2, or that can obtain an amplicon identical thereto; and b) A kit comprising at least one pair, preferably 2, 3, 4, 5, 6 or 7 pairs of primers capable of obtaining an amplicon containing or identical to the amplicon obtained by a primer pair selected from the group of primer pairs having the sequences of SEQ ID NOs: 3 to 16, preferably 7 pairs of primers capable of obtaining 7 amplicons containing or identical to the 7 amplicons obtained by 7 pairs of primers having the sequences of SEQ ID NOs: 3 to 16.

Images