Patent Application
20190185937
The present invention is drawn to a method for in vitro predicting the risk for a patient to present a pathology or to identify whether a patient is at risk to develop a pathology, such as psychiatric disorder, associated to an alteration of A-to-I editing on PDE8A transcripts, from body fluids such as a blood, urine or saliva sample of said patient. The present invention also relates to kits for the implementation of the method.
Suicide and suicidal behaviour are among major public health issues worldwide, as 1 million cases of completed suicides are reported in most Western countries and this is expected to rise up to 1.5 million by 2020. Today, suicide risk prevention using biologic tools is not validated, and clinical evaluation doesn't allow a good prediction of the occurrence of suicidal behaviour in a given patient. Furthermore, pharmacological treatments of psychiatric diseases have shown their limited effect on decreasing the rate of attempted and completed suicides. There is a pressing public health need to develop new strategies and promote preventive actions toward those most at risk for suicide. To achieve this goal, suicide prevention strategies require identification of individuals at risk.
Among the many factors involved in determining suicidal behaviour, some recent developments in molecular genetics and genomic research have unveiled that multiple factors may contribute to susceptibility for suicidal behaviour. This susceptibility is likely mediated by an underlying genetic predisposition interacting with environmental and epigenetic factors throughout the lifespan to modify the function of neuronal circuits [1-3]. RNA editing of receptors expressed in synaptic clefts and other associated proteins has been shown to be involved in etiology of different psychiatric disorders and linked to suicidal behaviour [4-7]. Simmons and colleagues have recently reported an increase in the expression of the RNA editing enzyme 1, Adenosine Deaminase Acting on RNA (ADAR1) mRNA in the cerebral cortex of depressive suicide victims [8]. The phospho di-esterase 8A (PDE8A) which is a target of ADARs, is expressed both in brain and blood tissues, and edited by ADARs in humans [9-11]. Alteration in the editing profile of PDE8A pre-mRNA which can by quantitatively evaluated from total RNA extracts of human tissues, including brain but practically more convenient also in blood samples, can be used to monitor the status of a patient. Based on these observations, the objective is to identify body fluids biomarkers to determine disease-specific molecular signatures. Application of this body fluids test will open new possibilities to evaluate primary or secondary risks of severe psychiatric side effects.
To date, no test has been specifically approved by the U.S. Food and Drug Administration (FDA), or by other drug regulatory agencies, as an effective test for predicting the risk for a patient to present or to develop a psychiatric disorder, such as depressive disorder or suicidal behaviour.
There is a great interest in reviewing any test that might demonstrate efficacy to determine the risk of suicidal behaviour or depressive disorder for a patient.
Today, there is no approved biological test to identify such patients.
Thus there is a need to provide with in vitro test, particularly easy to use from for example a blood sample of the patient to be tested, which can determine with high accuracy and with high discriminate power the risk for a patient to present or to develop a psychiatric disorder, such as depressive disorder or suicidal behaviour.
This is the object of the present invention.
In a first aspect, the present invention is directed to an in vitro method for predicting the risk for a patient to present a pathology or to identify whether a patient is at risk to develop a pathology, said pathology being selected from the group consisting of psychiatric disorder or neurological, immunological and degenerative syndromes associated to an alteration of A-to-I editing on PDE8A transcripts, said method comprising the following steps of:
from body fluids sample of said patient containing cells expressing the at least one of the editing enzymes ADAR1a, ADAR1b and ADAR2 and the PDE8A
the level of the expression of at least one or a combination of PDE8A isoforms or the non-edited transcript (Ne) which can be expressed and, preferably, associated with said pathology; and
The threshold value determined for the control sample in step c)i) or the algorithm used in step c)ii) can be obtained for example by a method comprising the steps of:
a) —selecting a collection of patients composed of a ratio of patients annotated with or without a risk to develop a psychiatric disorder or to identify the patient as presenting a psychiatric disorder,
selecting one or several PDE8A RNA editing sites and/or isoform(s), or a combination thereof;
b) analysing the target PDE8A RNA editing sites and/or isoform(s) in order to obtain the proportion of RNA editing level of said target site(s) or isoforms and for each of the patients of said collection,
c) —i) by an univariate analysis statistical method, evaluating for each RNA edited site and/or isoform, its threshold value and/or its accuracy and power to discriminate the risk to develop the said pathology, such as psychiatric disorder, or to identify the patient as presenting said pathology, and/or
ii) by a multivariate analysis statistical method, evaluating for each combination of RNA edited sites and/or isoforms, its accuracy and its power to discriminate the risk to develop said pathology, particularly a psychiatric disorder, or to identify the patient as presenting said pathology, and
iii) selecting the editing site and/or isoform or combination thereof exhibiting an acceptable discriminative performance; and
e) building an algorithm using said selected combination of editing sites and/or isoforms, and use said algorithm thus obtained for predicting for a given patient the risk to develop said pathology, particularly a psychiatric disorder, or to identify said patient as presenting said pathology.
In a preferred embodiment, the algorithm which can be used in the method according to the invention, is carried out by a multivariate method including:
mROC program, particularly to identify the linear combination, which maximizes the AUC (Area Under the Curve) ROC and wherein the equation for the respective combination is provided and can be used as a new virtual marker Z, as follows:
Z=a
1·(Biomarker 1)+a2·(Biomarker 2)+ . . . ai·(Biomarker i)+ . . . an·(Biomarker n)
where ai are calculated coefficients and (Biomarker i) are the relative proportion of individual level of RNA editing site or of isoform's target; and/or
a logistic regression model applied for univariate and multivariate analysis to estimate the relative risk of patient at different level of RNA editing site or isoforms values; and/or
a CART (Classification And Regression Trees) approach applied to assess RNA editing site(s) and/or isoforms combinations; and/or
a Random Forest (RF) approach applied to assess the RNA editing site(s) and/or isoforms combinations, particularly to rank the importance of the RNA editing site(s) and/or isoform(s), and to combine the best RNA editing site(s) and/or isoform(s) to classify the “relative risk”, and/or optionally
a multivariate analysis applied to assess the RNA editing site(s) and/or isoforms combinations for the “relative risk”, said multivariate analysis being selecting for example from the group consisting of as
Support Vector Machine (SVM) approach;
Artificial Neural Network (ANN) approach;
Bayesian network approach;
WKNN (weighted k-nearest neighbours) approach;
In a preferred embodiment, the body fluid sample is selected from the group of blood, urine and saliva sample, blood sample being the most preferred.
In a preferred embodiment, said pathology is a psychiatric disorder.
In another preferred embodiment, said pathology is selected from the group consisting of mental disorders, bipolar disorder, depressive disorders, schizophrenia, panic disorder, social anxiety, post-traumatic stress disorder (PTSD), substance dependence/abuse, abnormal feeding behaviour, preferably anorexia or obesity, obsessive compulsive disorder (OCD), early Alzheimer's disease, or Parkinson's disease.
In a more preferred embodiment, said pathology is a depressive disorder and more particularly suicidal behaviour.
In a more preferred embodiment of the method of the present invention, said method is for predicting the risk for a patient to attempt suicide, and wherein in step c)(i), the control body fluids samples is obtained from affecting controls group of patients.
In also more preferred embodiment of the method of the present invention, said method is a method to identify whether a patient exhibits a depression disorder, and wherein in step c)(i), the control body fluids samples is obtained from healthy group of patients.
In a particular embodiment, in the method according to the present invention, said patient is selected from patients already identified to present a psychiatric disorder which can be associated to a risk to develop a suicidal behaviour, particularly depressive disorder with or without history of suicide attempts and wherein in step c), it is identified whether said patient presents or is at risk to develop a suicidal behaviour.
In another embodiment, the method of the present invention allows to monitor and/or stratify patients between responder and non-responders to treatment.
Many disorders such as psychiatric disorders are known to sometimes be associated with suicidality. In some embodiments, the patient is suffering from mental disorders, bipolar disorder, schizophrenia, panic disorder, social anxiety, post-traumatic stress disorder (PTSD), substance dependence/abuse, eating disorder (abnormal feeding behaviour (like anorexia, obesity), obsessive compulsive disorder (OCD), early Alzheimer's disease, or Parkinson's disease.
In another embodiment, said patient can be a patient identified as not presenting a psychiatric disorder and treated for a non-psychiatric disorder, particularly treated against hepatitis.
Another aspect of the invention concerns the method of the present invention which further comprises:
In a preferred embodiment of the method of the present invention, said blood sample contains PBMC (Peripheral Blood Mononuclear Cells);
Preferably, in the method according to the present invention, in step a), the determination of the PDE8A RNA editing of a one site is carried for at least one site selected from the edited sites listed in Table III, more preferably for a several sites comprising at least one site O to ZZ of the Table III.
Preferably, in the method according to the present invention, in step a), the determination of the PDE8A RNA editing of a one site or of several sites is carried for at least site (s) selected from the group consisted of the sites A, B, C, D, E, F, G, Z, and ZZ.
More preferably, in the method according to the present invention, in step a), the determination of the PDE8A RNA editing of a one site or of several sites is carried for at least the site B.
Preferably, in the method according to the present invention, in step a), it is determined the relative proportion of PDE8A RNA isoform level comprising only said one site edited or a combination of some of said several sites edited to the PDE8A mRNA expression level.
Preferably, in the method according to the present invention, in step a), it is determined the relative proportion of PDE8A RNA isoform(s) selected from the group of isoforms B, BC, D, E, Ne (Non-edited), BE, G, BG, BF, A, Z, C, F, BZ and BD.
More preferably, in the method according to the present invention, in step a), it is determined at least the relative proportion of PDE8A RNA isoform B.
In a preferred embodiment, in the method of the present invention, said algorithm or statistical method in step c) includes:
Z=a
1·(Biomarker 1)+a2·(Biomarker 2)+ . . . ai·(Biomarker i)+ . . . an·(Biomarker n)
where a1 are calculated coefficients and (biomarker i) are the relative proportion of individual PDE8A RNA editing level of one site or one isoform target or the level of ADAR1a, 1b or ADAR2 expression; and/or
Preferably, in the method according to the present invention, in step c), said algorithm is selected from the group consisted of the mROC combinations as listed in Table VI.
Preferably, in the method according to the present invention, in step a) and b), the determination of the PDE8A mRNA expression level by qPCR and/or the level of the RNA editing of a one site is carried out by the NGS (Next Generation Sequencing) method.
In a preferred embodiment, the determination of the PDE8A mRNA expression level by qPCR and/or the level of the RNA editing at a given site is carried out using a set of a forward and reverse primers selected from the group of:
Seq1-Forward (SEQ ID No. 2) or Seq2-Forward (SEQ ID No. 3) for the forward primer;
Seq1-Reverse (SEQ ID No. 4), Seq2-Reverse (SEQ ID No. 5) or Seq3-Reverse (SEQ ID No. 6) for the reverse primer, and
A set of a forward and reverse primer meeting the following selection criteria:
In a more preferred embodiment, the following set of primers Seq2-Forward and Seq-3 Reverse is used in the method of the present invention to determine the level of RNA editing of PDE8A on one site.
In another aspect, the invention concerns a kit for determining whether a patient is at risk to present a pathology or to identify whether a patient is at risk to develop a pathology selected from the group consisting of psychiatric disorder or neurological, immunological and degenerative syndromes associated to an alteration of A-to-I editing on PDE8A transcripts, said kit comprising:
1) instructions to apply the method according to the present invention, in order to obtain the end value the analysis of which determining said risk to induce pathology, said instructions comprising optionally a ROC curve; and
2) a set of a forward and reverse primers selected from the group of:
Seq1-Forward (SEQ ID No. 2) or Seq2-Forward (SEQ ID No. 3) for the forward primer;
Seq1-Reverse (SEQ ID No. 4), Seq2-Reverse (SEQ ID No. 5) or Seq3-Reverse (SEQ ID No. 6) for the reverse primer, and
A set of a forward and reverse primer meeting the following selection criteria:
In a more preferred embodiment, the kit comprises the following set of primers Seq2-Forward (SEQ ID No. 3) and Seq-3 Reverse (SEQ ID No. 6).
The following examples and the figures and the legends hereinafter have been chosen to provide those skilled in the art with a complete description in order to be able to implement and use the present invention These examples are not intended to limit the scope of what the inventor considers to be its invention, nor are they intended to show that only the experiments hereinafter were carried out.
Other characteristics and advantages of the invention will emerge in the remainder of the description with the Examples and Figures, for which the legends are given hereinbelow.
Data from two different cohorts are presented: one cohort including depressed patients with or without history of suicide attempts (called the Suicide attempters study and follow-up) and one longitudinal study that analyses patients infected with hepatitis C virus and that were treated with Interferon α (called the Interferon study). Written informed consent was obtained from all subjects after a detailed discussion on the study aims and requirements. All subjects were able to understand informed consent detailing the research goals and procedure. The study was approved by the local Institutional Review Board, according to the approval requirements and good clinical practice.
The study enrolled 38 depressed patients consulting at the Department of Psychiatric Emergency or Post-Emergency of the CHU of Montpellier, France (n=17) or at the Psychiatric Residential Treatment center in Oviedo, Spain (n=21). The psychiatric diagnoses were established by a structured clinical interview. Psychiatric diagnostics were determined according to the Diagnostic and Statistical manual of Mental disorders IV (DSM-IV). The sample included 20 suicide attempters (SA) (52.63%) and 18 suicide non-attempters (affective controls, AC) (47.37%) (see Table I(A)).
Subjects were ethnically homogenous; all were Caucasian, coming from the west of Europe. The demographic data on age and gender were recorded, as well as patient psychiatric diagnosis, alcohol or substance consumption and the suicide attempt number.
This follow-up study enrolled 28 depressed suicide attempter's patients consulting at the Department of Psychiatric Emergency or Post-Emergency of the CHU of Montpellier, France. These patients were follow-up over a 6-month period (see Table I(B). During follow-up, 8 patients out of 28 (28.6%) have committed one or several new suicide attempts (“repeat suicide attempters”, RSA) while 20 patients (71.4%) did not commit new suicide attempts (“non-repeat suicide attempters”, NRSA). Psychiatric assessments of patients were realized as previously mentioned for the suicide attempters study. Depression severity at baseline and follow-up evaluation was assessed using 3 scales: Hamilton Depression scales (HAMD), Montgomery and Asberg Depression rating scale (MADRS) and Beck depression Inventory (BDI) scale.
The study enrolled 10 patients from 3 different departments in CHU (Centre Hospitalier Universitaire) of Marseille, Nancy and Strasbourg (France). Patients infected with hepatitis C virus (HCV), which did not meet any criteria for psychiatric disorders, were enrolled prior to onset of anti-viral treatment and followed for up to 12 weeks after onset of antiviral therapy. An initial blood sample was obtained 4 weeks prior treatment (−4). At start of the treatment blood was collected in PAXgene tubes every two weeks for up to 12 weeks (
A volume of 2.5 ml of whole blood sample from each patient was retrieved in PAXgene blood RNA tubes and stored at −20° C. for a couple of months and then transferred to −80° C. PAXgene™ Blood RNA tubes (PreAnalytix) contain a reagent that protects RNA molecules from degradation by RNAses and ex vivo changes in gene expression. Samples were distributed randomly in the different sets of extractions. Total RNA from the 2.5 ml of whole blood was extracted using the PAXgene™ Blood RNA kit (ref 28704, PreAnalytix). Extracted RNA was isolated using a Qiagen QIAcube system, following the manufacturer's protocol for PAXgene Blood RNA part 1, automated protocol. During sample preparation and RNA extraction, standard precautions were taken to avoid RNA degradation by RNAses. Total RNA concentrations were determined with a Qubit Fluorometer (Invitrogen) and the Quant-IT RNA BR assay (Invitrogen).
For NGS library preparation a 2-step PCR method was employed in order to selectively sequence the region of interest within intron 9 of the PDE8A gene. As shown in
For PCR amplification the Q5 Hot Start High Fidelity enzyme (New England Biolabs) was used according to manufacturer guidelines (ref#M0494S). The PCR reaction was performed on a Peqstar 96x thermocycler using optimized PCR protocol. Post PCR, all samples were analysed by LabChipGx (Perkin Elmer) and both quantity and quality of the PCR product was assessed. Purity of the amplicon was determined and quantification was performed using fluorescent based Qubit method. After quality control, the 96 PCR reactions (microplate) were purified using magnetic beads (High Prep PCR MAGbio system from Mokascience). Post purification DNA was quantified using Qubit system and purification yield was calculated. Next, samples were individually indexed by PCR amplification using Q5 Hot start High fidelity PCR enzyme (New England Biolabs) and the Illumina 96 Indexes kit (Nextera XT index kit; Illumina). Post PCR, samples were pooled into a library and purified using Magbio PCR cleanup system. The library was denatured and loaded onto a sequencing cartridge according to Illumina's guidelines for sequencing FASTQ only on a MiSeq platform. A commercial total RNA pool from human blood peripheral leukocytes (Clontech, ref#636592) was incorporated into the libraries to determine variability between different sequencing flow cells during the course of the experiment. NGS libraries were sequenced at standard concentrations and spiked in to introduce library diversity using PhiX Control V3 (Illumina). Experiments were performed five times independently.
The sequencing data was downloaded from the Miseq sequencer (Illumina) as fastq file. To evaluate sequencing quality, an initial quality of each raw fastq file was performed using FastQC software (version 0.11.3). A pretreatment step was performed consisting of removing adapter sequences and filtering of the sequences according to their size and quality score (all short reads (<50 nts) and reads with average QC<30 were removed). Next, to facilitate and improve the quality of alignment of the sequences flexible read trimming and filtering tools for Illumina NGS data was used (fastx toolkit v0.0.14 and prinseq version 0.20.4). After pre-processing steps were performed an additional quality control of each cleaned fastq file was carried out prior further sequence processing.
Alignment of the processed reads was performed using bowtie2 (version 2.2.5) with end-to-end sensitive mode. The alignment was done to the latest annotation of the human genome sequence (GRCh38) and reads multiple alignment regions, reads with poor alignment quality (Q<40) or reads containing insertion/deletion (INDEL) were taken out of the further analysis. Filtering of file alignment was carried out with SAMtools software (version 1.3.1) that provide various utilities for manipulating alignments in the SAM format, including sorting, merging, indexing and generating alignments in a per-position format.
Next, SAMtools mpileup was used to pileup obtained alignment results data from multiple samples simultaneously. An in-house script was run to count the number of different ATGC nucleotides in each genomic location (‘base count’). So, for each genomic location, the home-made script computes the percentage of reads that have a ‘G’ [Number of ‘G’ reads/(Number of ‘G’ reads+Number of ‘A’ reads)*100]. The genomic location ‘A’ reference with percentage in ‘G’ reads >0.1 are automatically detected by the script and are considered as ‘A-to-I edition site’. The last stage was to compute the percentage of all possible isoforms of PDE8A transcripts. By definition the relative proportion of RNA editing at a given editing ‘site’ represents the sum of editing modifications measured at this unique genomic coordinate. Oppositely a mRNA isoform is a unique molecule that may or may not contain multiple editing modifications on the same transcript. Example given, PDE8A mRNA isoform BC contains a modification on both site B and site C within the same transcript.
Reverse transcription was carried out using the Takara kit (PrimeScript RT, Takara, ref#RR037A). The resulting cDNA was combined with TaqMan universal PCR Master Mix (Applied Biosystems, ref#4369016) and with the following specific gene probes: ADAR1a (Hs01020780), ADAR1b (Hs01017596), ADAR2 (Hs00210562), PDE8A (Hs00400174), GAPDH (Hs02758991), β2M (Hs00984230), HPRT1 (Hs02800695), PGK (Hs99999906) and TBP (Hs00427620) (Applied Biosystems, from Life Technologies) in 20 μl final volume. Quantitative PCR were performed in 96-well plates on StepOnePlus real-time PCR instrument (Applied Biosystems) or in 384-well plates on LightCycler 480 real-time PCR instrument (Roche). For the study performed with depressive patients and suicide attempters, quantification of target gene expression in all patients was normalized to GAPDH and β2M expression and changes in target gene expression in each sample were calculated by 2−ΔΔCt. For the study performed with chronic hepatitis C virus (HCV) patients, the analysis was performed using a second derivative absolute quantification, normalized by the geometric mean of four housekeeping genes (GAPDH, HPRT1, PGK and TBP).
All statistics and figures were computed with the “R/Bioconductor” statistical open source software and GraphPad Prism software (version 7.0) [12,13]. Biomarkers (i.e RNA editing sites and isoforms of PDE8A and mRNA expression of ADARs) values are usually presented as mean±standard error of the mean (SEM). A differential analysis was carried out using the Mann-Whitney test and a p-value below 0.05 was considered as statistically significant. All data distributions are illustrated as medians and barplots or boxplots for each significant biomarker.
The relative proportion of RNA editing, on both sites and isoforms, were analyzed by adjusting to the relative transcript level of the PDE8A gene. The adjusted RNA editing values were calculated as following:
Adjusted editing value*=(RNA editing value×relative transcript level)/100
The biomarker diagnostic performance could be characterized by: sensitivity, which represents its ability to detect the ‘suicide attempters’ group and specificity which represents its ability to detect the ‘affective control’ group. The results of the evaluation of a diagnostic test can be summarized in a 2×2 contingency table comparing these two well-defined groups. By fixing a cut-off, the two groups could be classified into categories according to the results of the test, categorized as either positive or negative. Given a particular biomarker, we can identify a number of a patients with a positive test result among the suicide attempters group (the “True Positive”: TP) and b patients with a negative test result among the ‘affective control’ group (the “True Negative”: TN). In the same fashion, c patients with a negative test result among the ‘suicide attempters’ group (the “False Negative”: FN) and d patients with a positive test result among the ‘affective control’ group (the “False Positive”: FP) are observed. Sensitivity is defined as TP/(TP+FN); which is herein referred to as the “true positive rate”. Specificity is defined as TN/(TN+FP); which is herein referred to as the “true negative rate”.
The accuracy of each biomarkers and its discriminatory power was evaluated using a Receiving Operating Characteristics (ROC) analysis. ROC curves are the graphical visualization of the reciprocal relation between the sensitivity (Se) and the specificity (Sp) of a test for various values.
In addition, all biomarkers were combined with each other to evaluate the potential increase in sensibility and specificity using a multivariate approaches as for example mROC program or logistic regression [14]. mROC is a dedicated program to identify the linear combination [15,16], which maximizes the AUC (Area Under the Curve) ROC [17]. The equation for the respective combination is provided and can be used as a new virtual marker Z, as follows:
Z=a×biomarker1+b×biomarker2+c×biomarker3,
where a, b, c are calculated coefficients and biomarkers 1, 2, 3 are the level of biomarker.
Logistic regression model is applied to estimate the relative mood disorder risk using different combination of editing site(s) and/or isoforms and/or ADARs gene expression values for a patient.
A K-medians or K-means approach [18] was used to identify clusters of patients from the Interferon study. As example, the K-medians analysis was computed with the MEV v4.9 software (http://www.tm4.org/mev/) and Pearson or Euclidean correlation for distance. So, all patients present in the same cluster were considered different from patients of others clusters.
Characteristics of patients included in the clinical study are shown in Table I. This prospective study enrolled 38 patients that were all diagnosed with a psychiatric disorder:
a group of 18 patients who never attempted suicide (affective controls, AC) compared to a group of 20 patients that all attempted suicide at least once (SA). Patient age ranged from 20 to 77 years old (mean±SD: 50.16±13.5). The cohort was constituted by 9 males (23.68%) and 29 females (76.32%). All the patients presented depressive disorders. Suicide attempt number ranged from 1 to 20 attempts, with a mean±SD of 3.4±4.52.
We previously described a method used to determine the editing profile of the PDE8A mRNA using the capillary electrophoresis single-strand conformation polymorphism (CE-SSCP) technique (Patent PCT/EP2011/060444 filed on Jun. 24, 2011). Here, we developed a new experimental system for quantifying PDE8A RNA editing levels based on next-generation sequencing (NGS) which provides sufficient per-base depth to allow reliable quantification for all sites studied. Since this methodology is PCR based, we, first, selected several primer pairs to amplify the PDE8A mRNA region of interest (Table II). Different primer combinations meeting the following selection criteria to specifically amplify the region were tested: 1) the oligo's should be between 18-27 nucleotides long, 2) with preferentially a melting temperature surrounding 60° C. (57-63° C.), 3) an optimal GC content surrounding 50%, 4) a maximum allowable length of 5 mononucleotide repeat and 5) specifically amplify the region of interest depicted in
Orlowski and collaborators have previously identified eight editing sites (A to H) in intron 9 of the PDE8A human gene (see Table III) [10]. Later, we identified six additional editing sites (I to N) in this same region (Patent PCT/EP2011/060444 filed on Jun. 24, 2011). Several studies pointed out that most ADAR activity takes place in clusters [19,20]. Not surprisingly, using NGS-based sequencing on SH-SY5Y human neuroblastoma cell line, we confirmed previously identified editing sites and identified new A- to I-editing sites in intron 9 of the PDE8A human gene. These new edited sites were called O, P, Q, R, S, T, U, V, W, X, Y, Z and ZZ (see Table III,
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
On table IV and
Using TaqMan® real-Time PCR assay, we analyzed ADAR1a, ADAR1b and ADAR2 mRNA gene expression by the so-called delta delta CT method (
Likewise, an alteration of PDE8A expression level was observed in the SA group compared to the AC one (
A) PDE8A Site B mRNA Editing
Using NGS assay, we analyzed PDE8A mRNA editing profile in AC versus SA patients. As shown in
PDE8A mRNA B site is higher in SA compared to AC. In the AC (n=18), PDE8A edited transcripts were in a range of 11.2-21.8%, with a mean value of 17.4% (SD±2.8%). In the SA (n=20), the level of edited variants was in a range of 12.3-26.7%, with a mean value of 20.2% (SD±3.7%). The values for AC versus SA were significantly different (p=0.01). Further, we adjusted the relative proportion of RNA editing on the B site of PDE8A gene to the relative expression level of PDE8A mRNA (site B*). Results are presented in
B) Non-Edited PDE8A Transcript
We analysed the relative proportion of the Non-edited PDE8A transcript in affective controls (AC) and suicide attempters (SA). The relative proportion of the Non-edited PDE8A transcript is higher in AC compared to SA. In the AC, the relative proportion of PDE8A Non-edited transcripts was in a range of 77.1-87.9%, with a mean value of 81.7% (SD±2.9%). In the SA, the level of the Non-edited transcript was in a range of 71.5-87.2%, with a mean value of 78.9% (SD±3.8%). The values for AC versus SA were significantly different (p=0.0094).
We evaluated the diagnostic performance using the expression of ADARs and PDE8A (see Table V(A)), adjusted PDE8A mRNA editing on different sites (site A* to G*, Z* and ZZ*, table V(B)) and on different isoforms (Table V(C)) as biomarkers for suicidality using the receiver-operating characteristic (ROC) curve. Table V shows the results for each individual biomarker. We found the greatest area under the curve (AUC) for PDE8A site B* mRNA editing with a value of 0.878 (Table VB). Same results were obtained using PDE8A mRNA isoform B (Table V(C)).
Tables V(A)-V(C): Diagnostic performances of the relative expression of ADARs and of PDE8A individual editing site and isoform. The table V(A) represents the diagnostic performances of the relative expression of ADAR1a, ADAR1b, ADAR2 and PDE8A. The table V(B) represents the diagnostic performances of individual editing site of PDE8A. The table V(C) represents the diagnostic performances of individual editing isoform of PDE8A or the non-edited transcript (Ne). Only the most relevant editing isoforms and editing sites defined as having a p-value<0.1 are presented, p-values were calculated using the Mann-Whitney test. The symbol * indicate that PDE8A editing site or editing isoforms are adjusted to its mRNA relative expression.
We further examined whether a combinatorial approach including PDE8A mRNA editing along with other biomarkers such as other PDE8A mRNA editing sites or isoforms and ADARs mRNA expression could enhance our ability to predict future suicide.
For example, we found that the mROC curve improved from an AUC of 0.878 with PDE8A site B* editing alone, to an AUC of 0.956 by adding PDE8A site A* mRNA editing along with ADAR1a and ADAR2 mRNA expression (see Table VI and VII, lane 6 and
Statistical analysis using logistic regression model or mROC approach yielded similar results (Table VIII,
Major depression during IFN-α therapy for chronic hepatitis C virus (HCV) infection is common, with an incidence up to 45% [21]. This model represents a unique opportunity to assess individuals for depression and/or drug-induced psychiatric adverse effects within a short period of time (weeks). The longitudinal study has the major advantage that each patient acts as his own reference control ruling out genetic variability and environmental influence. In addition, ADAR1a is inducible by interferon stimulation [22]. In this study, we investigate whether PDE8A mRNA editing is modified during IFN-α treatment in HCV patients. 6 patients with HCV were assessed prospectively, 4 weeks before treatment, and every two weeks over 12-weeks of IFN-α and ribavirin treatment (
Suicide attempt constitutes one of the strongest risk factors for future attempts [23,24]. During one year after the suicide, the rate of suicide reattempts range from 12-15% [25, 26]. In a follow up study including 28 patients (table I(B), we analyzed the clinical evaluations of these patients at initial visit and 6 months later. We divided the whole group in 2 different subgroups; the first group (n=20) that did not reattempt suicide (NRSA) and the second group of patients (n=8) who have attempted suicide (RSA) at least once during the period. The average number of suicide attempts in this group during the 6 months follow-up period was 1.875. Three independent clinical evaluation scores (Hamilton, MADRS and BDI) were used to monitor the patients and the BDI score showed a significant improvement during follow up in the NRSA group (
Major depression during IFN-α therapy for chronic hepatitis C virus (HCV) infection is common, with an incidence up to 45% [21]. This model represents a unique opportunity to assess individuals for depression and/or drug-induced psychiatric adverse effects within a short period of time (weeks). In this study, we took advantage of the well-documented and well-characterized mood alterations observed in hepatitis C infected patients undergoing antiviral therapy with IFN and Ribavirin. A small cohort of ten individuals with hepatitis C virus without prior records for psychiatric disorders was recruited over different medical hospitals in France. At inclusion, patients underwent harmonized psychiatric assessment and at repeated interval during the course of treatment. In this particular setting, every patient acts as its own control and evolution of the patient can be monitored over time. All patients have been clinically evaluated using MADRS (Montgomery and Asberg Depression Scale), MINI (Mini International Neuropsychiatric Interview), MAThyS (Multidimensional Assessment of Thymic States scale) and YMRS (Young Mania Rating Scale) tests. Psychiatric evaluation clearly showed modifications of the mood such as irritability and/or depressive states as measured by abovementioned tests. To further study in more detail the events occurring in each patient treated with IFN, we analyzed MADRS scores during the 12 weeks of the treatment. We considered every patient with a high MADRS score combined with emotional reactivity as undergoing a mood alteration (depression). Out of the 10 patients, three patients were classified as having a depressive episode.
The longitudinal study has the major advantage that each patient acts as his own reference control ruling out genetic variability and environmental influence. In addition, ADAR1a is inducible by interferon stimulation [22]. While ADAR2 gene expression did not change during the course of the treatment, a clear upregulation of ADAR1a and ADAR1b transcript level was observed as early as two weeks after onset of therapy (
| Number | Date | Country | Kind |
|---|---|---|---|
| 16181619.4 | Jul 2016 | EP | regional |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/EP2017/069250 | 7/28/2017 | WO | 00 |
