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Use of electroretinography (ERG) for the assessment of psychiatric disorders

a psychiatric disorder and electroretinography technology, applied in the field of mental disorders, can solve the problems of no reliable diagnostic test for psychiatric disorders, hallucinations, delusions,

Inactive Publication Date: 2016-02-04
UNIV LAVAL
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

The present invention is about using markers of retinal function, specifically electroretinography (ERG) parameters, to diagnose, screen, and predict the response to treatment in patients with psychiatric disorders. The inventors have shown that by analyzing these markers, specific patterns can be identified that are associated with different types of mental disorders and with predisposition to them. The use of ERG parameters can also help to identify and differentiate between different types of mental diseases. The invention can also be used to monitor the condition of patients with these disorders and to predict the response to treatment. Overall, the invention provides a useful tool for diagnosis and management of psychiatric disorders.

Problems solved by technology

Psychotic symptoms include delusions, hallucinations, disorganized thinking and speech, and bizarre and inappropriate behavior.
There is no reliable diagnostic test for psychiatric disorders.

Method used

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  • Use of electroretinography (ERG) for the assessment of psychiatric disorders
  • Use of electroretinography (ERG) for the assessment of psychiatric disorders
  • Use of electroretinography (ERG) for the assessment of psychiatric disorders

Examples

Experimental program
Comparison scheme
Effect test

example 1

Materials and Methods

[0534]Study subjects for the Schizophrenia studies. The characteristics of the affected SZ patients and control subjects, are depicted in Table 1

TABLE 1Characteristics of the sample: 150 SZ cases and 150 controlsSZ casesControls(N = 150)(N = 150)Mean (SD) or N (%)Age39.4 (9.9) 40.6 (9.5)% Male*80.762Age of onset25.0 (6.4) —Duration of illness13.7 (9.3) —IQ b, *82.6 (12.9)102.9 (11.7)GAS-S (T3) a52.5 (8.8) —GAS-S (T1) a29.3 (10.1)—Olanzapine28 (19%)0Quetiapine32 (21%)0Clozapine45 (30%)0Risperidone32 (21%)0Abilify ®12 (8%) 0Lithium7 (5%)0Synthroid 1 (.7%)0*Comparison between groups: p a GAS-S for lifetime Global Assessment Scale-Severity, at two different period: - the time of first admission or first episode of illness (T1), - the last 6 to 24 months before the ERG recording (T3).b The IQ was measured on 127 SZ, and 121 controls.

[0535]ERG procedure. The ERG technique and protocol used in the present studies is as described in Hébert et al. (Hébert, M., et al. Bio...

example 2

Assessment of ERG Parameters in SZ Patients and Controls

[0546]The comparison of SZ patients to controls on each of the eight ERG parameters is depicted in Table 2. As can be seen in the section “Effect size (p-value)” of Table 2, the SZ subjects differ significantly (p<0.0001) from controls on at least five ERG parameters (cone a-wave amplitude, cone b-wave amplitude, cone b-wave implicit time, rod a-wave amplitude and rod b-wave amplitude) with effect sizes ranging from 0.49 to 1.31 (in absolute value). These univariate results show that prediction modeling based on multiple logistic regression may detect a judicious subset of ERG parameters that best predict the group membership, as detailed below.

TABLE 2Comparison of the 150 SZ patients to 150 controls on ERG parametersERG FlashMean (SD)Effectparametersintensitya150 SZ150 CTsizeP-valueConesa-Wave int112.58 15.60 0.64amplitude(5.2)(4.7)a-Wave 3-int14.60 14.80 0.210.064implicit time(1.0)(0.9)b-Wave Vmax83.25 92.45 0.51amplitude(19....

example 3

ERG Profile and Response to Psychotropic Treatment

[0558]The response to antipsychotic treatment in patients of the different ERG strata is depicted in Table 4. The Chi-square test for this 2×2 table revealed a significant p-value (p=0.0015) indicating that the strata are related to the response to psychotropic treatment. Indeed, stratum 1 contains SZ subjects having a very high probability (0.76) of being good responders, while strata 2 or 3 predict rather low chance (0.31 or 0.35) to respond well.

TABLE 4Response to antipsychotic treatment depends on ERG strataPoor-ERGGoodintermediateStratumresponseresponseTotal176% (22)24% (7) 29231% (8) 69% (18)26338% (20)62% (33)53458% (14)42% (10)24X23 = 15.4, p = .0015

[0559]In univariate analysis, when, on each ERG parameter, the good responders to any medication (antipsychotic treatment) were compared to the poor-intermediate responders, significant differences were observed on two ERG parameters (cone a-wave amplitude, with an effect size of ...

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Abstract

Methods for the diagnosis, prognosis, patient stratification and prediction of pharmacological response in patients afflicted by psychiatric disorders based on electroretinography (ERG) parameters are described.

Description

CROSS REFERENCE TO RELATED APPLICATIONS[0001]The present application claims the benefit of U.S. Provisional Application Ser. No. 61 / 781,520 filed on Mar. 14, 2013, which is incorporated herein by reference in its entirety.TECHNICAL FIELD[0002]The present invention generally relates to mental disorders, such as psychiatric disorders, and more particularly to the use of biomarkers for the screening, prognosis (predisposition or susceptibility), diagnosis, differential diagnosis, monitoring and / or stratification of patients afflicted by such disorders, as well as the use of different biomarkers for the prediction of pharmacological response and pharmacodynamics in patients afflicted by such disorders.BACKGROUND ART[0003]Psychiatric disorders are characterized by alterations in thinking, mood or behaviour—or some combination thereof—associated with significant distress and impaired functioning.[0004]Schizophrenia (SZ) and related disorders such as brief psychotic disorder, delusional di...

Claims

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Application Information

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Patent Type & Authority Applications(United States)
IPC IPC(8): A61B5/0496A61B5/00A61B5/16
CPCA61B5/0496A61B5/165A61B5/7246A61B5/7275A61B5/4848A61B5/16A61B5/72A61B5/167G16H50/20A61B5/4088A61B5/163A61B5/398A61B3/10
Inventor HEBERT, MARCMAZIADE, MICHELMERETTE, CHANTAL
Owner UNIV LAVAL
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