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

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.

What is claimed is: 
     
         1 . A method of identifying a model, based on one or more ERG parameters, that permits to discriminate between a first group of subjects and a second group of subjects that differ by at least one characteristics, wherein said first group and/or second group of subjects suffer from a psychiatric disorder or a has a predisposition thereto, said method comprising
 (a) measuring a plurality of ERG parameters in said subjects;   (b) performing a logistic regression analysis using the plurality of ERG parameters measured to identify a model that permits to discriminate between a first group and a second group of subjects.   
     
     
         2 . The method of  claim 1 , wherein said logistic regression analysis is multiple stepwise logistic regression analysis. 
     
     
         3 . The method of  claim 1  or  2 , wherein logistic regression analysis includes age, gender, or both age and gender as covariate(s). 
     
     
         4 . The method of any one of  claims 1  to  3 , wherein both age and gender are included as covariate in said analysis. 
     
     
         5 . The method of any one of  claims 1  to  4 , wherein said plurality of ERG parameters comprises at least two of the following parameters: the cone a-Wave amplitude (phAamp), the cone a-Wave implicit time (phAlat), the cone b-Wave amplitude (phBamp), the cone b-Wave implicit time (phBlat), the rod a-Wave amplitude (scAamp), the rod a-Wave implicit time (scAlat), rod b-Wave amplitude (scBamp), the rod b-Wave implicit time (scBlat), the LogK and the Vmax. 
     
     
         6 . The method of  claim 5 , wherein said plurality of ERG parameters comprises at least four of the following parameters: the cone a-Wave amplitude (phAamp), the cone a-Wave implicit time (phAlat), the cone b-Wave amplitude (phBamp), the cone b-Wave implicit time (phBlat), the rod a-Wave amplitude (scAamp), the rod a-Wave implicit time (scAlat), rod b-Wave amplitude (scBamp) and the rod b-Wave implicit time (scBlat), the LogK and the Vmax. 
     
     
         7 . The method of  claim 6 , wherein said plurality of ERG parameters comprises all the following parameters: the cone a-Wave amplitude (phAamp), the cone a-Wave implicit time (phAlat), the cone b-Wave amplitude (phBamp), the cone b-Wave implicit time (phBlat), the rod a-Wave amplitude (scAamp), the rod a-Wave implicit time (scAlat), rod b-Wave amplitude (scBamp) and the rod b-Wave implicit time (scBlat). 
     
     
         8 . The method of any one of  claims 1  to  7 , wherein said at least one characteristics comprises the type of psychiatric disorder or predisposition thereto, and wherein the first group of subjects suffer from a first psychiatric disorder or has a predisposition thereto and said second group of subjects suffer from a second psychiatric disorder or has a predisposition thereto. 
     
     
         9 . The method of  claim 8 , wherein said first psychiatric disorder is schizophrenia (SZ). 
     
     
         10 . The method of  claim 8  or  9 , wherein said second psychiatric disorder is bipolar disorder (BP). 
     
     
         11 . The method of  claim 8  or  9 , wherein said second psychiatric disorder is major depressive disorder (MDD). 
     
     
         12 . The method of  claim 8 , wherein said first psychiatric disorder is BP and said second psychiatric disorder is MDD. 
     
     
         13 . The method of any one of  claims 1  to  7 , wherein said at least one characteristics comprises the presence or absence of the psychiatric disorder or predisposition thereto, and wherein said first group of subjects suffer from a psychiatric disorder or has a predisposition thereto and said second group of subjects do not suffer from a psychiatric disorder or do not have a predisposition thereto. 
     
     
         14 . The method of  claim 13 , wherein said first group of subjects suffer from SZ or have a predisposition thereto. 
     
     
         15 . The method of  claim 13 , wherein said first group of subjects suffer from BP or have a predisposition thereto. 
     
     
         16 . The method of  claim 13 , wherein said first group of subjects suffer from MDD or have a predisposition thereto. 
     
     
         17 . The method of any one of  claims 1  to  7 , wherein the at least one characteristics comprises the response to a psychotropic medication, and wherein said at least one characteristics comprises the response to a psychotropic medication, and wherein said first group of subjects are good responders to a psychotropic medication and said second group of subjects are poor responders to said psychotropic medication. 
     
     
         18 . The method of  claim 17 , wherein said psychotropic medication is an antipsychotic medication or a mood stabilizer medication. 
     
     
         19 . The method of  claim 17  or  18 , wherein said psychotropic medication comprises quetiapine. 
     
     
         20 . The method of  claim 17  or  18 , wherein said psychotropic medication comprises aripiprazole. 
     
     
         21 . The method of  claim 17  or  18 , wherein said psychotropic medication comprises olanzapine. 
     
     
         22 . The method of  claim 17  or  18 , wherein said psychotropic medication comprises lithium. 
     
     
         23 . The method of  claim 17  or  18 , wherein said psychotropic medication comprises clozapine. 
     
     
         24 . The method of any one of  claims 1  to  23 , further comprising determining the accuracy, sensitivity and/or specificity of the model. 
     
     
         25 . The method of  claim 24 , wherein the accuracy, sensitivity and/or specificity of the model is determined by calculating the Area Under the Receiver Operating Curve (AU-ROC). 
     
     
         26 . A method of determining the likelihood that a test subject belongs to a first group of subjects or a second group of subjects that differ by at least one characteristics, said method comprising
 (a) measuring at least one ERG parameter in said test subject;   (b) analysing the at least one ERG parameter measured using the model identified according to the method of any one of  claims 1  to  23  to determine the likelihood that the test subject belongs to the first group or second group of subjects.   
     
     
         27 . A method for determining whether a subject suffers from schizophrenia (SZ) or has a predisposition thereto, said method comprising:
 (a) measuring one or more ERG parameters in the subject;   (b) calculating an SZ probability score by adjusting the value of the one or more of the ERG parameters by one or more transformation analyses; and   (c) determining whether the subject suffers from SZ or has a predisposition thereto based on the SZ probability score.   
     
     
         28 . The method of  claim 27 , wherein the one or more transformation analyses comprise (i) adjusting the value of the one or more of the ERG parameters by appropriate weighting coefficients to produce a weighted score for each ERG value, and (ii) combining the weighted score for each ERG value to generate the SZ probability score. 
     
     
         29 . The method of  claim 28 , wherein the one or more transformation analyses comprise applying the value of the one or more of the ERG parameters to a pre-determined logistic regression model. 
     
     
         30 . The method of  claim 28 , wherein the logistic regression model was determined using ERG parameter values measured in a first population of SZ subjects and a second population of control subjects. 
     
     
         31 . The method of  claim 30 , wherein the logistic regression model includes age, gender, or both age and gender, as covariate(s). 
     
     
         32 . The method of  claim 31 , wherein the logistic regression model includes both age and gender as covariates. 
     
     
         33 . The method of  claim 31  or  32 , wherein the SZ probability score is determined using at least one of logistic regression models 1, 2a-2h, 3, 4, 5 or 6 set forth in Table 3A or models 1, 2a-2h, 3, 4 or 5 set forth in Table 13A. 
     
     
         34 . The method of  claim 33 , wherein said SZ probability score is determined using logistic regression model 1 set forth in Table 3A that has the formula below:
   SZ probability score=Exp[−19.03−0.15(gender)−0.04(age)+1.61(phBlat)−0.86(scAlat)−0.02(scBamp)−0.11(phAamp)−0.65(phAlat)+0.10(scBlat)]/(1+Exp[−19.03−0.15(gender)−0.04(age)+1.61(phBlat)−0.86(scAlat)−0.02(scBamp)−0.11(phAamp)−0.65(phAlat)+0.10(scBlat)])
   in which   Gender=1 if the subject is a female and 0 if the subject is a male;   phBlat=cone b-Wave implicit time, average of three intensities (13.33, 23.71 and 50 cd.s/m 2 ; 3-int);   scAlat=rod a-Wave implicit time, flash intensity of 1 cd×s/m 2  (int2);   scBamp=rod b-Wave amplitude, flash intensity of 1 cd×s/m 2  (int2);   phAamp=cone a-Wave amplitude, fixed intensity of 7.5 cd×s/m 2 (int1);   phAlat=cone a-Wave implicit time, average of three intensities (13.33, 23.71 and 50 cd.s/m 2 ; 3-int); and   scBlat=rod b-Wave implicit time, flash intensity of 1 cd×s/m 2 (int2).   
     
     
         35 . The method of  claim 33 , wherein said SZ probability score is determined using logistic regression model 1 set forth in Table 14A that has the formula below:
   SZ probability score=Exp[−51.58−0.17(gender)+8.54(phBlat)−4.03(scAlat)−0.11(scBamp)−3.96(phBlat)+0.09(phBamp)]/(1+Exp[−51.58−0.17(gender)+8.54(phBlat)−4.03(scAlat)−0.11(scBamp)−3.96(phBlat)+0.09(phBamp)])
   in which   Gender=1 if the subject is a female and 0 if the subject is a male;   phBlat=cone b-Wave implicit time, average of three intensities (13.33, 23.71 and 50 cd.s/m 2 ; 3-int);   scAlat=rod a-Wave implicit time, flash intensity of 1 cd×s/m 2  (int2);   scBamp=rod b-Wave amplitude, flash intensity of 1 cd×s/m 2  (int2);   phAamp=cone a-Wave amplitude, fixed intensity of 7.5 cd×s/m 2 (int1);   phAlat=cone a-Wave implicit time, average of three intensities (13.33, 23.71 and 50 cd.s/m 2 ; 3-int); and   scBlat=rod b-Wave implicit time, flash intensity of 1 cd×s/m 2 (int2).   
     
     
         36 . A method for determining whether a subject suffers from a bipolar disorder (BP) or has a predisposition thereto, said method comprising
 (a) measuring one or more ERG parameters in the subject;   (b) calculating a BP probability score by adjusting the value of one or more of the ERG parameters by one or more transformation analyses; and   (c) determining whether the subject suffers from BP or has a predisposition thereto based on the BP probability score.   
     
     
         37 . The method of  claim 36 , wherein the one or more transformation analyses comprise (i) adjusting the value of the one or more of the ERG parameters by appropriate weighting coefficients to produce a weighted score for each ERG value, and (ii) combining the weighted score for each ERG value to generate the BP probability score. 
     
     
         38 . The method of  claim 37 , wherein the one or more transformation analyses comprise applying the value of the one or more of the ERG parameters to a pre-determined logistic regression model. 
     
     
         39 . The method of  claim 38 , wherein the logistic regression model was determined using ERG parameter values measured in a first population of BP subjects and a second population of control subjects. 
     
     
         40 . The method of  claim 39 , wherein the logistic regression model includes age, gender, or both age and gender, as covariate(s). 
     
     
         41 . The method of  claim 40 , wherein the logistic regression model includes both age and gender as covariates. 
     
     
         42 . The method of  claim 40  or  41 , wherein the BP probability score is determined using at least one of logistic regression models 1, 2a-2h, 3, 4, 5 or 6 set forth in Table 9A or models. 
     
     
         43 . The method of  claim 42 , wherein said BP probability score is determined using logistic regression model 1 set forth in Table 9A that has the formula below:
   BP probability score=Exp[−14.15+0.57(gender)−0.002(age)+1.46(phBlat)−1.24(scAlat)−0.03(scBamp)+0.17(scBlat)+0.04(phBamp)−0.55(phAlat)]/(1+Exp[−14.15+0.57(gender)−0.002(age)+1.46(phBlat)−1.24(scAlat)−0.03(scBamp)+0.17(scBlat)+0.04(phBamp)−0.55(phAlat)])
   in which:   gender=1 if the subject is a female and 0 if the subject is a male;   phBlat=cone b-Wave implicit time, average of three intensities (3-int);   scAlat=rod a-Wave implicit time, flash intensity of 1 cd×s/m 2  (int2);   scBamp=rod b-Wave amplitude, flash intensity of 1 cd×s/m 2 (int2);   scBlat=rod a-Wave implicit time, flash intensity of 1 cd×s/m 2  (int2);   phBamp=cone b-Wave amplitude, peak maximal response (Vmax);   phAlat=cone a-Wave implicit time, average of three intensities (3-int).   
     
     
         44 . A method for predicting if a subject suffering from a psychiatric disorder or having a predisposition thereto is likely to respond to a psychotropic medication, the method comprising:
 (a) measuring one or more ERG parameters in the subject;   (b) calculating a psychotropic medication response probability score by adjusting the value of one or more of the ERG parameters by one or more transformation analyses; and   (c) determining whether the subject is likely to respond to the psychotropic medication based on the psychotropic medication response probability score.   
     
     
         45 . The method of  claim 44 , wherein the psychiatric disorder is SZ. 
     
     
         46 . The method of  claim 44  or  45 , wherein the psychotropic medication is an antipsychotic medication. 
     
     
         47 . The method of any one of  claims 44 - 46 , wherein the one or more transformation analyses comprise (i) adjusting the value of the one or more of the ERG parameters by appropriate weighting coefficients to produce a weighted score for each ERG value, and (ii) combining the weighted score for each ERG value to generate the psychotropic medication response probability score. 
     
     
         48 . The method of  claim 47 , wherein the one or more transformation analyses comprise applying the value of the one or more of the ERG parameters to a pre-determined logistic regression model. 
     
     
         49 . The method of  claim 48 , wherein the logistic regression model was determined using ERG parameter values measured in a first population of psychotropic medication responsive subjects and a second population of psychotropic medication non-responsive subjects. 
     
     
         50 . The method of  claim 49 , wherein the logistic regression model includes age, gender, or both age and gender, as covariate(s). 
     
     
         51 . The method of  claim 50 , wherein the logistic regression model includes both age and gender as covariates. 
     
     
         52 . The method of  claim 50  or  51 , wherein the psychotropic medication responsive probability score is determined using at least one of logistic regression models 1 or 2a-2h set forth in Table 6A. 
     
     
         53 . The method of  claim 52 , wherein said psychotropic medication response probability score is determined using logistic regression model 1 set forth in Table 6A that has the formula below:
   Psychotropic medication response probability score=Exp[4.08−0.03(gender)+0.04(age)−0.29(scAlat)+0.10(phAamp)]/(1+Exp[4.08−0.03(gender)+0.04(age)−0.29(scAlat)+0.10(phAamp)])
   in which   Gender=1 if the subject is a female and 0 if the subject is a male;   scAlat=rod a-Wave implicit time, flash intensity of 1 cd×s/m 2  (int2); and   phAamp=cone a-Wave amplitude, fixed intensity of 7.5 cd×s/m 2 (int1).   
     
     
         54 . The method of any one of  claims 46 - 53 , wherein the central core of the psychotropic medication comprises a thienobenzodiazepine. 
     
     
         55 . The method of  claim 54 , wherein the psychotropic medication comprises olanzapine. 
     
     
         56 . The method of  claim 55 , wherein the psychotropic medication comprises olanzapine without clozapine. 
     
     
         57 . The method of any one of  claims 54 - 56 , wherein the psychotropic medication responsive probability score is determined using at least one of logistic regression models 3 or 4a-4h or 5 set forth in Table 6A. 
     
     
         58 . The method of  claim 58 , wherein the psychotropic medication responsive probability score is determined using logistic regression model 3 set forth in Table 6A that has the formula below:
   Psychotropic medication (olanzapine) response probability score=Exp[754.71−42.44(gender)−7.80(age)−36.68(scAlat int2 )+10.44(phAamp)+9.51(scAlat Vmax )]/(1+Exp754.71−42.44(gender)−7.80(age)−36.68(scAlat int2 )+10.44(phAamp)+9.51(scAlat Vmax )])
   in which   Gender=1 if the subject is a female and 0 if the subject is a male;   scAlat int2 =rod a-Wave implicit time, flash intensity of 1 cd×s/m 2  (int2);   phAamp=cone a-Wave amplitude, average of three intensities (13.33, 23.71 and 50 cd.s/m 2 ; 3-int); and   scAlat Vmax =rod a-Wave implicit time, peak maximal response (Vmax).   
     
     
         59 . The method of any one of  claims 44 - 51 , wherein the psychotropic medication comprises quetiapine. 
     
     
         60 . The method of  claim 59 , wherein the psychotropic medication comprises quetiapine without clozapine. 
     
     
         61 . The method of  claim 59  or  60 , wherein said psychotropic medication response probability score is determined using at least one of logistic regression models 6 or 7a-7h set forth in Table 6A. 
     
     
         62 . The method of  claim 61 , wherein the psychotropic medication responsive probability score is determined using logistic regression model 6 set forth in Table 6A that has the formula below:
   Psychotropic medication (quetiapine) response probability score=Exp[2.28−0.50(gender)−0.19(age)+0.34(phBamp)−0.61(scAamp)]/(1+Exp[2.28−0.50(gender)−0.19(age)+0.34(phBamp)−0.61(scAamp)])
   in which   Gender=1 if the subject is a female and 0 if the subject is a male;   phBamp=cone b-Wave amplitude, fixed intensity of 7.5 cd×s/m 2  (int1);   scAamp=rod a-Wave amplitude, peak maximal response (Vmax).   
     
     
         63 . The method of any one of  claims 44 - 51 , wherein the psychotropic medication comprises aripiprazole (Abilify®). 
     
     
         64 . The method of  claim 63 , wherein the psychotropic medication comprises aripiprazole without clozapine. 
     
     
         65 . The method of  claim 63  or  64 , wherein said psychotropic medication response probability score is determined using at least one of logistic regression models 8 or 9a-9g set forth in Table 6A. 
     
     
         66 . The method of  claim 65 , wherein the psychotropic medication responsive probability score is determined using logistic regression model 8 set forth in Table 6A that has the formula below:
   Psychotropic medication (aripiprazole) response probability score=Exp[7.85+1.11(gender)−0.13(age)−0.19(scAamp)]/(1+Exp[7.85+1.11(gender)−0.13(age)−0.19(scAamp)])
   in which   Gender=1 if the subject is a female and 0 if the subject is a male; and   scAamp=rod a-Wave amplitude, peak maximal response (Vmax).   
     
     
         67 . The method of  claim 44 , wherein the psychiatric disorder is SZ or BP. 
     
     
         68 . The method of  claim 67 , wherein the psychotropic medication comprises quetiapine. 
     
     
         69 . The method of  claim 67  or  68 , wherein the one or more transformation analyses comprise (i) adjusting the value of the one or more of the ERG parameters by appropriate weighting coefficients to produce a weighted score for each ERG value, and (ii) combining the weighted score for each ERG value to generate the psychotropic medication response probability score. 
     
     
         70 . The method of  claim 69 , wherein the one or more transformation analyses comprise applying the value of the one or more of the ERG parameters to a pre-determined logistic regression model. 
     
     
         71 . The method of  claim 70 , wherein the logistic regression model was determined using ERG parameter values measured in a first population of psychotropic medication responsive SZ and BP subjects and a second population of psychotropic medication non-responsive SZ and BP subjects. 
     
     
         72 . The method of  claim 71 , wherein the logistic regression model includes age, gender, or both age and gender, as covariate(s). 
     
     
         73 . The method of  claim 72 , wherein the logistic regression model includes both age and gender as covariates. 
     
     
         74 . The method of  claim 72  or  73 , wherein the psychotropic medication responsive probability score is determined using at least one of logistic regression models 15, 16a-16h, 17, 18 or 19 set forth in Table 20A. 
     
     
         75 . The method of  claim 74 , wherein said psychotropic medication response probability score is determined using logistic regression model 15 set forth in Table 20A that has the formula below:
   Psychotropic medication (quetiapine) SZ-BP response probability score=Exp[−69.38−2.73(gender)−0.44(age)+0.69(phAamp)−0.31(phBamp)+4.61(scAlat)+0.15(scBamp)−0.66(scBlat)]/(1+Exp[−69.38−2.73(gender)−0.44(age)+0.69(phAamp)−0.31(phBamp)+4.61(scAlat)+0.15(scBamp)−0.66(scBlat)])
   in which   Gender=1 if the subject is a female and 0 if the subject is a male;   phAamp=cone a-Wave amplitude, peak maximal response (Vmax);   phBamp=cone b-Wave amplitude, fixed intensity of 7.5 cd×s/m 2  (int1);   scAlat=rod a-Wave implicit time, flash intensity of 1 cd×s/m 2  (int2);   scBamp=rod b-Wave amplitude, peak maximal response (Vmax); and   scBlat=rod b-Wave implicit time, flash intensity of 1 cd×s/m 2  (int2).   
     
     
         76 . The method of  claim 44 , wherein the psychiatric disorder is BP. 
     
     
         77 . The method of  claim 76 , wherein the psychotropic medication comprises lithium. 
     
     
         78 . The method of  claim 77 , wherein the psychotropic medication comprises lithium without clozapine. 
     
     
         79 . The method of  claim 77  or  78 , wherein the one or more transformation analyses comprise (i) adjusting the value of the one or more of the ERG parameters by appropriate weighting coefficients to produce a weighted score for each ERG value, and (ii) combining the weighted score for each ERG value to generate the psychotropic medication response probability score. 
     
     
         80 . The method of  claim 79 , wherein the one or more transformation analyses comprise applying the value of the one or more of the ERG parameters to a pre-determined logistic regression model. 
     
     
         81 . The method of  claim 80 , wherein the logistic regression model was determined using ERG parameter values measured in a first population of lithium responsive BP subjects and a second population of lithium non-responsive BP subjects. 
     
     
         82 . The method of  claim 81 , wherein the logistic regression model includes age, gender, or both age and gender, as covariate(s). 
     
     
         83 . The method of  claim 82 , wherein the logistic regression model includes both age and gender as covariates. 
     
     
         84 . The method of  claim 83 , wherein the psychotropic medication responsive probability score is determined using at least one of logistic regression models 10, 11a-11h, 12, 13 or 14 set forth in Table 18A. 
     
     
         85 . The method of  claim 84 , wherein said psychotropic medication response probability score is determined using logistic regression model 10 set forth in Table 18A that has the formula below:
   Psychotropic medication (lithium) response probability score=Exp[−61.12+3.12(gender)+0.10(age)+0.16(phAamp)+1.05(phAlat)−2.49(phBlat Vmax )+0.77(phBlat 3int )+3.17(scAlat)]/(1+Exp[−61.12+3.12(gender)+0.10(age)+0.16(phAamp)+1.05(phAamp)−2.49(phBlat)+0.77(phBlat)+3.17(scAlat)])
   in which   Gender=1 if the subject is a female and 0 if the subject is a male;   phAamp=cone a-Wave amplitude, peak maximal response (Vmax);   phAlat=cone a-Wave implicit time, fixed intensity of 7.5 cd×s/m 2  (int1);   phBlat Vmax =cone b-Wave implicit time, peak maximal response (Vmax)   phBlat 3-int =cone b-Wave implicit time, average of 3 intensities (13.33, 23.71 and 50 cd×s/m 2 ; 3-int); and   scAlat=rod a-Wave implicit time, flash intensity of 1 cd×s/m 2  (int2).   
     
     
         86 . A method for identifying one or more ERG parameters useful for discriminating between subjects suffering from a psychiatric disorder having a likelihood to respond to a psychotropic medication of more than 50%, and subjects suffering from a psychiatric disorder having a likelihood to respond to a psychotropic medication of less than 50%, said method comprising:
 administering said psychotropic drug to a group of subjects;   determining whether the subjects have responded to the psychotropic drug;   measuring one or more ERG parameters in the subjects; and   identifying the one or more ERG parameters that permit to discriminate between the subjects who responded to the psychotropic drug and the subjects who responded poorly to the psychotropic drug.   
     
     
         87 . The method of  claim 86 , wherein the psychiatric disorder is SZ. 
     
     
         88 . The method of  claim 86  or  87 , wherein the psychotropic medication is an antipsychotic medication. 
     
     
         89 . The method of any one of  claims 86 - 88 , wherein said identifying comprises performing a logistic regression using the one or more ERG parameters. 
     
     
         90 . The method of  claim 89 , wherein said logistic regression includes age, gender, or both age and gender, as covariate. 
     
     
         91 . A method for determining whether a subject (i) suffers from SZ or has a predisposition thereto or (ii) suffers from BP or has a predisposition thereto, said method comprises
 (a) measuring one or more ERG parameters in the subject;   (b) calculating an SZ or BP probability score by adjusting the value of one or more of the ERG parameters by one or more transformation analyses; and   (c) determining whether the subject suffers from SZ or BP or has a predisposition thereto based on the SZ or BP probability score probability score.   
     
     
         92 . The method of  claim 91 , wherein the one or more transformation analyses comprise (i) adjusting the value of the one or more of the ERG parameters by appropriate weighting coefficients to produce a weighted score for each ERG value, and (ii) combining the weighted score for each ERG value to generate the SZ or BP probability score. 
     
     
         93 . The method of  claim 91  or  92 , wherein the one or more transformation analyses comprise applying the value of the one or more of the ERG parameters to a pre-determined logistic regression model. 
     
     
         94 . The method of  claim 93 , wherein the logistic regression model was determined using ERG parameter values measured in a first population of SZ subjects and a second population of BP subjects. 
     
     
         95 . The method of  claim 94 , wherein the logistic regression model includes age, gender, or both age and gender, as covariate(s). 
     
     
         96 . The method of  claim 95 , wherein the logistic regression model includes both age and gender as covariates. 
     
     
         97 . The method of  claim 95  or  96 , wherein the SZ or BP probability score is determined using at least one of logistic regression models 7, 8a-8h, 9 or 10 set forth in Table 9A or models 1 or 2a-2h set forth in Table 16A. 
     
     
         98 . The method of  claim 97 , wherein said SZ or BP probability score is determined using logistic regression model 7 set forth in Table 9A that has the formula below:
   SZ probability score=Exp[−4.26−0.91(gender)−0.04(age)−0.18(phAamp)+0.08(scAlat Vmax )+0.01(scBamp)+0.22(scAlat int2 )]/(1+Exp[−4.26−0.91(gender)−0.04(age)−0.18(phAamp)+0.08(scAlat Vmax )+0.01(scBamp)+0.22(scAlat int2 )])
   in which:   Gender=1 if the subject is a female and 0 if the subject is a male;   phAamp=cone a-Wave amplitude, average of three intensities (13.33, 23.71 and 50 cd.s/m 2 ; 3-int);   scAlat Vmax =rod a-Wave implicit time, saturating amplitude at first plateau, flash intensity of 0.1 cd×s/m 2 (Vmax);   scBamp=rod b-Wave amplitude, saturating amplitude at first plateau, flash intensity of 0.1 cd×s/m 2 (Vmax);   scAlat int2 =rod a-Wave implicit time, flash intensity of 1 cd×s/m 2  (int2).   
     
     
         99 . The method of  claim 98 , wherein said SZ or BP probability score is determined using logistic regression model 1 set forth in Table 16A that has the formula below:
   SZ probability score=Exp[−5.31−1.37(gender)−0.20(age)−0.36(phAamp)+0.08(scBlat)]/(1+Exp[−5.31−1.37(gender)−0.20(age)−0.36(phAamp)+0.08(scBlat)])
   in which:   Gender=1 if the subject is a female and 0 if the subject is a male;   phAamp=cone a-Wave amplitude, at fixed intensity of 7.5 cd×s/m 2  (int1);   scBlat=rod b-Wave implicit time, saturating amplitude at first plateau, flash intensity of 0.1 cd×s/m 2 (Vmax).   
     
     
         100 . A method for determining whether an asymptomatic young subject is at risk of suffering from a psychiatric disorder, said method comprising
 (a) measuring one or more ERG parameters in the subject;   (b) calculating a psychiatric disorder risk probability score by adjusting the value of one or more of the ERG parameters by one or more transformation analyses; and   (c) determining whether the asymptomatic young subject is at risk of suffering from a psychiatric disorder based on said psychiatric disorder risk probability score.   
     
     
         101 . The method of  claim 100 , wherein said subject is 25 years old or less. 
     
     
         102 . The method of  claim 101 , wherein said subject is 20 years old or less. 
     
     
         103 . The method of any one of  claims 100 - 102 , wherein said psychiatric disorder is SZ or BP. 
     
     
         104 . The method of any one of  claims 100 - 103 , wherein the one or more transformation analyses comprise (i) adjusting the value of the one or more of the ERG parameters by appropriate weighting coefficients to produce a weighted score for each ERG value, and (ii) combining the weighted score for each ERG value to generate the psychiatric disorder risk probability score. 
     
     
         105 . The method of  claim 104 , wherein the one or more transformation analyses comprise applying the value of the one or more of the ERG parameters to a pre-determined logistic regression model. 
     
     
         106 . The method of  claim 105 , wherein the logistic regression model was determined using ERG parameter values measured in a first population of nonaffected high-risk offspring (HR) of SZ or BP subjects and a second population of control subjects. 
     
     
         107 . The method of  claim 106 , wherein the logistic regression model includes age, gender, or both age and gender, as covariate(s). 
     
     
         108 . The method of  claim 107 , wherein the logistic regression model includes both age and gender as covariates. 
     
     
         109 . The method of  claim 107  or  108 , wherein the psychiatric disorder risk probability score is determined using at least one of logistic regression models 1, 2a-2h or 3 set forth in Table 12A. 
     
     
         110 . The method of  claim 109 , wherein said psychiatric disorder risk probability score is determined using logistic regression model 1 set forth in Table 12A that has the formula below:
   Psychiatric disorder risk probability score=Exp[−16.35+0.36(gender)+0.20(age)−0.05(scBamp)+0.50(phBlat)+0.07(phBamp)]/(1+Exp[−16.35+0.36(gender)+0.20(age)−0.05(scBamp)+0.50(phBlat)+0.07(phBamp)])
   
       in which:
 Gender=1 if the subject is a female and 0 if the subject is a male; 
 scBamp=rod b-Wave amplitude, flash intensity of 1 cd×s/m 2  (int2); 
 phBlat =cone b-Wave implicit time, peak maximal response (Vmax); and 
 phBamp=cone b-Wave amplitude, peak maximal response (Vmax). 
 
     
     
         111 . A method for determining whether a subject suffers from major depression (MDD) or has a predisposition thereto, said method comprising
 (a) measuring one or more ERG parameters in the subject;   (b) calculating an MDD probability score by adjusting the value of one or more of the ERG parameters by one or more transformation analyses; and   (c) determining whether the subject suffers from MDD or has a predisposition thereto based on said MDD probability score.   
     
     
         112 . The method of  claim 111 , wherein the one or more transformation analyses comprise (i) adjusting the value of the one or more of the ERG parameters by appropriate weighting coefficients to produce a weighted score for each ERG value, and (ii) combining the weighted score for each ERG value to generate the SZ probability score. 
     
     
         113 . The method of  claim 111  or  112 , wherein the one or more transformation analyses comprise applying the value of the one or more of the ERG parameters to a pre-determined logistic regression model. 
     
     
         114 . The method of  claim 113 , wherein the logistic regression model was determined using ERG parameter values measured in a first population of SZ subjects and a second population of control subjects. 
     
     
         115 . The method of  claim 114 , wherein the logistic regression model includes age, gender, or both age and gender, as covariate(s). 
     
     
         116 . The method of  claim 115 , wherein the logistic regression model includes both age and gender as covariates. 
     
     
         117 . A method for identifying one or more ERG parameters useful for discriminating between subjects suffering from MDD or predisposed thereto, and non-MDD subjects, said method comprising:
 selecting a group of subjects suffering from MDD;   selecting a group of non-MDD subjects;   measuring one or more ERG parameters in the subjects; and   identifying the one or more ERG parameters that permit to discriminate between the subjects suffering from MDD and the non-MDD subjects.   
     
     
         118 . The method of  claim 117 , wherein said identifying comprises performing a logistic regression using the one or more ERG parameters. 
     
     
         119 . The method of  claim 118 , wherein said logistic regression includes age, gender, or both age and gender, as covariate. 
     
     
         120 . A method for determining whether a subject suffers from or is predisposed to suffering from schizophrenia (SZ) or major depression (MDD), said method comprising
 (a) measuring one or more ERG parameters in the subject;   (b) calculating an SZ or MDD probability score by adjusting the value of one or more of the ERG parameters by one or more transformation analyses; and   (c) determining whether the subject suffers from SZ or MDD or has a predisposition thereto based on said SZ or MDD probability score.   
     
     
         121 . The method of  claim 120 , wherein the one or more transformation analyses comprise (i) adjusting the value of the one or more of the ERG parameters by appropriate weighting coefficients to produce a weighted score for each ERG value, and (ii) combining the weighted score for each ERG value to generate the SZ or MDD probability score. 
     
     
         122 . The method of  claim 121 , wherein the one or more transformation analyses comprise applying the value of the one or more of the ERG parameters to a pre-determined logistic regression model. 
     
     
         123 . The method of any one of  claims 120 - 122 , wherein the logistic regression model was determined using ERG parameter values measured in a first population of SZ subjects and a second population of MDD subjects. 
     
     
         124 . The method of  claim 122  or  123 , wherein the logistic regression model includes age, gender, or both age and gender, as covariate(s). 
     
     
         125 . The method of  claim 124 , wherein the logistic regression model includes both age and gender as covariates. 
     
     
         126 . A method for identifying one or more ERG parameters useful for the differential diagnosis of SZ and MDD or of a predisposition thereto, said method comprising:
 selecting a group of subjects suffering from SZ;   selecting a group of subjects suffering from MDD;   measuring one or more ERG parameters in the subjects; and   identifying the one or more ERG parameters that permit to discriminate between the subjects suffering from SZ and those suffering from MDD.   
     
     
         127 . The method of  claim 126 , wherein said identifying comprises performing a logistic regression using the one or more ERG parameters. 
     
     
         128 . The method of  claim 127 , wherein said logistic regression includes age, gender, or both age and gender, as covariate. 
     
     
         129 . A method for determining whether a subject suffers from or is predisposed to suffering from bipolar disorder (BP) or major depression (MDD), said method comprising
 (a) measuring one or more ERG parameters in the subject;   (b) calculating a BP or MDD probability score by adjusting the value of one or more of the ERG parameters by one or more transformation analyses; and   (c) determining whether the subject suffers from BP or MDD or has a predisposition thereto based on said BP or MDD probability score.   
     
     
         130 . The method of  claim 129 , wherein the one or more transformation analyses comprise (i) adjusting the value of the one or more of the ERG parameters by appropriate weighting coefficients to produce a weighted score for each ERG value, and (ii) combining the weighted score for each ERG value to generate the BP or MDD probability score. 
     
     
         131 . The method of  claim 130 , wherein the one or more transformation analyses comprise applying the value of the one or more of the ERG parameters to a pre-determined logistic regression model. 
     
     
         132 . The method of any one of  claims 129 - 131 , wherein the logistic regression model was determined using ERG parameter values measured in a first population of BP subjects and a second population of MDD subjects. 
     
     
         133 . The method of  claim 131  or  132 , wherein the logistic regression model includes age, gender, or both age and gender, as covariate(s). 
     
     
         134 . The method of  claim 133 , wherein the logistic regression model includes both age and gender as covariates. 
     
     
         135 . A method for identifying one or more ERG parameters useful for the differential diagnosis of BP and MDD or of a predisposition thereto, said method comprising:
 selecting a group of subjects suffering from BP;   selecting a group of subjects suffering from MDD;   measuring one or more ERG parameters in the subjects; and   identifying the one or more ERG parameters that permit to discriminate between the subjects suffering from BP and those suffering from MDD.   
     
     
         136 . The method of  claim 135 , wherein said identifying comprises performing a logistic regression using the one or more ERG parameters. 
     
     
         137 . The method of  claim 136 , wherein said logistic regression includes age, gender, or both age and gender, as covariate. 
     
     
         138 . A method for stratification of a subject suffering from a major psychiatric disorder, said method comprising measuring (i) the cone b-wave implicit time, (ii) the rod a-wave implicit time, (iii) the rod b-wave amplitude, (iv) the cone a-wave amplitude, (v) the cone a-wave implicit time, and (vi) the rod b-wave implicit time, in said subject, wherein:
 (a) a rod a-wave implicit time, a cone a-wave implicit time and/or rod b-wave implicit time that is/are lower relative to the corresponding value(s) in a control subject defines a first group of stratification;   (b) a rod b-wave implicit time that is higher relative to the corresponding value in a control subject defines a second group of stratification;   (c) a cone b-wave implicit time that is higher and a rod b-wave implicit time that is similar relative to the corresponding values in a control subject defines a third group of stratification;   (d) a cone b-wave implicit time that is substantially similar relative to the corresponding value in a control subject defines a fourth group of stratification.   
     
     
         139 . The method of  claim 138 , wherein said major psychiatric disorder is schizophrenia. 
     
     
         140 . A method of monitoring the response to a treatment in subject suffering from a major psychiatric disorder, said method comprising:
 (a) measuring one or more ERG parameters in the subject at a first, earlier time point and at a second, later time point, wherein said subject is treated between said first and second time points;   (b) calculating major psychiatric disorder probability scores at said first and second time points by adjusting the value of one or more of the ERG parameters by one or more transformation analyses;   (c) monitoring the response to the treatment in the subject based on the major psychiatric disorder probability scores at said first and second time points.   
     
     
         141 . The method of  claim 140 , wherein a decrease in said major psychiatric disorder probability score between said first and second time points is indicative that the subject is responsive to the treatment. 
     
     
         142 . A method of monitoring the condition of a subject suffering from a major psychiatric disorder, said method comprising:
 (a) measuring one or more ERG parameters in the subject at a first, earlier time point and at a second, later time point;   (b) calculating major psychiatric disorder probability scores at said first and second time points by adjusting the value of one or more of the ERG parameters by one or more transformation analyses;   (c) monitoring the condition the subject based on the major psychiatric disorder probability scores at said first and second time points.   
     
     
         143 . The method of  claim 142 , wherein a decrease in said major psychiatric disorder probability score between said first and second time points is indicative that the subject's condition has improved. 
     
     
         144 . A program storage device readable by an electronic medium and tangibly storing instructions executable by the electronic medium to perform the one or more transformation analyses defined in any of the precedent claims. 
     
     
         145 . A computer program product comprising a computer useable medium that tangibly stores as computer readable code instructions to perform the one or more transformation analyses defined in any of the precedent claims. 
     
     
         146 . A system for performing the one or more transformation analyses defined in any one of the preceding claims, said system comprising: (a) a data acquisition module configured to produce a data set comprising one or more ERG parameter value(s); (b) a data processing module configured to process the data set by applying one or more transformation analyses to the data set to produce a statistically derived probability score; and (c) a display module configured to display the statistically derived probability score.