The identified increase in variance explained by PTSD emphasizes that PTSD is a significant predictor of later addiction severity among individuals who face early substance use problems. These results are consistent with previous research, which associated early childhood experience of trauma with early substance use onset and transition to poly drug use . Additionally, previous handful evidence has consistently established associations between SUD and PTSD and provided explanatory hypotheses underlying these associations. Given that at SSA populations such Rwandans had experienced horrific events , these results may be interpreted through well-documented risky use of psychoactive substances for coping with post disaster distress . However, it is challenging to delineate which of the two conditions occurs first because SUD and PTSD affect the stress processing system. Chronic SUD, such as alcohol use disorders, increased individual vulnerability to PTSD due to alcohol related defects of endocrinal response to distress events and reduced cortisol release . On the other hand, PTSD influences neurotransmitters changes, such as serotonin, in the hypothalamic-pituitary-adrenaline axis, which have been linked to risks for worsened SUD . The identified positive association between level of education and addiction severity may be partially explained by the Rwandan cultural and conception of mental illness. Cultural expectations are strict on the use of alcohol that interferes with social and professional functioning . Thus,vertical hydroponic garden educated people may find it challenging to seek early help for their SUD due to fear of being subject to attached stigma and use psychoactive substances as self-medication.
The present study, to our knowledge, is the first to investigate the contributions of age, motives for first substance use, and post traumatic distress to later addiction problems using a clinical sample in sub-Saharan Africa. The study used a compelling alternative to the random sampling strategy, recruiting every participant presenting for inpatient addiction care in two existing settings over 8 months. This study has a few limitations, including relying on self-reported data that may be prone to recall and social desirability biases. However, we attempted to minimize these biases by collecting data through face-to-face semi-structured interviews conducted by trained and qualified mental health professionals who were not part of a healthcare circle .Underlying its clinical symptomatology, schizophrenia is characterized by a disturbance in the regulated processing of environmental information . Especially notable are impairments in identifying and responding to stimuli that are either salient or novel. The P300 event-related potential is a physiological index of the cognitive processes elicited by such task-relevant or novel deviant stimuli.However, the scalp-recorded P300 response to an auditory target stimulus – also referred to as P3b to differentiate it from the P3a orienting response to novelty – arises primarily from inferior parietal and supramarginal cortical regions . Reduced amplitude of this response is one of the most robust physiological abnormalities associated with schizophrenia, being replicated across hundreds of studies with a relatively large effect size . Although P300 amplitude varies to a certain extent with fluctuations in clinical symptomatology , it also exhibits characteristics of a trait-like disease marker. The measure has relatively high test-retest reliability , and the patient deficit persists regardless of the level of acute symptomatology or psychotropic medication . There is also strong evidence implicating a genetic contribution to P300 amplitude in both healthy subjects and patients . Thus, P300 amplitude meets the essential criteria for a schizophrenia endophenotype .
Historically, an impediment to the utility of the P300 as a schizophrenia biomarker has been its lack of specificity. P300 is disrupted in a variety of neuropsychiatric disorders associated with cognitive impairment. These include, among others, Alzheimer’s disease , alcoholism and affective illness . Additionally, the P300 response is influenced by a variety of factors, independent of clinical diagnosis. Most notable among these are age and sex; P300 amplitude is smaller, overall, in men and exhibits both reduced amplitude and prolonged latency in the elderly . It is also altered by both the acute and chronic administration of various psychoactive substances. P300 amplitude is smaller in active smokers compared to nonsmokers, and this decrement reflects both the current number of cigarettes smoked per day and the number of years of continuous smoking . It is similarly reduced following acute administration of marijuana , alcohol , and cocaine , and among chronic users of these substances . In contrast, the effect of antipsychotic medications, among schizophrenia patients, appears to be relatively inconsequential . Another potentially important factor that has only rarely been considered is race or ethnicity, and the little evidence that exists concerning this has been inconclusive . Given the frequent co-occurrence of schizophrenia with other co-morbid neuropsychiatric and substance use disorders, as well as the differences in smoking prevalence and racial stratification that is often found in schizophrenia patient vs. healthy control samples, a comprehensive understanding of the impact of such modulating factors is critical to enhancing the utility of P300 as a disease-specific schizophrenia biomarker. Recently, with the advent of studies of the schizophrenia prodrome, the importance of the P300 as a putative biomarker has taken on added significance. There is now substantial evidence that P300 amplitude is reduced in “high-risk” individuals with prodromal symptoms, prior to illness onset . Importantly, within a high-risk cohort, P300 appears to be a sensitive predictor of which individuals will, in fact, transition to frank psychosis. Moreover, the degree of impairment indicates the proximity of illness onset . The greater the magnitude of the amplitude reduction, the more likely that psychosis onset is imminent. P300 amplitude assessment may, therefore,plant bench indoor play an important part in the clinical evaluation of at-risk individuals.
However P300 studies have thus far been confined primarily to academic neurophysiology laboratories, and data analyses have been limited primarily to between-group comparisons of measures acquired in one laboratory under identical conditions. It is thus unclear whether specific values obtained in one experimental setting can be compared or co-mingled with values obtained in another setting under less-than identical conditions. The ability to aggregate quantitative data across multiple sites is critical to the strategy employed by the Consortium on the Genetics of Schizophrenia to identify the genetic substrates of disease endophenotypes. It is also critical to the utility of this measure as a specific predictive biomarker of impending psychosis. The purpose of the current analysis was therefore, first, to determine if a standardized P300 data acquisition system could be successfully deployed to multiple settings without on-site electrophysiology expertise. We assessed the overall usability of the ERP data and the ability to detect known schizophrenia deficits. We also considered the consistency of measurements across five COGS-2 sites, and examined various socio-demographic modulating factors that can contribute to measurement variability. As noted, a careful understanding of the quantitative impact of these modulating factors is an important prerequisite to any interpretation of a specific set of measurements. Healthy control subjects and schizophrenia patients were enrolled in the COGS-2 endophenotype study at 5 sites, as detailed in the introductory article of this Special Issue . Briefly, all participants were assessed using a modified version of the Structured Clinical Interview for DSM-IV-TR , Modules A-E . All patients met criteria for either SZ or schizo affective disorder, depressed subtype. HCS were excluded for any history of a psychotic disorder in either themselves or a 1 st-degree relative, a current Axis I mood disorder, a Cluster A Axis II disorder, or current psychoactive medication use. Subjects were also excluded for any medical or neurological condition that could interfere with endophenotype assessment, history of substance abuse in the past month or substance dependence in the past 6 months, or a positive toxicology screen at the time of testing. Clinical and demographic characteristics of the P300 sample are presented, by site, in Table 1. Specific past substance related diagnoses are detailed in Table 2. Adjunctive psychoactive medications used by patients are listed in Table 3. In addition to the structured clinical interview and the various endophenotype measures, all subjects were assessed with the Mini-Mental Status Examination and the Global Assessment of Functioning Scale . Patients were further assessed with two measures of functional capacity: the 15-item clinician rated Scale of Functioning, and the UCSD Performance-based Skills Assessment-Brief , which directly assesses an individual’s capacity in multiple domains of everyday functioning through the use of props and standardized skill performance tests.
There were significant group differences in age , sex and racial composition . There were also significant site differences for each of these measures, and group × site interactions for age and sex. As expected, patients and controls differed on education, GAF, and MMSE scores. There were also significant main effects of site and group × site interactions for both GAF and MMSE. Site differences were also evident for rates of past substance use, major depressive disorder, and nicotine use. Among patients, site differences were observed for duration of illness, age of onset, and current symptomatology . This variability indicates that different sites drew their samples from different socio-demographic and clinical pools. The auditory P300 was conducted as the last task of the COGS-2 battery, following completion of the Mismatch Negativity experiment described by Light et al. . A San Diego Instruments 2-channel ERP-LAB system with a pre-set P300 module was used for stimulus presentation and EEG recording. One channel recorded EEG activity at the vertex referenced to the left mastoid process . A second channel recorded eye movement activity from electrodes placed mid superior and lateral to the right orbit . A ground electrode was placed on the right mastoid. All electrode impedances were below 5kΩ. The Cz electrode location represented a compromise between the preferred electrode placements for MMN and P300 recordings, given the limitations of the 2-channel recording system and the need to dedicate one of these to the EOG. Subjects were seated in front of a computer monitor and directed to fixate their gaze on the center screen. A hearing test was conducted to ensure >40 dB hearing threshold bilaterally at 1000Hz. Subjects were instructed to press the button on a hand-held counter whenever they heard a 1500 Hz target tone amid a stream of 1000 Hz tones. They were given a brief practice period to ensure initial task comprehension and compliance. Unfortunately, the experimental hardware did not allow further real-time monitoring of button-press responses over the course of the experiment. Subjects were then presented a series of 400 tones, including 62 random targets. The ERP system digitally sampled the EEG at 1000 Hz and wrote 1400 ms of data for each stimulus trial, beginning 100 ms prior to stimulus onset. At the conclusion of the experiment, the number of button presses was recorded from the counter. Raw EEG data from all 5 COGS-2 sites were uploaded to a centralized database. Quality assurance data review and analysis was then conducted by a single investigator who was blind to all demographic and diagnostic information. EEG data were processed using Brain Vision Analyzer 1.5 . Data were digitally filtered between 0.1 and 30 Hz and eye movement artifact was removed using an automated algorithm . Intervals with additional EEG artifact were excluded from further analysis. Remaining trials were then sorted and combined to form separate average ERP wave forms for the target and frequent tone conditions. These were baseline corrected relative to the 100ms pre-stim interval and visually inspected to determine the presence or absence of reliably identifiable ERP components. A highly conservative, stringent, approach to data inclusion was employed. Data without an unambiguous N100/P200 response to the frequent tone, or a reliably identifiable P300 response to the target were excluded. Subjects were also excluded if their target count deviated by more than 20 from the actual number of 62, regardless of the quality of EEG data, since appropriate task engagement could not be documented. For the remaining subjects, P300 amplitude and latency were measured from the peak target response between 250 and 400 ms. . P300 amplitude and latency differences were analyzed in two separate general linear models , with diagnosis, sex and test site as categorical factors and age as a continuous predictor. Significant main effects and interactions were parsed with post-hoc paired contrasts. The effects of various modulating factors were then initially assessed by adding these individually as separate additional factors to the original model.