Relapse duration, treatment intensity, and brain tissue loss in schizophrenia: a prospective longitudinal MRI study.

OBJECTIVE: Longitudinal structural MRI studies have shown that patients with schizophrenia have progressive brain tissue loss after onset. Recurrent relapses are believed to play a role in this loss, but the relationship between relapse and structural MRI measures has not been rigorously assessed. The authors analyzed longitudinal data to examine this question. METHODS: The authors studied data from 202 patients drawn from the Iowa Longitudinal Study of first-episode schizophrenia for whom adequate structural MRI data were available (N=659 scans) from scans obtained at regular intervals over an average of 7 years. Because clinical follow-up data were obtained at 6-month intervals, the authors were able to compute measures of relapse number and duration and relate them to structural MRI measures. Because higher treatment intensity has been associated with smaller brain tissue volumes, the authors also examined this countereffect in terms of dose-years. RESULTS: Relapse duration was related to significant decreases in both general (e.g., total cerebral volume) and regional (e.g., frontal) brain measures. Number of relapses was unrelated to brain measures. Significant effects were also observed for treatment intensity. CONCLUSIONS: Extended periods of relapse may have a negative effect on brain integrity in schizophrenia, suggesting the importance of implementing proactive measures that may prevent relapse and improve treatment adherence. By examining the relative balance of effects, that is, relapse duration versus antipsychotic treatment intensity, this study sheds light on a troublesome dilemma that clinicians face. Relapse prevention is important, but it should be sustained using the lowest possible medication dosages that will control symptoms.

Progressive brain change in schizophrenia: a prospective longitudinal study of first-episode schizophrenia.

BACKGROUND: Schizophrenia has a characteristic onset during adolescence or young adulthood but also tends to persist throughout life. Structural magnetic resonance studies indicate that brain abnormalities are present at onset, but longitudinal studies to assess neuroprogression have been limited by small samples and short or infrequent follow-up intervals. METHODS: The Iowa Longitudinal Study is a prospective study of 542 first-episode patients who have been followed up to 18 years. In this report, we focus on those patients (n = 202) and control subjects (n = 125) for whom we have adequate structural magnetic resonance data (n = 952 scans) to provide a relatively definitive determination of whether progressive brain change occurs over a time interval of up to 15 years after intake. RESULTS: A repeated-measures analysis showed significant age-by-group interaction main effects that represent a significant decrease in multiple gray matter regions (total cerebral, frontal, thalamus), multiple white matter regions (total cerebral, frontal, temporal, parietal), and a corresponding increase in cerebrospinal fluid (lateral ventricles and frontal, temporal, and parietal sulci). These changes were most severe during the early years after onset. They occur at severe levels only in a subset of patients. They are correlated with cognitive impairment but only weakly with other clinical measures. CONCLUSIONS: Progressive brain change occurs in schizophrenia, affects both gray matter and white matter, is most severe during the early stages of the illness, and occurs only in a subset of patients. Measuring severity of progressive brain change offers a promising new avenue for phenotype definition in genetic studies of schizophrenia.

Cannabinoid receptor 1 gene polymorphisms and marijuana misuse interactions on white matter and cognitive deficits in schizophrenia.

Marijuana exposure during the critical period of adolescent brain maturation may disrupt neuro-modulatory influences of endocannabinoids and increase schizophrenia susceptibility. Cannabinoid receptor 1 (CB1/CNR1) is the principal brain receptor mediating marijuana effects. No study to-date has systematically investigated the impact of CNR1 on quantitative phenotypic features in schizophrenia and inter-relationships with marijuana misuse. We genotyped 235 schizophrenia patients using 12 tag single nucleotide polymorphisms (tSNPs) that account for most of CB1 coding region genetic variability. Patients underwent a high-resolution anatomic brain magnetic resonance scan and cognitive assessment. Almost a quarter of the sample met DSM marijuana abuse (14%) or dependence (8%) criteria. Effects of CNR1 tSNPs and marijuana abuse/dependence on brain volumes and neurocognition were assessed using ANCOVA, including co-morbid alcohol/non-marijuana illicit drug misuse as covariates. Significant main effects of CNR1 tSNPs (rs7766029, rs12720071, and rs9450898) were found in white matter (WM) volumes. Patients with marijuana abuse/dependence had smaller fronto-temporal WM volumes than patients without heavy marijuana use. More interestingly, there were significant rs12720071 genotype-by-marijuana use interaction effects on WM volumes and neurocognitive impairment; suggestive of gene-environment interactions for conferring phenotypic abnormalities in schizophrenia. In this comprehensive evaluation of genetic variants distributed across the CB1 locus, CNR1 genetic polymorphisms were associated with WM brain volume variation among schizophrenia patients. Our findings suggest that heavy cannabis use in the context of specific CNR1 genotypes may contribute to greater WM volume deficits and cognitive impairment, which could in turn increase schizophrenia risk.

Long-term antipsychotic treatment and brain volumes: a longitudinal study of first-episode schizophrenia.

CONTEXT: Progressive brain volume changes in schizophrenia are thought to be due principally to the disease. However, recent animal studies indicate that antipsychotics, the mainstay of treatment for schizophrenia patients, may also contribute to brain tissue volume decrement. Because antipsychotics are prescribed for long periods for schizophrenia patients and have increasingly widespread use in other psychiatric disorders, it is imperative to determine their long-term effects on the human brain. OBJECTIVE: To evaluate relative contributions of 4 potential predictors (illness duration, antipsychotic treatment, illness severity, and substance abuse) of brain volume change. DESIGN: Predictors of brain volume changes were assessed prospectively based on multiple informants. SETTING: Data from the Iowa Longitudinal Study. PATIENTS: Two hundred eleven patients with schizophrenia who underwent repeated neuroimaging beginning soon after illness onset, yielding a total of 674 high-resolution magnetic resonance scans. On average, each patient had 3 scans (≥2 and as many as 5) over 7.2 years (up to 14 years). MAIN OUTCOME MEASURE: Brain volumes. RESULTS: During longitudinal follow-up, antipsychotic treatment reflected national prescribing practices in 1991 through 2009. Longer follow-up correlated with smaller brain tissue volumes and larger cerebrospinal fluid volumes. Greater intensity of antipsychotic treatment was associated with indicators of generalized and specific brain tissue reduction after controlling for effects of the other 3 predictors. More antipsychotic treatment was associated with smaller gray matter volumes. Progressive decrement in white matter volume was most evident among patients who received more antipsychotic treatment. Illness severity had relatively modest correlations with tissue volume reduction, and alcohol/illicit drug misuse had no significant associations when effects of the other variables were adjusted. CONCLUSIONS: Viewed together with data from animal studies, our study suggests that antipsychotics have a subtle but measurable influence on brain tissue loss over time, suggesting the importance of careful risk-benefit review of dosage and duration of treatment as well as their off-label use.

Anterior cingulate cortex: an MRI-based parcellation method.

OBJECTIVE: The anterior cingulate cortex (ACC) is an important part of the limbic system involved in emotions, cognition and executive function. The ACC has structurally distinct subregions, both microscopically and functionally, that have been implicated in several major psychiatric disorders. However, a structural analysis of these subregions with magnetic resonance imaging (MRI) has not been done. Our main purpose was to develop an MRI-based parcellation method of the ACC that permits us to explore plausible abnormalities in 4 functionally relevant subregions: dorsal, rostral, subcallosal and subgenual. METHODS: The reliability study for gray matter volume and surface area of each subregion was performed on 14 randomly selected MR scans by 3 different raters. Our method posits to conserve the topographic uniqueness of individual brains and is based on our ability to visualize both the 3-dimensional rendered brain and the 3 orthogonal planes simultaneously with BRAINS2 software. We developed rules to hand-trace regions of interest (ROI) to surround contiguous areas of gray matter for dorsal, rostral, subcallosal and subgenual regions. The ACC was then parcellated into these 4 distinct subregions (8 when both right and left hemispheres were measured). RESULTS AND DISCUSSION: The intraclass R coefficients for gray matter volume of each subregion ranged between 0.85 and 0.93. The current study describes a new highly reliable and reproducible topography-based parcellation method of the ACC into its dorsal, rostral, subcallosal and subgenual regions. CONCLUSIONS: This new parcellation method provides a new means of exploring the role of the functionally and structurally distinct subregions of the ACC in schizophrenia, depression and various other brain illnesses.

Manual and automated measurement of the whole thalamus and mediodorsal nucleus using magnetic resonance imaging.

The thalamus is an important relay structure in the brain that may be relevant to a variety of brain diseases. It is divided into multiple subnuclei with different cortical connections. The medial dorsal (MD) nucleus is particularly important because it forms key connections with the prefrontal cortex. The current study reports precise and efficient methods for measuring the whole thalamus and the MD with MRI that have a high degree of interrater reliability. A multispectral image acquisition and novel image processing technique were used to improve structure visibility. The tricolor image assigns a color to each of the T1, T2, and PD weighted images, represented by red, green, and blue, respectively. The manually defined regions were then used to train an artificial neural network (ANN) to automatically define both the whole thalamus and the MD. The ANN provides an efficient automated method, making studies using larger sample sizes more feasible.