Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk.

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.

Association between urban upbringing and functional brain connectivity in schizophrenia.

Background: Environmental factors considerably influence the development of the human cortex during the perinatal period, early childhood, and adolescence. Urban upbringing in the first 15 years of life is a known risk factor for schizophrenia (SCZ). Though the risk of urban birth and upbringing is well-examined from an epidemiological perspective, the biological mechanisms underlying urban upbringing remain unknown. The effect of urban birth and upbringing on functional brain connectivity in SCZ patients is not yet examined. Methods: This is a secondary data analysis of three studies that included 87 patients with SCZ and 70 healthy volunteers (HV) aged 18 to 50 years. We calculated the developmental urbanicity index using a validated method in earlier studies. Following standard pre-processing of resting functional magnetic resonance imaging (fMRI) scans, seed-return on investment (ROI) functional connectivity analysis was performed. Results: The results showed a significant association between urban birth and upbringing on functional connectivity in SCZ patients and HV (P < 0.05). In SCZ patients, connections from the right caudate, anterior cingulate cortex, left and right intracalcarine cortices, left and right lingual gyri, left posterior parahippocampal cortex to the cerebellum, fusiform gyri, lateral occipital cortex, and amygdala were significantly associated with the urbanicity index (P < 0.05). Conclusions: These study findings suggest a significant association between urban birth and upbringing on functional brain connectivity in regions involved in reward processing and social cognition in SCZ. Assessment of social cognition could have implications in developing an in-depth understanding of this impairment in persons with SCZ.

Country-level gender inequality is associated with structural differences in the brains of women and men.

Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women's worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7,876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women's brains and provide initial evidence for neuroscience-informed policies for gender equality.

Endocannabinoid system in psychotic and mood disorders, a review of human studies.

Despite widespread evidence of endocannabinoid system involvement in the pathophysiology of psychiatric disorders, our understanding remains rudimentary. Here we review studies of the endocannabinoid system in humans with psychotic and mood disorders. Postmortem, peripheral, cerebrospinal fluid and in vivo imaging studies provide evidence for the involvement of the endocannabinoid system in psychotic and mood disorders. Psychotic disorders and major depressive disorder exhibit alterations of brain cannabinoid CB1 receptors and peripheral blood endocannabinoids. Further, these changes may be sensitive to treatment status, disease state, and symptom severity. Evidence from psychotic disorder extend to endocannabinoid metabolizing enzymes in the brain and periphery, whereas these lines of evidence remain poorly developed in mood disorders. A paucity of studies examining this system in bipolar disorder represents a notable gap in the literature. Despite a growing body of productive work in this field of research, there is a clear need for investigation beyond the CB1 receptor in order to more fully elucidate the role of the endocannabinoid system in psychotic and mood disorders.

Perceptual Priming Can Increase or Decrease With Aging.

A decline in declarative or explicit memory has been extensively characterized in cognitive aging and is a hallmark of cognitive impairments. However, whether and how implicit perceptual memory varies with aging or cognitive impairment is unclear. Here, we compared implicit perceptual memory and explicit memory measures in three groups of participants: (1) 59 healthy young volunteers (20-30 years); (2) 269 healthy old volunteers (50-90 years) and (3) 21 patients with mild cognitive impairment, i.e., MCI (50-90 years). To measure explicit memory, participants were tested on standard recognition and recall tasks. To measure implicit perceptual memory, we used a classic perceptual priming paradigm. Participants had to report the shape of a visual search pop-out target whose color or position was varied randomly across trials. Perceptual priming was measured as the speedup in response time for targets that repeated in color or position. Our main findings are as follows: (1) Explicit memory was weaker in old compared to young participants, and in MCI patients compared to age- and education-matched controls; (2) Surprisingly, perceptual priming did not always decline with age: color priming was smaller in older participants but position priming was larger; (3) Position priming was less frequent in the MCI group compared to matched controls; (4) Perceptual priming and explicit memory were uncorrelated across participants. Thus, perceptual priming can increase or decrease with age or cognitive impairment, but these changes do not covary with explicit memory.

Evidence That Cannabis Exposure, Abuse, and Dependence Are Related to Glutamate Metabolism and Glial Function in the Anterior Cingulate Cortex: A 1H-Magnetic Resonance Spectroscopy Study.

There is evidence that long-term cannabis use is associated with alterations to glutamate neurotransmission and glial function. In this study, 26 long-term cannabis users (males=65.4%) and 47 non-cannabis using healthy controls (males=44.6%) underwent proton magnetic resonance spectroscopy (1H-MRS) of the anterior cingulate cortex (ACC) in order to characterize neurometabolite alterations in cannabis users and to examine associations between neurometabolites, cannabis exposure, and cannabis use behaviors. Myo-inositol, a marker of glial function, and glutamate metabolites did not differ between healthy controls and cannabis users or cannabis users who met criteria for DSM5 cannabis use disorder (n=17). Lower myo-inositol, a putative marker of glial function, was related to greater problematic drug use (F1,22 = 11.95, p=.002; Cohen's f=0.59, large effect; Drug Abuse Screening Test) and severity of cannabis dependence (F1,22 = 6.61, p=.17; Cohen's f=0.44, large effect). Further, past-year cannabis exposure exerted different effects on glutamate and glutamate+glutamine in males and females (glutamate: F1,21 = 6.31, p=.02; glutamate+glutamine: F1,21 = 7.20, p=.014), such that greater past-year cannabis exposure was related to higher concentrations of glutamate metabolites in male cannabis users (glutamate: F1,14 = 25.94, p=.00016; Cohen's f=1.32, large effect; glutamate+glutamine: F1,14 = 23.24, p=.00027, Cohen's f=1.24, large effect) but not in female cannabis users (glutamate: F1,6 = 1.37, p=0.78; glutamate+glutamine: F1,6 = 0.001, p=.97). The present results extend existing evidence of altered glial function and glutamate metabolism with cannabis use by providing evidence linking problematic drug use behaviors with glial function as measured with myo-inositol and recent chronic cannabis exposure to alterations in glutamate metabolism. This provides novel directions for the interrogation of the impact of cannabis use on brain neurochemistry.