Hypoperfusion may be an early feature in the development of periventricular lesions in ILA and may play a direct pathogenic role. Serial studies are now needed to determine whether these changes herald the appearance of new lesions and represent "at risk" white matter, and to determine whether pharmacological agents can restore perfusion of normal-appearing white matter.

Background: The glutamate model of schizophrenia proposes that altered glutamatergic neurotransmission is fundamental to the development of the disorder. In addition, its potential to mediate neurotoxicity raises the possibility that glutamate dysfunction could underlie neuroanatomical changes in schizophrenia. Here we determine whether changes in brain glutamate are present in subjects at ultra high risk of developing psychosis, and whether these changes are related to reductions in cortical gray matter volume.Methods: Twenty-seven individuals with an At Risk Mental State (ARMS) and a group of 27 healthy volunteers underwent proton magnetic resonance spectroscopy and volumetric proton magnetic resonance imaging using a 3 Tesla scanner.Glutamate and glutamine levels were measured in anterior cingulate, left hippocampus and left thalamus. These measures were then related to cortical gray matter volume.Results: ARMS subjects had significantly lower levels of glutamate than controls in the thalamus (p<0.05), but higher glutamine in the anterior cingulate (p<0.05). Within the ARMS group, the level of thalamic glutamate was directly correlated with gray matter volume in the medial temporal cortex and insula (p<0.01). Conclusions:This study provides the first evidence that brain glutamate function is perturbed in people with prodromal signs of schizophrenia, and that glutamatergic dysfunction is associated with a reduction in gray matter volume in brain regions thought to be critical to the pathogenesis of the disorder. These findings support the hypothesis that drugs affecting the glutamate system may be of benefit in the early stages of psychotic illness.

BackgroundThe tremendous clinical and aetiological diversity among individuals with autism spectrum disorder (ASD) has been a major obstacle to the development of new treatments, as many may only be effective in particular subgroups. Precision medicine approaches aim to overcome this challenge by combining pathophysiologically based treatments with stratification biomarkers that predict which treatment may be most beneficial for particular individuals. However, so far, we have no single validated stratification biomarker for ASD. This may be due to the fact that most research studies primarily have focused on the identification of mean case-control differences, rather than within-group variability, and included small samples that were underpowered for stratification approaches. The EU-AIMS Longitudinal European Autism Project (LEAP) is to date the largest multi-centre, multi-disciplinary observational study worldwide that aims to identify and validate stratification biomarkers for ASD.MethodsLEAP includes 437 children and adults with ASD and 300 individuals with typical development or mild intellectual disability. Using an accelerated longitudinal design, each participant is comprehensively characterised in terms of clinical symptoms, comorbidities, functional outcomes, neurocognitive profile, brain structure and function, biochemical markers and genomics. In addition, 51 twin-pairs (of which 36 had one sibling with ASD) are included to identify genetic and environmental factors in phenotypic variability.ResultsHere, we describe the demographic characteristics of the cohort, planned analytic stratification approaches, criteria and steps to validate candidate stratification markers, pre-registration procedures to increase transparency, standardisation and data robustness across all analyses, and share some ‘lessons learnt’. A clinical characterisation of the cohort is given in the companion paper (Charman et al., accepted).ConclusionWe expect that LEAP will enable us to confirm, reject and refine current hypotheses of neurocognitive/neurobiological abnormalities, identify biologically and clinically meaningful ASD subgroups, and help us map phenotypic heterogeneity to different aetiologies.Electronic supplementary materialThe online version of this article (doi:10.1186/s13229-017-0146-8) contains supplementary material, which is available to authorized users.