Background According to Bayesian hypotheses, individuals with Autism Spectrum Disorder (ASD) have difficulties making accurate predictions about their environment. In particular, the mechanisms by which they assign precision to predictions or sensory inputs would be suboptimal in ASD. These mechanisms are thought to be mostly mediated by glutamate and GABA. Here, we aimed to shed light on prediction learning in ASD and on its neurobiological correlates. Methods Twenty-six neurotypical and 26 autistic adults participated in an associative learning task where they had to learn a probabilistic association between a tone and the rotation direction of two dots, in a volatile context. They also took part in magnetic resonance spectroscopy (MRS) measurements to quantify Glx (glutamate and glutamine), GABA + and glutathione in a low-level perceptual region (occipital cortex) and in a higher-level region involved in prediction learning (inferior frontal gyrus). Results Neurotypical and autistic adults had their percepts biased by their expectations, and this bias was smaller for individuals with a more atypical sensory sensitivity. Both groups were able to learn the association and to update their beliefs after a change in contingency. Interestingly, the percentage of correct predictions was correlated with the Glx/GABA + ratio in the occipital cortex (positive correlation) and in the right inferior frontal gyrus (negative correlation). In this region, MRS results also showed an increased concentration of Glx in the ASD group compared to the neurotypical group. Limitations We used a quite restrictive approach to select the MR spectra showing a good fit, which led to the exclusion of some MRS datasets and therefore to the reduction of the sample size for certain metabolites/regions. Conclusions Autistic adults appeared to have intact abilities to make predictions in this task, in contrast with the Bayesian hypotheses of ASD. Yet, higher ratios of Glx/GABA + in a frontal region were associated with decreased predictive abilities, and ASD individuals tended to have more Glx in this region. This neurobiological difference might contribute to suboptimal predictive mechanisms in ASD in certain contexts.

Multiple sclerosis (MS) is a chronic inflammatory demyelinating and degenerative disorder of the central nervous system. Accelerated brain volume loss (BVL) has emerged as a promising magnetic resonance imaging marker (MRI) of neurodegeneration, correlating with present and future clinical disability. We have systematically selected MS patients fulfilling ‘no evidence of disease activity-3′ (NEDA-3) criteria under high-efficacy disease-modifying treatment (DMT) from the database of two Belgian MS centers. BVL between both MRI scans demarcating the NEDA-3 period was assessed and compared with a group of prospectively recruited healthy volunteers who were matched for age and gender. Annualized whole brain volume percentage change was similar between 29 MS patients achieving NEDA-3 and 24 healthy controls (−0.25 ± 0.49 versus −0.24 ± 0.20, p = 0.9992; median follow-up 21 versus 33 months; respectively). In contrast, we found a mean BVL increase of 72%, as compared with the former, in a second control group of MS patients (n = 21) whom had been excluded from the NEDA-3 group due to disease activity (p = 0.1371). Our results suggest that neurodegeneration in MS can slow down to the rate of normal aging once inflammatory disease activity has been extinguished and advocate for an early introduction of high-efficacy DMT to reduce the risk of future clinical disability.

Inflammatory processes are involved in the pathophysiology of both Alzheimer’s disease (AD) and multiple sclerosis (MS) but their exact contribution to disease progression remains to be deciphered. Biomarkers are needed to define pathophysiological processes of these disorders, who may increasingly co-exist in the elderly generations of the future, due to the rising prevalence in both and ameliorated treatment options with improved life expectancy in MS. The purpose of this review was to provide a systematic overview of inflammatory biomarkers, as measured in the cerebrospinal fluid (CSF), that are associated with clinical disease progression. International peer-reviewed literature was screened using the PubMed and Web of Science databases. Disease progression had to be measured using clinically validated tests representing baseline functional and/or cognitive status, the evolution of such clinical scores over time and/or the transitioning from one disease stage to a more severe stage. The quality of included studies was systematically evaluated using a set of questions for clinical, neurochemical and statistical characteristics of the study. A total of 84 papers were included (twenty-five for AD and 59 for MS). Elevated CSF levels of chitinase-3-like protein 1 (YKL-40) were associated with disease progression in both AD and MS. Osteopontin and monocyte chemoattractant protein-1 were more specifically related to disease progression in AD, whereas the same was true for interleukin-1 beta, tumor necrosis factor alpha, C-X-C motif ligand 13, glial fibrillary acidic protein and IgG oligoclonal bands in MS. We observed a broad heterogeneity of studies with varying cohort characterization, non-disclosure of quality measures for neurochemical analyses and a lack of adequate longitudinal designs. Most of the retrieved biomarkers are related to innate immune system activity, which seems to be an important mediator of clinical disease progression in AD and MS. Overall study quality was limited and we have framed some recommendations for future biomarker research in this field.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42021264741.