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Bolte, L.

Publications and source records attributed to Bolte, L..

3 recordsLinked to original sources

Longitudinal White Matter Microstructure and Transition to Psychosis in Individuals at Clinical High Risk

Altered white matter microstructure, commonly indexed by fractional anisotropy (FA), has been reported in individuals at clinical high-risk of psychosis (CHR-P) across multiple white matter tracts. However, the relationship between these alterations and later transition to psychosis remains unclear. To address this gap, we investigated whether baseline and longitudinally updated FA measurements were associated with risk of transition to psychosis in a large cohort of individuals at CHR-P. We analysed diffusion tensor imaging data from N = 205 participants at CHR-P, 23 of whom developed psychosis within 3 years of follow-up. Data were collected at baseline, 6 months, and 12 months. Associations between global and tract-specific FA and transition risk were examined using Cox proportional hazards models of baseline data and longitudinally updated data. Point estimates were directionally consistent, with hazard ratios <1 for FA across all white matter tracts in both baseline and longitudinal models. Associations reached nominal significance in the hippocampal cingulum, anterior thalamic radiation, and forceps minor, but none of these remained significant after correcting for multiple comparisons (pcorr > .05). The directionally consistent estimates are compatible with small, distributed effects across multiple white matter pathways being associated with transition to psychosis, although this requires replication. Longitudinally updated FA measurements did not yield stronger associations than were available from baseline imaging data alone. Studies at an even larger scale are needed to establish whether these associations are robust and clinically meaningful.

neuroscience↗

Longitudinal White Matter Trajectories in Clinical High Risk and First-Episode Psychosis: Findings from the Multi-Centre PSYSCAN Study

Psychosis has been linked to changes in diffusion-derived fractional anisotropy (FA) across multiple white matter tracts, yet most evidence is cross-sectional. Longitudinal findings are inconsistent, and the clinical relevance of white matter changes over time remains unclear. To address this gap, we investigated longitudinal white matter changes and their clinical correlates in early psychosis in a large, multi-centre diffusion-tensor imaging study. Across 18 sites, 407 participants (healthy controls: n = 97, 59.8% men, mean age 23.9{+/-}4.6 years; clinical high risk of psychosis: n = 158, 53.5% men, mean age 23.0{+/-}4.9 years; first-episode psychosis: n = 152, 71.1% men, mean age 25.1{+/-}5.4 years) were scanned at up to three time points over 12 months. FA was assessed in the cingulum bundle, the superior longitudinal fasciculus, the inferior fronto-occipital fasciculus, and at the whole brain level. FA trajectories were analysed using linear mixed-effects models to test effects of group, social and occupational functioning, and (attenuated) psychotic symptoms, while controlling for demographic and socioeconomic covariates. No significant group differences in FA were observed, either globally or within tracts (p > .05). Longitudinal FA trajectories were not associated with changes in (attenuated) psychotic symptoms or functioning (p > .05). In contrast, higher baseline antipsychotic medication dose was significantly associated with lower FA (pcorr < .05). Overall, these findings indicate that white matter microstructure is relatively stable during the clinical-high-risk and first-episode phases of psychosis, and that it is not clearly associated with variation in symptom severity or functional outcomes over time.

neuroscience↗

The faecal metabolome and its determinants in inflammatory bowel disease

ObjectiveInflammatory bowel disease (IBD) is a multifactorial immune-mediated inflammatory disease of the intestine, comprising Crohns disease and ulcerative colitis. By characterising metabolites in faeces, combined with faecal metagenomics, host genetics and clinical characteristics, we aimed to unravel metabolic alterations in IBD. DesignWe measured 1,684 different faecal metabolites and 8 short-chain and branched-chain fatty acids in stool samples of 424 IBD patients and 255 non-IBD controls. Regression analyses were used to compare concentrations of metabolites between cases and controls and determine the relationship between metabolites and each participants lifestyle, clinical characteristics and gut microbiota composition. Moreover, genome-wide association analysis was conducted on faecal metabolite levels. ResultsWe identified over 300 molecules that were differentially abundant in the faeces of patients with IBD. The ratio between a sphingolipid and L-urobilin could discriminate between IBD and non-IBD samples (AUC = 0.85). We found changes in the bile acid pool in patients with dysbiotic microbial communities and a strong association between faecal metabolome and gut microbiota. For example, the abundance of Ruminococcus gnavus was positively associated with tryptamine levels. In addition, we found 158 associations between metabolites and dietary patterns, and polymorphisms near NAT2 strongly associated with coffee metabolism. ConclusionIn this large-scale analysis, we identified alterations in the metabolome of patients with IBD that are independent of commonly overlooked confounders such as diet and surgical history. Considering the influence of the microbiome on faecal metabolites, our results pave the way for future interventions targeting intestinal inflammation.

microbiology↗