Biology subjects

van Os, J.

Publications and source records attributed to van Os, J..

7 recordsLinked to original sources

bioRxiv2026

Consolidating species boundaries in the Fusarium oxysporum species complex based on genomic evidence

The Fusarium oxysporum species complex (FOSC) comprises numerous plant pathogens infecting crops such as tomato, lettuce, melon, and banana. Despite its economic and ecological importance and decades of research, the species names linked to different phylogenetic lineages within this species complex remain largely controversial. Earlier taxonomic frameworks relied on a limited number of marker genes, variable taxon sampling and inconsistent species definitions, leading to a fragmented and unstable taxonomy. To address these challenges, we here analysed nearly 2,500 conserved marker genes from 660 genomes, including genome assemblies from 22 ex-type strains that were sequenced using long-read sequencing technology, representing nearly half of the 51 currently described species within FOSC. Maximum likelihood- and coalescence-based analyses of the full phylogenomic data matrix as well as subsets yielded a robust phylogeny of FOSC, which was furthermore corroborated by whole genome comparisons. Many previously described species are redundant, while two novel lineages remain undescribed. Direct comparisons to traditional marker gene-based approaches demonstrate their inadequacy for species delimitation in FOSC. We show that our phylogenomic framework can guide the detection of novel marker genes able to distinguish the major lineages within FOSC, which will be essential for taxon delineation and classification in future studies. Thus, our phylogenomic analyses provide a stable cornerstone for revising FOSC taxonomy and offers a critical resource for the broader research community.

evolutionary biology↗

bioRxiv2026

Co-expression-based models improve eQTL predictions and highlightnovel transcriptome-wide genes associated with schizophrenia

Non-coding genetic variants statistically associated with complex heritability phenotypes are thought to act primarily through transcriptome regulatory mechanisms. Predictions of gene expression in tissue like the human brain traditionally rely primarily on cis-eQTLs. Here, we introduce INGENE and MODULE, trans-eQTLs models designed to enhance the prediction of gene expression by capturing the collective impact of candidate trans-eQTLs acting within co-expression networks. Exploiting RNA-seq data in six post-mortem brain regions (amygdala, caudate nucleus, dorsal/subgenual anterior cingulate cortex, dorsolateral prefrontal cortex, and hippocampus), we validate our models on two testing datasets, demonstrating increased gene predictability compared to both an original cis-based model and to EpiXcan, the leading benchmark in cis-model performance. Integration of cis- and trans-predictions significantly improves gene-level expression imputation (MLE = 0.05) for 18,744 genes across the six brain regions considered. Applying cis and trans models to PGC wave 3 genotypes identifies 766 SCZ-associated genes across brain regions (pFDR < .01), emphasizing the complementary nature of cis and trans predictions in trait association discovery. Of these genes, 641 represent novel transcriptome-wide associations with schizophrenia, highlighting the role of trans-heritability and genetic interactions underlying risk for this disorder, in addition to further supporting 125 previous candidates.

genomics↗

bioRxiv2019

Interaction between polygenic liability for schizophrenia and childhood adversity influences daily-life emotional dysregulation and psychosis proneness

BackgroundThe earliest stages of the pluripotent psychopathology on the pathway to psychotic disorders is represented by emotional dysregulation and subtle psychosis expression, which can be measured using the Ecological Momentary Assessment (EMA). However, it is not clear to what degree common genetic and environmental risk factors for psychosis contribute to variation in these early expressions of psychopathology.\n\nMethodsIn this largest ever EMA study of a general population twin cohort including 593 adolescents and young adults between the ages of 15 and 35 years, we tested whether polygenic risk score for schizophrenia (PRS-S) interacts with childhood adversity (the Childhood Trauma Questionnaire score) and daily-life stressors to influence momentary mental state domains (negative affect, positive affect, and subtle psychosis expression) and stress-sensitivity measures.\n\nResultsBoth childhood adversity and daily-life stressors were associated with increased negative affect, decreased positive affect, and increased subtle psychosis expression, while PRS-S was only associated with increased positive affect. No gene-environment correlation was detected. We have provided novel evidence for interaction effects between PRS-S and childhood adversity to influence momentary mental states [negative affect (b = 0.07, 95% CI 0.01 to 0.13, P = 0.013), positive affect (b = -0.05, 95% CI -0.10 to -0.00, P = 0.043), and subtle psychosis expression (b = 0.11, 95% CI 0.03 to 0.19, P = 0.007)] and stress-sensitivity measures.\n\nConclusionExposure to childhood adversities, particularly in individuals with high PRS-S, is pleiotropically associated with emotional dysregulation and psychosis proneness.

genomics↗

bioRxiv2019

Association of extent of cannabis use and psychotic like intoxication experiences in a multi-national sample of First Episode Psychosis patients and controls

AimsFirst Episode Psychosis (FEP) patients who use cannabis experience more frequent psychotic and euphoric intoxication experiences compared to controls. It is not clear whether this is consequent to patients being more vulnerable to the effects of cannabis use or to their heavier pattern of use. We aimed to determine whether extent of use predicted psychotic-like and euphoric intoxication experiences in FEP patients and controls and whether this differs between groups. MethodsWe analysed data on lifetime cannabis using patients (n=655) and controls (n=654) across 15 sites from six countries in the EU-GEI study (2010-2015). We used multiple regression to model predictors of cannabis-induced experiences and to determine if there was an interaction between caseness and extent of use. ResultsCaseness, frequency of cannabis use and money spent on cannabis predicted psychotic-like and euphoric experiences, independent of other experiences (p[≤]0.001). For psychotic-like experiences there was a significant interaction for caseness x frequency of use (p<0.001) and caseness x money spent on cannabis (p=0.001) such that FEP patients had increased experiences at increased levels of use compared to controls. There was no similar significant interaction for euphoric experiences (p>0.5). Conclusions and RelevanceFEP patients are particularly sensitive to increased psychotic-like, but not euphoric experiences, at higher frequency and amount of cannabis use compared to controls. This suggests a specific psychotomimetic response in patients related particularly to heavy cannabis use.

neuroscience↗

bioRxiv2019

Jumping To Conclusions, General Intelligence, And Psychosis Liability: Findings From The Multicentric EU-GEI Case-Control Study

BackgroundThe \"jumping to conclusions\" (JTC) bias is associated with both psychosis and general cognition but their relationship is unclear. In this study, we set out to clarify the relationship between the JTC bias, IQ, psychosis and polygenic liability to schizophrenia and IQ.\n\nMethods817 FEP patients and 1294 population-based controls completed assessments of general intelligence (IQ), and JTC (assessed by the number of beads drawn on the probabilistic reasoning \"beads\" task) and provided blood or saliva samples from which we extracted DNA and computed polygenic risk scores for IQ and schizophrenia.\n\nResultsThe estimated proportion of the total effect of case/control differences on JTC mediated by IQ was 79%. Schizophrenia Polygenic Risk Score (SZ PRS) was non-significantly associated with a higher number of beads drawn (B= 0.47, 95% CI -0.21 to 1.16, p=0.17); whereas IQ PRS (B=0.51, 95% CI 0.25 to 0.76, p<0.001) significantly predicted the number of beads drawn, and was thus associated with reduced JTC bias. The JTC was more strongly associated with higher level of psychotic-like experiences (PLE) in controls, including after controlling for IQ (B= -1.7, 95% CI -2.8 to -0.5, p=0.006), but did not relate to delusions in patients.\n\nConclusionsthe JTC reasoning bias in psychosis is not a specific cognitive deficit but is rather a manifestation or consequence, of general cognitive impairment. Whereas, in the general population, the JTC bias is related to psychotic-like experiences, independent of IQ. The work has potential to inform interventions targeting cognitive biases in early psychosis.

neuroscience↗

bioRxiv2019

Cannabis-associated symptom profiles in patients with first episode psychosis and population controls

ObjectiveThe evidence is mixed on whether cannabis use is associated with a particular symptomatology in first episode psychosis (FEP) patients.\n\nThe authors set out to investigate a) patterns of association between cannabis use and transdiagnostic symptom dimensions; b) whether the extent of use of cannabis contributes to the variation in clinical and subclinical symptom profiles.\n\nMethodThe authors analysed data from 901 patients and 1235 controls recruited across six countries, as part of the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI) study. Item response modelling was used to estimate two bifactor models, which included general and specific dimensions of psychotic symptoms in patients and psychotic experiences in controls. The associations between these dimensions and cannabis use was evaluated using linear mixed effects models analyses.\n\nResultsIn patients, there was a linear relationship between the positive symptom dimension and the extent of lifetime exposure to cannabis, with daily users of high potency cannabis having the highest score (B=0.35; 95%CI 0.14 to 0.56). Moreover, negative symptoms were more common among patients who never used cannabis compared with those with any pattern of use (B=-0.27; 95%CI -0.42 to -0.12).\n\nIn controls, psychotic experiences were associated with current use of cannabis but not with the extent of lifetime use.\n\nNeither patients nor controls presented differences in the depressive dimension related to cannabis use.\n\nConclusionsThe extent of use of cannabis explains part of the heterogeneous distribution of positive and negative symptoms of FEP patients.

neuroscience↗

bioRxiv2018

Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia related genes

Schizophrenia has been conceived as a disorder of brain connectivity but it is unclear how this network phenotype is related to the emerging genetics. We used morphometric similarity analysis of magnetic resonance imaging (MRI) data as a marker of inter-areal cortical connectivity in three prior case-control studies of psychosis: in total, N=185 cases and N=227 controls. Psychosis was associated with globally reduced morphometric similarity (MS) in all 3 studies. There was also a replicable pattern of case-control differences in regional MS which was significantly reduced in patients in frontal and temporal cortical areas, but increased in parietal cortex. Using prior brain-wide gene expression data, we found that the cortical map of case-control differences in MS was spatially correlated with cortical expression of a weighted combination of genes enriched for neu-robiologically relevant ontology terms and pathways. In addition, genes that were normally over-expressed in cortical areas with reduced MS were significantly up-regulated in a prior post mortem study of schizophrenia. We propose that this combination of neuroimaging and transcriptional data provides new insight into how previously implicated genes and proteins, as well as a number of unreported proteins in their vicinity on the protein interaction network, may interact to drive structural brain network changes in schizophrenia.

neuroscience↗