Biology subjects

Kahn, R.

Publications and source records attributed to Kahn, R..

14 recordsLinked to original sources

bioRxiv2026

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↗

bioRxiv2026

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↗

bioRxiv2026

Sulcal Widening in Schizophrenia Maps onto Sulcal Hubs and Energy-Synaptic Genes

Schizophrenia (SZ) is increasingly framed as a disorder of large-scale brain networks emerging from atypical early neurodevelopment, yet how network architecture relates to cortical folding abnormalities remains unclear. Here, we introduce a sulcal morphological-centred network framework that integrates normative modelling of sulcal width with diffusion-derived structural connectivity and transcriptomic data in a large multisite cohort (n = 5,392; 377 SZ). Individuals with SZ showed widespread sulcal widening, affecting 30 of 40 sulci and most pronounced in frontal, temporal and occipital regions. Critically, sulci with higher degree centrality, reflecting greater embedding within the structural connectome, exhibited disproportionately greater widening in SZ (pspin = 0.02), indicating that network hubs of cortical folding are preferentially affected. Transcriptomic integration using partial least squares regression identified a single component explaining 56.5% of SZ-related sulcal widening variance (pperm = 0.041), implicating genes enriched for synaptic signalling and energy metabolism with adult cortical expression bias and genetic enrichment for cross-disorder psychiatric risk. In contrast, oppositely weighted genes showed prenatal expression bias and enrichment for rare disruptive variants in autism spectrum disorder. Together, these findings link aberrant sulcal morphology in SZ to the brains network topology and molecular architecture, positioning cortical folding as a network-embedded phenotype in SZ.

neuroscience↗

bioRxiv2025

Pre-clinical validation of in vitro engineered but cell-free human tissue grafts for skeletal regeneration

Tissue engineering strategies predominantly consist of the autologous generation of living substitutes capable of restoring damaged body parts. Persisting challenges with patient-specific approaches include inconsistent performance, high costs and delayed graft availability. Towards developing a one-for-all solution, a more attractive paradigm lies in the exploitation of dedicated cell lines for the fabrication of human tissue grafts. Following decellularization, this new class of biomaterials relies on the sole extracellular matrix and embedded growth factors instructing endogenous repair. This conceptual approach was previously validated using a custom mesenchymal line for the manufacturing of human cartilage, exhibiting remarkable osteoinductive capacity following lyophilization. Key missing criteria to envision clinical translation include proper decellularization as well as stringent assessment of both immunogenicity and regenerative performance. Here, we report the engineering and subsequent decellularization of human cartilage tissue with minimal matrix impairment. Ectopic evaluation in immunocompetent and immunocompromised animals reveal preservation of osteoinductivity predicted by macrophage kinetic of polarization. By establishing in vitro human allogeneic co-culture models, we evidenced the immuno-evasive properties of cell-free human cartilages, controlling macrophages and dendritic cells maturation as well as T cell activation. Lastly, regenerative performance was stringently assessed in an immunocompetent rat orthotopic model whereby decellularized human cartilage grafts achieved morphological and mechanical restoration of all critical-sized femoral defects. Taken together, our study compiles robust safety and efficacy pre-requisites prompting a first-in-human trial for engineered and decellularized human tissue grafts.

bioengineering↗

bioRxiv2024

Heterogeneity of morphometric similarity networks in health and schizophrenia

IntroductionMorphometric similarity is a recently developed neuroimaging phenotype of inter-regional connectivity by quantifying the similarity of a region to other regions based on multiple MRI parameters. Altered average morphometric similarity has been reported in psychotic disorders at the group level, with considerable heterogeneity across individuals. We used normative modeling to address cross-sectional and longitudinal inter-individual heterogeneity of morphometric similarity in health and schizophrenia. MethodsMorphometric similarity for 62 cortical regions was obtained from baseline and follow-up T1-weighted scans of healthy individuals and patients with chronic schizophrenia. Cortical regions were classified into seven predefined brain functional networks. Using Bayesian Linear Regression and taking into account age, sex, image quality and scanner, we trained and validated normative models in healthy controls from eleven datasets (n = 4310). Individual deviations from the norm (z-scores) in morphometric similarity were computed for each participant for each network and region at both timepoints. A z-score [greater double equals] than 1.96 was considered supra-normal and a z-score [less double equals] -1.96 infra-normal. As a longitudinal metric, we calculated the change over time of the total number of infra- or supra-normal regions per participant. ResultsAt baseline, patients with schizophrenia had decreased morphometric similarity of the default mode network and increased morphometric similarity of the somatomotor network when compared with healthy controls. The percentage of patients with infra- or supra-normal values for any region at baseline and follow-up was low (<6%) and did not differ from healthy controls. Mean intra-group changes over time in the total number of infra- or supra-normal regions were small in schizophrenia and healthy control groups (<1) and there were no significant between-group differences. ConclusionsIn a case-control setting, a decrease of morphometric similarity within the default mode network may be a robust finding implicated in schizophrenia. However, normative modeling suggests that significant reductions and changes over time of regional morphometric similarity are evident only in a minority of patients.

neuroscience↗

bioRxiv2024

Integrated GWAS and Transcriptomic Analysis Identify New Candidate Genes for Seminal Root Growth Angle in Wheat (Triticum aestivum L.)

Increased interest in root system architecture (RSA) and its major importance for nutrient and water uptake have intensified the efforts for a detailed study of the different root types within the homorhizic root system found in most monocotyledons as wheat. Mature homorhizic root system comprises two root types regarding their origin: embryonic and pot embryonic. However, knowledge of the different root type ss physiology and RSA plasticity is still limited. In wheat, embryonic roots are the first to develop after seed germination and have an important role in crop establishment. Wheat seedlings develop between 3 and 5 embryonic roots that have the same origin, but they differ in their spatial distribution. The first emerging root of a wheat seedling develops from the base of the embryo and grows vertically down. The rest of the seminal roots emerge from the lateral sides of the embryo and grow with a very specific set-point angle dependent on variety. In this study, we showed that seminal roots with different set-point angle displayed differences in response to gravity and in auxin transport. We hypothesized that the differences in RSA among root types will be directed by differences in their transcriptomic profiles. To that end, we performed an RNA sequencing analysis on both root types. With the aim of gaining a more complete understanding of the seminal root architecture plasticity, we also studied the genetic variability associated with root set-point angle performing a Genome-Wide Association Study in a wheat genetic panel of 200 accessions. Our results combined, uncovered a cluster of genes located in Chromosome 2B that comprises new players in wheat RSA with potential roles in plant response to abiotic stress.

plant biology↗

bioRxiv2023

Fibroblasts as an in vitro model of circadian genetic and genomic studies

Bipolar disorder (BD) is a heritable disorder characterized by shifts in mood that manifest in manic or depressive episodes. Clinical studies have identified abnormalities of the circadian system in BD patients as a hallmark of underlying pathophysiology. Fibroblasts are a well-established in vitro model for measuring circadian patterns. We set out to examine the underlying genetic architecture of circadian rhythm in fibroblasts, with the goal to assess its contribution to the polygenic nature of BD disease risk. We collected, from primary cell lines of 6 healthy individuals, temporal genomic features over a 48 hour period from transcriptomic data (RNA-seq) and open chromatin data (ATAC-seq). The RNA-seq data showed that only a limited number of genes, primarily the known core clock genes such as ARNTL, CRY1, PER3, NR1D2 and TEF display circadian patterns of expression consistently across cell cultures. The ATAC-seq data identified that distinct transcription factor families, like those with the basic helix-loop-helix motif, were associated with regions that were increasing in accessibility over time. Whereas known glucocorticoid receptor target motifs were identified in those regions that were decreasing in accessibility. Further evaluation of these regions using stratified linkage disequilibrium score regression (sLDSC) analysis failed to identify a significant presence of them in the known genetic architecture of BD, and other psychiatric disorders or neurobehavioral traits in which the circadian rhythm is affected. In this study, we characterize the biological pathways that are activated in this in vitro circadian model, evaluating the relevance of these processes in the context of the genetic architecture of BD and other disorders, highlighting its limitations and future applications for circadian genomic studies.

genomics↗

bioRxiv2023

Fructose Induced KHK-C Increases ER Stress and Modulates Hepatic Transcriptome to Drive Liver Disease in Diet-Induced and Genetic Models of NAFLD.

Non-alcoholic fatty liver disease (NAFLD) is a liver manifestation of metabolic syndrome, and is estimated to affect one billion individuals worldwide. An increased intake of a high-fat diet (HFD) and sugar-sweetened beverages are risk-factors for NAFLD development, but how their combined intake promotes progression to a more severe form of liver injury is unknown. Here we show that fructose metabolism via ketohexokinase (KHK) C isoform increases endoplasmic reticulum (ER) stress in a dose dependent fashion, so when fructose is coupled with a HFD intake it leads to unresolved ER stress. Conversely, a liver-specific knockdown of KHK in C57BL/6J male mice consuming fructose on a HFD is adequate to improve the NAFLD activity score and exert a profound effect on the hepatic transcriptome. Overexpression of KHK-C in cultured hepatocytes is sufficient to induce ER stress in fructose free media. Upregulation of KHK-C is also observed in genetically obesity ob/ob, db/db and lipodystrophic FIRKO male mice, whereas KHK knockdown in these mice improves metabolic function. Additionally, in over 100 inbred strains of male or female mice hepatic KHK expression correlates positively with adiposity, insulin resistance, and liver triglycerides. Similarly, in 241 human subjects and their controls, hepatic Khk expression is upregulated in early, but not late stages of NAFLD. In summary, we describe a novel role of KHK-C in triggering ER stress, which offers a mechanistic understanding of how the combined intake of fructose and a HFD propagates the development of metabolic complications.

molecular biology↗

bioRxiv2021

Phylogenetic profiling and cellular analyses of ARL16 reveal roles in traffic of IFT140 and INPP5E

The ARF family of regulatory GTPases is ancient, with 16 members predicted to have been present in the last eukaryotic common ancestor. Our phylogenetic profiling of paralogs in diverse species identified four family members whose presence correlates with that of a cilium/flagellum: ARL3, ARL6, ARL13, and ARL16. No prior evidence links ARL16 to cilia or other cell functions, despite its presence throughout eukaryotes. Deletion of ARL16 in MEFs results in decreased ciliogenesis yet increased ciliary length. We also found Arl16 KO in MEFs to alter ciliary protein content, including loss of ARL13B, ARL3, INPP5E, and the IFT-A core component IFT140. Instead, both INPP5E and IFT140 accumulate at the Golgi in Arl16 KO lines, while other IFT proteins do not, suggesting a specific defect in traffic from Golgi to cilia. We propose that ARL16 regulates a Golgi-cilia traffic pathway and is required specifically in the export of IFT140 and INPP5E from the Golgi. SummaryPhylogenetic analyses of ARF family GTPases predict that ARL16 is linked to cilia. This was confirmed using MEFs deleted for ARL16, resulting in defects in Golgi to cilium traffic, with accumulation of IFT140 and INPP5E at Golgi.

cell biology↗

bioRxiv2021

Longitudinal allometry of sulcal morphology in health and schizophrenia

Scaling between subcomponents of cortical folding and total brain volume (TBV) in healthy individuals (HI) is allometric, i.e. non-linear. It is unclear whether this is also true in individuals with schizophrenia (SZ) or first-episode psychosis (FEP). The current study first confirmed normative allometric scaling norms in HI using discovery and replication samples. Cross-sectional and longitudinal diagnostic differences in folding subcomponents were then assessed using an allometric analytic framework. Structural imaging from a longitudinal (sample 1: HI and SZ, nHI Baseline = 298, nSZ Baseline = 169, nHI Follow-up = 293, nSZ Follow-up = 168, a total of 1087 images, all individuals [≥] 2 images, age 16-69 years) and a cross-sectional sample (sample 2: nHI = 61 and nFEP = 89, age 10-30 years) is leveraged to calculate global folding and its nested subcomponents: sulcation index (SI, total sulcal/cortical hull area) and determinants of sulcal area; sulcal length and sulcal depth. Scaling of the SI, sulcal area, and sulcal length with TBV in SZ and FEP was allometric and did not differ from HI. Longitudinal age trajectories demonstrated steeper loss of SI and sulcal area through adulthood in SZ. Longitudinal allometric analysis revealed that both annual change in SI and sulcal area was significantly stronger related to change in TBV in SZ compared to HI. Our results detail the first evidence of the disproportionate contribution of changes in SI and sulcal area to TBV changes in SZ. Longitudinal allometric analysis of sulcal morphology provides deeper insight into lifespan trajectories of cortical folding in SZ.

neuroscience↗

bioRxiv2020

Brain age prediction in schizophrenia: does the choice of machine learning algorithm matter?

BackgroundSchizophrenia has been associated with lifelong deviations in the normative trajectories of brain structure. These deviations can be captured using the brain-predicted age difference (brainPAD), which is the difference between the biological age of an individuals brain, as inferred from neuroimaging data, and their chronological age. Various machine learning algorithms are currently used for this purpose but their comparative performance has yet to be systematically evaluated. MethodsSix linear regression algorithms, ordinary least squares (OLS) regression, ridge regression, least absolute shrinkage and selection operator (Lasso) regression, elastic-net regression, linear support vector regression (SVR), and relevance vector regression (RVR), were applied to brain structural data acquired on the same 3T scanner using identical sequences from patients with schizophrenia (n=90) and healthy individuals (n=200). The performance of each algorithm was quantified by the mean absolute error (MAE) and the correlation (R) between predicted brain-age and chronological age. The inter-algorithm similarity in predicted brain-age, brain regional regression weights and brainPAD were compared using correlation analyses and hierarchical clustering. ResultsIn patients with schizophrenia, ridge regression, Lasso regression, elastic-net regression, and RVR performed very similarly and showed a high degree of correlation in predicted brain-age (R>0.94) and brain regional regression weights (R>0.66). By contrast, OLS regression, which was the only algorithm without a penalty term, performed markedly worse and showed a lower similarity with the other algorithms. The mean brainPAD was higher in patients than in healthy individuals but varied by algorithm from 3.8 to 5.2 years although all analyses were performed on the same dataset. ConclusionsLinear machine learning algorithms, with the exception of OLS regression, have comparable performance for age prediction on the basis of a combination of cortical and subcortical structural measures. However, algorithm choice introduced variation in brainPAD estimation, and therefore represents an important source of inter-study variability.

neuroscience↗

bioRxiv2020

Large-scale analysis of DNA methylation identifies cellular alterations in blood from psychosis patients and molecular biomarkers of treatment-resistant schizophrenia.

ObjectivePsychosis - a complex and heterogeneous neuropsychiatric condition characterized by hallucinations and delusions - is a common feature of schizophrenia. There is evidence for altered DNA methylation (DNAm) associated with schizophrenia in both brain and peripheral tissues. We aimed to undertake a systematic analysis of variable DNAm associated with psychosis, schizophrenia, and treatment-resistant schizophrenia, also exploring measures of biological ageing, smoking, and blood cell composition derived from DNAm data to identify molecular biomarkers of disease. MethodsWe quantified DNAm across the genome in blood samples from 4,483 participants from seven case-control cohorts including patients with schizophrenia or first-episode psychosis. Measures of biological age, cellular composition and smoking status were derived from DNAm data using established algorithms. DNAm and derived measures were analyzed within each cohort and the results combined by meta-analysis. ResultsPsychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNAm data, with the largest differences seen in treatment-resistant schizophrenia patients. DNAm at 95 CpG sites was significantly different between psychosis cases and controls, with 1,048 differentially methylated positions (DMPs) identified between schizophrenia cases and controls. Schizophrenia-associated DMPs colocalize to regions identified in genetic association studies, with genes annotated to these sites enriched for pathways relevant to disease. Finally, a number of the schizophrenia associated differences were only present in the treatment-resistant schizophrenia subgroup. ConclusionsWe show that DNAm data can be leveraged to derive measures of blood cell counts and smoking that are strongly associated with psychosis. Our DNAm meta-analysis identified multiple DMPs associated with both psychosis and a more refined diagnosis of schizophrenia, with evidence for differential methylation associated with treatment-resistant schizophrenia that potentially reflects exposure to clozapine.

genomics↗

bioRxiv2018

Modeling Vaccine Trials in Epidemics with Mild and Asymptomatic Infection

Vaccine efficacy against susceptibility to infection (VES), regardless of symptoms, is an important endpoint of vaccine trials for pathogens with a high proportion of asymptomatic infection, as such infections may contribute to onward transmission and outcomes such as Congenital Zika Syndrome. However, estimating VES is resource-intensive. We aim to identify methods to accurately estimate VEs when limited information is available and resources are constrained. We model an individually randomized vaccine trial by generating a network of individuals and simulating an epidemic. The disease natural history follows a Susceptible, Exposed, Infectious and Symptomatic or Infectious and Asymptomatic, Recovered model. We then use seven approaches to estimate VES, and we also estimate vaccine efficacy against progression to symptoms (VEP). A corrected relative risk and an interval censored Cox model accurately estimate VES and only require serologic testing of participants once, while a Cox model using only symptomatic infections returns biased estimates. Only acquiring serological endpoints in a 10% sample and imputing the remaining infection statuses yields unbiased VES estimates across values of R0 and accurate estimates of VEP for higher values. Identifying resource-preserving methods for accurately estimating VES is important in designing trials for diseases with a high proportion of asymptomatic infection.

epidemiology↗

bioRxiv2018

Choices in Vaccine Trial Design for Epidemics of Emerging Infections

The 2014-2016 Ebola epidemic highlighted the lack of consensus on the design of trials for investigational vaccine products in an emergency setting. With the advent of the ring vaccination strategy, it also underscored that the range of design options is evolving according to scientific need and creativity. Ideally, principles and protocols will be drawn up in advance, facilitating expediency and trust, for rapid deployment early in an epidemic. Here, we attempt a summary of the scientific, ethical and feasibility considerations relevant to different trial designs. We focus on four elements of design choices which, in our view, are most fundamental to designing an experimental vaccine trial and for which the most distinctive issues arise in the setting of an emerging infectious disease for which no proven vaccines exist: 1) randomization unit, 2) trial population, 3) comparator intervention and 4) trial implementation. Likewise, we focus on three of several ethical considerations in clinical research, namely the trials social and scientific value, its risk-benefit profile and its participant selection. A catalogue of possible designs to guide trial design choices is offered, along with a systematic evaluation of the benefits and drawbacks of each in given contexts.

epidemiology↗