Biology subjects

Homan, P.

Publications and source records attributed to Homan, P..

11 recordsLinked to original sources

bioRxiv2026

Teaching others reveals hidden structure in conceptual cognitive maps

Disorganized thought is a core feature of the psychosis spectrum. It is recognized, clinically and in daily life, through language, yet its proposed cognitive basis, shallow cognitive maps, the relational structures that organize knowledge, has been tested almost exclusively with task performance and neural measures. Here we show that the organization of a learned conceptual map can be read out from natural speech. Adults varying in schizotypal cognitive disorganization (n = 107) learned the same two-dimensional conceptual structure from images or sentences, then described their memory strategy and explained the material to a novice. Explaining elicited two-dimensional spatial descriptions selectively after image-based learning. Higher cognitive disorganization was associated with answers that tracked the question asked less closely, on an automated, rater-free embedding measure robust to report language, again selectively after image-based learning. Natural speech thus provides a scalable behavioral readout of conceptual map organization and its disorganization.

neuroscience↗

bioRxiv2026

CX3CR1 And MHCII Define Distinct Synovial Macrophage Populations With Conserved Inflammatory Response Across Mouse Models Of Rheumatoid Arthritis.

Macrophages in the synovial lining are critical for the maintenance of healthy tissue while also contributing to the pathogenesis of rheumatoid arthritis (RA). However, the field currently lacks a unifying characterization of synovial macrophage heterogeneity across steady-state and inflammation. Here, we defined 4 transcriptionally distinct populations of synovial macrophages CX3CR1+MHCII- (lining); CX3CR1-MHCII- (interstitial/sublining); CX3CR1-MHCII+ (monocyte-derived); and CX3CR1+MHCII+ (infiltrating). The MHCII-populations are long-lived and derived from embryonic precursors regardless of localization while the MHCII+ populations differentiate from bone marrow (BM) progenitors dependent on CCR2. We identified conserved activation pathways between acute and chronic mouse models of inflammatory arthritis as well as novel arthritis-associated subpopulations. During peak inflammation, the influx of BM-derived cells was associated with upregulation of monocyte-related genes with concurrent down-regulation of tissue-resident genes. Our results provide a unifying schema for describing synovial macrophages across conditions and pave the way for future studies in modulating transcriptional activity in rheumatoid arthritis.

immunology↗

bioRxiv2026

Reproducible Human Reward Imaging Phenotypes Exhibit Differential Sensitivity to Dopamine D2 Receptor Antagonism

Human reward processing varies along cue-centric and outcome-centric axes, but a reproducible mechanistic account of individual variation in incentive salience attribution has been lacking. Using fMRI across five cohorts (N-total=1,251; N1=890; N2=245; N3=34; N4=48; N5=34), we identified two robust imaging phenotypes mirroring sign- and goal-tracking (ST-like, GT-like). ST-like individuals showed dominant ventral striatal responses to reward-anticipation cues and sustained incentive salience attribution; GT-like individuals showed heightened responses to reward outcomes. This distinction was replicable across sites and independent samples. Single-dose and repeated-dose D2/D3 antagonism (risperidone, haloperidol, amisulpride) selectively reduced anticipatory ventral striatal activity in ST, with single-dose antagonism additionally producing a parallel drop in self-reported energy. Instead, D2/D3 partial agonism (aripiprazole) increased anticipatory and reduced outcome-phase responses in GT. In a psychosis cohort, antipsychotic D2 affinity was associated with blunted anticipatory signals and higher negative symptom burden, offering a neuroimaging-driven basis for stratifying patients and predicting response to dopaminergic agents.

neuroscience↗

bioRxiv2025

Disorganization impairs cognitive maps built from visual inputs

Background and HypothesisCognitive disorganization is a core disturbance across the psychosis spectrum, characterized by difficulties integrating perceptual information into coherent representations. How such disturbances affect the construction of internal cognitive maps remains unclear. A key question is whether these maps emerge from visual input as readily as from language structure. We hypothesized that cognitive disorganization would impair cognitive maps derived from visual input while sparing performance when structure was provided linguistically. Study DesignParticipants with varying schizotypy learned food items associated with two attributes: who consumed the food (age group) and when it was consumed (time of day). These attributes were presented as images or language descriptions and organized in a two-dimensional (2D) conceptual space. Participants then completed similarity judgment and reward-learning tasks requiring inference of the underlying relational structure. Study ResultsAmong individuals with higher cognitive disorganization, 2D distances were less predictive of similarity judgments, but only when relational structure had to be inferred from visual input. In the reward-learning task, computational modeling indicated that decisions were guided by spatial representations (Gaussian process). Higher cognitive disorganization was associated with weakened spatial generalization when structure had to be inferred from visual input, but not when it was provided through language. ConclusionsCognitive disorganization disrupts the ability to build and use cognitive maps from visual input, while performance appeared preserved when structure was conveyed through language. These findings support the shallow cognitive map hypothesis and suggest that cognitive disorganization selectively disrupts the transformation of perceptual input into stable relational representations.

neuroscience↗

bioRxiv2025

Multimodal Approach for Identification and Validation of Hepatocellular Carcinoma Targets for Radiotheranostics

Identifying tumor selective targets is critical for the development of precision diagnostic and therapeutic agents in oncology. Despite advances in precision oncology elsewhere, there are no FDA-approved hepatocellular carcinoma (HCC)-selective treatments. HCC is the most common type of liver cancer and accounts for significant morbidity and mortality worldwide. Here, we sought to integrate bulk (371 cases) and single cell RNA sequencing (scRNAseq, n=2 datasets, 34 cases, 102,956 cells) of patient samples to enrich for molecules that are overexpressed in HCC, which could serve as HCC-selective targets. To guide definitions of tumor and normal cell clusters with higher fidelity, we also imported a normal liver scRNAseq dataset. Using this integrated approach, we identified several HCC-selective plasma membrane molecules. To validate these targets, we performed immunohistochemical staining of HCC and normal tissue microarrays and confirmed HCC-selective staining of identified targets. Next, we verified the presence of these targets in several commercially available HCC cell lines by flow cytometry and western blot. Finally, we designed, engineered, and tested novel antibody-based positron emission tomography (immunoPET) agents to these targets in various murine models of liver cancer. Our findings confirm that we can leverage this multimodal approach to identify and validate of HCC-selective targets, which can be used to develop tumor-selective diagnostic and therapeutic radiopharmaceuticals, or radiotheranostics, and other precision oncology agents. One Sentence SummaryA multimodal pipeline defines and validates tumor-selective surface targets for radiotheranostic use in hepatocellular carcinoma.

cancer biology↗

bioRxiv2024

Genetic analysis of retinal cell types reveals synaptic pathology in schizophrenia

ImportanceAs an accessible part of the central nervous system, the retina provides a unique window to study pathophysiological mechanisms of brain disorders in humans. Imaging and electrophysiological studies have revealed retinal alterations across several neuropsychiatric and neurological disorders. However, it remains largely unclear whether primary disease mechanisms within the retina contribute to the observed retinal alterations and which specific retinal cell types and biological mechanisms are involved. ObjectiveTo determine whether specific retinal cell types are affected by genomic risk for neuropsychiatric and neurological disorders and to explore the mechanisms through which genomic risk converges in these cell types. Design, Setting, and ParticipantsIn this study, we combined findings from genome-wide association studies in schizophrenia, bipolar disorder, major depressive disorder, multiple sclerosis, Parkinson disease, Alzheimer disease, and stroke with retinal single-cell transcriptomic data sets from humans, macaques, and mice. To identify susceptible cell types, we applied MAGMA cell type enrichment analyses and performed subsequent pathway analyses. Furthermore, we translated the cellular top hit to the structural level by using retinal optical coherence tomography and genotyping data in the large population-based UK Biobank cohort (n = 36,349). Main Outcomes and MeasuresCell type-specific enrichment of genetic risk loading for neuropsychiatric and neurological disorder traits in the gene expression profiles of retinal cells. ResultsAmacrine cells (interneurons within the retina) were robustly enriched in schizophrenia genetic risk across mammalian species and in different developmental stages. This enrichment was primarily driven by genes involved in synapse biology. On the structural level, higher polygenic risk for schizophrenia was associated with thinning of the ganglion cell-inner plexiform layer, which contains dendrites and synaptic connections of amacrine cells. Moreover, retinal immune cell populations were enriched in multiple sclerosis genetic risk. No consistent cell type associations were found for bipolar disorder, major depressive disorder, Parkinson and Alzheimer disease, or stroke. Conclusions and RelevanceThis study provides novel insights into the cellular underpinnings of retinal alterations in neuropsychiatric and neurological disorders and highlights the retina as a potential proxy to study synaptic pathology in schizophrenia.

neuroscience↗

bioRxiv2024

Mechanistic Analysis of Riboswitch Ligand Interactions Provides Insights into Pharmacological Control over Gene Expression

Riboswitches are structured RNA elements that regulate gene expression upon binding to small molecule ligands. Understanding the mechanisms by which small molecules impact riboswitch activity is key to developing potent, selective ligands for these and other RNA targets. We report the structure-informed design of chemically diverse synthetic ligands for PreQ1 riboswitches. Multiple X-ray co-crystal structures of synthetic ligands with the Thermoanaerobacter tengcongensis (Tte)-PreQ1 riboswitch confirm a common binding site with the cognate ligand, despite considerable chemical differences among the ligands. Structure probing assays demonstrate that one ligand causes conformational changes similar to PreQ1 in six structurally and mechanistically diverse PreQ1 riboswitch aptamers. Single-molecule force spectroscopy is used to demonstrate differential modes of riboswitch stabilization by the ligands. Binding of the natural ligand brings about the formation of a persistent, folded pseudoknot structure, whereas a synthetic ligand decreases the rate of unfolding through a kinetic mechanism. Single round transcription termination assays show the biochemical activity of the ligands, while a GFP reporter system reveals compound activity in regulating gene expression in live cells without toxicity. Taken together, this study reveals that diverse small molecules can impact gene expression in live cells by altering conformational changes in RNA structures through distinct mechanisms.

biochemistry↗

bioRxiv2023

Estimating multimodal brain variability in schizophreniaspectrum disorders: A worldwide ENIGMA study

ObjectiveSchizophrenia is a multifaceted disorder associated with structural brain heterogeneity. Despite its relevance for identifying illness subtypes and informative biomarkers, structural brain heterogeneity in schizophrenia remains incompletely understood. Therefore, the objective of this study was to provide a comprehensive insight into the structural brain heterogeneity associated with schizophrenia. MethodsThis meta- and mega-analysis investigated the variability of multimodal structural brain measures of white and gray matter in individuals with schizophrenia versus healthy controls. Using the ENIGMA dataset of MRI-based brain measures from 22 international sites with up to 6139 individuals for a given brain measure, we examined variability in cortical thickness, surface area, folding index, subcortical volume and fractional anisotropy. ResultsWe found that individuals with schizophrenia are distinguished by higher heterogeneity in the frontotemporal network with regard to multimodal structural measures. Moreover, individuals with schizophrenia showed higher homogeneity of the folding index, especially in the left parahippocampal region. ConclusionsHigher multimodal heterogeneity in frontotemporal regions potentially implies different subtypes of schizophrenia that converge on impaired frontotemporal interaction as a core feature of the disorder. Conversely, more homogeneous folding patterns in the left parahippocampal region might signify a consistent characteristic of schizophrenia shared across subtypes. These findings underscore the importance of structural brain variability in advancing our neurobiological understanding of schizophrenia, and aid in identifying illness subtypes as well as informative biomarkers.

neuroscience↗

bioRxiv2019

Relapse prevention through health technology program reduces hospitalization in schizophrenia

ImportancePsychiatric hospitalization is a major driver of cost in the treatment of schizophrenia. Symptom relapses are a frequent cause of hospitalization and both are primary source of burden to patients and their supporters.\n\nObjectiveTo determine whether a novel, multicomponent, and technology-enhanced approach to relapse prevention in outpatients following a psychiatric hospitalization could reduce days spent in a hospital after discharge.\n\nDesignThe Improving Care and Reducing Cost (ICRC) study was a quasi-experimental clinical trial in outpatients with schizophrenia conducted between February 2013 and April 2015 at 10 different sites in the US. Data were obtained from 89 participants who received usual relapse prevention services, followed by a second cohort of 349 participants who received the technology-enhanced relapse prevention program. Both groups were followed for 6 months.\n\nSettingOutpatient setting.\n\nParticipantsPatients were between 18 and 60 years old; had a diagnosis of schizophrenia, schizoaffective disorder, or psychotic disorder not otherwise specified; and were currently hospitalized or had been hospitalized within the past 30 days.\n\nInterventionPatients received usual care or a technology-enhanced relapse prevention program during a 6-month period after discharge.\n\nMain Outcome(s) and Measure(s)Days spent in a psychiatric hospital during 6 months after discharge.\n\nResultsThe study included 438 patients. Control participants (N = 89; 37 females) were enrolled first and received usual care for relapse prevention, and followed by 349 participants (128 females) who received technology-enhanced relapse prevention. Days of hospitalization were reduced by 4 days (Mean days: b = -4.25, 95% CI: -8.29; -0.21, P = 0.039) during follow-up in the intervention condition compared to control.\n\nConclusions and RelevanceThe reduction in days spent in the hospital for participants in the technology-informed relapse prevention program compared to those who received usual care, and the previously reported high satisfaction and usability suggest that technology-enhanced relapse prevention is an effective and feasible way to reduce rehospitalization days among patients with schizophrenia.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSCan rehospitalizations in schizophrenia be prevented at reduced cost by innovative mobile technology-delivered interventions?\n\nFindingsIn this clinical trial with 438 patients, a technology-enhanced relapse prevention program compared to usual services reduced an average of four days of hospitalization per patient during the first 6 months following an index hospitalization.\n\nMeaningRelapse prevention through a health technology may improve care while reducing costs associated with hospitalization.

neuroscience↗

bioRxiv2018

Affective flexibility without perceptual awareness

In an ever-changing environment, survival depends on learning which stimuli represent threat, and also on updating such associations when circumstances shift. Humans can acquire physiological responses to threat-associated stimuli even when they are unaware of them, but the role of awareness in updating threat contingencies remains unknown. This complex process - generating novel responses while simultaneously suppressing learned ones - relies on distinct neural mechanisms from initial learning, and has only been shown with awareness. Can it occur unconsciously? Here we show that it can. Participants underwent classical threat conditioning to visual stimuli that were suppressed from their awareness. One of two images was paired with an electric shock; halfway through the experiment, contingencies were reversed and the shock was paired with the other image. We found that physiological responses reflected changes in stimulus-threat pairings independently of stimulus awareness, demonstrating the sophistication of unconscious affective flexibility.

neuroscience↗

bioRxiv2018

Striatal volume and functional connectivity predict weight gain in early-phase psychosis

BackgroundSecond-generation antipsychotic drugs (SGAs) are essential in the treatment of psychotic disorders, but are well-known for inducing substantial weight gain and obesity. Critically, weight gain may reduce life expectancy for up to 20-30 years in patients with psychotic disorders, and prognostic bio-markers are generally lacking. The dorsal striatum, rich in dopamine D2 receptors which are antagonized by antipsychotic medications, plays a key role in the human reward system and in appetite regulation, suggesting that altered dopamine activity in the striatal reward circuitry may be responsible for increased food craving and resultant weight gain.\n\nMethodsHere, we measured striatal volume and striatal resting state functional connectivity at baseline, and weight gain over the course of 12 weeks of antipsychotic treatment in 81 patients with early-phase psychosis. We also included a sample of 58 healthy controls. Weight measurements were completed at baseline, and then weekly for 4 weeks, and every 2 weeks until week 12. We used linear mixed models to compute individual weight gain trajectories. Striatal volume and whole-brain striatal connectivity were then calculated for each subject, and used to assess the relationship between striatal structure and function and individual weight gain in multiple regression models.\n\nOutcomesPatients had similar baseline weights and body mass indices (BMI) compared to healthy controls. There was no evidence that prior drug exposure or duration of untreated psychosis correlated with baseline BMI. Higher left putamen volume and lower frontopolar connectivity predicted magnitude of weight gain in patients, and these effects multiplied when the structure-function interaction was considered.\n\nInterpretationThese results provide evidence for a synergistic effect of striatal structure and function on antipsychotics-induced weight gain. Lower fronto-striatal connectivity, implicated in less optimal long-term decision making, was associated with more weight gain, and this relationship was stronger for higher compared to lower left putamen volumes.\n\nFundingSupported by NIMH grant P50MH080173 to Dr. Malhotra, grant R01MH060004 to Dr. Robinson, grant R01MH076995 to Dr. Szeszko and R21MH101746 to Drs. Robinson and Szeszko.

neuroscience↗