Biology subjects

Theis, H.

Publications and source records attributed to Theis, H..

12 recordsLinked to original sources

bioRxiv2026

Deep FLASH-seq profiling of purified canine sensory neurons uncovers species-specific signatures relevant to pain and itch

Naturally occurring pain and itch disorders in the domestic dog represent an important and underexploited opportunity for translational sensory neuroscience. These conditions largely mirror human disease, highlighting the need for detailed comparative understanding of canine somatosensory neurobiology. Here, we present a single-cell transcriptomic characterisation of the canine dorsal root ganglion (DRG), providing molecular insights into sensory neuron diversity in a species of direct veterinary and biomedical relevance. We develop a novel mechanical dissociation and fluorescence-activated cell sorting strategy enabling purification of intact whole neurons from adult canine DRG, followed by deep, full-length RNA sequencing using FLASH-seq. This approach yields high-quality transcriptional profiles with molecular depth analogous to deep neuronal profiling in human DRG, enabling resolution of neuronal identities and subtype-specific gene programs. Using these data, we identify canine sensory neuron clusters conforming to conserved principles of DRG molecular organization observed across species, including peptidergic and non-peptidergic nociceptors, low-threshold mechanoreceptors, proprioceptors, and thermosensory populations. Cross-species comparisons with human and mouse DRG datasets reveal broad conservation of pain- and itch-relevant pathways and therapeutic targets, alongside biologically meaningful divergence. We further identify species-specific differences in subtype-restricted expression of the pharmacologically relevant receptors IL31RA and SSTR2, which we validate using in situ hybridization and contextualize with human spatial transcriptomic data. Finally, we provide evidence that domestication-associated genes are non-randomly enriched in specific sensory neuron populations, suggesting that evolutionary history may have shaped somatosensory function. These data represent a resource for comparative sensory neuroscience and inform translational interpretation of pain and itch therapeutics across species.

neuroscience↗

bioRxiv2026

A high-throughput cost-efficient in vitro platform for the screening of immune senomodulators

With advancing age, the immune systems capacity to effectively combat pathogens diminishes. This decline of the overall immune function impacts both the innate and adaptive compartments, contributing in many cases to a systemic state of chronic inflammation which further increases the risk of the most prevalent non-communicable diseases and severe infections. Given the increase in median life expectancy with a demographic development towards a larger number of elderly people, identifying interceptive strategies to mitigate the individual and societal impact of diseases related to immune aging is of paramount importance. We developed a molecularly defined strategy to guide interventions with the aim to reduce immune aging. We introduce an omics-based drug screening platform to identify and characterize the pharmacological profile of immune senomodulators applicable to cross-age human cohorts using human-derived peripheral immune cells. To this aim we developed a robust experimental approach to screen for effective anti-aging compounds directly on human cells. This methodology allows us to quickly screen for drug candidates at different scales: from cost-effective bulk transcriptomics for a broader high-throughput overview of cellular responses, down to single-cell resolution approaches for a more detailed look at gene expression and other molecular data. This in vitro screening method is designed to maximize the clinical relevance of our findings, providing a direct link between preclinical research and patient care. By analyzing how different compounds affect the immune cells of individual persons, we can identify treatments that are most likely to be effective against aging in a subject-specific manner--a key step toward personalized medicine. In short, our approach enables a faster translation of anti-aging immune treatments from the lab to the clinic, tailoring them to each individuals unique biological makeup.

systems biology↗

bioRxiv2026

Individual Differences in Dopaminergic Modulation of Exploration-Exploitation Behaviour

Dopamine (DA) has been implicated in exploration-exploitation behaviour, i.e., exploring novel, potentially better options vs. exploiting known, previously rewarding options. Impairments in this trade-off occur in psychiatric disorders involving DAergic dysfunction, including addiction and schizophrenia. Pharmacological studies revealed a contribution of DA to exploration, but inconsistent findings suggest that interindividual variability in baseline DA may modulate effects. To address this, we investigated the effects of the DA precursor L-DOPA on exploration-exploitation during reinforcement learning in a sample of N = 75 healthy participants (n = 32 women), following a randomised, double-blind, placebo-controlled, pre-registered design (https://osf.io/p2r7u). We assessed whether putative baseline DA markers, including spontaneous eye blink rate, working memory (WM) capacity, and impulsivity, modulated drug effects and probed visual fixation patterns and pupil dilation as markers of exploration. L-DOPA had no overall effect on computational model parameters of random exploration, directed exploration or choice perseveration. WM capacity moderated drug effects on random exploration, with stronger effects at higher WM capacity. Remaining DA proxies showed no credible effects. Pooling the data from male participants with that from an earlier male-only study (Chakroun et al., 2020; total N = 74), L-DOPA increased uncertainty-dependent value weighting and perseveration strength, while decreasing habit updating, indicating a stronger tendency to repeat previous choices and slower decay of their influence over time. No credible drug effects were observed in female participants. Pupil dilation was tonically increased under L-DOPA and scaled with exploration behaviour and prediction error, confirming that pupillometry can index exploration-exploitation dynamics. Visual exploration patterns reflected uncertainty-driven sampling, but were unaffected by L-DOPA. Taken together, results suggest that DAergic modulation of exploration and perseveration behaviour may be contingent on cognitive capacity and sex, rather than exerting uniform effects across individuals.

neuroscience↗

bioRxiv2025

Ischemic injury triggers a protective microglial phenotype in models of Aβ pathology

Microglia are highly plastic cells that are capable of integrating subsequent insults. As the majority of Alzheimers Disease (AD) patients also show cerebrovascular pathology, we here aimed to dissect the interactions between AD and ischemic brain injury on the microglial response to amyloid beta (A{beta}) pathology. Surprisingly, we find that ischemic stroke in the presence of cerebral {beta}-amyloidosis results in the generation of a novel neuroprotective microglial phenotype. These microglia drive a rapid accumulation of highly dense A{beta} plaques that exhibit a relatively benign nature and are strikingly similar to A{beta} plaques observed in patients that are resilient to AD pathology. Thus, our data do not only highlight the impact of a co-morbid state of brain ischemia and A{beta} pathology on the microglial phenotype but also identify novel molecular pathways that may serve to promote beneficial microglial functions in AD.

neuroscience↗

bioRxiv2025

Lifetime physical activity and network attack tolerance contribute to the preservation of motor function in Parkinson's disease

We tested whether network resilience, quantified by network attack tolerance (NAT), is associated with dopamine terminal (DaT) integrity, motor function and lifetime factors in Parkinsons disease (PD). Data from 22 PD patients and 39 healthy controls included information on lifetime physical activity (PA), cognitive/motor performance, putaminal DaT integrity, and resting-state fMRI. NAT was assessed at global and subnetwork level by calculating global efficiency upon iterative node removal. Generalized linear-mixed-effects models were used to test the effects of PA, education, and dopamine integrity on NAT. Next, the moderating effect of lifetime factors on the association between NAT and motor function were assessed, controlling for DaT integrity. Greater putaminal DaT integrity was linked to higher somatomotor NAT. Higher global and somatomotor NAT supported motor function, especially in patients with moderate lifetime PA. Lifestyle factors may thus serve network-specific attack tolerance, thereby promoting motor preservation in PD, independent of dopaminergic impairment.

neuroscience↗

bioRxiv2024

Dopamine and temporal discounting: revisiting pharmacology and individual differences

Disorders characterised by changes in dopamine (DA) neurotransmission are often linked to changes in the temporal discounting of future rewards. Likewise, pharmacological manipulations of DA neuro-transmission in healthy individuals modulate temporal discounting, but there is considerable variability in the directionality of reported pharmacological effects, as enhancements and reductions of DA signalling have been linked to both increases and reductions of temporal discounting. This may be due to meaningful individual differences in drug effects and/or false positive findings in small samples. To resolve these inconsistencies, we 1) revisited pharmacological effects of the DA precursor L-DOPA on temporal discounting in a large sample of N = 76 healthy participants (n = 44 male) and 2) examined several putative proxy measures for DA to revisit the role of individual differences in a randomised, double-blind placebo-controlled pre-registered study (https://osf.io/a4k9j/). Replicating previous findings, higher rewards were discounted less (magnitude effect). Computational modelling using hierarchical Bayesian parameter estimation confirmed that the data in both drug conditions were best accounted for by a non-linear temporal discounting drift diffusion model. In line with recent animal and human work, L-DOPA reliably reduced the discount rate with a small effect size, challenging earlier findings in substantially smaller samples. We found no credible evidence for linear or quadratic effects of putative DA proxy measures on model parameters, calling into question the role of these measures in accounting for individual differences in DA drug effects.

neuroscience↗

bioRxiv2024

Putaminal dopamine modulates movement motivation in Parkinson's disease

The relative inability to produce effortful movements (akinesia) is the most specific motor sign of Parkinsons disease. The motor motivation hypothesis suggests that akinesia may not reflect a deficiency in motor control per se, but a deficiency in cost-benefit considerations for motor effort. For the first time, we investigated the quantitative effect of dopamine depletion on the motivation of motor effort in Parkinsons disease. A total of 21 patients with Parkinsons disease and 26 healthy controls were included. An incentivized force task was used to capture the amount of effort participants were willing to invest for different monetary incentive levels and dopamine transporter depletion in the bilateral putamen was assessed. Our results demonstrate that patients with Parkinsons disease applied significantly less grip force than healthy controls, especially for low incentive levels. Congruously, decrease of motor effort with greater loss of putaminal dopaminergic terminals was most pronounced for low incentive levels. This signifies that putaminal dopamine is most critical to motor effort when the trade-off with the benefit is poor. Taken together, we provide direct evidence that the reduction of effortful movements in Parkinsons disease depends on motivation and that this effect is associated with putaminal dopaminergic degeneration.

neuroscience↗

bioRxiv2024

Dynamic properties in functional connectivity changes and striatal dopamine deficiency in Parkinson's disease

IntroductionRecent studies in Parkinsons disease (PD) patients reported disruptions in dynamic functional connectivity (dFC, i.e., a characterization of spontaneous fluctuations in functional connectivity over time). Here, we assessed whether the integrity of striatal dopamine terminals directly modulates dFC metrics in separate PD cohorts, indexing dopamine-dependent changes in large-scale brain network dynamics and its implications in clinical features. MethodsWe pooled data from two cohorts reflecting early PD. From the Parkinsons Progression Marker Initiative (PPMI) cohort, resting-state functional magnetic resonance imaging (rsfMRI) and dopamine transporter (DaT) SPECT were available for 63 PD patients and 16 age- and sex-matched healthy controls. From the clinical research group 219 (KFO) cohort, rsfMRI imaging was available for 52 PD patients and 17 age- and sex-matched healthy controls. A subset of 41 PD patients and 13 healthy control subjects additionally underwent 18F-DOPA-PET imaging. The striatal synthesis capacity of 18F-DOPA PET and dopamine terminal quantity of DaT SPECT images were extracted for the putamen and the caudate. After rsfMRI pre-processing, an independent component analysis was performed on both cohorts simultaneously. Based on the derived components, an individual sliding window approach (44s window) and a subsequent k-means clustering were conducted separately for each cohort to derive dFC states (reemerging intra- and interindividual connectivity patterns). From these states we derived temporal metrics, such as average dwell time per state, state attendance, and number of transitions and compared them between groups and cohorts. Further, we correlated these with the respective measures for local dopaminergic impairment and clinical severity. ResultsIn both cohorts, dFC analysis resulted in three distinct states, varying in connectivity patterns and strength. In the PPMI cohort, PD patients showed a lower state attendance for the globally integrated (GI) state (X2(1, N=79) = 5.82, p= 0.016) and a lower number of transitions (U(N=79) = 337.5, z = -2.06 p= .039) than controls. Significantly, worse motor scores (UPDRS-III) and dopaminergic impairment in the putamen and the caudate were associated with low average dwell time in the GI state (UPDRS-III: {tau}b(N=63) = -.281; p =.003, DaT putamen: {tau}b(N=63)=.213, p= .023, DaT caudate: {tau}b(N=63)=.209, p= .025) and a low total number of transitions (UPDRS-III: {tau}b(N=63)= -.308; p = .001, DaT putamen: {tau}b(N=63)=.350, p<.001, DaT caudate: {tau}b(N=63)=.251, p=.007). Additionally, worse motor performance was associated with a low number of bi-directional transitions between the GI and the lesser connected (LC) state ({tau}b(N=63)= -.237; p =.019). These results could not be reproduced in the KFO cohort: No group differences in dFC measures or associations between dFC variables and dopamine synthesis capacity or clinical measure were observed. ConclusionIn early PD, relative preservation of motor performance may be linked to a more dynamic engagement of an interconnected brain state. Specifically, those large-scale network dynamics seem to depend on striatal dopamine availability. Notably, we obtained these results in only one cohort, but not in a replication sample. Key pointsO_LIExploring dopamines role in brain network dynamics in two Parkinsons disease (PD) cohorts, we unraveled PD-specific changes in dynamic functional connectivity (dFC). C_LIO_LIIn the discovery cohort, results suggest striatal dopamine availability influences large-scale network dynamics that are relevant in motor control. C_LIO_LIIn the confirmation cohort, these findings were not replicated, indicating PD-specific dFC changes are dependent on unrecognized cohort features. C_LI

neuroscience↗

bioRxiv2023

Pharmacological enhancement of dopamine neurotransmission does not affect illusory pattern perception

Psychotic symptoms and delusional belief have been linked to dopamine transmission in both healthy and clinical samples and are assumed to result at least in part from perceiving illusory patterns in noise. However, the existing literature on the role of dopamine in detecting patterns in noise is inconclusive. To address this issue, we assessed the effect of manipulating dopaminergic neurotransmission on illusory pattern perception in healthy individuals (n = 48, n = 19 female) in a double-blind placebo-controlled within-subjects design (see preregistration at https://osf.io/a4k9j/). We predicted individuals on vs. off L-DOPA to be more likely to perceive illusory patterns, specifically objects in images containing only noise. Using a signal detection model, however, we found no credible evidence that L-DOPA compared to placebo increased false alarm rates. Further, L-DOPA did not modulate measures of accuracy, discrimination sensitivity and response bias. In all cases, Bayesian statistics revealed strong evidence in favour of the null hypothesis Future studies should address possible dose-dependent effects and differential effects in healthy vs. clinical samples.

neuroscience↗

bioRxiv2020

Swarm Learning as a privacy-preserving machine learning approach for disease classification

Identification of patients with life-threatening diseases including leukemias or infections such as tuberculosis and COVID-19 is an important goal of precision medicine. We recently illustrated that leukemia patients are identified by machine learning (ML) based on their blood transcriptomes. However, there is an increasing divide between what is technically possible and what is allowed because of privacy legislation. To facilitate integration of any omics data from any data owner world-wide without violating privacy laws, we here introduce Swarm Learning (SL), a decentralized machine learning approach uniting edge computing, blockchain-based peer-to-peer networking and coordination as well as privacy protection without the need for a central coordinator thereby going beyond federated learning. Using more than 14,000 blood transcriptomes derived from over 100 individual studies with non-uniform distribution of cases and controls and significant study biases, we illustrate the feasibility of SL to develop disease classifiers based on distributed data for COVID-19, tuberculosis or leukemias that outperform those developed at individual sites. Still, SL completely protects local privacy regulations by design. We propose this approach to noticeably accelerate the introduction of precision medicine.

bioinformatics↗

bioRxiv2020

Alterations of multiple alveolar macrophage states in chronic obstructive pulmonary disease

Despite the epidemics of chronic obstructive pulmonary disease (COPD), the cellular and molecular mechanisms of this disease are far from being understood. Here, we characterize and classify the cellular composition within the alveolar space and peripheral blood of COPD patients and control donors using a clinically applicable single-cell RNA-seq technology corroborated by advanced computational approaches for: machine learning-based cell-type classification, identification of differentially expressed genes, prediction of metabolic changes, and modeling of cellular trajectories within a patient cohort. These high-resolution approaches revealed: massive transcriptional plasticity of macrophages in the alveolar space with increased levels of invading and proliferating cells, loss of MHC expression, reduced cellular motility, altered lipid metabolism, and a metabolic shift reminiscent of mitochondrial dysfunction in COPD patients. Collectively, single-cell omics of multi-tissue samples was used to build the first cellular and molecular framework for COPD pathophysiology as a prerequisite to develop molecular biomarkers and causal therapies against this deadly disease.

systems biology↗

bioRxiv2017

Cellular reprogramming of human monocytes is regulated by time-dependent IL4 signalling and NCOR2

The clinical and therapeutic value of human in vitro generated monocyte-derived dendritic cell (moDC) and macrophages is well established. However, in line with recent findings regarding myeloid cell ontogeny and due to our limited understanding of their physiological counterparts, transcriptional regulation and heterogeneity, the full potential of these important cellular systems is still underestimated.\n\nIn this study, we use cutting edge high-dimensional analysis methods to better understand the transcriptional organization, phenotypic heterogeneity and functional differences between human ex vivo isolated and in vitro generated mononuclear phagocytes with the aim to better realize their full potential in the clinic.\n\nWe demonstrate that human monocytes activated by MCSF or GMCSF most closely resemble inflammatory macrophages identified in vivo, while IL4 signalling in the presence of GMCSF generates moDCs resembling inflammatory DCs in vivo, but not steady state cDC1 or cDC2. Moreover, these reprogramming regimes lead to activated monocytes that present with profoundly different transcriptomic, metabolic, phenotypic and functional profiles. Furthermore, we demonstrate that CD14+ monocytes are integrating multiple exogenous activation signals such as GMCSF and IL4 in a combinatorial and temporal fashion, resulting in a high-dimensional cellular continuum of reprogrammed monocytes dependent on the mode and timing of cytokine exposure. Utilizing nanostraw-based knockdown technology, we demonstrate that the IL4-dependent generation of moDCs relies on the induction, nuclear localization and function of the transcriptional regulator NCOR2.\n\nFinally, we unravel unappreciated heterogeneity within the clinically moDCs population and propose a novel high-dimensional phenotyping strategy to better tailor clinical quality control strategies for patient need and culture conditions to enhance therapeutic outcome.

immunology↗