Biology subjects

Loeffler, M.

Publications and source records attributed to Loeffler, M..

12 recordsLinked to original sources

bioRxiv2025

Chronic pain is linked to a resting-state neural archetype that optimizes learning from punishments

Chronic pain is a leading cause of disability, yet its underlying susceptibility traits remain unclear. Disorders like chronic pain may stem from extreme neural types, or archetypes, optimized for specific cognitive strategies and reflected in patterns of resting-state networks. Here, we examined a sample from the general population (n = 892) and three clinical samples with subacute back pain (n = 76), chronic back pain (n = 30), and treatment-resistant depression (n = 24). Using the sample from the general population, we found three neural archetypes that prioritize different cognitive strategies. Clinical pain samples, compared to the sample from the general population, mapped close to an archetype optimized for punishment learning (Archetype P). We replicated these results by recomputing the archetypes starting from the clinical pain samples, additionally revealing an association between Archetype P and pain severity. These findings suggest a neural-cognitive trait underlying susceptibility to chronic pain.

neuroscience↗

bioRxiv2024

The utility of explainable A.I. for MRI analysis: Relating model predictions to neuroimaging features of the aging brain

IntroductionDeep learning models highly accurately predict brain-age from MRI but their explanatory capacity is limited. Explainable A.I. (XAI) methods can identify relevant voxels contributing to model estimates, yet, they do not reveal which biological features these voxels represent. In this study, we closed this gap by relating voxel-based contributions to brain-age estimates, extracted with XAI, to human-interpretable structural features of the aging brain. MethodsTo this end, we associated participant-level XAI-based relevance maps extracted from two ensembles of 3D-convolutional neural networks (3D-CNN) that were trained on T1-weighted and fluid attenuated inversion recovery images of 2016 participants (age range 18-82 years), respectively, with regional cortical and subcortical gray matter volume and thickness, perivascular spaces (PVS) and water diffusion-based fractional anisotropy of main white matter tracts. ResultsWe found that all neuroimaging markers of brain aging, except for PVS, were highly correlated with the XAI-based relevance maps. Overall, the strongest correlation was found between ventricular volume and relevance (r = 0.69), and by feature, temporal-parietal cortical thickness and volume, cerebellar gray matter volume and frontal-occipital white matter tracts showed the strongest correlations with XAI-based relevance. ConclusionOur ensembles of 3D-CNNs took into account a plethora of known aging processes in the brain to perform age prediction. Some age-associated features like PVS were not consistently considered by the models, and the cerebellum was more important than expected. Taken together, we highlight the ability of end-to-end deep learning models combined with XAI to reveal biologically relevant, multi-feature relationships in the brain.

neuroscience↗

bioRxiv2024

Dense but not alpha granules of platelets are required for insulin secretion from pancreatic beta cells

ObjectivesPlatelets, originally described for their role in blood coagulation, are now also recognized as key players in modulating inflammation, tissue regeneration, angiogenesis, and carcinogenesis. Recent evidence suggests that platelets also influence insulin secretion from pancreatic {beta} cells. The multifaceted functions of platelets are mediated by the factors stored in their alpha granules (AGs) and dense granules (DGs). AGs primarily contain proteins, while DGs are rich in small molecules, and both types of granules are released during blood coagulation. Specific components stored in AGs and DGs are implicated in various inflammatory, regenerative, and tumorigenic processes. However, the relative contributions of AGs and DGs to the regulation of pancreatic {beta} cell function have not been previously explored. MethodsIn this study, we utilized mouse models deficient in AG content (neurobeachin-like 2 (Nbeal2) -deficient mice) and models with defective DG release (Unc13d-deficiency in bone marrow-derived cells) to investigate the impact of platelet granules on insulin secretion from pancreatic {beta} cells. ResultsOur findings indicate that AG deficiency has little to no effect on pancreatic {beta} cell function and glucose homeostasis. Conversely, mice with defective DG release exhibited glucose intolerance and reduced insulin secretion. Furthermore, Unc13d-deficiency in hematopoietic stem cells led to a reduction in adipose tissue gain in obese mice. ConclusionsObtained data suggest that DGs, but not AGs, mediate the influence of platelets on pancreatic {beta} cells, thereby modulating glucose metabolism.

physiology↗

bioRxiv2024

Peptide-stimulation of autologous T cells reverts immune checkpoint inhibitor resistance of hypermutated colorectal cancer cells

Two hypermutated colon cancer cases with patient-derived cell lines, peripheral and tumor-infiltrating T cells available were selected for detailed investigation of immunological response. T cells co-cultured with autologous tumor cells showed only low levels of pro-inflammatory cytokines and failed at tumor recognition. Similarly, treatment of co-cultures with immune checkpoint inhibitors (ICI) did not boost antitumor immune responses. Since proteinase inhibitor 9 (PI-9) was detected in tumor cells, a specific inhibitor (PI-9i) was used in addition to ICI in T cell cytotoxicity testing. However, only pre-stimulation with tumor-specific peptides (cryptic and neoantigenic) significantly increased recognition and elimination of tumor cells by T cells independently of ICI or PI-9i. We showed, that ICI resistant tumor cells can be targeted by tumor-primed T cells and also demonstrated the superiority of tumor-naive peripheral blood T cells compared to highly exhausted tumor-infiltrating T cells. Future precision immunotherapeutic approaches should include multimodal strategies to successfully induce durable anti-tumor immune responses.

cancer biology↗

bioRxiv2023

Event-related modulation of alpha rhythm explains the auditory P300 evoked response in EEG

Evoked responses and oscillations represent two major electrophysiological phenomena in the human brain yet the link between them remains rather obscure. Here we show how most frequently studied EEG signals: the P300-evoked response and alpha oscillations (8-12 Hz) can be linked with the baseline-shift mechanism. This mechanism states that oscillations generate evoked responses if oscillations have a non-zero mean and their amplitude is modulated by the stimulus. Therefore, the following predictions should hold: 1) the temporal evolution of P300 and alpha amplitude is similar, 2) spatial localisations of the P300 and alpha amplitude modulation overlap, 3) oscillations are non-zero mean, 4) P300 and alpha amplitude correlate with cognitive scores in a similar fashion. To validate these predictions, we analysed the data set of elderly participants (N=2230, 60-82 years old), using a) resting-state EEG recordings to quantify the mean of oscillations, b) the event-related data, to extract parameters of P300 and alpha rhythm amplitude envelope. We showed that P300 is indeed linked to alpha rhythm, according to all four predictions. Our results provide an unifying view on the interdependency of evoked responses and neuronal oscillations and suggest that P300, at least partly, is generated by the modulation of alpha oscillations.

neuroscience↗

bioRxiv2021

Investigating the genetic and environmental basis of head micromovements during MRI

IntroductionHead motion during magnetic resonance imaging is heritable. Further, it shares phenotypical and genetic variance with body mass index (BMI) and impulsivity. Yet, to what extent this trait is related to single genetic variants and physiological or behavioral features is unknown. We investigated the genetic basis of head motion in a meta-analysis of genome-wide association studies. Further, we tested whether physiological or psychological measures, such as respiratory rate or impulsivity, mediated the relationship between BMI and head motion. MethodsWe conducted a genome-wide association meta-analysis for mean and maximal framewise head displacement (FD) in seven population neuroimaging cohorts (UK Biobank, LIFE-Adult, Rotterdam Study cohort 1-3, Austrian Stroke Prevention Family Study, Study of Health in Pomerania; total N = 35.109). We performed a pre-registered analysis to test whether respiratory rate, respiratory volume, self-reported impulsivity and heart rate mediated the relationship between BMI and mean FD in LIFE-Adult. ResultsNo variant reached genome-wide significance for neither mean nor maximal FD. Neither physiological nor psychological measures mediated the relationship between BMI and head motion. ConclusionBased on these findings from a large meta-GWAS and pre-registered follow-up study, we conclude that the previously reported genetic correlation between BMI and head motion relies on polygenic variation, and that neither psychological nor simple physiological parameters explain a substantial amount of variance in the association of BMI and head motion. Future imaging studies should thus rigorously control for head motion at acquisition and during preprocessing.

neuroscience↗

bioRxiv2018

Use of IFNγ/IL10 ratio for stratification of hydrocortisone therapy in patients with septic shock

BackgroundLarge clinical trials testing hydrocortisone therapy in septic shock have produced conflicting results. Subgroups may however benefit depending on their individual immune response.\n\nMethodsWe performed an exploratory analysis of the CORTICUS trial database employing machine learning to a panel of 137 variables collected from 83 patients (60 survivors, 23 non-survivors) including demographic and clinical measures, organ failure scores, leukocyte counts and circulating cytokine levels. The identified biomarker was validated against data collected from patients enrolled into a cohort of the Hellenic Sepsis Study Group (HSSG) (n=162) and two data sets of two other clinical trials. Ex vivo studies were performed on this biomarker to assess a possible mechanistic role.\n\nResultsA low serum IFN{gamma}/IL10 ratio predicted increased survival in the hydrocortisone group whereas a high ratio predicted better survival in the placebo group. Using this ratio for a decision rule, we found significant improvement in survival in the groups of patients being in compliance with the prediction rule (discovery set: OR=3.03 [95% Cl: 1.05-8.75], P=0.031, validation set: OR=2.01 [95% CI: 1.04-3.88], P=0.026). Applying the rule to two further, smaller datasets showed the same tendency. Mechanistic studies revealed that IFN{gamma}/IL10 was negatively associated with pathogen load in spiked human blood. An in silico analysis of published IFN{gamma} and IL10 values in bacteremic and non-bacteremic SIRS patients supported this association between the ratio and pathogen burden.\n\nConclusionIf confirmed prospectively, the IFN{gamma}/IL10 ratio could be used as a rapidly available theranostic for use of hydrocortisone therapy in septic shock.

immunology↗

bioRxiv2018

Genetic Determinants of Cortical Structure (Thickness, Surface Area and Volumes) among Disease Free Adults in the CHARGE Consortium

Cortical thickness, surface area and volumes (MRI cortical measures) vary with age and cognitive function, and in neurological and psychiatric diseases. We examined heritability, genetic correlations and genome-wide associations of cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprised 22,822 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the United Kingdom Biobank. Significant associations were replicated in the Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA) consortium, and their biological implications explored using bioinformatic annotation and pathway analyses. We identified genetic heterogeneity between cortical measures and brain regions, and 161 genome-wide significant associations pointing to wnt/{beta}-catenin, TGF-{beta} and sonic hedgehog pathways. There was enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.

genetics↗

bioRxiv2018

Planar cell polarity pathway and development of the human visual cortex

The radial unit hypothesis provides a framework for global (proliferation) and regional (distribution) expansion of the primate cerebral cortex. Using principal component analysis (PCA), we have identified cortical regions with shared variance in their surface area and cortical thickness, respectively, segmented from magnetic resonance images obtained in 23,800 participants. We then carried out meta-analyses of genome-wide association studies of the first two principal components for each phenotype. For surface area (but not cortical thickness), we have detected strong associations between each of the components and single nucleotide polymorphisms in a number of gene loci. The first (global) component was associated mainly with loci on chromosome 17 (9.5e-32 [≤] p [≤] 2.8e-10), including those detected previously as linked with intracranial volume and/or general cognitive function. The second (regional) component captured shared variation in the surface area of the primary and adjacent secondary visual cortices and showed a robust association with polymorphisms in a locus on chromosome 14 containing Disheveled Associated Activator of Morphogenesis 1 (DAAM1; p=2.4e-34). DAAM1 is a key component in the planar-cell-polarity signaling pathway. In follow-up studies, we have focused on the latter finding and established that: (1) DAAM1 is highly expressed between 12th and 22nd post-conception weeks in the human cerebral cortex; (2) genes co-expressed with DAAM1 in the primary visual cortex are enriched in mitochondria-related pathways; and (3) volume of the lateral geniculate nucleus, which projects to regions of the visual cortex staining for cytochrome oxidase (a mitochondrial enzyme), correlates with the surface area of the visual cortex in major-allele homozygotes but not in carriers of the minor allele. Altogether, we speculate that, in concert with thalamocortical input to cortical subplate, DAAM1 enables migration of neurons to cytochrome-oxidase rich regions of the visual cortex, and, in turn, facilitates regional expansion of this set of cortical regions during development.

neuroscience↗

bioRxiv2018

The age-dependent relationship between resting heart rate variability and functional brain connectivity

Resting heart rate variability (HRV), an index of parasympathetic cardioregulation and an individual trait marker related to mental and physical health, decreases with age. Previous studies have associated resting HRV with structural and functional properties of the brain - mainly in cortical midline and limbic structures. We hypothesized that HRV may alter its relationship with brain structure and function across the adult lifespan. In 388 healthy subjects of three age groups (140 younger: 26.0{+/-}4.2 years, 119 middle-aged: 46.3{+/-}6.2 years, 129 older: 66.9{+/-}4.7 years), gray matter structure (voxel-based morphometry) and resting-state functional connectivity (eigenvector centrality mapping and exploratory seed-based functional connectivity) were related to resting HRV, measured as the root mean square of successive differences (RMSSD). Confirming previous findings, resting HRV decreased with age. For HRV-related gray matter volume, there were no statistically significant differences between the age groups, nor similarities across all age groups. In whole-brain functional connectivity analyses, we found an age-dependent association between resting HRV and eigenvector centrality in the bilateral ventromedial prefrontal cortex (vmPFC), driven by the younger adults. Across all age groups, HRV was positively correlated with network centrality in bilateral posterior cingulate cortex. Seed-based functional connectivity analysis using the vmPFC cluster revealed an HRV-related cortico-cerebellar network in younger but not in middle-aged or older adults. Our results indicate that the decrease of HRV with age is accompanied by changes in functional connectivity along the cortical midline. This extends our knowledge of brain-body interactions and their changes over the lifespan.

neuroscience↗

bioRxiv2018

MDM4 is an essential disease driver targeted by 1q gain in Burkitt lymphoma

Oncogenic MYC activation promotes cellular proliferation in Burkitt lymphoma (BL), but also induces cell cycle arrest and apoptosis mediated by TP53, a tumor suppressor gene that is mutated in 40% of BL cases. To identify therapeutic targets in BL, we investigated molecular dependencies in BL cell lines using RNAi-based, loss-of-function screening. By integrating genotypic and RNAi data, we identified a number of genotype-specific dependencies including the dependence of TCF3/ID3 mutant cell lines on TCF3 and of MYD88 mutant cell lines on TLR signaling. TP53 wild-type (TP53wt) BL were dependent on MDM4, a negative regulator of TP53. In BL cell lines, MDM4 knockdown induced cell cycle arrest and decreased tumor growth in a xenograft model in a p53-dependent manner, while small molecule inhibition of the MDM4-p53 interaction restored p53 activity resulting in cell cycle arrest. Consistent with the pathogenic effect of MDM4 upregulation in BL, we found that TP53wt BL samples were enriched for gain of chromosome 1q which includes the MDM4 locus. 1q gain was also enriched across non-BL cancer cell lines (n=789) without TP53 mutation (23% in TP53wt and 12% in TP53mut, p<0.001). In a set of 216 cell lines representing 19 cancer entities from the Achilles project, MDM4 was the strongest genetic dependency in TP53wt cell lines (p<0.001).\n\nOur findings show that in TP53wt BL, MDM4-mediated inhibition of p53 is a mechanism to evade cell cycle arrest. The data highlight the critical role of p53 as a tumor suppressor in BL, and identifies MDM4 as a key functional target of 1q gain in a wide range of cancers, which is therapeutically targetable.

cancer biology↗

bioRxiv2016

Predicting brain-age from multimodal imaging data captures cognitive impairment

The disparity between the chronological age of an individual and their brain-age measured based on biological information has the potential to offer clinically-relevant biomarkers of neurological syndromes that emerge late in the lifespan. While prior brain-age prediction studies have relied exclusively on either structural or functional brain data, here we investigate how multimodal brainimaging data improves age prediction. Using cortical anatomy and whole-brain functional connectivity on a large adult lifespan sample (N = 2354, age 19-82), we found that multimodal data improves brain-based age prediction, resulting in a mean absolute prediction error of 4.29 years. Furthermore, we found that the discrepancy between predicted age and chronological age captures cognitive impairment. Importantly, the brain-age measure was robust to confounding effects: head motion did not drive brain-based age prediction and our models generalized reasonably to an independent dataset acquired at a different site (N = 475). Generalization performance was increased by training models on a larger and more heterogeneous dataset. The robustness of multimodal brain-age prediction to confounds, generalizability across sites, and sensitivity to clinically-relevant impairments, suggests promising future application to the early prediction of neurocognitive disorders.\n\nHighlightsO_LIBrain-based age prediction is improved with multimodal neuroimaging data.\nC_LIO_LIParticipants with cognitive impairment show increased brain aging.\nC_LIO_LIAge prediction models are robust to motion and generalize to independent datasets from other sites.\nC_LI

neuroscience↗