Biology subjects

Wahl, S.

Publications and source records attributed to Wahl, S..

9 recordsLinked to original sources

bioRxiv2024

Neural contrast sensitivity is not affected by myopic blur

PurposeThe prevalence of myopia is increasing worldwide, accompanied by an increase of potentially under-corrected myopes. Because the neural pathways processing the retinal image are prone to adaptation in relation to the retinal image quality, we wondered to what extent neural contrast sensitivity (NCS) is altered in the presence of myopic blur. Additionally, the impact of retinal abnormalities like foveal hypoplasia with albinism on NCS was tested. MethodsNCS was psychophysically determined for 11 emmetropic, 23 myopic well-corrected and 15 myopic under-corrected otherwise healthy young (27 {+/-} 6 years) participants and 1 albinism patient. Aberration-free stimulation, independent of the eyes refractive state, was achieved by using a unique spatial light modulator-based interferometric system to bypass the eyes optics. ResultsNo significant differences in NCS were observed between the three groups (Median area-under-curve: 61.9, 62.1, and 62.9 for emmetropes, well-corrected, and under-corrected myopes, respectively; all p > 0.1) but were significantly equivalent between emmetropes and myopes (all p < 0.001). However, the NCS function of the albinism patient differed significantly from the here defined "normal" NCS function. ConclusionsNCS is unaffected by myopic blur and remains stable even for under-correction of up to 1.5 D. This means, that long-term under-corrected myopes still can achieve normal visual acuity as soon as their refractive errors are sufficiently corrected. Furthermore, NCS testing can relate visual deficits to an underlying neurological disorder.

neuroscience↗

bioRxiv2024

Assessing visual performance during intense luminance changes in virtual reality

During indoor-outdoor transitions humans encounter luminance changes beyond the functional range of the photoreceptors, leaving the individual at risk of overlooking harmful low-contrast objects until adaptation processes re-enable optimal vision. To study human visual performance during intense luminance changes, we propose a virtual reality based testbed. After linearization of the headsets luminance output, detection times were recorded for ten participants. The small (FWHM = 0.6 degree) low-contrast stimuli appeared randomly in one of four corners ({+/-}10 degree) after luminance changes of three magnitudes within 1 or 3 seconds. Significantly decreased detection times were observed for the conditions with simulated self-tinting lenses compared to lenses with fixed transmission rates after luminance decreases. In cases of luminance increases all detection times were similar. In conclusion, the proposed virtual reality testbed allows for studying vision during or after steep luminance changes and helps to design technical aids like self-tinting lenses. HighlightsThe HTC Vive headset provides a practicable luminance range of 3 magnitudes, allowing the simulation of indoor-outdoor transitions. Visual performance after steep luminance decreases was significantly better with simulated self-tinting spectacles reducing the encountered luminance step. Different transmission rates of the simulated lenses did not affect the detection times for small low-contrast stimuli after luminance increases.

neuroscience↗

bioRxiv2022

Fine-scale measurement of the blind spot borders

The blind spot is both a necessity and a nuisance for seeing. It is the portion of the visual field projecting to where the optic nerve crosses the retina, a region devoid of photoreceptors and hence visual input. The precise way in which vision transitions into blindness at the blind spot border is to date unknown. A chief challenge to map this transition is the incessant movement of the eye, which unavoidably smears measurements across space. In this study, we used high-resolution eye-tracking and state-of-the-art retinal stabilization to finely map the blind spot borders. Participants reported the onset of tiny high-contrast probes that were briefly flashed at precise positions around the blind spot. This method has sufficient resolution to enable mapping of blood vessels from psychophysical measurements. Our data show that, even after accounting for eye movements, the transition zones at the edges of the blind spot are considerable. On the horizontal meridian, the regions with detection rates between 80% and 20% span approximately 25% of the overall width of the blind spot. These borders also vary considerably in size across different axes. These data show that the transition from full visibility to blindness at the blind spot border is not abrupt but occurs over a broad area.

neuroscience↗

bioRxiv2020

Eye-tracking for low vision with virtual reality (VR): testing status quo usability of the HTC Vive Pro Eye

BackgroundAdding an eye tracker inside a head-mounted display (HMD) can offer a variety of novel functions in virtual reality (VR). Promising results point towards its usability as a flexible and interactive tool for low vision assessments and research of low vision functional impairment. Visual field (VF) perimetry performed using VR methodologies evidenced a correlation between the reliability of visual field testing in VR and the Humphrey test. The simulation of visual loss in VR is a powerful method used to investigate the impact and the adaptation to visual diseases. The present study presents a preliminary assessment of the HTC Vive Pro Eye for its potential use for these applications. MethodsWe investigated data quality over a wide visual field and tested the effect of head motion. An objective direct end-to-end temporal precision test simulated two different scenarios: the appearance of a pupil inside the eye tracker and a shift in pupil position, known as artificial saccade generator. The technique is low-cost thanks to a Raspberry Pi system and automatic. ResultsThe target position on the screen and the head movement limit the HTC Vive Pro Eyes usability. All the simulated scenarios showed a systems latency of 58.1 milliseconds (ms). ConclusionThese results point towards limitations and improvements of the HTC Vive Pro Eyes status quo for visual loss simulation scenarios and visual perimetry testing.

neuroscience↗

bioRxiv2020

Network reconstruction for trans acting genetic loci using multi-omics data and prior information

BackgroundMolecular multi-omics data provide an in-depth view on biological systems, and their integration is crucial to gain insights in complex regulatory processes. These data can be used to explain disease related genetic variants by linking them to intermediate molecular traits (quantitative trait loci, QTL). Molecular networks regulating cellular processes leave footprints in QTL results as so-called trans -QTL hotspots. Reconstructing these networks is a complex endeavor and use of biological prior information has been proposed to alleviate network inference. However, previous efforts were limited in the types of priors used or have only been applied to model systems. In this study, we reconstruct the regulatory networks underlying trans -QTL hotspots using human cohort data and data-driven prior information. ResultsWe devised a strategy to integrate QTL with human population scale multi-omics data and comprehensively curated prior information from large-scale biological databases. State-of-the art network inference methods applied to these data and priors were used to recover the regulatory networks underlying trans -QTL hotspots. We benchmarked inference methods and showed, that Bayesian strategies using biologically-informed priors outperform methods without prior data in simulated data and show better replication across datasets. Application of our approach to human cohort data highlighted two novel regulatory networks related to schizophrenia and lean body mass for which we generated novel functional hypotheses. ConclusionWe demonstrate, that existing biological knowledge can be leveraged for the integrative analysis of networks underlying trans associations to deduce novel hypotheses on cell regulatory mechanisms.

bioinformatics↗

bioRxiv2019

A genome-wide analysis of DNA methylation identifies a novel association signal for Lp(a) concentrations in the LPA promoter

Lipoprotein(a) [Lp(a)] is a major cardiovascular risk factor, which is largely genetically determined by one major gene locus, the LPA gene. Many aspects of the transcriptional regulation of LPA are poorly understood and the role of epigenetics has not been addressed yet. Therefore, we conducted an epigenome-wide analysis of DNA methylation on Lp(a) levels in two population-based studies (total n=2208). We identified a CpG site in the LPA promoter which was significantly associated with Lp(a) concentrations. Surprisingly, the identified CpG site was found to overlap the SNP rs76735376. We genotyped this SNP de-novo in three studies (total n=7512). The minor allele of rs76735376 (1.1% minor allele frequency) was associated with increased Lp(a) values (p=1.01e-59) and explained 3.5% of the variation of Lp(a). Statistical mediation analysis showed that the effect on Lp(a) is rather originating from the base change itself and is not mediated by DNA methylation levels. This finding is supported by eQTL data from 153 liver tissue samples from the GTEx project, which shows a significant association of the rs76735376 minor allele with increased LPA expression. In summary, our data supports a functional role of rs76735376 in the regulation of LPA expression.

genetics↗

bioRxiv2018

Epigenetic derepression of FKBP5 by aging and stress contributes to NF-kB-driven inflammation and cardiovascular risk

Aging and psychosocial stress are associated with increased inflammation and disease risk, but the underlying molecular mechanisms are poorly understood. Because both aging and stress are also associated with lasting epigenetic changes, a plausible hypothesis is that stress exposure along the lifespan could confer disease risk by epigenetically deregulating molecules involved in inflammatory processes. Here, by combining large-scale analyses in human cohorts with mechanistic in vitro investigations, we found that FKBP5, a protein implicated in stress physiology, contributes to these relations. Across independent human cohorts (total n=3,131), aging and stress-related phenotypes were synergistically associated with epigenetic derepression of FKBP5. These age/stress-related epigenetic effects were recapitulated in an in vitro model of replicative senescence, whereby we exposed replicating human fibroblasts to stress (glucocorticoid) hormones. Unbiased genome-wide analyses in human blood linked higher FKBP5 mRNA with a proinflammatory profile and altered NF-{kappa}B-related gene networks. Accordingly, experiments in immune cells showed that FKBP5 overexpression promotes inflammation by strengthening the interactions of NF-{kappa}B regulatory kinases, whereas opposing FKBP5 either by genetic deletion (CRISPR/Cas9-mediated) or selective pharmacological inhibition prevented the effects on NF-{kappa}B. Further, the age/stress-related epigenetic signature enhanced FKBP5 responsivity to NF-{kappa}B through a positive feedback loop and was present in individuals with a history of acute myocardial infarction, a disease state linked to peripheral inflammation. These findings suggest that FKBP5-NF-{kappa}B signaling mediates inflammation associated with aging and stress, potentially contributing to cardiovascular risk, and may thus point to novel biomarker and treatment possibilities.\n\nSignificanceDiseases of the aging are the leading cause of morbidity and mortality. Elucidating the molecular mechanisms through which modifiable factors, such as psychosocial stress, confer risk for aging-related disease can have profound implications. Here, by combining studies in humans with experiments in cells, we find that aging and stress synergize to epigenetically derepress FKBP5, a protein implicated in stress physiology. Higher FKBP5 promotes inflammation by activating the master immune regulator NF-{kappa}B, whereas opposing FKBP5 - either genetically or pharmacologically- prevents the effects on NF-{kappa}B. Further, the age/stress-related epigenetic signature of FKBP5 is associated with history of myocardial infarction, a disease state linked to inflammation. These findings provide molecular insights into stress-related disease and may point to novel biomarker and treatment possibilities.

genomics↗

bioRxiv2018

Characterization of missing values in untargeted MS-based metabolomics data and evaluation of missing data handling strategies

BACKGROUNDUntargeted mass spectrometry (MS)-based metabolomics data often contain missing values that reduce statistical power and can introduce bias in epidemiological studies. However, a systematic assessment of the various sources of missing values and strategies to handle these data has received little attention. Missing data can occur systematically, e.g. from run day-dependent effects due to limits of detection (LOD); or it can be random as, for instance, a consequence of sample preparation.\n\nMETHODSWe investigated patterns of missing data in an MS-based metabolomics experiment of serum samples from the German KORA F4 cohort (n = 1750). We then evaluated 31 imputation methods in a simulation framework and biologically validated the results by applying all imputation approaches to real metabolomics data. We examined the ability of each method to reconstruct biochemical pathways from data-driven correlation networks, and the ability of the method to increase statistical power while preserving the strength of established genetically metabolic quantitative trait loci.\n\nRESULTSRun day-dependent LOD-based missing data accounts for most missing values in the metabolomics dataset. Although multiple imputation by chained equations (MICE) performed well in many scenarios, it is computationally and statistically challenging. K-nearest neighbors (KNN) imputation on observations with variable pre-selection showed robust performance across all evaluation schemes and is computationally more tractable.\n\nCONCLUSIONMissing data in untargeted MS-based metabolomics data occur for various reasons. Based on our results, we recommend that KNN-based imputation is performed on observations with variable pre-selection since it showed robust results in all evaluation schemes.\n\nKey messagesO_LIUntargeted MS-based metabolomics data show missing values due to both batch-specific LOD-based and non-LOD-based effects.\nC_LIO_LIStatistical evaluation of multiple imputation methods was conducted on both simulated and real datasets.\nC_LIO_LIBiological evaluation on real data assessed the ability of imputation methods to preserve statistical inference of biochemical pathways and correctly estimate effects of genetic variants on metabolite levels.\nC_LIO_LIKNN-based imputation on observations with variable pre-selection and K = 10 showed robust performance for all data scenarios across all evaluation schemes.\nC_LI

systems biology↗

bioRxiv2016

Leveraging uncertainty information from deep neural networks for disease detection

Deep learning (DL) has revolutionized the field of computer vision and image processing. In medical imaging, algorithmic solutions based on DL have been shown to achieve high performance on tasks that previously required medical experts. However, DL-based solutions for disease detection have been proposed without methods to quantify and control their uncertainty in a decision. In contrast, a physician knows whether she is uncertain about a case and will consult more experienced colleagues if needed. Here we evaluate drop-out based Bayesian uncertainty measures for DL in diagnosing diabetic retinopathy (DR) from fundus images and show that it captures uncertainty better than straightforward alternatives. Furthermore, we show that uncertainty informed decision referral can improve diagnostic performance. Experiments across different networks, tasks and datasets show robust generalization. Depending on network capacity and task/dataset difficulty, we surpass 85% sensitivity and 80% specificity as recommended by the NHS when referring 0%-20% of the most uncertain decisions for further inspection. We analyse causes of uncertainty by relating intuitions from 2D visualizations to the high-dimensional image space. While uncertainty is sensitive to clinically relevant cases, sensitivity to unfamiliar data samples is task dependent, but can be rendered more robust.

bioinformatics↗