Biology subjects

Moll, M.

Publications and source records attributed to Moll, M..

6 recordsLinked to original sources

bioRxiv2026

Feature-based valuation and its impairment in people with compulsive and addictive symptoms

Effective decision-making requires evaluating options based on relevant features while reducing attention to those that are not. However, how attention prioritizes one source of information over another during value-based decisions remains unknown. Across 7 experiments, we show that irrelevant features both constructively and destructively interfered with how values are assigned to choice options. When relevant and irrelevant features agreed, choice accuracy and speed were facilitated; when they conflicted, accuracy decreased and choices slowed in proportion to the value of the irrelevant feature. We modeled this interference as a weighted sum of relevant and irrelevant feature values. This model explained individual differences in choice behavior and, critically, tracked psychiatric symptom severity related to substance abuse and obsessive-compulsive disorder. This suggests that these symptoms may, in part, reflect an impaired ability to weigh relevant against irrelevant information when assigning value to choice options - a process we term feature-based valuation.

neuroscience↗

bioRxiv2025

DNA-methylation markers associated with lung function at birth and childhood reveal early life programming of inflammatory pathways

RationaleLung function deficits may be caused by early life epigenetic programming. Early childhood studies are necessary to understand life-course trends in lung diseases. ObjectivesWe aimed to examine whether DNA-methylation at birth and childhood is associated with lung function growth. MethodsWe measured DNA-methylation in leukocytes from participants in two childhood asthma cohorts (CAMP [n=703, mean-age 12.9 years] and GACRS [n=788, mean-age 9.3 years]) and cord blood from participants in the VDAART study (n=572) to identify CpGs and pathways associated with lung function. ResultsWe identified 1,049 consistent differentially methylated CpGs (608 relatively hypermethylated) across all three studies (FDR-P<0.05). Relatively hypomethylated CpGs were enriched for gluconeogenesis, cell adhesion and VEGF signaling. Relatively hypermethylated CpGs were enriched for Hippo, B-cell and growth hormone receptor signaling. Functional enrichment suggested potential regulatory roles for active enhancers and histone modifications. Additionally, enrichment in PI3K/AKT and Notch pathways in males and enrichment in hormonal pathways in females was identified. Gaussian graphical models identified sex-differential DNA-methylation nodes and hub scores at birth and childhood. Integrating with previously identified polygenic risk scores for asthma and drug-target enrichment identified seven robust genes including MPO, CHCHD3, CACNA1S, PI4KA, EP400, CREBBP and KCNA10 with known associations as biomarkers for asthma severity and drug targets for airway inflammation. ConclusionsEpigenetic variability from birth through puberty provides mechanistic insights into fetal programming of developmental and immune pathways associated with lung function. These early life observations reveal potential targets for mitigating risk for lung function decline and asthma progression in later life. Key messagesO_LIWe identified consistent DNA methylation signatures between birth and childhood in critical metabolic, lung development and immune pathways that were associated with lung function and may be influenced by sex and genetics. C_LIO_LIOur integrative findings provide a deeper understanding for accelerated lung function decline across the life-course and could pave the way for translational interventions for lung diseases based on epigenetic plasticity. C_LI

genomics↗

bioRxiv2025

miRNA-mRNA network analysis identifies PAX5 as a potential regulator of adaptive immune response in COPD

Micro-ribonucleic acids (miRNAs) are key post-transcriptional regulators of the immune system and may play a role in Chronic Obstructive Pulmonary Disease (COPD). In this paper, we constructed subject-specific miRNA-mRNA regulatory networks using bulk and deconvoluted whole blood RNA-sequencing, whole blood miRNA-sequencing, and B-cell receptor-sequencing data from up to 570 miRNAs, 11,859 mRNAs, and 3,190 participants in the COPDGene study. Analysis of whole blood networks revealed two subnetworks of miRNA-mRNA interactions significantly (FDR<0.05) associated with changes in FEV1/FVC. We found that miRNAs (and mRNAs) in the network-identified groups had distinct expression patterns, with miRNAs (and mRNAs) in one group having overall higher expression in COPD (decreasing FEV1/FVC) and miRNAs (and mRNAs) in the other group having overall higher expression in controls (increasing FEV1/FVC). In addition, miRNAs (and mRNAs) within the same group were positively correlated, while those in different groups were negatively correlated, indicating distinct functional roles for these miRNAs (and mRNAs) as a function of increased COPD severity. Network analysis also identified PAX5, a transcription factor master regulator of B-cell development, as the main mRNA network hub. Using ChIP-seq data in lymphoblastoid cells, we identified a PAX5 binding site overlapping with a COPD genome-wide association signal in the promoter region of ADAM19. We also found a loss of co-expression between PAX5 and ADAM19 in COPD subjects. Furthermore, in B-cell deconvoluted data, PAX5 was differentially co-expressed with genes associated with B-cell activation and differentiation, revealing a possible mechanism for the regulation of the immune response in COPD. Finally, in B-cell receptor sequencing data, PAX5 and the identified mRNA subnetworks were negatively associated (FDR<0.05) with immunoglobulin class switching, and positively associated with IgM and IgD counts. In conclusion, PAX5 is a known regulator of B-cell identity. B cells are recognized as key players in chronic inflammation and immune dysregulation in COPD. Our work suggests that PAX5 plays a mediating role both in ADAM19 regulation and in miRNA regulation of early B cells in COPD.

systems biology↗

bioRxiv2024

A Cortical Microcircuit for Region-Specific Credit Assignment in Reinforcement Learning

The distributed architecture of the cortex poses a fundamental challenge for reinforcement learning: how to assign credit specifically to regions that contribute to successful behavior? Cortical neurons can be driven by both global reinforcers, like rewards, and local sensory features, making it difficult to disentangle these influences. To address this, we investigated cortical reinforcement learning by manipulating the reward-predictive sensory modality during learning tasks, while monitoring key regulators of cortical activity--local inhibitory neurons, and cholinergic inputs. We found that VIP interneurons are broadly recruited by reward-predictive cues via a modality-independent cholinergic signal. However, when task demands aligned with local computation, SST interneurons suppressed VIP recruitment through an inhibitory feedback loop. A computational model demonstrates that this cholinergic-VIP-SST interneuron circuit motif enables targeted reinforcement learning and region-specific credit assignment in the cortex. These results offer a neurobiologically-grounded framework for how the cortex uses global reinforcement signals to direct plasticity to task-relevant regions, enabling those regions to adapt and fine-tune their responses.

neuroscience↗

bioRxiv2024

Naturally acquired IgG responses to Plasmodium falciparum do not target the conserved termini of the malaria vaccine candidate merozoite surface protein 2

Malaria remains a significant burden, and a fully protective vaccine against Plasmodium falciparum is critical for reducing morbidity and mortality. Antibody responses against the blood-stage antigen merozoite surface protein 2 (MSP2) are associated with protection from P. falciparum malaria, but its extensive polymorphism is a barrier to its development as a vaccine candidate. New tools, such as long-read sequencing and accurate protein structure modelling allow us to more easily study the genetic diversity and immune responses towards antigens from clinical isolates. This study sought to better understand naturally acquired MSP2-specific antibody responses. IgG responses against recombinantly expressed full- length, central polymorphic regions, and peptides derived from the conserved termini of MSP2 variants sequenced from patient isolates, were tested in plasma from travelers with recent, acute malaria and from individuals living in an endemic area of Tanzania. IgG responses towards full MSP2 and truncated MSP2 antigens were variant specific. IgG antibodies in the plasma of first-time infected or previously exposed travelers did not recognize the conserved termini of expressed MSP2 variants by ELISA, but they bound 13- amino acid long linear epitopes from the termini in a custom-made peptide array. Alphafold3 modelling suggests extensive structural heterogeneity in the conserved termini upon antigen oligomerization. IgG from individuals living in an endemic region, many who were asymptomatically infected, did not recognize the conserved termini by ELISA. Our results suggest that responses to the variable regions are important for the development of naturally acquired immunity towards MSP2.

immunology↗

bioRxiv2021

A robust and adaptive framework for interaction testing in quantitative traits between multiple genetic loci and exposure variables

The identification and understanding of gene-environment interactions can provide insights into the pathways and mechanisms underlying complex diseases. However, testing for gene-environment interaction remains a challenge since statistical power is often limited, the specification of environmental effects is nontrivial, and such misspecifications can lead to false positive findings. To address the lack of statistical power, recent methods aim to identify interactions on an aggregated level using, for example, polygenic risk scores. While this strategy increases power to detect interactions, identifying contributing key genes and pathways is difficult based on these global results. Here, we propose RITSS (Robust Interaction Testing using Sample Splitting), a gene-environment interaction testing framework for quantitative traits that is based on sample splitting and robust test statistics. RITSS can incorporate multiple genetic variants and/or multiple environmental factors. Using sample splitting, a screening step enables the selection and combination of potential interactions into scores with improved interpretability, based on the users unrestricted choices for statistical/machine learning approaches. In the testing step, the application of robust test statistics minimizes the susceptibility of the results to main effect misspecifications. Using extensive simulation studies, we demonstrate that RITSS controls the type 1 error rate in a wide range of scenarios. In an application to lung function phenotypes and human height in the UK Biobank, RITSS identified genome-wide significant interactions with subcomponents of genetic risk scores. While the contributing single variant interactions are moderate, our analysis results indicate interesting interaction patterns that result in strong aggregated signals that provide further insights into gene-environment interaction mechanisms.

bioinformatics↗