Biology subjects

Lange, K.

Publications and source records attributed to Lange, K..

12 recordsLinked to original sources

bioRxiv2026

Leveraging AI and structural proteomics for rational design of a KAT6A degrader

While targeted protein degraders such as PROTACs are a clinically proven therapeutic strategy, the discovery of novel degraders remains hampered by trial-and-error process. To address this challenge, we developed the AIMS platform, which combines structural proteomics with AI models for rational PROTAC design. AIMS is an end-to-end toolkit for PROTAC optimization, encompassing structure solving using proteomics and AI, prediction of ADME and degradation properties, and prospective ranking of compound design ideas. Altogether, this integrated platform successfully enabled the multi-parameter optimization of a potent and bioavailable in vivo validated KAT6A degrader, establishing a versatile framework for PROTAC development across various targets. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=71 SRC="FIGDIR/small/727609v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@13596d0org.highwire.dtl.DTLVardef@140500eorg.highwire.dtl.DTLVardef@147e585org.highwire.dtl.DTLVardef@12dbdfe_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

Genetic, intrinsic, and environmental determinants of innate immune cytokine responses in healthy four-year-old children

Abstract/SummaryInnate immune responses are crucial for host defence but vary markedly between individuals. Although determinants of this variation are well characterised in adults, data from healthy children remain scarce. We therefore profiled whole-blood cytokine responses to innate immune stimulation in 286 children aged approximately four years and examined genetic, host-intrinsic, and environmental correlates of response. Cytokine responses showed marked inter-individual heterogeneity and stimulus-specific patterns. The top 50 genetic variants explained a substantial proportion ([~]20-45%) of this variance across many stimulus conditions, including a biologically coherent association of the STING locus with cGAMP-induced cytokine production. In contrast, sex, age, adiposity, and perinatal variables showed limited or modest associations. Systemic inflammatory biomarkers of systemic inflammation (hsCRP, glycoprotein acetyls, granulocyte-to-lymphocyte ratio) were strongly positively associated with cytokine responses. Finally, seasonal population-level viral infection burden was positively associated with antiviral and inflammatory cytokine responses. Collectively, these findings advance our understanding of variation in early-life whole-blood cytokine responses, underscoring this developmental period as a critical window for understanding immune development trajectories relevant to long-term health.

immunology↗

bioRxiv2025

Genome-wide analysis of social behaviour in context: a meta-regression approach across social domains, reporters and developmental stages

Social behaviour is a heritable, context-dependent trait that changes across social settings and development, influencing wellbeing and mental health. We present the first genome-wide meta-regression study of social behaviour from infancy to early adulthood, leveraging 491,246 repeat measures of low prosocial behaviour and peer/social difficulties in European-ancestry cohorts (Neff=121,777, Nind=73,321). We modelled heterogeneity in genetic effects across social domains, informants, and ages (2-29 years), capturing social context through genomic influences. Six loci were identified, including variation within CADM2 (p=2.51x10-9). The SNP-based heritability was modest (2-7%), and the genetic architecture of social behaviour multidimensional. Polygenic scores demonstrated predictability and accuracy in independent European-ancestry cohorts and, partially, in African-ancestry cohorts (Nind=16,305). Genetic correlations with later-life and mental health outcomes showed context-dependent patterns. Modelling predicted onsets of associations with social behaviour revealed distinct profiles, as observed for autism, ADHD, depression and schizophrenia, highlighting novel opportunities to genetically proxy developmental trajectories.

genomics↗

bioRxiv2025

Mucus-associated microbiota consortia: Insights from the advanced TIM-2muc model

The mucus layer lining the epithelium of the colon contains a microbiome that is distinct from the luminal microbiome; this is referred to as the mucus-associated microbiome (MAM). Recently, research on the MAM has gained momentum due to its significant role in immune and metabolic health. However, the study of the MAM is limited by conventional experimental techniques, as sampling this microbiome often requires invasive procedures, making in vivo research challenging. Additionally, obtaining samples from the MAM can compromise the lumen, complicating simultaneous studies of both the MAM and the lumen. To address these limitations, we present the TIM-2muc, an advanced version of the colonic in vitro model TIM-2, which includes a mucus compartment comprising both colonic mucus beads - Gut3Beads and an electrospun sheet coated with Gut3Gel. To validate whether the integrated mucus compartment behaves like the in vivo MAM, we examined the bacterial composition, alpha and beta diversity, and the MAMs composition compared to the lumen compartment of both the TIM-2muc and the conventional TIM-2 model. Our findings suggest that the MAM in the TIM-2muc model closely resembles its in vivo counterpart, thereby enhancing the physiological relevance of the luminal microbiome. TIM-2muc, an advanced TIM-2 model, presents a novel, precise, standardized, and non-invasive method for studying the MAM and LM simultaneously.

microbiology↗

bioRxiv2023

Inactivation of p53 drives breast cancer brain metastasis by altering fatty acid metabolism

Brain metastasis (BM) is a dire prognosis across cancer types. It is largely unknown why some tumors metastasize to the brain whereas others do not. We analyzed genomic and transcriptional data from clinical samples of breast cancer BM (BCBM) and found that nearly all of them carried p53-inactivating genetic alterations through mutations, copy-number loss, or both. Importantly, p53 pathway activity was already perturbed in primary tumors giving rise to BCBM, often by loss of the entire 17p chromosome-arm. This association was recapitulated across other carcinomas. Experimentally, p53 knockout was sufficient to drastically increase BCBM formation and growth in vivo, providing a causal link between p53 inactivation and brain tropism. Mechanistically, p53-deficient BC cells exhibited altered lipid metabolism, particularly increased fatty acid (FA) synthesis and uptake, which are characteristic of brain-metastasizing cancer cells. FA metabolism was further enhanced by astrocytes in a p53-dependent manner, as astrocyte-conditioned medium increased FASN, SCD1, and CD36 expression and activity, and enhanced the survival, proliferation and migration of p53-deficient cancer cells. Consequently, these cells were more sensitive than p53-competent cells to FA synthesis inhibitors, in isogenic cell cultures, in BCBM-derived spheroids, and across dozens of BC cell lines. Lastly, a significant association was observed between p53 inactivation, astrocyte infiltration, and SCD1 expression in clinical human BCBM samples. In summary, our study identifies p53 inactivation as a driver of BCBM and potentially of BM in general; suggests a p53-dependent effect of astrocytes on BC cell behavior; and reveals FA metabolism as an underlying, therapeutically-targetable molecular mechanism.

cancer biology↗

bioRxiv2023

CARD-like domains mediate anti-phage defense in bacterial gasdermin systems

Caspase recruitment domains (CARDs) and pyrin domains are important facilitators of inflammasome activity and pyroptosis. Upon pathogen recognition by NLR proteins, CARDs recruit and activate caspases, which, in turn, activate gasdermin pore forming proteins to and induce pyroptotic cell death. Here we show that CARD-like domains are present in defense systems that protect bacteria against phage. The bacterial CARD is essential for protease-mediated activation of certain bacterial gasdermins, which promote cell death once phage infection is recognized. We further show that multiple anti-phage defense systems utilize CARD-like domains to activate a variety of cell death effectors. We find that these systems are triggered by a conserved immune evasion protein that phages use to overcome the bacterial defense system RexAB, demonstrating that phage proteins inhibiting one defense system can activate another. We also detect a phage protein with a predicted CARD-like structure that can inhibit the CARD-containing bacterial gasdermin system. Our results suggest that CARD domains represent an ancient component of innate immune systems conserved from bacteria to humans, and that CARD-dependent activation of gasdermins is conserved in organisms across the tree of life.

microbiology↗

bioRxiv2022

Genomic contributions to infant and toddler vocabulary scores: Implications for association with health-, cognition- and behaviour-related outcomes

BackgroundThe number of words children produce (expressive vocabulary) and understand (receptive vocabulary) changes rapidly during early development, partially due to genetic factors, although mechanisms are not well understood. Here, we performed a meta-genome-wide association study within the EAGLE consortium and investigated polygenic overlap with later-life traits, including Attention-Deficit/Hyperactivity Disorder (ADHD) and cognition. MethodsWe studied 37,913 parent-reported vocabulary size measures (English, Dutch, Danish) for 17,298 children of European descent. Meta-analyses were performed for early-phase expressive (infancy, 15-18 months), late-phase expressive (toddlerhood, 24-38 months) and late-phase receptive (toddlerhood, 24-38 months) vocabulary. Subsequently, we estimated Single-Nucleotide Polymorphism heritability (SNP-h2), genetic correlations (rg) and modelled underlying genetic factor structures with multivariate models. ResultsContributions of common genetic variation to early-life vocabulary were modest (SNP-h2: 0.08(SE=0.01) to 0.24(SE=0.03)) and multi-factorial. Genetic overlap between infant expressive and toddler receptive vocabulary was near zero (rg=0.07(SE=0.10)), although both measures were genetically related to toddler expressive vocabulary (rg=0.69(SE=0.14) and rg=0.67(SE=0.16), respectively). Consistently, polygenic association patterns with later-life traits differed: Genetic links with cognition emerged only in toddlerhood (e.g. toddler receptive vocabulary and intelligence: rg=0.36(SE=0.12)), despite comparable study power for infant measures. Furthermore, increased polygenic ADHD risk was associated with larger infant expressive vocabulary (rg=0.23(SE=0.08)), as confirmed by ADHD-symptom-based follow-up analyses in the Avon Longitudinal Study of Parents and Children (ALSPAC-rg=0.54(SE=0.26)). Genetic relationships with toddler receptive vocabulary were, however, opposite (ALSPAC-rg=-0.74(SE=0.23)), highlighting developmental changes in genetic architectures. ConclusionsMultiple genetic components contribute to early-life vocabulary development, shaping polygenic association patterns with later-life ADHD symptoms and cognition.

genomics↗

bioRxiv2022

Reconstitution of renal cyst formation in 3D culture reveals a role for AMOT and Yap1 in determining cyst size.

Despite substantial progress in identifying and understanding causative mutations in autosomal dominant polycystic kidney disease (ADPKD), little is known about subsequent cellular events leading to cyst formation. In prior studies we reported that Cadherin 8, a type II Cadherin, expression is sufficient to induce cyst emergence from HK-2 cells grown as tubule arrays in collagen matrix (1). However, emergent cysts did not exhibit the luminal enlargement observed in ADPKD. In this communication, we reconstitute cyst emergence with consequent cyst lumen expansion in 3D culture by stable co-expression of Cadherin 8 in combination with a constitutively active mutant of YAP1, the key effector of the HIPPO pathway. Specifically, immortalized cells derived from ADPKD cyst epithelia formed cysts with substantially larger lumen sizes when transduced with YAP1-5SA. Conversely, expression of the YAP1 inhibitor, AMOTL1, in these cells resulted in their forming cysts with smaller lumens than control cells. Our data show that cyst formation results from a sequential two-step process consisting of cyst initiation and subsequent cyst expansion. Taken together, cyst initiation induced by Cadherin 8 expression is proposed to result from decreased cell-cell adhesion while cyst expansion is driven by increased Yap1 activity.

cell biology↗

bioRxiv2021

Differential Methods for Assessing Sensitivity in Biological Models

Differential sensitivity analysis is indispensable in fitting parameters, understanding uncertainty, and forecasting the results of both thought and lab experiments. Although there are many methods currently available for performing differential sensitivity analysis of biological models, it can be difficult to determine which method is best suited for a particular model. In this paper, we explain a variety of differential sensitivity methods and assess their value in some typical biological models. First, we explain the mathematical basis for three numerical methods: adjoint sensitivity analysis, complex-perturbation sensitivity analysis, and forward-mode sensitivity analysis. We then carry out four instructive case studies. (i) The CARRGO model for tumor-immune interaction highlights the additional information that differential sensitivity analysis provides beyond traditional naive sensitivity methods, (ii) the deterministic SIR model demonstrates the value of using second-order sensitivity in refining model predictions, (iii) the stochastic SIR model shows how differential sensitivity can be attacked in stochastic modeling, and (iv) a discrete birth-death-migration model illustrates how the complex-perturbation method of differential sensitivity can be generalized to a broader range of biological models. Finally, we compare the speed, accuracy, and ease of use of these methods. We find that forward-mode automatic differentiation has the quickest computation time, while the complex-perturbation method is the simplest to implement and the most generalizable. Author SummaryOver the past few decades, mathematical modeling has become an indispensable tool in the biologists toolbox. From deterministic to stochastic to statistical models, computational modeling is ubiquitous in almost every field of biology. Because model parameter estimates are often noisy or depend on poorly understood interactions, it is crucial to examine how both quantitative and qualitative predictions change as parameter estimates change, especially as the number of parameters increase. Sensitivity analysis is the process of understanding how a models behavior depends on parameter values. Sensitivity analysis simultaneously quantifies prediction certainty and clarifies the underlying biological mechanisms that drive computational models. While sensitivity analysis is universally recognized to be an important step in modeling, it is often unclear how to best leverage the available differential sensitivity methods. In this manuscript we explain and compare various differential sensitivity methods in the hope that best practices will be widely adopted. In particular, we stress the relative advantages of existing software and their limitations. We also present a new numerical technique for computing differential sensitivity.

systems biology↗

bioRxiv2020

A Fast Data-Driven Method for Genotyp Imputation, Phasing, and Local Ancestry Inference: MendelImpute.jl

1Current methods for genotype imputation and phasing exploit the sheer volume of data in haplotype reference panels and rely on hidden Markov models. Existing programs all have essentially the same imputation accuracy, are computationally intensive, and generally require pre-phasing the typed markers. We propose a novel data-mining method for genotype imputation and phasing that substitutes highly efficient linear algebra routines for hidden Markov model calculations. This strategy, embodied in our Julia program MendelImpute.jl, avoids explicit assumptions about recombination and population structure while delivering similar prediction accuracy, better memory usage, and an order of magnitude or better run-times compared to the fastest competing method. MendelImpute operates on both dosage data and unphased genotype data and simultaneously imputes missing genotypes and phase at both the typed and untyped SNPs. Finally, MendelImpute naturally extends to global and local ancestry estimation and lends itself to new strategies for data compression and hence faster data transport and sharing.

genetics↗

bioRxiv2019

Pooled analysis of radiation hybrids identifies loci for growth and drug action in mammalian cells

Genetic screens in mammalian cells commonly focus on loss-of-function approaches. To evaluate the phenotypic consequences of extra gene copies, we used bulk segregant analysis (BSA) of radiation hybrid (RH) cells. We constructed six pools of RH cells, each consisting of ~2500 independent clones, and placed the pools under selection in media with or without paclitaxel. Low pass sequencing identified 859 growth loci, 38 paclitaxel loci, 62 interaction loci and 3 loci for mitochondrial abundance at genome-wide significance. Resolution was measured as ~30 kb, close to single-gene. Divergent properties were displayed by the RH-BSA growth genes compared to those from loss-of-function screens, refuting the balance hypothesis. In addition, enhanced retention of human centromeres in the RH pools suggests a new approach to functional dissection of these chromosomal elements. Pooled analysis of RH cells showed high power and resolution and should be a useful addition to the mammalian genetic toolkit.

genetics↗

bioRxiv2019

Multivariate GWAS: Generalized Linear Models, Prior Weights, and Double Sparsity

1BackgroundConsecutive testing of single nucleotide polymorphisms (SNPs) is usually employed to identify genetic variants associated with complex traits. Ideally one should model all covariates in unison, but most existing analysis methods for genome-wide association studies (GWAS) perform only univariate regression. ResultsWe extend and efficiently implement iterative hard thresholding (IHT) for multiple regression, treating all SNPs simultaneously. Our extensions accommodate generalized linear models (GLMs), prior information on genetic variants, and grouping of variants. In our simulations, IHT recovers up to 30% more true predictors than SNP-by-SNP association testing, and exhibits a 2 to 3 orders of magnitude decrease in false positive rates compared to lasso regression. We also test IHT on the UK Biobank hypertension phenotypes and the Northern Finland Birth Cohort of 1966 cardiovascular phenotypes. We find that IHT scales to the large datasets of contemporary human genetics and recovers the plausible genetic variants identified by previous studies. ConclusionsOur real data analysis and simulation studies suggest that IHT can (a) recover highly correlated predictors, (b) avoid over-fitting, (c) deliver better true positive and false positive rates than either marginal testing or lasso regression, (d) recover unbiased regression coefficients, (e) exploit prior information and group-sparsity and (f) be used with biobank sized data sets. Although these advances are studied for GWAS inference, our extensions are pertinent to other regression problems with large numbers of predictors.

genomics↗