Biology subjects

Stoffers, D.

Publications and source records attributed to Stoffers, D..

4 recordsLinked to original sources

bioRxiv2026

The ortholog of the Human T2D Risk Gene STEAP2 is Required for Glucose Stimulated Insulin Secretion in Mice

Type 2 diabetes is a complex metabolic disease with a strong genetic component, yet this genetic risk is driven by common variants in up to 600 loci with small effect sizes. Variants in the STEAP2 locus, encoding Six-transmembrane epithelial antigen of the prostate-2, are highly associated with altered glycemic traits and type 2 diabetes risk. To elucidate its function in pancreatic beta-cells, we utilized Crisp-Cas9 assisted homologous recombination to derive a conditional null allele for Steap2 (Steap2fl/fl) in mice and crossed this to the rat insulin promoter (Rip)-Cre transgene. Ablation of Steap2 induced glucose intolerance, blunted glucose-stimulated Ca2+ mobilization and stunted first phase glucose-simulated insulin secretion. In contrast, the incretin effect and second phase insulin secretion were not affected. Islet respirometry and transmission electron microscopy (TEM) identified disrupted cristate morphology and impaired glucose-stimulated oxygen consumption as causally responsible for the observed, impaired triggering pathway of insulin secretion. These findings suggest that at least part of the genetic risk for T2D conferred by Steap2 variants is likely due to its function in maintaining optimal mitochondrial respiration in pancreatic beta-cells.

genetics↗

bioRxiv2026

Molecular and phenotypic footprints of climate in native Arabidopsis thaliana

Climate change poses a major threat to humanity by driving biodiversity loss and reducing crop yields1,2. To understand the molecular and developmental impacts of rising temperatures, plant science has relied heavily on the model organism Arabidopsis thaliana. Despite decades of research, its development under fully natural conditions remains poorly understood, and only [~]30% of genes have experimental functional annotations, largely because many functions are subtle or manifest only in specific laboratory or ecological contexts3. Here, we address this gap with a landscape transcriptomic approach that integrates intensive phenotyping and transcriptomic profiling of naturally occurring plants in their native habitats4. Across two contrasting field sites and five growing seasons (2021-2025), we phenotyped more than 3,000 A. thaliana plants and generated >1,600 matching transcriptomes. The resulting >30,000 quantitative trait measurements provide a unique opportunity to link climate fluctuations with plant traits and gene expression. Seasons characterized by extreme temperature anomalies directly influenced plant traits, and climatic variables together explained up to 17% of phenotypic variation. In situ transcriptomes carried clear temperature and local environmental signatures, closely matching temperature-response programs known from the laboratory. Leveraging paired per-plant transcriptomes and phenotypes, we applied machine learning to predict regulators of climate-relevant and other plant traits under natural conditions. The models recovered canonical thermomorphogenesis regulators, including PHYTOCHROME INTERACTING FACTOR 4 (PIF4)5,6, providing ecological evidence that temperature signaling pathways defined in controlled environments operate in the wild, and expanded this regulatory landscape by identifying hormonal receptors, signaling components, and previously uncharacterized genes, some of which we functionally validated. Together, this work demonstrates that landscape transcriptomics, by integrating natural field transcriptomes with phenotypes, and thus, capturing environmental and regulatory states, enables the predictive identification of genetic regulators of temperature responses and broader plant traits. This makes landscape transcriptomics a scalable framework for climate-aware functional genomics in plants.

plant biology↗

bioRxiv2023

Insomnia subtypes have differentiating deviations in brain structural connectivity

ObjectiveInsomnia disorder is the most common sleep disorder. A better understanding of insomnia-related deviations in the brain could inspire better treatment. Insufficiently recognized heterogeneity within the insomnia population could obscure involved brain circuits. The present study investigated whether structural brain connectivity deviations differ between recently discovered and validated insomnia subtypes. MethodsStructural and diffusion weighted 3-Tesla MRI data of four independent studies were harmonized. The sample consisted of 73 controls without sleep complaints and 204 participants with insomnia grouped into five subtypes based on their fingerprint of personality and mood traits assessed with the Insomnia Type Questionnaire. Linear regression correcting for age, sex, and brain volume evaluated group differences in structural connectivity strength, indicated by fractional anisotropy and mean diffusivity, and evaluated within two different atlases. ResultsInsomnia subtypes showed differentiating profiles of deviating structural connectivity which moreover concentrated in different functional networks. Permutation testing against randomly drawn heterogeneous subsamples indicated significant specificity of deviation profiles in four of the five subtypes: highly distressed (p=0.019), moderately distressed reward insensitive (p=0.014), slightly distressed low reactive (p=0.006) and slightly distressed high reactive (p=0.006). ConclusionsOur results provide a first indication that different insomnia subtypes exhibit distinct profiles of deviations in structural brain connectivity. Subtyping of insomnia could be essential for a better understanding of brain mechanisms that contribute to insomnia vulnerability.

neuroscience↗

bioRxiv2021

Alpha cell dysfunction in early type 1 diabetes

Multiple islet autoantibodies (AAb) predict type 1 diabetes (T1D) and hyperglycemia within 10 years. By contrast, T1D develops in just [~]15% of single AAb+ (generally against glutamic acid decarboxylase, GADA+) individuals; hence the single GADA+ state may represent an early stage of T1D amenable to interventions. Here, we functionally, histologically, and molecularly phenotype human islets from non-diabetic, GADA+ and T1D donors. Similar to the few remaining beta cells in T1D islets, GADA+ donor islets demonstrated a preserved insulin secretory response. By contrast, alpha cell glucagon secretion was dysregulated in both T1D and GADA+ islets with impaired glucose suppression of glucagon secretion. Single cell RNA sequencing (scRNASeq) of GADA+ alpha cells revealed distinct abnormalities in glycolysis and oxidative phosphorylation pathways and a marked downregulation of PKIB, providing a molecular basis for the loss of glucose suppression and the increased effect of IBMX observed in GADA+ donor islets. The striking observation of a distinct early defect in alpha cell function that precedes beta cell loss in T1D suggests that not only overt disease, but also the progression to T1D itself, is bihormonal in nature.

physiology↗