Biology subjects

Arndt, V.

Publications and source records attributed to Arndt, V..

6 recordsLinked to original sources

bioRxiv2026

In vitro programming and pseudounipolarization of human iPSC-derived sensory neurons

Ectopic expression of NGN1, BRN3A and ISLET1 (NBI) from a safe harbor locus in induced pluripotent stem cells (iPSCs) yielded robust differentiation into functional sensory neurons (iNBI-SNs) within seven days. Single nucleus transcriptomics identified peripheral sensory neuron profiles of nociceptors and mechanoreceptors. Electrophysiological studies showed that more than 98 % of iNBI-SNs display TTX-resistant sodium currents and that they establish functional connections to excitatory CNS neurons. iNBI-SNs derived from patients with inherited erythromelalgia, a pain disorder associated with gain-of-function mutations in the Nav1.7 sodium channel showed pathologically increased firing rates which could be partially rescued with a Nav1.7 inhibitor. Notably, iNBI-SNs acquire a characteristic pseudounipolar morphology upon co-culture with embryonic rodent DRG cells. Taken together, NBI-based forward programming of iPSCs represents a robust approach for the generation of human sensory neurons suitable for developmental, disease- and therapy-related studies.

neuroscience↗

bioRxiv2026

T-cell distribution in the dorsal root ganglion across species, sex, and age

T-cells infiltrate somatosensory ganglia in response to nerve damage, autoimmune disease, and infection, contributing to sensory abnormalities and pain. In naive states, T-cells are rare in the rodent dorsal root ganglion (DRG) but have been reported in human and non-human primates without known relevant exposures. It remains unclear whether there are inherent evolutionary or species differences in DRG T-cell residence. Using a comparative biology approach, we investigated the frequency and distribution of T-cells in the mammalian DRG across humans, non-human primates, pigs, and rodents, and in humans investigated the contributions of sex and age. Spatial transcriptomics and immunofluorescence independently verified the robust presence of DRG T-cells at similar levels in humans, non-human primates, and pigs, but were fewer in rats and largely absent in mice. In humans, premenopausal females were more likely to have elevated DRG endoneurial T-cells than post-menopausal females or adult males. T-cells were detected in human dorsal root ganglion at as early as two months of age but were less abundant within the perineuronal niche. Most human DRG T-cells expressed distinct markers consistent with a resident memory (Trm) phenotype. We discuss the importance of studying the functional roles of DRG-resident T-cells and raise broader considerations for modelling peripheral nervous system disease.

neuroscience↗

bioRxiv2021

Rare copy number variants (CNVs) and breast cancer risk

BackgroundCopy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. ResultsGene burden tests detected the strongest association for deletions in BRCA1 (P= 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P= 0.0008), ATM (P= 0.002) and BRCA2 (P= 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. ConclusionsThis is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.

genetics↗

bioRxiv2019

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype. To identify novel loci, we performed a genome-wide association study (GWAS) including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status and tumor grade. We identified 32 novel susceptibility loci (P<5.0x10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate <0.05). Five loci showed associations (P<0.05) in opposite directions between luminal- and non-luminal subtypes. In-silico analyses showed these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 37.6% for triple-negative and 54.2% for luminal A-like disease. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

genetics↗

bioRxiv2019

Common breast cancer risk loci predispose to distinct tumor subtypes

BackgroundGenome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER), but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. MethodsAmong 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. ResultsEighty-five of 173 variants were associated with at least one tumor feature (false discovery rate <5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at P<0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. ConclusionThis report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.

genetics↗

bioRxiv2019

Fine-mapping of 150 breast cancer risk regions identifies 178 high confidence target genes

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants (CCVs) in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium, and enriched genomic features to determine variants with high posterior probabilities (HPPs) of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of potentially causal variants, using gene expression (eQTL), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways, were over-represented among the 178 highest confidence target genes.

genetics↗