Biology subjects

Van Booven, D. J.

Publications and source records attributed to Van Booven, D. J..

5 recordsLinked to original sources

bioRxiv2024

Gene expression and chromatin accessibility comparison in iPSC-derived microglia in African, European, and Amerindian genomes in Alzheimer's patients and controls.

Alzheimers disease (AD) risk differs between population groups, with African Americans and Hispanics being the most affected groups compared to non-Hispanic Whites. Genetic factors contribute significant risk to AD, but the genetic regulatory architectures (GRA) have primarily been studied in Europeans. Many AD genes are expressed in microglia; thus, we explored the impact of genetic ancestry (Amerindian (AI), African (AF), and European (EU)) on the GRA in iPSC-derived microglia from 13 individuals ([~]4 each with high global ancestry, AD and controls) through ATAC-seq and RNA-seq analyses. We identified several differentially accessible and expressed genes (2 and 10 AD-related, respectively) between ancestry groups. We also found a high correlation between the transcriptomes of iPSC-derived and brain microglia, supporting their use in human studies. This study provides valuable insights into genetically diverse microglia beyond the analysis of AD.

genomics↗

bioRxiv2024

Synthetic Histology Images for Training AI Models: A Novel Approach to Improve Prostate Cancer Diagnosis

Prostate cancer (PCa) poses significant challenges for timely diagnosis and prognosis, leading to high mortality rates and increased disease risk and treatment costs. Recent advancements in machine learning and digital imagery offer promising potential for developing automated and objective assessment pipelines that can reduce human capital and resource costs. However, the reliance of AI models on large amounts of clinical data for training presents a significant challenge, as this data is often biased, lacking diversity, and not readily available. Here we aim to address this limitation by employing customized generative adversarial network (GAN) models to produce high-quality synthetic images of different PCa grades (radical prostatectomy (RP)) and needle biopsies, which were customized to account for the granularity associated with each Gleason grade. The generated images were subjected to multiple rounds of benchmarking, quantifications and quality control assessment before being used to train an AI model (EfficientNet) for grading digital histology images of adenocarcinoma specimens (RP sections) and needle biopsies obtained from the PANDA challenge repository. Validation was performed using the AI model trained with synthetic data to grade digital histology from the cancer genome atlas (TCGA) (RP sections) and needle biopsy data from Radboud University Medical Center and Karolinska Institute. Results demonstrated that the AI model trained with a combination of image patches derived from original and enhanced synthetic images outperformed the model trained with original digital histology images. Together, this study demonstrates the potential of customized GAN models to generate a large cohort of synthetic data that can train AI models to effectively grade PCa specimens. This approach could potentially eliminate the need for extensive clinical data for training any AI model in the domain of digital imagery, leading to cost and time-effective diagnosis and prognosis.

cancer biology↗

bioRxiv2023

An Alzheimer's disease risk variant in TTC3 modifies the actin cytoskeleton organization and the PI3K-Akt signaling pathway in iPSC-derived forebrain neurons

A missense variant in the tetratricopeptide repeat domain 3 (TTC3) gene (rs377155188, p.S1038C, NM_003316.4:c.3113C>G) was found to segregate with disease in a multigenerational family with late onset Alzheimers disease. This variant was introduced into induced pluripotent stem cells (iPSCs) derived from a cognitively intact individual using CRISPR genome editing and the resulting isogenic pair of iPSC lines were differentiated into cortical neurons. Transcriptome analysis showed an enrichment for genes involved in axon guidance, regulation of actin cytoskeleton, and GABAergic synapse. Functional analysis showed that the TTC3 p.S1038C iPSC-derived neuronal progenitor cells had altered 3D morphology and increased migration, while the corresponding neurons had longer neurites, increased branch points, and altered expression levels of synaptic proteins. Pharmacological treatment with small molecules that target the actin cytoskeleton could revert many of these cellular phenotypes, suggesting a central role for actin in mediating the cellular phenotypes associated with the TTC3 p.S1038C variant. HighlightsO_LIThe AD risk variant TTC3 p.S1038C reduces the expression levels of TTC3 C_LIO_LIThe variant modifies the expression of AD specific genes BACE1, INPP5F, and UNC5C C_LIO_LINeurons with the variant are enriched for genes in the PI3K-Akt pathway C_LIO_LIiPSC-derived neurons with the alteration have increased neurite length and branching C_LIO_LIThe variant interferes with actin cytoskeleton and is ameliorated by Cytochalasin D C_LI

genetics↗

bioRxiv2020

Linkage Analysis in Caribbean Hispanic Families with Puerto Rican Ancestry Idenitfies an Alzheimer Disease Locus on chromosome 9.

BackgroundThe ancestral genetic heterogeneity (admixture) of Caribbean Hispanics makes studies of this population critical to the discovery of ancestry-specific genetic factors in Alzheimer disease. In this study, we performed whole genome sequencing in multiplex Caribbean Hispanic Puerto Rican families to identify rare causal variants influencing Alzheimer disease through linkage and segregation-based approaches. MethodsAs part of the Puerto Rican Alzheimer Disease Initiative, whole genome sequencing data were generated for 100 individuals (61 affected) from 23 Puerto Rican families. To identify the genetic loci likely to carry risk variants, we performed a parametric multipoint affected individuals-only linkage analysis using MERLIN software. Following the linkage analysis, we identified the consensus region (heterogeneity logarithm of the odds score (HLOD) > 5.1), annotated variants using Ensembl Variant Effect Predictor, and combined annotation dependent depletion score (CADD). Finally, we prioritized variants according to allele frequency (< 0.01), function (CADD > 10), and complete segregation among affected individuals. ResultsA locus at 9p21 produced a linkage HLOD score of 5.1 in the parametric affecteds-only multipoint affected individuals-only model supported by 9 families. Through the prioritization step, we selected 36 variants (22 genic variants). Candidate genes in the regions include C9orf72, UNC13B, and ELAVL2. ConclusionsLinkage analysis of Caribbean Hispanics Puerto Rican families confirmed previously reported linkage to 9p21 in non-Hispanic White and Israeli-Arap families. Our results suggest several candidates in the region as conferring AD risk. Identified putative damaging rare variants in multiplex families indicates the critical role of rare variation in Alzheimer disease etiology.

genetics↗

bioRxiv2017

SUPERmerge: ChIP-Seq Coverage Island Analysis Algorithm For Broad Histone Marks

SUPERmerge is a ChIP-seq read pileup analysis and annotation algorithm for investigating alignment (BAM) files of diffuse histone modification ChIP-seq datasets with broad chromatin domains at a single base pair resolution level. SUPERmerge allows flexible regulation of a variety of read pileup parameters, thereby revealing how read islands aggregate into areas of coverage across the genome and what annotation features they map to within individual biological replicates. SUPERmerge is especially useful for investigating low sample size ChIP-seq experiments in which epigenetic histone modifications (e.g., H3K9me1, H3K27me3) result in inherently broad peaks with a diffuse range of signal enrichment spanning multiple consecutive genomic loci and annotated features.

bioinformatics↗