Biology subjects

Marshall, C. R.

Publications and source records attributed to Marshall, C. R..

4 recordsLinked to original sources

bioRxiv2026

Multimodal Molecular Mapping of the Vasculature in Human Cortex Reveals Lipid Markers of Cerebral Amyloid Angiopathy

Cerebral amyloid angiopathy (CAA) commonly co-occurs with Alzheimers disease (AD), yet the molecular changes that accompany vascular {beta}-amyloid deposition in human tissue remain incompletely defined. Herein, we use a novel imaging approach that combines matrix-assisted laser desorption/ionization imaging mass spectrometry (IMS) with immunofluorescence microscopy on the same sections of postmortem human frontal cortex to map the lipid microenvironment of leptomeningeal vasculature in cases with and without CAA. Autofluorescence-guided regions-of-interest were imaged by IMS in both negative and positive ion modes and registered to post-IMS-acquired microscopy images. Immunofluorescence microscopy using collagen IV, -smooth muscle actin (SMA), and thiazine red enabled automated segmentation of total, amyloidpositive, and amyloid-negative vasculature regions. A CAA index, the ratio of amyloid-positive area to total vasculature area in a region imaged by IMS, was used to define vasculature and classify each case into having CAA, or CAA-present and not having CAA, or CAA-absent. An interpretable machine learning approach (XGBoost models with Shapley additive explanations for interpretation) was trained on pixel-level spectra and identified lipid signatures of vascular identity shared across groups as well as class-specific marker candidates that distinguished CAA-present from CAA-absent vasculature. CAA-present vessels were enriched for gangliosides (e.g., GM1), whereas CAA-absent vessels were characterized by higher contributions from phosphatidylserines (e.g., long-chain polyunsaturated PS species). Univariate differences were inconsistent between the two groups, but multivariate models in negative mode yielded stable discriminatory features. These results define spatial lipid correlates of vascular amyloid pathology in the human brain and establish a multimodal framework for mechanistically linking lipid metabolism, vascular integrity, and CAA in AD.

neuroscience↗

bioRxiv2025

Spatial Dependence and Heterogeneity in Molecular Imaging: Moran Quadrant Maps Enable Advanced Spatial-Statistical Analysis

Multiplexed molecular imaging, such as imaging mass spectrometry, provides spatially-contextualized insights that are transforming biomedical research by advancing our understanding of tissue organization and disease mechanisms. However, the spatial-statistical properties of molecular imaging data are often underutilized, and scalable computational tools to analyze them are lacking. Here, we demonstrate how local and global spatial autocorrelation (SAC) metrics can be used to quantify spatial dependence and spatial heterogeneity, properties that violate the common assumption of independent and identically distributed measurements. We develop mathematically rigorous methods for SAC-based exploratory analysis. Furthermore, we introduce a novel spatial feature extractor, the Moran quadrant map, and develop two advanced workflows based on it: Moran-Felsenszwalb segmentation for tissue domain segmentation and Moran-HOG clustering for colocalization-based image analysis. Finally, our open-source Moran Imaging toolbox (https://github.com/vandeplaslab/Moran_Imaging) provides scalable Python implementations, including a novel parallelized spatial lag algorithm, unlocking SAC-based analyses and biological insights for large-scale imaging.

bioinformatics↗

bioRxiv2020

Integrative analysis of genomic variants reveals new associations of candidate haploinsufficient genes with congenital heart disease

Congenital Heart Disease (CHD) affects approximately 7-9 children per 1000 live births. Numerous genetic studies have established a role for rare genomic variants at the copy number variation (CNV) and single nucleotide variant level. In particular, the role of de novo mutations (DNM) has been highlighted in syndromic and non-syndromic CHD. To identify novel haploinsufficient CHD disease genes we performed an integrative analysis of CNVs and DNMs identified in probands with CHD including cases with sporadic thoracic aortic aneurysm (TAA). We assembled CNV data from 7,958 cases and 14,082 controls and performed a gene-wise analysis of the burden of rare genomic deletions in cases versus controls. In addition, we performed mutation rate testing for DNMs identified in 2,489 parent-offspring trios. Our combined analysis revealed 21 genes which were significantly affected by rare genomic deletions and/or constrained non-synonymous de novo mutations in probands. Fourteen of these genes have previously been associated with CHD while the remaining genes (FEZ1, MYO16, ARID1B, NALCN, WAC, KDM5B and WHSC1) have only been associated in singletons and small cases series, or show new associations with CHD. In addition, a systems level analysis revealed shared contribution of CNV deletions and DNMs in CHD probands, affecting protein-protein interaction networks involved in Notch signaling pathway, heart morphogenesis, DNA repair and cilia/centrosome function. Taken together, this approach highlights the importance of re-analyzing existing datasets to strengthen disease association and identify novel disease genes.

genetics↗

bioRxiv2020

Genes and pathways implicated in tetralogy of Fallot revealed by ultra-rare variant burden analysis in 231 genome sequences

Recent genome-wide studies of rare genetic variants have begun to implicate novel mechanisms for tetralogy of Fallot (TOF), a severe congenital heart defect (CHD). To provide statistical support for case-only data without parental genomes, we re-analyzed genome sequences of 231 individuals with TOF or related CHD. We adapted a burden test originally developed for de novo variants to assess singleton variant burden in individual genes, and in gene-sets corresponding to functional pathways and mouse phenotypes, accounting for highly correlated gene-sets, and for multiple testing. The gene burden test identified a significant burden of deleterious missense variants in NOTCH1 (Bonferroni-corrected p-value <0.01). These NOTCH1 variants showed significant enrichment for those affecting the extracellular domain, and especially for disruption of cysteine residues forming disulfide bonds (OR 39.8 vs gnomAD). Individuals with NOTCH1 variants, all with TOF, were enriched for positive family history of CHD. Other genes not previously implicated in TOF had more modest statistical support and singleton missense variant results were non-significant for gene-set burden. For singleton truncating variants, the gene burden test confirmed significant burden in FLT4. Gene-set burden tests identified a cluster of pathways corresponding to VEGF signaling (FDR=0%), and of mouse phenotypes corresponding to abnormal vasculature (FDR=0.8%), that suggested additional candidate genes not previously identified (e.g., WNT5A and ZFAND5). Analyses using unrelated sequencing datasets supported specificity of the findings for CHD. The findings support the importance of ultra-rare variants disrupting genes involved in VEGF and NOTCH signaling in the genetic architecture of TOF. These proof-of-principle data indicate that this statistical methodology could assist in analyzing case-only sequencing data in which ultra-rare variants, whether de novo or inherited, contribute to the genetic etiopathogenesis of a complex disorder. Author summaryWe analyzed the ultra-rare nonsynonymous variant burden for genome sequencing data from 231 individuals with congenital heart defects, most with tetralogy of Fallot. We adapted a burden test originally developed for de novo variants. In line with other studies, we identified a significant truncating variant burden for FLT4 and deleterious missense burden for NOTCH1, both passing a stringent Bonferroni multiple-test correction. For NOTCH1, we observed frequent disruption of cysteine residues establishing disulfide bonds in the extracellular domain. We also identified genes with BH-FDR <10% that were not previously implicated. To overcome limited power for individual genes, we tested gene-sets corresponding to functional pathways and mouse phenotypes. Gene-set burden of truncating variants was significant for vascular endothelial growth factor signaling and abnormal vasculature phenotypes. These results confirmed previous findings and suggested additional candidate genes for experimental validation in future studies. This methodology can be extended to other case-only sequencing data in which ultra-rare variants make a substantial contribution to genetic etiology.

genomics↗