Biology subjects

Adam, J.

Publications and source records attributed to Adam, J..

8 recordsLinked to original sources

bioRxiv2026

Intraindividual longitudinal changes of the proteome reveal dynamic markers of biological aging

Proteomic aging clocks have emerged as biomarkers of aging, but most rely on cross-sectional data. Here, we present a proteomic aging clock based on longitudinal measurements of liquid chromatography-mass spectrometry plasma proteomics at up to three time points in the population-based KORA cohort, comprising 9,105 samples from 4,100 individuals in the final dataset aged 25-88 years. The model predicts chronological age and yields a measure of proteomic age acceleration associated with lifestyle and clinical risk factors. Risk factor-stratified analyses reveal shared proteomic signatures among cardiometabolic exposures and distinct signatures for smoking and physical activity. Within individuals, dyslipidemia and impaired kidney function track transitions to increases in age acceleration, while higher age acceleration is associated with increased all-cause mortality. Mediation analysis suggests that risk factors are linked to mortality indirectly through age acceleration. Affected proteins and pathways highlight extracellular matrix remodeling, complement and coagulation pathways, and liver-derived plasma proteins as key contributors to aging. Mendelian randomization identifies proteins with evidence consistent with a causal role in aging-related traits. Together, these findings are consistent with biological aging being dynamically responsive to changes in modifiable risk factors.

bioinformatics↗

bioRxiv2026

Nonlinear Impacts of Herbivory on Plants Explain the Herbivory Paradox

Herbivores strongly shape plant ecology and evolution. Yet plants typically sustain low, tolerable levels of damage, raising the question of how herbivory influences plant biology despite often weak fitness effects. Analyzing 1,145 datasets of the effects of damage on fitness for 103 plant species worldwide, we show that nonlinear tolerance to damage is one explanation for this paradoxical contradiction. Plants are tolerant of low levels of damage, but infrequent, severe damage levels disproportionately reduce plant fitness. Models incorporating nonlinear tolerance suggest that disproportionate tolerance to low levels of damage stabilizes population dynamics and promotes coevolutionary feedback with herbivores. Pervasive nonlinear tolerance shows consistent patterns across environmental gradients, may alter the stability of food webs, and may explain why herbivory matters despite the world being green.

ecology↗

bioRxiv2026

Discrete genetic effects of VHL and PBRM1 inactivation co-operate to disrupt epithelial homeostasis and promote ccRCC

Inactivation of VHL is a truncal alteration in clear cell renal cell carcinoma, but additional events are required for oncogenesis, most commonly PBRM1 inactivation. To better understand this co-operation, we used an oncogenic cell-tagging strategy to analyze the earliest transcriptional and cellular consequences of Vhl and/or Pbrm1 inactivation in the renal tubular epithelium, in vivo, at single-cell resolution. Pbrm1 inactivation did not globally alter HIF-dependent transcription or increase early tubular proliferation induced by Vhl inactivation. Instead, it had independent effects on epithelial organization. Combined genetic and morphological analyses suggested that Pbrm1 inactivation allows cells to sustain Vhl/HIF-dependent proliferation by disrupting tubular architectures that ordinarily restrain this proliferation, resulting in extra-tubular cell accumulation, multilayered epithelia, and tumor formation. Our findings frame a new model for the VHL-PBRM1 interaction that explains loss of epithelial homeostasis through an interaction between discrete effects that drive proliferation and remove structural tissue restraints on that proliferation. Statement of SignificanceVHL and PBRM1 are frequently co-inactivated in ccRCC. Combining transcriptomic and histological analyses of Vhl and/or Pbrm1-inactivated renal cells in vivo, this study highlights independent effects on transcription and epithelial organization that converge to promote sustained proliferation and dysplasia. The work illuminates how tissue homeostasis is disrupted by oncogenic co-operation.

cancer biology↗

bioRxiv2024

HIFalpha isoform specific activities drive cell-type specificity of VHL-associated oncogenesis

Cancers arising from dysregulation of generally operative signaling pathways are often tissue specific, but the mechanisms underlying this paradox are poorly understood. Based on striking cell-type specificity, we postulated that these mechanisms must operate early in cancer development and set out to study them in a model of von Hippel Lindau (VHL) disease. Biallelic mutation of the VHL ubiquitin ligase leads to constitutive activation of hypoxia inducible factors HIF1A and HIF2A and is generally a truncal event in clear cell renal carcinoma. We used an oncogenic tagging strategy in which VHL-mutant cells are marked by tdTomato, enabling their observation, retrieval, and analysis early after VHL-inactivation. Our findings reveal markedly different consequences of HIF1A and HIF2A activation, but that both contribute to renal cell-type specific consequences of VHL-inactivation in the kidney. Early involvement of HIF2A in promoting proliferation within proximal tubular epithelium supports therapeutic targeting of HIF2A early in VHL disease.

cancer biology↗

bioRxiv2024

Multimodal CustOmics: A Unified and Interpretable Multi-Task Deep Learning Framework for Multimodal Integrative Data Analysis in Oncology

Characterizing cancer poses a delicate challenge as it involves deciphering complex biological interactions within the tumors microenvironment. Histology images and molecular profiling of tumors are often available in clinical trials and can be leveraged to understand these interactions. However, despite recent advances in representing multimodal data for weakly supervised tasks in the medical domain, numerous challenges persist in achieving a coherent and interpretable fusion of whole slide images and multi-omics data. Each modality operates at distinct biological levels, introducing substantial correlations both between and within data sources. In response to these challenges, we propose a deep-learning-based approach designed to represent multimodal data for precision medicine in a readily interpretable manner. While demonstrating superior performance compared to state-of-the-art methods across multiple test cases, our approach also provides robust results and extracts various scores characterizing the activity of each modality and their interactions at the pathway and gene levels. The strength of our method lies in its capacity to unravel pathway activation through multimodal relationships and extend enrichment analysis to spatial data for supervised tasks. We showcase the efficiency and robustness of its predictive capacity and interpretation scores through an extensive exploration of multiple TCGA datasets and validation cohorts, underscoring its value in advancing our understanding of cancer. The method is publicly available in Github.

cancer biology↗

bioRxiv2022

Spatial positioning and matrix programs of cancer-associated fibroblasts promote T cell exclusion in human lung tumors

It is currently accepted that activated cancer-associated fibroblasts (CAF) participate in T cell exclusion from tumor nests, but it remains unclear how they promote barrier phenotypes, and whether specific subsets are involved. Here, using single-cell RNA sequencing coupled with multiplex imaging on a large cohort of lung tumors, we identify four main CAF populations, of which only two are associated with T cell exclusion: (i) MYH11+SMA+ CAF, which are present in early-stage tumors and form a single-cell layer lining cancer aggregates, and (ii) FAP+SMA+ CAF, which appear in more advanced tumors and organize in patches within the stroma or in multiple layers around tumor nests. Both CAF populations show a contractility phenotype together with dense and aligned matrix fiber deposition compared to the T cell-permissive CAF. Yet they express distinct matrix genes, including COL4A1/COL9A1 (MYH11+SMA+ CAF) and COL11A1/COL12A1 (FAP+SMA+ CAF). Hereby, we uncovered unique molecular programs of CAF driving T cell marginalization, whose targeting should increase immunotherapy efficacy in patients bearing T cell-excluded tumors. SIGNIFICANCEThe cellular and molecular programs driving T cell marginalization in solid tumors remain unclear. Here, we describe two CAF populations associated with T cell exclusion in human lung tumors. We demonstrate the importance of pairing molecular and spatial analysis of the tumor microenvironment, a prerequisite to develop new strategies targeting T cell-excluding CAF.

cancer biology↗

bioRxiv2020

Sources of genomic diversity in the self-fertile plant pathogen, Sclerotinia sclerotiorum, and consequences for resistance breeding

The ascomycete, Sclerotinia sclerotiorum, has a broad host range and causes yield loss in dicotyledonous crops world wide. Genomic diversity and aggressiveness were determined in a population of 127 isolates from individual canola (Brassica napus) fields in western Canada. Genotyping with 39 simple sequence repeat (SSR) markers revealed each isolate was an unique haplotype. Analysis of molecular variation showed 97% was due to isolate and 3% to geographical location. Testing of mycelium compatibility identified clones of mutually compatible isolates, and stings of pairwise compatible isolates not seen before. Importantly, mutually compatible isolates had similar SSR haplotype, in contrast to high diversity among incompatible isolates. Isolates from the Province of Manitoba had higher allelic richness and higher mycelium compatibility (61%) than Alberta (35%) and Saskatchewan (39%). All compatible Manitoba isolates were interconnected in clones and strings, which can be explained by wetter growing seasons and more susceptible crops species both favouring more mycelium interaction and life cycles. Analysis of linkage disequilibrium rejected random recombination, consistent with a self-fertile fungus and restricted outcrossing due to mycelium incompatibility, and only one meiosis per lifecycle. More probable sources of genomic diversity is slippage during DNA replication and point mutation affecting single nucleotides, not withstanding the high mutation rate of SSRs compared to genes. It seems accumulation of these polymorphisms lead to increasing mycelium incompatibility in a population over time. A phylogenetic tree grouped isolates into 17 sub-populations. Aggressiveness was tested by inoculating one isolate from each sub-population onto B. napus lines with quantitative resistance. Results were significant for isolate, line, and isolate by line interaction. These isolates represent the genomic and pathogenic diversity in western Canada, and are suitable for resistance screening in canola breeding programs. Since the S. sclerotiorum life cycle is universal, conclusions on sources of genomic diversity extrapolates to populations in other geographical areas and host crops. Author summarySclerotinia sclerotiorum populations from various plant species and geographical areas have been studied extensively using mycelium compatibility tests and genotyping with a shared set of 6-13 SSR markers published in 2001. Most conclude the pathogen is clonally propagated with some degree of outcrossing. In the present study, a population of S. sclerotiorum isolates from 1.5 million km2 area in western Canada were tested for mycelium compatibility, and genotyped with 9 published and 30 newly developed SSR markers targeting all chromosomes in the dikaryot genome (8+8). A new way of visualizing mycelium compatibility results revealed clones of mutual compatible isolates, as well as long and short strings of pairwise compatible isolates. Importantly, clonal isolates had similar SSR haplotype, while incompatible isolates were highly dissimilar; a relationship difficult to discern previously. Analysis of population structure found a lack of linkage disequilibrium ruling out random recombination. Outcrossing, a result of alignment of non-sister chromosomes during meiosis, is unlikely in S. sclerotiorum, since mycelium incompatibility prevents karyogamy, and compatibility only occur between isolates with similar genomic composition. Instead, genomic diversity comprise transfer of nuclei through hyphal anastomosis, allelic modifications during cell division and point mutation. Genomic polymorphisms accumulate over time likely result in gradual divergence of individuals, which seems to resemble the ring-species concept. We are currently studying whether nuclei in microconidia might also contribute to diversity. A phylogenetic analysis grouped isolates into 17 sub-populations. One isolate from each sub-population showed different level of aggressiveness when inoculated onto B. napus lines previously determined to have quantitative resistance to a single isolate. Seed of these lines and S. sclerotiorum isolates have been transferred to plant breeders, and can be requested from the corresponding author for breeding purposes. Quantitative resistance is likely to hold up over time, since the rate of genomic change is relatively slow in S. sclerotiorum.

microbiology↗

bioRxiv2018

The Integrated Rapid Infectious Disease Analysis (IRIDA) Platform

Whole genome sequencing (WGS) is a powerful tool for public health infectious disease investigations owing to its higher resolution, greater efficiency, and cost-effectiveness over traditional genotyping methods. Implementation of WGS in routine public health microbiology laboratories is impeded by a lack of user-friendly automated and semi-automated pipelines, restrictive jurisdictional data sharing policies, and the proliferation of non-interoperable analytical and reporting systems. To address these issues, we developed the Integrated Rapid Infectious Disease Analysis (IRIDA) platform (irida.ca), a user-friendly, decentralized, open-source bioinformatics and analytical web platform to support real-time infectious disease outbreak investigations using WGS data. Instances can be independently installed on local high-performance computing infrastructure, enabling private and secure data management and analyses according to organizational policies and governance. IRIDAs data management capabilities enable secure upload, storage and sharing of all WGS data and metadata. The core platform currently includes pipelines for quality control, assembly, annotation, variant detection, phylogenetic analysis, in silico serotyping, multi-locus sequence typing, and genome distance calculation. Analysis pipeline results can be visualized within the platform through dynamic line lists and integrated phylogenomic clustering for research and discovery, and for enhancing decision-making support and hypothesis generation in epidemiological investigations. Communication and data exchange between instances are provided through customizable access controls. IRIDA complements centralized systems, empowering local analytics and visualizations for genomics-based microbial pathogen investigations. IRIDA is currently transforming the Canadian public health ecosystem and is freely available at https://github.com/phac-nml/irida and www.irida.ca.\n\nImpact StatementWhole genome sequencing (WGS) is revolutionizing infectious disease analysis and surveillance due to its cost effectiveness, utility, and improved analytical power. To date, no \"one-size-fits-all\" genomics platform has been universally adopted, owing to differences in national (and regional) health information systems, data sharing policies, computational infrastructures, lack of interoperability and prohibitive costs. The Integrated Rapid Infectious Disease Analysis (IRIDA) platform is a user-friendly, decentralized, open-source bioinformatics and analytical web platform developed to support real-time infectious disease outbreak investigations using WGS data. IRIDA empowers public health, regulatory and clinical microbiology laboratory personnel to better incorporate WGS technology into routine operations by shielding them from the computational and analytical complexities of big data genomics. IRIDA is now routinely used as part of a validated suite of tools to support outbreak investigations in Canada. While IRIDA was designed to serve the needs of the Canadian public health system, it is generally applicable to any public health and multi-jurisdictional environment. IRIDA enables localized analyses but provides mechanisms and standard outputs to enable data sharing. This approach can help overcome pervasive challenges in real-time global infectious disease surveillance, investigation and control, resulting in faster responses, and ultimately, better public health outcomes.\n\nDATA SUMMARYO_LIData used to generate some of the figures in this manuscript can be found in the NCBI BioProject PRJNA305824.\nC_LI

bioinformatics↗