Biology subjects

Saadat, A.

Publications and source records attributed to Saadat, A..

10 recordsLinked to original sources

bioRxiv2026

Multi-omics integration identifies a reproducible inflammatory host-response axis in pediatric sepsis

Sepsis is a major cause of morbidity and mortality in children, yet biological heterogeneity in host responses has limited progress toward targeted therapies and patient stratification. Multiomics integration can combine complementary molecular layers to identify coordinated disease programs not captured by individual assays. Here, we integrated genomic, bulk transcriptomic, proteomic and metabolomic data from blood samples of 22 children with culture-confirmed bacterial sepsis enrolled in the Swiss Pediatric Sepsis Study. Multi-Omics Factor Analysis identified a dominant host-response axis reflecting systemic inflammation. This axis was driven primarily by transcriptomic variation and supported by coordinated proteomic and metabolomic signals, including circulating inflammatory mediators and altered amino-acid metabolism. It was associated with C-reactive protein and a severity score proxy. Projection into an independent pediatric sepsis cohort (n = 22) reproduced the inflammatory and severity-related interpretation of this axis. Single-omic projections showed that the integrated signal could be approximated from individual layers, particularly transcriptomics. In three external pediatric whole-blood transcriptomic datasets, the RNA-derived projection separated septic shock from healthy controls and increased across clinical inflammatory syndromes. These findings define a reproducible inflammatory host-response axis in pediatric sepsis and support multi-omics-guided selection of molecular readouts suitable for clinical translation.

immunology↗

bioRxiv2026

Complement modulation synergizes with therapeutic hypothermia in a rat model of neonatal HIE

BackgroundNeurodevelopmental impairment remains common in neonatal hypoxic-ischemic encephalopathy (HIE) despite treatment with the standard of care, therapeutic hypothermia (TH). The complement response activates at reperfusion and is known to exacerbate neuroinflammation and injury, though its full role and interaction with hypothermia are incompletely defined. We hypothesized that modulating the complement response could improve structural and functional outcomes in HIE, and tested a novel complement therapy (CT), consisting of C3a peptides and the C5a-receptor antagonist PMX205, as both a stand-alone treatment and as an adjuvant to TH. MethodsWistar rat pups were randomized to the following treatment groups: Sham (uninjured control), NT (uninjured, normothermia/not treated control), or injured and treated with either TH, CT, or CT+TH. At term-equivalence, mild-moderate hypoxic-ischemic injury was induced by Vannuccis method. To capture the short and long-term effects of the treatments, cohorts were harvested 3 or 66-72 days post-injury, respectively. Cerebral injury was measured by quantifying levels of inflammatory markers and cerebral tissue loss, and functional outcomes were assessed in a series of behavioral tests. The data were stratified to detect sexual dimorphisms. ResultsCT and TH treatments demonstrated test and sex-dependent differences in improvement compared to untreated, injured rats. In male rats, TH treatment worsened long-term hippocampal and thalamic brain injury and functional measures of ataxia and attention. CT-treatment worsened long-term thalamic loss in females. Combining the two treatments (CT+TH) demonstrated additive improvement in both sexes, including short and long-term cortical loss and ataxia. ConclusionsComplement modulation enhances the neuroprotective effects of TH after neonatal hypoxic-ischemic injury, with sex-specific effects on inflammation and behavior. Combining complement modulation with the standard of care often demonstrated synergistic improvement in both sexes, supporting complement-targeted therapy as a promising adjunct to hypothermia in neonatal HIE. Graphical abstract. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/717097v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1025d1forg.highwire.dtl.DTLVardef@2fa4e5org.highwire.dtl.DTLVardef@1f2c1c4org.highwire.dtl.DTLVardef@8f3410_HPS_FORMAT_FIGEXP M_FIG C_FIG Created with BioRender. Saadat, A. (2026) https://BioRender.com/siwm825.

neuroscience↗

bioRxiv2025

The 9p21.3 Coronary Artery Disease Risk Locus Modulates Vascular Cell-State Transitions via Enhancer-Driven Regulation of MTAP

The 9p21.3 locus is the strongest genetic association with coronary artery disease (CAD), yet its causal mechanisms remain unresolved. We map the regulatory architecture of 9p21.3 in disease-relevant vascular cells, identifying 12 enhancers within the CAD risk haplotype that respond dynamically to inflammatory and metabolic stress in fibroblasts and smooth muscle cells. These activated states are enriched for CAD heritability, implicating stress-responsive vascular wall cells in disease pathophysiology. Dense CRISPRi tiling integrated with fine-mapping and genomic constraint across >500,000 individuals nominates MTAP as the effector gene, with rs1537371 as a likely causal variant. Perturbation and multi-modal analyses show that MTAP loss induces pro-fibrotic and angiogenic programs and sensitizes vascular cells to TGF-{beta}-driven pathological transitions. Our findings reveal a vascular-specific enhancer network through which noncoding variation at 9p21.3 modulates CAD risk via MTAP--a previously unrecognized regulator of vascular remodeling located 269 kb from the risk haplotype. HighlightsO_LI9p21.3 CAD risk locus harbors 12 functional enhancers active in vascular wall cell types C_LIO_LICAD heritability is enriched in stressed vascular fibroblasts and smooth muscle cells C_LIO_LIHigh-resolution CRISPRi-MAC-seq maps 9p21.3 enhancer-gene and SNP-gene interactions C_LIO_LIMTAP identified as a causal effector gene regulated by 9p21.3 fine-mapped and constrained variants C_LIO_LIMTAP modulates TGF-{beta}-driven pathological vascular cell transitions C_LI

genomics↗

bioRxiv2025

Identification of genetic and non-genetic modifiers of genomic imprinting through whole genome screening in humans

Genomic imprinting is required for normal development, and abnormal methylation of differentially methylated regions (iDMRs) controlling the parent of origin-dependent expression of the imprinted genes has been found in constitutional disorders affecting growth, metabolism, neurobehavior, and in cancer. In most of these cases the cause of the imprinting abnormalities is unknown. Also, these studies have generally been performed on a limited number of CpGs, and a systematic investigation of iDMR methylation in the general population is lacking. By analysing the iDMRs in a large number of peripheral blood DNA methylation array datasets of unaffected individuals and patients with rare disorders, we determined the most common iDMR methylation profiles and identified many genetic and non-genetic factors contributing to their variability. We found that methylation variability is not homogeneous within the iDMRs and that the CpGs closer to the ZFP57 binding sites are less susceptible to methylation changes. We demonstrated the methylation polymorphism of three iDMRs and the atypical behaviour of several others, and reported the association of 25 disease- and 47 non-disease-complex traits, including blood cell type composition, as well as 15 mendelian or chromosomal disorders, with iDMR methylation changes in blood DNA. These findings identify several genetic and non-genetic factors associated with genomic imprinting maintenance in humans, which may have a role in the aetiology of the diseases associated with imprinting abnormalities and have clear implications in molecular diagnostics.

genetics↗

bioRxiv2025

Life as a Function: Why Transformer Architectures Struggle to Gain Genome-Level Foundational Capabilities

Recent advances in generative models for nucleotide sequences have shown promise, but their practical utility remains limited. In this study, we explore DNA as a complex functional representation of evolutionary processes and assess the ability of transformer-based models to capture this complexity. Through experiments with both synthetic and real DNA sequences, we demonstrate that current transformer architectures, particularly auto-regressive models relying on next-token prediction, struggle to effectively learn the underlying biological functions. Our findings suggest that these models face inherent limitations, that cannot be overcome with scale, highlighting the need for alternative approaches that incorporate evolutionary constraints and structural information. We propose potential future directions, including the integration of topological methods or the switch of modelling paradigms, to enhance the generation of genomic sequences.

synthetic biology↗

bioRxiv2022

Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries

Reducing disparities is critical to promote equity of access to precision treatments for all patients with cancer. While socioenvironmental factors are a major driver behind such disparities, biological differences also are likely to contribute. The prioritization of cancer drug targets is foundational for drug discovery, yet whether ancestry-related signals in target discovery pipelines exist has not been systematically explored due to the absence of data at the appropriate scale. Here, we analyzed data from 611 genome-scale CRISPR/Cas9 viability experiments in human cell line models as part of the Cancer Dependency Map to identify ancestry-associated genetic dependencies. Surprisingly, we found that most putative associations between ancestry and dependency arose from artifacts related to germline variants that are present at different frequencies across ancestry groups. In 2-5% of genes profiled in each cellular model, germline variants in sgRNA targeting sequences likely reduced cutting by the CRISPR/Cas9 nuclease. Unfortunately, this bias disproportionately affected cell models derived from individuals of recent African descent because their genomes tended to diverge more from the consensus genome typically used for CRISPR/Cas9 guide design. To help the scientific community begin to resolve this source of bias, we report three complementary methods for ancestry-agnostic CRISPR experiments. This report adds to a growing body of literature describing ways in which ancestry bias impacts cancer research in underappreciated ways.

cancer biology↗

bioRxiv2022

Identification of a weight loss-associated causal eQTL in MTIF3 and the effects of MTIF3 deficiency on human adipocyte function

BackgroundGenetic variation at the MTIF3 (Mitochondrial Translational Initiation Factor 3) locus has been robustly associated with obesity in humans, but the functional basis behind this association is not known. MethodsHere, we applied luciferase reporter assay to map potential functional variants in the haplotype block tagged by rs1885988 and used CRISPR-Cas9 to edit the potential functional variants to confirm the regulatory effects on MTIF3 expression. We further conducted functional studies on MTIF3-deficient differentiated human white adipocyte cell line (hWAs-iCas9), generated through inducible expression of CRISPR-Cas9 combined with delivery of synthetic MTIF3-targeting guide RNA. ResultsWe demonstrate that rs67785913-centered DNA fragment (in LD with rs1885988, r2>0.8) enhances transcription in a luciferase reporter assay, and CRISPR/Cas9 edited rs67785913 CTCT cells show significantly higher MTIF3 expression than rs67785913 CT cells. Perturbed MTIF3 expression changed the expression of mitochondrial DNA-encoded genes, and reduced mitochondrial respiration, as well as altered endogenous fatty acid oxidation. Furthermore, after glucose restriction, the MTIF3 knockout cells retained more triglycerides than control cells. ConclusionsThis study demonstrates an adipocyte function-specific role of MTIF3, which originates in the maintenance of mitochondrial function, providing potential explanations for why MTIF3 genetic variation at rs67785913 is associated with body corpulence and response to weight loss interventions.

genetics↗

bioRxiv2021

Discovering cellular programs of intrinsic and extrinsic drivers of metabolic traits using LipocyteProfiler

A primary obstacle in translating genetics and genomics data into therapeutic strategies is elucidating the cellular programs affected by genetic variants and genes associated with human diseases. Broadly applicable high-throughput, unbiased assays offer a path to rapidly characterize gene and variant function and thus illuminate disease mechanisms. Here, we report LipocyteProfiler, an unbiased high-throughput, high-content microscopy assay that is amenable to large-scale morphological and cellular profiling of lipid-accumulating cell types. We apply LipocyteProfiler to adipocytes and hepatocytes and demonstrate its ability to survey diverse cellular mechanisms by generating rich context-, and process-specific morphological and cellular profiles. We then use LipocyteProfiler to identify known and novel cellular programs altered by polygenic risk of metabolic disease, including insulin resistance, waist-to-hip ratio and the polygenic contribution to lipodystrophy. LipocyteProfiler paves the way for large-scale forward and reverse phenotypic profiling in lipid-storing cells, and provides a framework for the unbiased identification of causal relationships between genetic variants and cellular programs relevant to human disease.

genomics↗

bioRxiv2019

Simulation of Red Blood Cell Migration in Small Arterioles: Effect of Cytoplasmic Viscosity

The dynamics of red blood cells in small arterioles are important as these dynamics affect many physiological processes such as hemostasis and thrombosis. However, studying red blood cell flows via computer simulations is challenging due to the complex shapes and the non-trivial viscosity contrast of a red blood cell. To date, little progress has been made studying small arteriole flows (20-40m) with a hematocrit (red blood cell volume fraction) of 10-20% and a physiological viscosity contrast. In this work, we present the results of large-scale simulations that show how the channel size, viscosity contrast of the red blood cells, and hematocrit affect cell distributions and the cell-free layer in these systems. We utilize a massively-parallel immersed boundary code coupled to a finite volume solver to capture the particle resolved physics. We show that channel size qualitatively changes how the cells distribute in the channel. Our results also indicate that at a hematocrit of 10% that the viscosity contrast is not negligible when calculating the cell free layer thickness. We explain this result by comparing lift and collision trajectories of cells at different viscosity contrasts.

biophysics↗

bioRxiv2017

High-resolution genome-wide functional dissection of transcriptional regulatory regions in human

Genome-wide epigenomic maps revealed millions of regions showing signatures of enhancers, promoters, and other gene-regulatory elements1. However, high-throughput experimental validation of their function and high-resolution dissection of their driver nucleotides remain limited in their scale and length of regions tested. Here, we present a new method, HiDRA (High-Definition Reporter Assay), that overcomes these limitations by combining components of Sharpr-MPRA2 and STARR-Seq3 with genome-wide selection of accessible regions from ATAC-Seq4. We used HiDRA to test ~7 million DNA fragments preferentially selected from accessible chromatin in the GM12878 lymphoblastoid cell line. By design, accessibility-selected fragments were highly overlapping (up to 370 per region), enabling us to pinpoint driver regulatory nucleotides by exploiting subtle differences in reporter activity between partially-overlapping fragments, using a new machine learning model SHARPR2. Our resulting maps include ~65,000 regions showing significant enhancer function and enriched for endogenous active histone marks (including H3K9ac, H3K27ac), regulatory sequence motifs, and regions bound by immune regulators. Within them, we discover ~13,000 high-resolution driver elements enriched for regulatory motifs and evolutionarily-conservednucleotides, and help predict causal genetic variants underlying disease from genome-wide association studies. Overall, HiDRA provides a general, scalable, high-throughput, and high-resolution approach for experimental dissection of regulatory regions and driver nucleotides in the context of human biology and disease.

genomics↗