Biology subjects

Krieger, J. E.

Publications and source records attributed to Krieger, J. E..

5 recordsLinked to original sources

bioRxiv2026

From mice to humans: A multi-omic predictive framework for translational immunology

Mice are key preclinical animal models in vaccine and immunological research, yet their predictive value for human immunity remains contested. Here, we evaluated the translatability of murine models across inactivated and subunit vaccination (influenza, hepatitis B), acute infection (S. aureus, E. coli), and injury (burns and trauma), integrating transcriptomic profiles with sequence evolution, cis-regulatory architecture, and functional annotation. Functional modules were more conserved between species than individual orthologous genes. Translational accuracy depended on stimulus intensity, as infections and injuries engaged conserved signatures, while single-dose vaccination diverged. We then built multilayer models to predict human expression rank and direction of change, and to classify shared leading-edge genes. Adding evolutionary and regulatory layers improved these predictions. We provide a step-by-step R Markdown notebook to apply the models to user data. The study code and datasets are available at https://github.com/wapsyed/mousetohuman_multilayer

bioinformatics↗

bioRxiv2026

Capturing Regional Variation in Aortic Mechanics: Dual-Estimation Method for Material Parameter Identification and Biological Correlation

The aorta shows significant regional variation in geometry and composition. This complexity makes numerical modeling challenging, as it requires identifying material parameters. Typically, the Holzapfel-Gasser-Ogden model is used. However, it suffers from nonuniqueness and sensitivity to outliers, which can obscure biological variation. In addition, standard compressible formulations with a volumetric-isochoric split fail to couple volumetric and anisotropic responses. To address these issues, a regularized dual-estimation framework was introduced. This framework combines a global baseline estimator with local refinement while maintaining structural material continuity. Furthermore, it uses a Modified Anisotropic model to improve the representation of compressibility physics. For validation, the approach included uniaxial extension and protein quantification from Wistar rats. The results show that the proximal ascending/aortic-arch segment is most compliant at low stretch, whereas the abdominal aorta stiffens earlier and becomes fiber-dominated at lower stretch levels. Notably, these trends align directionally with regional composition. However, the fitted stress components are model-based descriptors rather than direct measurements of individual constituents.

bioengineering↗

bioRxiv2022

In silico network-based screening reveals candidates for endothelial dysfunction therapy

Endothelial dysfunction (ED) is a hallmark of cardiovascular (CV) disorders and influences their progression; however, there are currently no direct therapeutic targets, primarily due to the lack of knowledge regarding EDs molecular basis. We used a computational approach to identify candidate targets for ED treatment. We constructed an ED disease gene network by combining the integration of epigenomics (ATAC-seq and ChIP-seq-H3K27ac) and transcriptomics data (RNA-seq) from human aorta endothelial cells (HAEC) exposed to surrogates of primary CV risk factors using network propagation. We then used in silico perturbation to prioritise genes that could influence the ED network most when removed. This process resulted in identifying 17 key candidates for which chemical inhibitors are available. These are genes associated with ED and atherosclerosis, and drugs that target those genes have not yet been tested for the treatment of CV disorders. The EGLN3 target and its inhibitor displayed significant anti-inflammatory and antioxidant properties in ECs assessed using a high-content screening platform. These findings illustrate the potential of in silico knockouts to discover disease-specific candidate targets for drug development or repositioning.

systems biology↗

bioRxiv2021

Ancestral diversity improves discovery and fine-mapping of genetic loci for anthropometric traits - the Hispanic/Latino Anthropometry Consortium

Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite notable anthropometric variability with ancestry proportions, and a high burden of growth stunting and overweight/obesity in Hispanic/Latino populations. This address this knowledge gap, we analyzed densely-imputed genetic data in a sample of Hispanic/Latino adults, to identify and fine-map common genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (Stage 1, n=59,769) and validated our findings in 9 additional studies (HISLA Stage 2, n=9,336). We conducted a trans-ethnic GWAS with summary statistics from HISLA Stage 1 and existing consortia of European and African ancestries. In our HISLA Stage 1+2 analyses, we discovered one novel BMI locus, as well two novel BMI signals and another novel height signal, each within established anthropometric loci. In our trans-ethnic meta- analysis, we identified three additional novel BMI loci, one novel height locus, and one novel WHRadjBMI locus. We also identified three secondary signals for BMI, 28 for height, and two for WHRadjBMI. We replicated >60 established anthropometric loci in Hispanic/Latino populations at genome-wide significance--representing up to 30% of previously-reported index SNP anthropometric associations. Trans-ethnic meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our novel findings demonstrate that future studies may also benefit from leveraging differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification.

genetics↗

bioRxiv2020

Genome-wide association of PCSK9 (Proprotein Convertase Subtilisin/Kexin Type 9) plasma levels in the ELSA-Brasil study

Pharmacological inhibition of PCSK9 (proprotein convertase subtilisin/kexin type 9) is an established therapeutic option to treat hypercholesterolemia and plasma PCSK9 levels have been implicated in cardiovascular disease incidence. A number of genetic variants within the PCSK9 gene locus have been shown to modulate PCSK9 levels, but these only explain a very small percentage of the overall PCSK9 interindividual variation. Here we present data on the genetic association structure between PCSK9 levels and genome-wide genetic variation in a healthy sample from the general population. We performed a genome-wide association study of plasma PCSK9 levels in a sample of Brazilian individuals enrolled in the ELSA-Brasil cohort (n=810). Enrolled individuals were free from cardiovascular disease, diabetes and were not under lipid-lowering medication. Genome-wide genotyping was conducted using the Axiom_PMRA.r3 array and imputation used the TOPMED multi-ancestry sample panel. Total PCSK9 plasma concentrations were determined using the Quantikine SPC900 ELISA kit. We observed two genome-wide significant loci and seven loci that reached the pre-defined p value threshold of 1 x 10-6. Significant variants were near KCNA5 and KCNA1, and LINC00353. Genetic variation at the PCSK9 locus was able to explain approximately 4% of the overall interindividual variation in PCSK9 levels. Colocalization analysis using eQTL data suggested RWDD3, ATXN7L1, KCNA1, and FAM177A1 to be potential mediators of some of the observed associations. Our results suggest that PCSK9 levels may be modulated by trans genetic variation outside of the PCSK9 gene and this may have clinical implications. Understanding both environmental and genetic predictors of PCSK9 levels may help identifying new targets for cardiovascular disease treatment and contribute to a better assessment of the benefits of long-term PCSK9 inhibition.

genetics↗