Biology subjects

Mendez, K.

Publications and source records attributed to Mendez, K..

3 recordsLinked to original sources

bioRxiv2025

A matrix-mimicking bioadhesive epicardium for tunable modulation of biomechanics in the acutely infarcted heart

Mitigating adverse tissue remodeling after a heart attack or myocardial infarction (MI) is critical to prevent the development of heart failure. Among various post-MI treatment strategies, mechanical reinforcement of the infarcted region with epicardial patches has promise due to its consistent improvement of chronic cardiac function and its drug- or biologic-free nature. However, despite the variety of patch materials studied to date, the lack of a programmable platform that predictably modifies early-stage cardiac biomechanics to different degrees has prevented further optimization of this strategy. Here, we introduce the matrix-mimicking bioadhesive epicardium (MMBE), a platform that can be rationally designed to achieve a wide range of anisotropic mechanical properties to offer quantifiable mechanical reinforcement of the heart upon application. The platform synergistically combines fully programmable direct-ink-writing of extracellular matrix-inspired crimped fibers and a bioadhesive for sutureless integration to the epicardium. The MMBE platform achieves an array of matrix-mimicking mechanical properties and acute modulation of cardiac biomechanics using numerical analysis, in silico studies and experimental characterizations. Furthermore, the feasibility of the MMBE platform in an in vivo rat model of MI is demonstrated. The MMBE platform can be used to systematically identify patch design parameters that alter post-MI remodeling without introducing confounding biological variables.

bioengineering↗

bioRxiv2024

A genome-wide association study of mass spectrometry proteomics using the Seer Proteograph platform

Genome-wide association studies (GWAS) with proteomics are essential tools for drug discovery. To date, most studies have used affinity proteomics platforms, which have limited discovery to protein panels covered by the available affinity binders. Furthermore, it is not clear to which extent protein epitope changing variants interfere with the detection of protein quantitative trait loci (pQTLs). Mass spectrometry-based (MS) proteomics can overcome some of these limitations. Here we report a GWAS using the MS-based Seer ProteographTM platform with blood samples from a discovery cohort of 1,260 American participants and a replication in 325 individuals from Asia, with diverse ethnic backgrounds. We analysed 1,980 proteins quantified in at least 80% of the samples, out of 5,753 proteins quantified across the discovery cohort. We identified 252 and replicated 90 pQTLs, where 30 of the replicated pQTLs have not been reported before. We further investigated 200 of the strongest associated cis-pQTLs previously identified using the SOMAscan and the Olink platforms and found that up to one third of the affinity proteomics pQTLs may be affected by epitope effects, while another third were confirmed by MS proteomics to be consistent with the hypothesis that genetic variants induce changes in protein expression. The present study demonstrates the complementarity of the different proteomics approaches and reports pQTLs not accessible to affinity proteomics, suggesting that many more pQTLs remain to be discovered using MS-based platforms. Graphical AbstractSummarizing the approach taken to identify potential epitope effects. O_FIG O_LINKSMALLFIG WIDTH=166 HEIGHT=200 SRC="FIGDIR/small/596028v1_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@34d11aorg.highwire.dtl.DTLVardef@18c0211org.highwire.dtl.DTLVardef@dbb003org.highwire.dtl.DTLVardef@1009fa7_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2023

A meta-analysis of immune cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes

AbstractO_ST_ABSBackgroundC_ST_ABSChanges in cell-type composition of complex tissues are associated with a wide range of diseases, environmental risk factors and may be causally implicated in disease development and progression. However, these shifts in cell-type fractions are often of a low magnitude, or involve similar cell-subtypes, making their reliable identification challenging. DNA methylation profiling in a tissue like blood is a promising approach to discover shifts in cell-type abundance, yet studies have only been performed at a relatively low cellular resolution and in isolation, limiting their power to detect these shifts in tissue composition. MethodsHere we derive a DNA methylation reference matrix for 12 immune cell-types in human blood and extensively validate it with flow-cytometric count data and in whole-genome bisulfite sequencing data of sorted cells. Using this reference matrix and Stouffers method, we perform a meta-analysis encompassing 25,629 blood samples from 22 different cohorts, to comprehensively map associations between the 12 immune-cell fractions and common phenotypes, including health outcomes. ResultsOur meta-analysis reveals many associations with age, sex, smoking and obesity, many of which we validate with single-cell RNA-sequencing. We discover that T-regulatory and naive T-cell subsets are higher in women compared to men, whilst the reverse is true for monocyte, natural killer, basophil and eosinophil fractions. In a large subset encompassing 5000 individuals we find associations with stress, exercise, sleep and health outcomes, revealing that naive T-cell and B-cell fractions are associated with a reduced risk of all-cause mortality independently of age, sex, race, smoking, obesity and alcohol consumption. We find that decreased natural killer cell counts are associated with smoking, obesity and stress levels, whilst an increased count correlates with exercise, sleep and a reduced risk of all-cause mortality. ConclusionsThis work derives and extensively validates a high resolution DNAm reference matrix for blood, and uses it to generate a comprehensive map of associations between immune cell fractions and common phenotypes, including health outcomes. AvailabilityThe 12 immune cell-type DNAm reference matrices for Illumina 850k and 450k beadarrays alongside tools for cell-type fraction estimation are freely available from our EpiDISH Bioconductor R-package http://www.bioconductor.org/packages/devel/bioc/html/EpiDISH.html

bioinformatics↗