Biomedical subjects

Eric E Schadt

Publications and source records attributed to Eric E Schadt.

6 recordsLinked to original sources

PubMed2026

Proteogenomic analysis of pediatric and AYA high-grade glioma reveals age-dependent biology, female-male differences, and kinase targets.

High-grade gliomas (HGGs) in children and adolescents and young adults (AYA) exhibit distinct biology across the neurodevelopmental spectrum. To dissect tumor-intrinsic molecular characteristics independent of developmental variation, we perform comprehensive proteogenomic analyses of tumors from 112 HGG patients aged 0-40 years. Our multi-omics analysis identifies two AYA subgroups-adolescents (aged 15-26 years) and young adults (aged 26-40 years)-with distinct molecular profiles and survival outcomes. Tumor-normal comparisons and survival modeling highlight roles of oxidative phosphorylation and neuronal system biology in glioma progression. Causal network analysis and cell line studies provide a rationale for personalized therapies targeting candidate kinases, such as CDK8. Survival modeling, clustering, and immune-landscape analyses identify proteins, post-translational modifications, and immune signatures linked to outcomes and reveal clinically relevant differences between male and female patients.

adolescent and young adult glioma↗

PubMed2026

Plasma proteins are integral to cross-tissue gene regulatory networks implicated in cardiometabolic disorders and coronary artery disease.

The plasma proteome has demonstrated promise for identifying diagnostic markers for cardiometabolic disorders (CMDs) and coronary artery disease (CAD). However, identifying the organ of origin for these biomarkers is critical for establishing biological relevance. We performed a multi-omic integrative analysis across multiple tissues from the STARNET study by profiling 974 plasma proteins in 532 CAD patients, integrating RNA sequencing (RNA-seq) data from the arterial wall, major metabolic organs, and blood. We identified 144 cis-protein quantitative trait loci in plasma, colocalizing with tissue cis-expression quantitative trait loci. Additionally, by mapping tissue mRNA "seed genes," we traced 262 plasma proteins to their source organs, primarily the liver. Crucially, we found that 851 plasma proteins are associated with the activity of cross-tissue gene regulatory networks (GRNs), including GRNs implicated in CMD and CAD development. Our findings demonstrate that plasma proteins are integral components of GRNs, with potential for developing reliable diagnostics and precise therapeutic targets. A record of this paper's transparent peer review process is included in the supplemental information.

cardiometabolic disorders↗

PubMed2026

Elective genomic sequencing for adults in research, clinical and commercial contexts.

PURPOSE: Elective genomic sequencing (EGS) returns monogenic disease findings in multiple genes, including potentially novel variants, and may also provide participants with carrier status, pharmacogenomic and other health-related information. The PeopleSeq Study assessed participants' motivations for and concerns about EGS and the associated clinical and psychosocial outcomes across diverse EGS providers. METHODS: We administered a shared questionnaire to participants who chose to undergo EGS via 18 academic, clinical, or commercial EGS platforms. RESULTS: We enrolled 1575 participants, of whom 1147 (72.8%) completed a questionnaire after receiving their EGS results. A majority (60.3%) of the participants who completed a post-result questionnaire self-reported receiving results they assessed as important, including negative findings, and 75.9% reported a form of health-related utility. Among a subset (19.4%) who shared their EGS reports, 16.6% (37 of n = 223) received a monogenic finding and self-reported results deemed "important" were consistent with EGS reports. Most participants (74.1%) discussed their results with their family, but fewer discussed their results with a healthcare provider other than the site team (41.7%) or had one or more medical visits as a direct result of their EGS testing (23.1%). Participants expressed diverse motivations for EGS, with 91.4% expressing interest in their personal disease risk and 54% who expressed quasi-indication-based motivations related to family medical history. Individuals motivated by family history reported important results at a significantly higher rate. CONCLUSIONS: Early adopters of EGS are motivated by general interest in their health as well as quasi-indication-based considerations such as family history. A majority of participants learned results they considered medically important, but a much smaller segment engaged healthcare providers with their results.

Genomic testing↗

PubMed2003

Microarray standard data set and figures of merit for comparing data processing methods and experiment designs.

MOTIVATION: There is a very large and growing level of effort toward improving the platforms, experiment designs, and data analysis methods for microarray expression profiling. Along with a growing richness in the approaches there is a growing confusion among most scientists as to how to make objective comparisons and choices between them for different applications. There is a need for a standard framework for the microarray community to compare and improve analytical and statistical methods. RESULTS: We report on a microarray data set comprising 204 in-situ synthesized oligonucleotide arrays, each hybridized with two-color cDNA samples derived from 20 different human tissues and cell lines. Design of the approximately 24 000 60mer oligonucleotides that report approximately 2500 known genes on the arrays, and design of the hybridization experiments, were carried out in a way that supports the performance assessment of alternative data processing approaches and of alternative experiment and array designs. We also propose standard figures of merit for success in detecting individual differential expression changes or expression levels, and for detecting similarities and differences in expression patterns across genes and experiments. We expect this data set and the proposed figures of merit will provide a standard framework for much of the microarray community to compare and improve many analytical and statistical methods relevant to microarray data analysis, including image processing, normalization, error modeling, combining of multiple reporters per gene, use of replicate experiments, and sample referencing schemes in measurements based on expression change. AVAILABILITY/SUPPLEMENTARY INFORMATION: Expression data and supplementary information are available at http://www.rii.com/publications/2003/HE_SDS.htm

Base Sequence↗

PubMed2003

Genetics of gene expression surveyed in maize, mouse and man.

Treating messenger RNA transcript abundances as quantitative traits and mapping gene expression quantitative trait loci for these traits has been pursued in gene-specific ways. Transcript abundances often serve as a surrogate for classical quantitative traits in that the levels of expression are significantly correlated with the classical traits across members of a segregating population. The correlation structure between transcript abundances and classical traits has been used to identify susceptibility loci for complex diseases such as diabetes and allergic asthma. One study recently completed the first comprehensive dissection of transcriptional regulation in budding yeast, giving a detailed glimpse of a genome-wide survey of the genetics of gene expression. Unlike classical quantitative traits, which often represent gross clinical measurements that may be far removed from the biological processes giving rise to them, the genetic linkages associated with transcript abundance affords a closer look at cellular biochemical processes. Here we describe comprehensive genetic screens of mouse, plant and human transcriptomes by considering gene expression values as quantitative traits. We identify a gene expression pattern strongly associated with obesity in a murine cross, and observe two distinct obesity subtypes. Furthermore, we find that these obesity subtypes are under the control of different loci.

Animals↗

PubMed2002

Applications of codon and rate variation models in molecular phylogeny.

The current article illustrates the practical advantages of some new models and statistical algorithms for codon substitution and spatial rate variation in molecular phylogeny. Our companion paper in this issue discusses at length the mathematical properties of these models for nucleotide and codon substitution, for site-to-site and branch-to-branch heterogeneity in rates of evolution, and for spatial correlation in the assignment of rates. In this study we summarize the theoretical background and apply the models and algorithms to data on beta-globin, the complete HIV genome, and the mitochondrial genome. Our complex but realistic models enhance biological interpretation of sequence data and show substantial improvements in model fit over existing models. All the new statistical algorithms applied are incorporated in our phylogeny software LINNAEUS, which is tuned for performance and modeling flexibility.

Animals↗