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PubMed2026

Integrative TWAS and multi-omics analyses prioritize HSPE1 as a candidate risk gene for bipolar disorder with immune cell-specific regulatory evidence.

BACKGROUND: Bipolar disorder (BD) is a severe psychiatric disorder associated with substantial disability. Although genome-wide association studies have identified multiple BD-associated loci, the underlying genes and mechanisms remain incompletely understood. METHODS: We integrated a European-ancestry BD genome-wide association dataset with cross-tissue and tissue-specific transcriptome-wide association studies (TWAS) and complementary gene-based analysis. Candidate genes were further evaluated using differential expression analysis, consensus clustering, immune infiltration analysis, machine learning, summary-data-based Mendelian randomization, Mendelian randomization using single-cell expression quantitative trait locus data, single-nucleus transcriptomics, phenome-wide association analysis, and virtual screening. RESULTS: The integrative analyses prioritized 37 candidate genes. Peripheral-blood differential-expression analysis identified 14 genes that remained significant after FDR correction, and their expression profiles separated BD samples into two expression-defined clusters. Machine-learning analysis selected UNC50, LMAN2L, LYG2, HSPE1, and KANSL3 for an exploratory classification nomogram. SMR associated genetically predicted higher HSPE1 expression with increased BD risk in two blood eQTL datasets. Cell-type-specific analyses indicated HSPE1-related associations in T-cell and natural killer cell subsets, while single-nucleus analysis descriptively showed higher HSPE1 expression in medial thalamic T cells from BD samples. PheWAS identified no genome-wide significant associations for HSPE1, whereas virtual screening identified candidate compounds with favorable predicted docking scores against the HSPE1 structure. CONCLUSION: This integrative multi-omics study identified HSPE1 as a candidate BD risk gene with immune-cell-related regulatory evidence, providing insight into BD pathogenesis and supporting functional validation.

Humans↗

PubMed2026

From stress signaling to yield stability: physiological and molecular mechanisms of wheat resilience to heat and drought stress.

Wheat resilience depends on coordinated signaling, reproductive protection, and source-sink regulation, providing a framework to breed robust trait combinations that stabilize yield under combined heat and drought. Climate change is increasing the frequency and severity of heat and drought events, posing a major threat to wheat productivity, yield stability, and food security. Because these stresses often coincide in the field, their combined effects can impair growth, reproductive development, grain filling, and final yield more severely than either stress alone. Wheat resilience under such conditions depends on coordinated physiological adjustment and molecular regulation that sustain cellular homeostasis, protect reproductive tissues, and preserve yield-related traits. This review synthesizes current knowledge on the physiological and molecular bases of wheat resilience to heat and drought, with emphasis on their combined effects. We discuss major physiological responses, including photosynthetic adjustment, stomatal regulation, canopy cooling, osmotic balance, antioxidant defense, membrane stability, and source-sink coordination. We also examine key regulatory pathways involved in stress perception and adaptation, including calcium and reactive oxygen species signaling, mitogen-activated protein kinase cascades, phytohormonal crosstalk, transcriptional regulation, heat shock proteins, late embryogenesis abundant proteins, and osmoprotective and redox-associated pathways. In addition, we highlight the growing contribution of transcriptomics, proteomics, metabolomics, and phenomics to the identification of candidate genes, biomarkers, and adaptive traits. Finally, we consider how mechanistic insights can be translated into wheat improvement through molecular markers, genomic selection, gene editing, and climate-realistic phenotyping. An integrated understanding of stress signaling and adaptive trait deployment will be essential for developing wheat cultivars with improved resilience and yield stability under future climates.

Triticum↗

PubMed2026

Holistic approaches for improvement of maize resistance against lodging stress: current status and future perspective.

Lodging is a major constraint in maize production, causing significant yield losses, reduced grain quality, and harvesting inefficiencies, thereby posing a serious challenge to global food security and climate-resilient agriculture. This review synthesizes current knowledge on the genetic, physiological, and agronomic determinants of maize lodging resistance and evaluates holistic strategies for improving tolerance to lodging stress. Recent advances in quantitative trait locus (QTL) mapping, genome-wide association studies (GWAS), functional gene characterization, genome editing, high-throughput phenotyping, and precision agronomy have provided powerful tools to enhance stalk biomechanics, root anchorage, and adaptive plant architecture. Integrating genomic discovery with advanced phenomics and optimized agronomic management offers a scalable framework for accelerating the development of high-yielding, lodging-resilient maize cultivars. However, critical gaps remain in understanding the genetic coordination between stalk strength and root system architecture, integrating multi-omics approaches to unravel regulatory networks, validating genome-editing interventions across diverse agro-ecologies, and developing environment-responsive predictive breeding models and cost-effective phenotyping tools, particularly for stress-prone regions. Addressing these challenges through coordinated multi-environment trials and integrative molecular-agronomic strategies will facilitate the translation of genomic discoveries into climate-resilient, high-performing maize cultivars. By consolidating molecular insights with applied breeding and management practices, this review provides a comprehensive framework that guides researchers in designing genome-informed and field-validated approaches to improve maize resistance to lodging stress and support sustainable crop production systems.

Zea mays↗

PubMed2026

Genetic Evidence That Stroke Causally Increases Circulating PDGFB Levels: a Two-Sample Mendelian Randomization Study.

Platelet-derived growth factor subunit B (PDGFB) is a key regulator of vascular remodeling, angiogenesis, and blood-brain barrier integrity. Although elevated PDGFB levels have been reported after ischemic injury, whether stroke liability itself causally influences circulating PDGFB levels remains unclear. We performed a two-sample Mendelian randomization (MR) analysis to assess the causal effects of genetically predicted all stroke, ischemic stroke, and cardioembolic stroke on plasma PDGFB concentrations. Genetic instruments were obtained from large-scale GIGASTROKE genome-wide association studies, and outcome data were derived from a proteomics GWAS. Instruments were then filtered by removing variants associated with established cardiovascular risk factors in a phenome-wide screen and outliers identified by RadialMR. The inverse variance-weighted (IVW) method was used as the primary analysis, complemented by weighted median, weighted mode, and MR-Egger approaches. Sensitivity analyses included Cochran's Q statistics, MR-Egger intercept tests, single-SNP analyses, leave-one-out analyses, and MR-PRESSO. IVW analysis demonstrated a significant positive causal association between genetic liability to all stroke and plasma PDGFB levels (β = 0.209, SE = 0.062, 95% CI 0.088 to 0.331, p = 7.3 × 10-4). A similar association was observed for ischemic stroke (β = 0.155, SE = 0.059, 95% CI 0.039 to 0.270, p = 0.009), with directionally consistent results across sensitivity analyses. MR-Egger regression for ischemic stroke initially suggested pleiotropy.After removal of a radial-MR outlier (rs2289252), the intercept was attenuated and no longer statistically significant (- 0.0190, p = 0.282). In contrast, no evidence of a causal association was found between cardioembolic stroke liability and plasma PDGFB levels across all MR methods (β = - 0.078, SE = 0.087, 95% CI - 0.248 to 0.092, p = 0.368). These findings provide genetic evidence that liability to stroke, particularly ischemic stroke, is causally associated with increased circulating PDGFB levels, whereas cardioembolic stroke does not show such an effect. This suggests that elevated PDGFB reflects vascular responses specific to ischemic stroke rather than a general consequence of all stroke subtypes.

Humans↗

PubMed2025

Unveiling the mechanism of micro-and-nano plastic phytotoxicity on terrestrial plants: A comprehensive review of omics approaches.

Micro-and-nano plastics (MNPs) are pervasive in terrestrial ecosystems and represent an increasing threat to plant health; however, the mechanisms underlying their phytotoxicity remain inadequately understood. MNPs can infiltrate plants through roots or leaves, causing a range of toxic effects, including inhibiting water and nutrient uptake, reducing seed germination rates, and impeding photosynthesis, resulting in oxidative damage within the plant system. The effects of MNPs are complex and influenced by various factors including size, shape, functional groups, and concentration. Recent advancements in omics technologies such as proteomics, metabolomics, transcriptomics, and microbiomics, coupled with emerging technologies like 4D omics, phenomics, spatial transcriptomics, and single-cell omics, offer unprecedented insight into the physiological, molecular, and cellular responses of terrestrial plants to MNPs exposure. This literature review synthesizes current findings regarding MNPs-induced phytotoxicity, emphasizing alterations in gene expression, protein synthesis, metabolic pathways, and physiological disruptions as revealed through omics analyses. We summarize how MNPs interact with plant cellular structures, disrupt metabolic processes, and induce oxidative stress, ultimately affecting plant growth and productivity. Furthermore, we have identified critical knowledge gaps and proposed future research directions, highlighting the necessity for integrative omics studies to elucidate the complex pathways of MNPs toxicity in terrestrial plants. In conclusion, this review underscores the potential of omics approaches to elucidate the mechanisms of MNPs-phytotoxicity and to develop strategies for mitigating the environmental impact of MNPs on plant health.

Plants↗

PubMed2026

Genetic evidence for a causal relationship between melatonin metabolism and depression.

To investigate the causal relevance of melatonin metabolism, which provides the biological basis for circulating melatonin levels, to specific depression symptom subtypes, we performed a targeted systematic review of melatonin metabolism pathways in the human brain and liver. Using two-sample Mendelian randomization (MR), we assessed the causal effects of metabolism pathways and/or individual genes on major depressive disorder (MDD) and nine symptom subtypes derived from Patient Health Questionnaire-9 (PHQ-9). Instrumental variables (IVs) were expression quantitative trait loci (eQTL) for eight individual genes, one synthesis route, and three degradation routes. Results were assessed using Bayesian colocalization and phenome-wide association analyses. At the pathway-level, the genetically proxied synthesis-route signal was associated with PHQ-9 Assessment 5 (PHQ9A5, OR: 0.89, 95% CI: 0.85-0.93), but sensitivity analyses suggested this association was primarily driven by TPH1 and may reflect serotonin-related biology. In contrast, higher brain melatonin degradation raised the risk of both PHQ9A1 (OR: 1.03, 95% CI: 1.02-1.04) and PHQ9A7 (OR: 1.03, 95% CI: 1.02-1.03). Within degradation, up-regulation of the kynurenine sub-pathway increased the odds of PHQ9A3 (OR: 1.05, 95% CI: 1.02-1.07), PHQ9A4 (OR = 1.04, 95% CI: 1.02-1.06) and PHQ9A7 (OR: 1.05, 95% CI: 1.02-1.07). Gene-level analyses were largely concordant, except for SULT1A1, whose higher expression was genetically protective for PHQ9A3 but risk-increased for PHQ9A1 and PHQ9A4. Overall, these results demonstrate that melatonin metabolism exerts symptom-specific and pathway-specific causal effects on depression. A stratified view of melatonin's role may help optimize the application of exogenous melatonin supplementation.

Melatonin↗

PubMed2025

Potential therapeutic targets for ovarian hyperstimulation syndrome revealed by proteome-wide mendelian randomization and colocalization analysis.

Ovarian hyperstimulation syndrome (OHSS) is a severe complication associated with assisted reproductive technologies, characterized by metabolic, immune and vascular disorders. Understanding the molecular mechanisms underlying OHSS could reveal potential therapeutic targets and improve patient outcomes. In this study, We aimed to utilize proteome-wide Mendelian randomization (MR) and colocalization analysis to identify plasma proteins associated with OHSS and evaluate their potential as therapeutic targets through druggability assessment. We employed proteome-wide MR analysis summary data-based Mendelian randomization (SMR) analysis and phenome-wide association study (PheWAS) analysis to establish causal relationships between plasma proteins and OHSS. Colocalization analysis confirmed overlaps between proteins and genetic signals associated with OHSS. Pathway and network analyses were conducted to explore biological functions and protein interactions, while drug-target databases were queried for potential therapeutic interventions. Our results showed that 4 key proteins, including Suprabasin (SBSN), SLAMF4 (CD244), Enolase 3 (ENO3) and Thioredoxin domain-containing protein 12 (TXNDC12) were identified as significant contributors to OHSS. Pathway enrichment and interaction analyses further supported their involvement in metabolic, immune and structural pathways related to OHSS. Drug availability for colocalized proteins reveled potential drug targets for ENO3 (2-deoxy-D-glucose), CD244 (lenalidomide) and TXNDC12 (Auranofin), while no potential drug targets were identified for SBSN. Over all, our study identified15 plasma proteins, including SBSN, CD244, ENO3, and TXNDC12, as key contributors to the risk of OHSS through MR and colocalization analysis. These proteins were involved in metabolic regulation, immune response and antioxidant pathways, highlighting potential therapeutic targets and suggesting new directions for treatment strategies.

Humans↗

PubMed2024

A Proteogenomic Pipeline for the Analysis of Protein Biosynthesis Errors in the Human Pathogen Candida albicans.

Candida albicans is a diploid pathogen known for its ability to live as a commensal fungus in healthy individuals but causing both superficial infections and disseminated candidiasis in immunocompromised patients where it is associated with high morbidity and mortality. Its success in colonizing the human host is attributed to a wide range of virulence traits that modulate interactions between the host and the pathogen, such as optimal growth rate at 37 °C, the ability to switch between yeast and hyphal forms, and a remarkable genomic and phenotypic plasticity. A fascinating aspect of its biology is a prominent heterogeneous proteome that arises from frequent genomic rearrangements, high allelic variation, and high levels of amino acid misincorporations in proteins. This leads to increased morphological and physiological phenotypic diversity of high adaptive potential, but the scope of such protein mistranslation is poorly understood due to technical difficulties in detecting and quantifying amino acid misincorporation events in complex protein samples. We have developed and optimized mass spectrometry and bioinformatics pipelines capable of identifying rare amino acid misincorporation events at the proteome level. We have also analyzed the proteomic profile of an engineered C. albicans strain that exhibits high level of leucine misincorporation at protein CUG sites and employed an in vivo quantitative gain-of-function fluorescence reporter system to validate our LC-MS/MS data. C. albicans misincorporates amino acids above the background level at protein sites of diverse codons, particularly at CUG, confirming our previous data on the quantification of leucine incorporation at single CUG sites of recombinant reporter proteins, but increasing misincorporation of Leucine at these sites does not alter the translational fidelity of the other codons. These findings indicate that the C. albicans statistical proteome exceeds prior estimates, suggesting that its highly plastic phenome may also be modulated by environmental factors due to translational ambiguity.

Candida albicans↗

PubMed2004

A genotoxic screen: rapid analysis of cellular dose-response to a wide range of agents that either damage DNA or alter genome maintenance pathways.

SNP analysis has come to the forefront of genomics since the mouse and human genomes have been sequenced. High throughput functional screens are necessary to evaluate these sequence databases. Described here is a genotoxic screen: a rapid method that determines the cellular dose-response to a wide range of agents that either damage DNA or alter basic cellular pathways important for maintaining genomic integrity. Importantly, a single person utilizing standard tissue culture equipment may perform these assays composed of 20 agents that attack genomic integrity or maintenance at many different levels. Thus, a small lab may perform this screen to determine the integrity of a wide range of DNA repair, chromatin metabolism, and response pathways without the limitations of investigator bias. A genotoxic screen will be useful when analyzing cells with either known genetic alterations (generated directly by the investigator or derived from individuals with known mutations) or unknown genetic alterations (cells with spontaneous mutations such as cancer-derived cells). Screening many genotoxins at one time will aid in determining the biological importance of these altered genes. Here we show the dose-response curves of mouse embryonic stem (ES) cells and HeLa cells exposed to 20 genotoxic agents. ES cells were chosen since they are amenable to genetic alteration by the investigator. HeLa cells were chosen since they were derived from cancer and are commonly used. Comparing the dose-response curves of these two cell lines show their relative sensitivity to these agents and helps define their genotoxic profile. As a part of phenomics, a large genotoxic profile database for cancer-derived cells, when integrated with other databases such as expression profiles and comparative genomic hybridization, may aid in maximizing the effectiveness of developing anti-cancer protocols.

Alkylating Agents↗

PubMed2005

A three-dimensional digital atlas database of the adult C57BL/6J mouse brain by magnetic resonance microscopy.

A comprehensive three-dimensional digital atlas database of the C57BL/6J mouse brain was developed based on magnetic resonance microscopy images acquired on a 17.6-T superconducting magnet. By using both manual tracing and an atlas-based semi-automatic segmentation approach, T2-weighted magnetic resonance microscopy images of 10 adult male formalin-fixed, excised C57BL/6J mouse brains were segmented into 20 anatomical structures. These structures included the neocortex, hippocampus, amygdala, olfactory bulbs, basal forebrain and septum, caudate-putamen, globus pallidus, thalamus, hypothalamus, central gray, superior colliculi, inferior colliculi, the rest of midbrain, cerebellum, brainstem, corpus callosum/external capsule, internal capsule, anterior commissure, fimbria, and ventricles. The segmentation data were formatted and stored into a database containing three different atlas types: 10 single-specimen brain atlases, an average brain atlas and a probabilistic atlas. Additionally, quantitative group information, such as variations in structural volume, surface area, magnetic resonance microscopy image intensity and local geometry, were computed and stored as an integral part of the database. The database augments ongoing efforts with other high priority strains as defined by the Mouse Phenome Database focused on providing a quantitative framework for accurate mapping of functional, genetic and protein expression patterns acquired by a myriad of technologies and imaging modalities.

Anatomy, Artistic↗

PubMed2026

Mapping the Immune cell-specific gene regulatory network in bipolar disorder: A framework from scTWMR to exploratory drug-target annotation.

BACKGROUND: Although the involvement of the immune system in the genetic susceptibility of bipolar disorder (BD) is widely acknowledged, the causal relationship between gene expression in specific immune cell subtypes and BD requires systematic elucidation. METHODS: We implemented an analytical framework integrating single-cell transcriptome-wide Mendelian randomization (scTWMR) with colocalization analysis. This approach utilized cis-expression quantitative trait loci (cis-eQTLs) derived from 14 distinct immune cell types as instrumental variables to interrogate BD genome-wide association study (GWAS) summary statistics (comprising 41,917 cases and 371,549 controls). Subsequent investigations encompassed functional enrichment analysis, protein-protein interaction (PPI) network construction, phenome-wide association study (PheWAS), and performed an exploratory drug-target annotation. RESULTS: Our analysis identified 33 gene-immune cell associations. Colocalization analysis provided robust evidence (PPH4 > 90%) for shared causal variants implicating the MAD1L1, APOM, and NFKBIL1 loci. Significantly enriched biological pathways included cell cycle regulation, circadian rhythm entrainment, and neuroinflammation. The PPI network revealed a core regulatory module centered on histone-encoding and immune-related genes. Exploratory drug-target annotation nominated compounds for further investigation for compounds targeting APOM, TMEM258, and NFKBIL1. CONCLUSION: This study systematically delineates a genetically supported regulatory network of immune cell-specific gene expression in BD, predominantly implicating CD8⁺ effector T cells, plasma cells, and B cells. The findings corroborate established pathological pathways while uncovering novel cell type-specific therapeutic targets, thereby providing a genetic framework for prioritizing candidate targets for future investigation.

Bipolar disorder↗

PubMed2007

What can microbial genetics teach sociobiology?

Progress in our understanding of sociobiology has occurred with little knowledge of the genetic mechanisms that underlie social traits. However, several recent studies have described microbial genes that affect social traits, thereby bringing genetics to sociobiology. A key finding is that simple genetic changes can have marked social consequences, and mutations that affect cheating and recognition behaviors have been discovered. The study of these mutants confirms a central theoretical prediction of social evolution: that genetic relatedness promotes cooperation. Microbial genetics also provides an important new perspective: that the genome-to-phenome mapping of social organisms might be organized to constrain the evolution of social cheaters. This constraint can occur both through pleiotropic genes that link cheating to a personal cost and through the existence of phoenix genes, which rescue cooperative systems from selfish and destructive strategies. These new insights show the power of studying microorganisms to improve our understanding of the evolution of cooperation.

Animals↗

PubMed2006

Heterosis: revisiting the magic.

Heterosis results in the phenotypic superiority of a hybrid over its parents with respect to traits such as growth rate, reproductive success and yield. This hybrid vigor is determined by non-mutually exclusive mechanisms, including dominance complementation, overdominance and epistasis. Heterotic genes responsible for elevating crop yields are now being sought using genomics, particularly transcriptomics, but with contradictory results. Because heterosis is an environmentally modified quantitative phenotype, genomic analyses alone will not suffice. Future research should focus on integrating genomic tools in a framework of comprehensive quantitative trait locus (QTL)-based phenotyping, followed by map-based cloning. This 'phenomics' approach should identify loci controlling heterotic phenotypes, and improve understanding of the role of heterosis in evolution and the domestication of crop plants.

Animals↗

PubMed2024

Exome-wide evidence of compound heterozygous effects across common phenotypes in the UK Biobank.

The phenotypic impact of compound heterozygous (CH) variation has not been investigated at the population scale. We phased rare variants (MAF ∼0.001%) in the UK Biobank (UKBB) exome-sequencing data to characterize recessive effects in 175,587 individuals across 311 common diseases. A total of 6.5% of individuals carry putatively damaging CH variants, 90% of which are only identifiable upon phasing rare variants (MAF < 0.38%). We identify six recessive gene-trait associations (p < 1.68 × 10-7) after accounting for relatedness, polygenicity, nearby common variants, and rare variant burden. Of these, just one is discovered when considering homozygosity alone. Using longitudinal health records, we additionally identify and replicate a novel association between bi-allelic variation in ATP2C2 and an earlier age at onset of chronic obstructive pulmonary disease (COPD) (p < 3.58 × 10-8). Genetic phase contributes to disease risk for gene-trait pairs: ATP2C2-COPD (p = 0.000238), FLG-asthma (p = 0.00205), and USH2A-visual impairment (p = 0.0084). We demonstrate the power of phasing large-scale genetic cohorts to discover phenome-wide consequences of compound heterozygosity.

Humans↗

PubMed2025

The extracellular vesicle transcriptome provides tissue-specific functional genomic annotation relevant to disease susceptibility in obesity.

We characterized circulating extracellular vesicles (EVs) in obese and lean humans, identifying transcriptional cargo differentially expressed in obesity (277 unique genes; false discovery rate < 10%). Since circulating EVs may have broad origin, we compared this obesity EV transcriptome with expression from human visceral-adipose-tissue-derived EVs from freshly collected and cultured biopsies from the same obese individuals, observing high concordance. Using a comprehensive set of adipose-specific epigenomic and chromatin conformation assays, we found that the differentially expressed transcripts from the EVs were those regulated in adipose by body mass index-associated SNPs (p < 5 × 10-8) from a large-scale genome-wide association study (GWAS). Using a phenome-wide association study of the regulatory SNPs for the EV-derived transcripts, we identified a substantial enrichment for inflammatory phenotypes, including type 2 diabetes. Collectively, these findings represent the convergence of the GWAS (genetics), epigenomics (transcript regulation), and EV (liquid biopsy) fields, enabling powerful future genomic studies of complex diseases.

Humans↗

PubMed2026

Inherited Predisposition to Increased Systemic Inflammation Predicts a Broad Class of Disease Phenotypes.

Chronic, low-grade systemic inflammation is a polygenic trait captured with the INFLA-score, a composite of C-reactive protein, platelet count, leukocyte count, and granulocyte-to-lymphocyte ratio. We derived a polygenic risk score from the INFLA-score (iPRS) in a multi-ancestry population from the UK Biobank (n=421,368), then evaluated and used it in a phenome-wide association study among participants in the All of Us Research Program (AoU). The multi-ancestry iPRS was tested for association with the INFLA-score in AoU (N=4,833 with biomarker data) via linear regression, adjusting for age, sex, and genetically-determined principal components (PCs) and with 2,821 phecodeX-defined phenotypes in AoU (N=265,068) via logistic regression, adjusting for sex, age, EHR length, race, ethnicity and PCs. The iPRS predicted the INFLA-score (R-squared=0.026, beta=0.980, p<2x10-16) and was associated with 47 phenotypes (Bonferroni-corrected p<0.05). The strongest associations were with blood-related phenotypes: elevated white blood cell count (OR=1.19, p=3.85x10-66), thrombocytopenia (OR=0.86, p=5.70x10-44), platelet defects (OR=0.86, p=2.47x10-43), neutropenia (OR= 0.86, p=5.52x10-18), myeloproliferative disorder (OR= 1.2, p=2.77x10-15). Others included celiac disease (OR=0.713, p=2.98x10-46), ankylosing spondylitis (OR=1.4, p=1.33 x 10-17), hypertension (OR=1.04, p=4.56x10-15), rheumatoid arthritis (OR=1.09, p=1.02x10-13), hematuria (OR=1.05, p=1.96x10-10). Removing major-histocompatibility-complex SNPs abolished associations with known autoimmune diseases, while all other associations remained. We replicated 17 (42.5%) of 40 significant phenotypes available in the Vanderbilt University Medical Center's BioVU. Our findings demonstrate that systemic inflammation can be predicted using the iPRS across multiple ancestries, and the iPRS is associated with numerous clinical endpoints. This multi-ancestry iPRS may have future utility in stratifying risk for inflammation-driven conditions across diverse populations.

Journal Article↗

PubMed2003

Survey of 21 inbred mouse strains in two laboratories reveals that BTBR T/+ tf/tf has severely reduced hippocampal commissure and absent corpus callosum.

A morphometric survey of brain size and forebrain commissures of 21 inbred mouse strains from the Jackson Laboratory was done with animals tested in two laboratories as part of the Mouse Phenome Project. Strain BTBR T/+ tf/tf was found to have 100% total absence of the corpus callosum as well as severe reduction of the hippocampal commissure in almost every animal, the most severe commissure defect observed to date in any commercially available mouse strain. The strain 129S1/SvImJ had a milder defect with incomplete penetrance. Crosses of BTBR mice with inbred strains BALB/cWah1, 129P1/ReJ, and the recombinant strain 9XCA/Wah having a severe commissure defect supported a two-locus model of the genetic defect in these strains. Brain size varied greatly among strains but for any one strain was almost identical in mice housed for 5 weeks in the two laboratories. Sex differences in brain weight and forebrain commissure sizes were not statistically significant.

Agenesis of Corpus Callosum↗

PubMed2002

Rational drug discovery: what can we learn from regulatory networks?

To enable the list of genes and proteins contained within genomic databases to be useful for drug discovery, we need to understand how the genome maps into the phenome. An essential, but not explicitly listed ingredient of the genome is the regulatory interactions between genes and proteins that form a genome-wide network. How can the concept of regulatory networks increase our understanding of living systems? Networks are more than just static "wiring diagrams". Gene interactions impose dynamic constraints, which, although obvious in emergent phenotypic properties, are not captured by traditional one gene-one trait approaches. Understanding the nature of these constraints in gene-activation state space will pave the way to a holistic yet formal and genomics-based approach to rational drug development.

Computational Biology↗