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At least 19 recordsLinked to original sources

PubMed2026

FM-GPT: Bayesian fine mapping for phenome-wide transcriptome-wide association studies.

Transcriptome-wide association studies (TWAS) integrate genome wide association studies with expression quantitative trait locus reference panels to identify genes associated with traits of interest. However, linkage disequilibrium and correlated gene expression can induce spurious TWAS signals, motivating fine mapping methods to prioritize putatively causal genes within associated loci. The rapid growth of large-scale phenomic resources (e.g. electronic health records (EHRs)) has shifted genetic studies from single-trait analyses to phenome-wide investigations that jointly evaluate many closely related phenotypes. We introduce FM-GPT (Fine-mapping of causal Genes for Phenome-wide Transcriptome-wide association studies), a novel Bayesian fine mapping method for prioritizing causal genes across multiple correlated phenotypes with potentially mixed outcome types (e.g., binary, count or continuous) in phenome-wide TWAS. FM-GPT performs gene-guided dimension reduction of the phenotypes and reveals pleiotropic or phenotype-specific effects of the identified genes. In simulations, FM-GPT identified true causal genes more accurately than other fine mapping methods while controlling false positives. We applied FM-GPT to two applications using data from UK Biobank: a brain-wide genetic analysis of MRI data derived regional cortical thickness measures and a phenome-wide genetic analysis of clinical phenotypes derived from EHR data. FM-GPT greatly narrowed down the set size of putatively causal genes and identified: 1. genes with pleiotropic effects on regional cortical thickness across the cerebral cortex, including five genes BCAS3, LRRC37A, NOS2P3, ARL17B and UBB on chromosome 17 regulating neuronal morphology and cortical organization; and 2. genes that influence multiple medical conditions across the circulatory, metabolic, digestive, respiratory and genitourinary systems, revealing two major axes of variation among these conditions that point to a potential trade-off in gene regulation between immune and metabolic functions. These results highlight FM-GPT's power to disentangle complex gene-phenotype relationships in large-scale phenome-wide studies, uncovering shared biological mechanisms across diverse human traits and advancing translational and comorbidity research.

Bayesian fine mapping↗

PubMed2006

Cancer phenomics: RET and PTEN as illustrative models.

Cancer phenomics, the systematic acquisition and objective documentation of host and/or somatic cancer phenotypic data at many levels, is a young field compared with other molecular-based 'omics'. Two relatively advanced phenomic paradigms are associated with phosphatase and tensin homologue (PTEN) and rearranged during transfection (RET), genes that are associated with cancer predisposition syndromes in addition to developmental disorders. The phenomic characterization of PTEN and RET underscores the importance of incorporating robust phenomics into the host 'omic' profile, and shows that the evolution of phenomics will be crucial to the advancement of personalized medicine.

Evolution, Molecular↗

PubMed2007

Computational approaches to phenotyping: high-throughput phenomics.

The recent completion of the Human Genome Project has made possible a high-throughput "systems approach" for accelerating the elucidation of molecular underpinnings of human diseases, and subsequent derivation of molecular-based strategies to more effectively prevent, diagnose, and treat these diseases. Although altered phenotypes are among the most reliable manifestations of altered gene functions, research using systematic analysis of phenotype relationships to study human biology is still in its infancy. This article focuses on the emerging field of high-throughput phenotyping (HTP) phenomics research, which aims to capitalize on novel high-throughput computation and informatics technology developments to derive genomewide molecular networks of genotype-phenotype associations, or "phenomic associations." The HTP phenomics research field faces the challenge of technological research and development to generate novel tools in computation and informatics that will allow researchers to amass, access, integrate, organize, and manage phenotypic databases across species and enable genomewide analysis to associate phenotypic information with genomic data at different scales of biology. Key state-of-the-art technological advancements critical for HTP phenomics research are covered in this review. In particular, we highlight the power of computational approaches to conduct large-scale phenomics studies.

Computational Biology↗

PubMed2025

The Effect of Alcohol Intake on Brain White Matter Microstructural Integrity: A New Causal Inference Framework for Incomplete Phenomic Data.

Although substance use, such as alcohol intake, is known to be associated with cognitive decline during aging, its direct influence on the central nervous system remains incompletely understood. In this study, we investigate the influence of alcohol intake frequency on reduction of brain white matter microstructural integrity in the fornix, a brain region considered a promising marker of age-related microstructural degeneration, using a large UK Biobank (UKB) cohort with extensive phenomic data reflecting a comprehensive lifestyle profile. Two major challenges arise: (a) potentially nonlinear confounding effects from phenomic variables and (b) a limited proportion of participants with complete phenomic data. To address these challenges, we develop a novel ensemble learning framework tailored for robust causal inference and introduce a data integration step to incorporate information from UKB participants with incomplete phenomic data, improving estimation efficiency. Our analysis reveals that daily alcohol intake may significantly reduce fractional anisotropy, a neuroimaging-derived measure of white matter structural integrity, in the fornix and increase systolic and diastolic blood pressure levels. Moreover, extensive numerical studies demonstrate the superiority of our method over competing approaches in terms of estimation bias, while outcome regression-based estimators may be preferred when minimizing mean squared error is prioritized. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.

Brain aging↗

PubMed2004

After the genome--the phenome?

What next? The Human Genome Project signifies complexity rather than simplification in the relationship between genotype and phenotype. Genotypes are embedded in genomes. Individuality in phenotypes is embedded in components of the phenome (transcriptome, metabolome, proteome, etc.). The phenome, its layers, and its nodes, links and networks, require elucidation; there is a need for a Human Phenome Project (Freimer and Sabatti 2003). Biology has largely been a reductive science in the recent past; integrative biology lies ahead. Clinician-scientists (including human biochemical geneticists) will be recognized as key participants in the 'medical' Phenome Project as it reveals components of individuality, and their contributions, in simple or combinatorial fashion, to Mendelian and complex traits; better ways to treat 'genetic disease' will be by-products of the project. Although the Word is common to all, most men live as if each had a private wisdom of his own.Herakleitos

Genomics↗

PubMed2003

Human Phenome based on traditional Chinese medicine--a solution to congenital syndromology.

The occurrence of many congenital syndromes has long been an enigma. Clinically, the phenotype of any given genetic defect usually varies to some extent, whilst, pathogenetically, features within each syndrome are probably interconnected, albeit by largely unknown mechanisms. Through its unique theories such as the Jing-Mai (variously translated as the Channels, Vessels or Meridians), Zang-Fu (the Yin and Yang internal organs) and Wu-Xing (translated as the Five-Phase Correspondence or Five-Element theory), traditional Chinese medicine (TCM) seems to have comprehensively summarized the makeup of the human phenotypes. By combining the above TCM theories with modem medical knowledge, the intrinsic mechanisms between various aspects of the phenotypic makeup of the human individual, i.e. the Human Phenome, may be deduced. Analysis of congenital syndromes in light of the Human Phenome seems to suggest that various genetic defects may cause diseases in a similar fashion; i.e. primarily with structural abnormalities distributed along the four Jing-Mai connected with the Kidneys (midline defects) as well as "Marrow" aberrations (anomalies of hematology/immunology, endocrine, central nervous system and the bones). The derived Human Phenome may thereby enable a better understanding of such conditions and provide a model for the study of multigenic traits. On the other hand, blind spots of clinical observation and unknown aspects of human nature, e.g. circuits formed by the JingMai, symmetries of the Jing-Mai and Zang-Fu, and correspondences between body physiques, spiritual factors and the external world may also be deduced. The TCM-based Human Phenome may thereby offer a fresh view for genotype-phenotype correlations, insights into genedevelopment mechanisms, as well as potential directions for the development of new treatments.

Congenital Abnormalities↗

PubMed2026

Polygenic risk factors for comorbid diagnoses in individuals with substance use disorders: A phenome-wide survival analysis.

OBJECTIVE: Persons with substance use disorders (SUD) often suffer from additional comorbidities. Researchers have explored this overlap via phenome-wide association studies (PheWASs). However, PheWASs are largely cross-sectional, limiting our understanding of whether diagnoses predate the development of an SUD. We characterize whether polygenic scores (PGSs) are associated with time to comorbid diagnoses in electronic health records (EHR) after the first documented SUD diagnosis. METHODS: Using data from All of Us (N = 393,596), we explored: (1) whether social determinants of health (SDoHs) are associated with lifetime risk of SUD (N cases = 42,568) and (2) within a subset those with a diagnosed SUD and available genetic data SUD (N = 21,357), whether PGS for alcohol use disorders, cannabis use disorders, depression, externalizing, posttraumatic stress disorder, and schizophrenia were associated with subsequent diagnoses via a phenome-wide survival analysis. RESULTS: Multiple SDoHs were associated with lifetime SUD diagnosis, with annual household income having the largest overall associations (e.g. <$10 K annually vs $100 K-$150 K annually: OR = 4.18; 95% CI = 3.92, 4.45). There were 86 phenome-wide significant PGS associations with subsequent diagnoses across various bodily systems. PGSs for alcohol use disorders, posttraumatic stress disorder, and schizophrenia were each associated with time to their respective diagnoses. CONCLUSIONS: Social determinants, especially those related to income, have profound associations with lifetime SUD risk. Additionally, PGSs for psychiatric conditions are associated with multiple post-SUD diagnoses within those with a SUD, suggesting PGS may capture information beyond lifetime risk, including timing and severity of comorbidities related to SUD.

Humans↗

PubMed2000

The use of peptides in Diogenesis: a novel approach to drug discovery and phenomics.

The Diogenesis Process is an integrated drug discovery platform that allows target validation, partner identification, and the identification of small molecule drug candidates for protein:protein interactions. Diogenesis utilizes the well-established methods of peptide display, synthetic and recombinant peptide production, in vitro biochemical and cell-based testing to form a universal drug discovery engine with distinct advantages over competing protocols. The process creates a library of diverse peptides, and selects rare and unique binders that identify and simplify surface "hot spots" on protein targets through which target activity can be regulated. In many cases, these peptide "Surrogates" have the minimal sequence and structural information needed to induce a change in the biological activity of the target; in pharmacological terms, only after inducing agonism or antagonism. The use of Surrogates in hot spot identification also allows subdivision of rather large surface domains into smaller domains that alone, or in combination with another subdomain, offers sufficient territory for modification of target activity. These Surrogates, in turn, provide the necessary ligands to develop appropriate Site Directed Assays (SDAs) for each essential subdomain. The SDAs provide the screening mode for finding competitive small molecules by high throughput screening. The other arm of the Diogenesis system is an application in the new area of "Phenomics." This part of the discovery process is a form of phenotypic analysis of genomic information that has also been referred to as "functional" genomics. Phenomics, done via the Diogenesis system, uses peptide Surrogates as modifiers of the activity of, and identifiers of the partners of, gene products of known and unknown function. Actually, in many instances, the same Surrogate isolated for use in Phenomics will be used to create SDAs for discovery of small molecule drug candidates. In this simple fashion, the two applications of Diogenesis are integrated to provide savings in research time and money.

Amino Acid Sequence↗

PubMed2002

Integrating interactome, phenome, and transcriptome mapping data for the C. elegans germline.

By integrating functional genomic and proteomic mapping approaches, biological hypotheses should be formulated with increasing levels of confidence. For example, yeast interactome and transcriptome data can be correlated in biologically meaningful ways. Here, we combine interactome mapping data generated for a multicellular organism with data from both large-scale phenotypic analysis ("phenome mapping") and transcriptome profiling. First, we generated a two-hybrid interactome map of the Caenorhabditis elegans germline by using 600 transcripts enriched in this tissue. We compared this map to a phenome map of the germline obtained by RNA interference (RNAi) and to a transcriptome map obtained by clustering worm genes across 553 expression profiling experiments. In this dataset, we find that essential proteins have a tendency to interact with each other, that pairs of genes encoding interacting proteins tend to exhibit similar expression profiles, and that, for approximately 24% of germline interactions, both partners show overlapping embryonic lethal or high incidence of males RNAi phenotypes and similar expression profiles. We propose that these interactions are most likely to be relevant to germline biology. Similar integration of interactome, phenome, and transcriptome data should be possible for other biological processes in the nematode and for other organisms, including humans.

Animals↗

PubMed2001

Evolution of genome-phenome diversity under environmental stress.

The genomic era revolutionized evolutionary biology. The enigma of genotypic-phenotypic diversity and biodiversity evolution of genes, genomes, phenomes, and biomes, reviewed here, was central in the research program of the Institute of Evolution, University of Haifa, since 1975. We explored the following questions. (i) How much of the genomic and phenomic diversity in nature is adaptive and processed by natural selection? (ii) What is the origin and evolution of adaptation and speciation processes under spatiotemporal variables and stressful macrogeographic and microgeographic environments? We advanced ecological genetics into ecological genomics and analyzed globally ecological, demographic, and life history variables in 1,200 diverse species across life, thousands of populations, and tens of thousands of individuals tested mostly for allozyme and partly for DNA diversity. Likewise, we tested thermal, chemical, climatic, and biotic stresses in several model organisms. Recently, we introduced genetic maps and quantitative trait loci to elucidate the genetic basis of adaptation and speciation. The genome-phenome holistic model was deciphered by the global regressive, progressive, and convergent evolution of subterranean mammals. Our results indicate abundant genotypic and phenotypic diversity in nature. The organization and evolution of molecular and organismal diversity in nature at global, regional, and local scales are nonrandom and structured; display regularities across life; and are positively correlated with, and partly predictable by, abiotic and biotic environmental heterogeneity and stress. Biodiversity evolution, even in small isolated populations, is primarily driven by natural selection, including diversifying, balancing, cyclical, and purifying selective regimes, interacting with, but ultimately overriding, the effects of mutation, migration, and stochasticity.

Animals↗

PubMed2006

PROPHECY--a yeast phenome database, update 2006.

Connecting genotype to phenotype is fundamental in biomedical research and in our understanding of disease. Phenomics--the large-scale quantitative phenotypic analysis of genotypes on a genome-wide scale--connects automated data generation with the development of novel tools for phenotype data integration, mining and visualization. Our yeast phenomics database PROPHECY is available at http://prophecy.lundberg.gu.se. Via phenotyping of 984 heterozygous diploids for all essential genes the genotypes analysed and presented in PROPHECY have been extended and now include all genes in the yeast genome. Further, phenotypic data from gene overexpression of 574 membrane spanning proteins has recently been included. To facilitate the interpretation of quantitative phenotypic data we have developed a new phenotype display option, the Comparative Growth Curve Display, where growth curve differences for a large number of mutants compared with the wild type are easily revealed. In addition, PROPHECY now offers a more informative and intuitive first-sight display of its phenotypic data via its new summary page. We have also extended the arsenal of data analysis tools to include dynamic visualization of phenotypes along individual chromosomes. PROPHECY is an initiative to enhance the growing field of phenome bioinformatics.

Chromosomes, Fungal↗

PubMed2025

Polygenic Risk Factors for Comorbid Diagnoses in Individuals with Substance Use Disorders: A Phenome-Wide Survival Analysis.

OBJECTIVE: Persons with substance use disorders (SUD) often suffer from additional comorbidities. Researchers have explored this overlap via phenome wide association studies (PheWAS). However, PheWAS are largely cross-sectional, limiting our understanding of whether diagnoses predate development of an SUD. We characterize whether polygenic scores (PGS) are associated with time to comorbid diagnoses in electronic health records (EHR) after the first documented SUD diagnosis. METHODS: Using data from All of Us (N = 393,596), we explored: 1) whether social determinants of health (SDoH) are associated with lifetime risk of SUD (N cases = 42,568) and 2) within a subset those with a diagnosed SUD and available genetic data SUD (N = 21,357), whether PGS for alcohol use disorders, cannabis use disorders, depression, externalizing, post-traumatic stress disorder, and schizophrenia were associated with subsequent diagnoses via a phenome-wide survival analysis. RESULTS: Multiple SDoH were associated with lifetime SUD diagnosis, with annual household income having the largest overall associations (e.g., <$10K annually vs $100K-$150K annually: OR = 3.89, 95% CI = 3.66, 4.13). There were 101 phenome-wide significant PGS associations with subsequent diagnoses across various bodily systems. PGSs for alcohol use disorders, post-traumatic stress disorder, and schizophrenia were each associated with time to their respective diagnoses. CONCLUSIONS: Social determinants, especially those related to income, have profound associations with lifetime SUD risk. Additionally, PGS for psychiatric conditions are associated with multiple post-SUD diagnoses within those with a SUD, suggesting PGS may capture information beyond lifetime risk, including timing and severity of comorbidities related to SUD.

Journal Article↗

PubMed2001

Directed evolution and Phenomics screening of new biocatalysts.

Biodiversity screening and directed evolution are two fruitful complementary approaches for the discovery and design of novel biocatalysts. A new technology for directed evolution, L-Shuffling, has been designed and patented by Proteus. L-Shuffling technology offers several competitive advantages over other technologies including (i) directed evolution of large genes: L-Shuffling" means "Large-Shuffling"; (ii) high fidelity recombination and (iii) Control over location and frequency of recombination. The thousands of new recombinants generated by L-Shuffling can be further screened for their biochemical characteristics using Phenomics. Phenomics is a proprietary functional HTS technology designed and patented by Proteus for the screening of natural biodiversity as well as biodiversity generated by combinatorial biology. Phenomics is a function to gene structure approach which provides an alternative to genomics and proteomics. The traditional limits of expression libraries are thereby circumvented especially those related to cytotoxic products in usual or specific surrogate hosts. The quality of the answer given by the screening is directed dependent on the quality of the question asked. Thanks to a new substrates synthesis technology named CLIPS-O, the company can design highly specific molecules simulating the chemical structure and energetic state of the industrial substrates. The whole process of novel biocatalysts discovery has been automated using commercially available high throughput robotics.

Bacteria↗

PubMed2004

The Mouse Phenome Project.

The laboratory mouse is the organism of choice for many studies in biology and medicine. Reliable phenotypic data are essential for the full utility of genotypic information emerging from efforts to sequence human and mouse genomes. The Mouse Phenome Project has been organized to help accomplish this task by establishing a collection of baseline phenotypic data on commonly used and genetically diverse inbred mouse strains and making this information publicly available through a web-accessible database. The Mouse Phenome Database (MPD) is being developed to manage these data and to provide researchers with tools for exploring both raw phenotypic data and comparative summary analyses. The MPD serves as a repository for detailed protocols and raw data. This resource enables investigators to identify appropriate strains for (1) physiological testing, (2) drug discovery, (3) toxicology studies, (4) mutagenesis, (5) modeling human diseases, (6) QTL analyses and identification of new genes and (7) unraveling the influence of environment on genotype.

Animals↗

PubMed2005

The ageing phenome: caloric restriction and hormones promote neural cell survival, growth, and de-differentiation.

The phenome represents the observable properties of an organism that have developed under the continued influences of both genome and environmental factors. Phenotypic properties are expressed through the functions of cells, organs and body systems that operate optimally, close to equilibrium. In complex organisms, maintenance of the equilibrium is achieved by the interplay of several regulatory mechanisms. In the elderly, dynamic instability may lead to progressive loss of normal function, failure of adaptation and increased pathology. Extensive research (reported elsewhere in this journal) has demonstrated that genetic manipulations of endocrine signaling in flies, worms and mice increase longevity. Another effective strategy for prolonging the lifespan is caloric restriction: in data presented here, the persistence of estrogen-sensitive cells in the hypothalamus of caloric restricted 22-month-old female mice, may explain the persistence of reproductive function at an age, when reproductive function has long ceased in ad libitum fed controls. Still another strategy utilizes the effects of epidermal growth factor (EGF) to promote in vitro proliferation of neuroglia, astrocytes and oligodendrocytes. Their subsequent de-differentiation generates immature precursor cells potentially capable of differentiating into neuroblasts and neurons. These and other examples suggest that, in terms of functional outcomes, "the genome proposes but the phenome disposes".

Aging↗

PubMed2026

Sex-specific aging clocks from a large-scale human phenome reveal distinct aging transitions and circulating signatures.

Aging is a primary risk factor for chronic diseases, yet its progression varies among individuals and between sexes. Here, under the X-Age Project, we profiled the clinical aging phenome of the Multicentric Chinese Aging Study (mCAS) through a cross-sectional analysis of 172 clinical measures from more than 100,000 participants aged 18-98 years across three centers. These profiles enabled sex-specific clinical aging clocks that revealed divergent aging trajectories between women and men during midlife that converged in later life. Phenome-wide analyses revealed age-related accumulation of metabolic factors, including low-density lipoprotein, triglycerides, glucose and uric acid, and tumor markers, such as carcinoembryonic antigen and human epithelial protein 4. These age-accumulating factors induced senescence-related phenotypes in human endothelial cells. Furthermore, a high-fat diet mouse model with dietary reversal supported the modifiability of metabolic burden-induced aging. Together, this work establishes metabolic and tumor marker accumulation as actionable drivers of human aging, paving the way for personalized, sex-stratified geroprotective interventions.

Humans↗

PubMed2003

High-resolution yeast phenomics resolves different physiological features in the saline response.

We present a methodology for gene functional prediction based on extraction of physiologically relevant growth variables from all viable haploid yeast knockout mutants. This quantitative phenomics approach, here applied to saline cultivation, identified marginal but functionally important phenotypes and allowed the precise determination of time to adapt to an environmental challenge, rate of growth, and efficiency of growth. We identified approximately 500 salt-sensitive gene deletions, the majority of which were previously uncharacterized and displayed salt sensitivity for only one of the three physiological features. We also report a high correlation to protein-protein interaction data; in particular, several salt-sensitive subcellular networks indicating functional modules were revealed. In contrast, no correlation was found between gene dispensability and gene expression. It is proposed that high-resolution phenomics will be instrumental in systemwide descriptions of intragenomic functional networks.

Cytoskeleton↗

PubMed2004

Omic space: coordinate-based integration and analysis of genomic phenomic interactions.

MOTIVATION: With the recent progress in genomics, various data sets of omic interactions describing networks of omic elements have become available. In order to obtain reliable hypotheses from the data, it is effective to integrate interactions from different sorts of data sets. In order to facilitate a coordinate-based integration and analysis of omic interactions, we introduce the concept of an omic space comprising a comprehensive set of omic planes. Genomic, transcriptomic, proteomic, metabolomic, phenomic and other omic planes are defined by two orthogonal genomic-coordinate axes. RESULTS: We show that the omic space concept helps us to assimilate biological findings comprehensively into hypotheses or models combining higher-order phenomena and lower-order mechanisms by demonstrating that a comprehensive ranking of correspondences among interactions in the space can be used effectively for estimating candidates of responsible gene pairs for epistatic interacting loci of tumors in mice. We also show that the omic space offers a convenient framework for database integration, by presenting a system named the 'Genome <==> Phenome Superhighway' (GPS) that serves as a framework for integration and visualization of omic interactions based on omic spaces of some model species including Homo sapiens, Mus musculus, Caenorhabditis elegans and Arabidopsis thaliana. AVAILABILITY: For the GPS web site, see http://omicspace.riken.jp/gps/.

Algorithms↗