Computable phenotype

RATIONALE: Chest computed tomography -scans (CTs) are essential to diagnose and monitor bronchiectasis (BE). To date, little quantitative data is available about the nature and extent of structural lung abnormalities (SLA) on CTs of BE patients. OBJECTIVES: to investigate SLA on CTs of patients with bronchiectasis and the relationship of SLAs to clinical features using the European Bronchiectasis Registry (EMBARC) Methods: CTs from BE patients included in the EMBARC registry were analyzed using the validated Bronchiectasis Scoring Technique for CT (BEST-CT)...

BACKGROUND: Our understanding of the specific aspects of vascular contributions to dementia remains unclear. OBJECTIVES: We aim to identify the correlates of incident dementia in a multi-ethnic cardiovascular cohort. METHODS: A total of 6806 participants with follow-up data for incident dementia were included. Probable dementia diagnoses were identified using hospitalization discharge diagnoses according to the International Classification of Diseases Codes (ICD)...

Research in the human genome sciences generates a substantial amount of genetic data for hundreds of thousands of individuals, which concomitantly increases the number of variants of unknown significance (VUS). Bioinformatic analyses can successfully reveal rare variants and variants with clear associations with disease-related phenotypes. These studies have had a significant impact on how clinical genetic screens are interpreted and how patients are stratified for treatment. There are few, if any, computational methods for variants comparable to biological activity predictions...

CONTEXT: Insulin sensitivity (IS) is an important factor in type 2 diabetes (T2D) and can be estimated by many different indices. OBJECTIVE: We aimed to compare the genetic components underlying IS indices obtained from fasting and oral glucose-stimulated plasma glucose and serum insulin levels. METHODS: We computed 21 IS indices, classified as fasting, OGTT0,120 and OGTT0,30,120 indices, using fasting and oral glucose tolerance test (OGTT) data in two cohorts...

BACKGROUND: Deciphering gene regulation is essential for understanding the underlying mechanisms of healthy and disease states. While the regulatory networks formed by transcription factors (TFs) and their target genes has been mostly studied with relation to cis effects such as in TF binding sites, we focused on trans effects of TFs on the expression of their transcribed genes and their potential mechanisms. RESULTS: We provide a comprehensive tissue-specific atlas, spanning 49 tissues of TF variations affecting gene expression through computational models considering two potential mechanisms, including combinatorial regulation by the expression of the TFs, and by genetic variants within the TF...

MOTIVATION: It is difficult to generate new molecules with desirable bioactivity through ligand-based de novo drug design, and receptor-based de novo drug design is constrained by disease target information availability. The combination of artificial intelligence and phenotype-based de novo drug design can generate new bioactive molecules, independent from disease target information. Gene expression profiles can be used to characterize biological phenotypes. The Transformer model can be utilized to capture the associations between gene expression profiles and molecular structures due to its remarkable ability in processing contextual information...

MOTIVATION: As the availability of larger and more ethnically diverse reference panels grows, there is an increase in demand for ancestry-informed imputation of genome-wide association studies (GWAS), and other downstream analyses, e.g., fine-mapping. Performing such analyses at the genotype level is computationally challenging and necessitates, at best, a laborious process to access individual-level genotype and phenotype data. Summary-statistics-based tools, not requiring individual-level data, provide an efficient alternative that streamlines computational requirements and promotes open science by simplifying the re-analysis and downstream analysis of existing GWAS summary data...

BACKGROUND: Natural killer (NK) cells are cytotoxic cells capable of recognizing heterogeneous cancer targets without prior sensitization, making them promising prospects for use in cellular immunotherapy. Companion dogs develop spontaneous cancers in the context of an intact immune system, representing a valid cancer immunotherapy model. Previously, CD5 depletion of peripheral blood mononuclear cells (PBMCs) was used in dogs to isolate a CD5dim -expressing NK subset prior to co-culture with an irradiated feeder line, but this can limit the yield of the final NK product...

BACKGROUND: Recurrent malignant pleural effusion (MPE) resulting from non-small-cell lung cancer (NSCLC) is easily refractory to conventional therapeutics and lacks predictive markers. The cellular or genetic signatures of recurrent MPE still remain largely uncertain. METHODS: 16 NSCLC patients with pleural effusions were recruited, followed by corresponding treatments based on primary tumours. Non-recurrent or recurrent MPE was determined after 3-6 weeks of treatments...

Image segmentation is commonly used to estimate the location and shape of plants and their external structures. Segmentation masks are then used to localize landmarks of interest and compute other geometric features that correspond to the plant's phenotype. Despite its prevalence, segmentation-based approaches are laborious (requiring extensive annotation to train) and error-prone (derived geometric features are sensitive to instance mask integrity). Here, we present a segmentation-free approach that leverages deep learning-based landmark detection and grouping, also known as pose estimation...

Machine learning (ML) methods are increasingly becoming crucial in genome-wide association studies for identifying key genetic variants or SNPs that statistical methods might overlook. Statistical methods predominantly identify SNPs with notable effect sizes by conducting association tests on individual genetic variants, one at a time, to determine their relationship with the target phenotype. These genetic variants are then used to create polygenic risk scores (PRSs), estimating an individual's genetic risk for complex diseases like cancer or cardiovascular disorders...

BACKGROUND: Combining conventional radiomics models with deep learning features can result in superior performance in predicting the prognosis of patients with tumors; however, this approach has never been evaluated for the prediction of metachronous distant metastasis (MDM) among patients with retroperitoneal leiomyosarcoma (RLS). Thus, the purpose of this study was to develop and validate a preoperative contrast-enhanced computed tomography (CECT)-based deep learning radiomics model for predicting the occurrence of MDM in patients with RLS undergoing complete surgical resection...

BACKGROUND: Bud sports occur spontaneously in plants when new growth exhibits a distinct phenotype from the rest of the parent plant. The Witch's Broom bud sport occurs occasionally in various grapevine (Vitis vinifera) varieties and displays a suite of developmental defects, including dwarf features and reduced fertility. While it is highly detrimental for grapevine growers, it also serves as a useful tool for studying grapevine development. We used the Witch's Broom bud sport in grapevine to understand the developmental trajectories of the bud sports, as well as the potential genetic basis...

BACKGROUND: The habenula is a major regulator of serotonergic neurons in the dorsal raphe, and thus of brain state. The functional connectivity between these regions is incompletely characterized. Here, we use the ability of changes in irradiance to trigger reproducible changes in activity in the habenula and dorsal raphe of zebrafish larvae, combined with two-photon laser ablation of specific neurons, to establish causal relationships. RESULTS: Neurons in the habenula can show an excitatory response to the onset or offset of light, while neurons in the anterior dorsal raphe display an inhibitory response to light, as assessed by calcium imaging...

More and more evidence shows that abnormal lipid metabolism leads to immune system dysfunction in AMD and promotes the occurrence of AMD by changing the homeostasis of ocular inflammation. However, the molecular mechanism underlying the effect of lipid metabolism on the phenotype and function of macrophages is still unclear, and the mechanism of association between AMD and cancer and COVID-19 has not been reported. The purpose of this study is to explore the interaction between lipid metabolism related genes, ferroptosis related genes and immunity in AMD, find out the key genes that affect the ferroptosis of AMD through lipid metabolism pathway and the molecular mechanism that mediates the action of macrophages, and find out the possible mechanism of lipid metabolism and potential co-therapeutic targets between AMD and cancer and COVID-19, so as to improve treatment decision-making and clinical results...

Detecting epistatic drivers of human phenotypes is a considerable challenge. Traditional approaches use regression to sequentially test multiplicative interaction terms involving pairs of genetic variants. For higher-order interactions and genome-wide large-scale data, this strategy is computationally intractable. Moreover, multiplicative terms used in regression modeling may not capture the form of biological interactions. Building on the Predictability, Computability, Stability (PCS) framework, we introduce the epiTree pipeline to extract higher-order interactions from genomic data using tree-based models...

BACKGROUND: PEComa is a mesenchymal tumor that can occur in various organs including the uterus and soft tissues. PEComas are composed of perivascular epithelioid cells, and angiomyolipoma (AML), clear cell sugar tumor (CCST), and lymphangiomyomatosis (LAM) are considered lesions of the same lineage as tumors of the PEComa family. Histologically, a common PEComa shows solid or sheet-like proliferation of epithelioid cells. This is accompanied by an increase in the number of dilated blood vessels...

Germline cells are critical for transmitting genetic information to subsequent generations in biological organisms. While their differentiation from somatic cells during embryonic development is well-documented in most animals, the regulatory mechanisms initiating plant germline cells are not well understood. To thoroughly investigate the complex morphological transformations of their ultrastructure over developmental time, nanoscale 3D reconstruction of entire plant tissues is necessary, achievable exclusively through electron microscopy imaging...

Most traits are polygenic, and the contributing loci can be identified by GWAS. The genetic basis of adaptation is, however, difficult to characterize. Here, we propose to study the genetic basis of trait evolution by monitoring the evolution of their phenotypic variance during adaptation to a new environment in well-defined laboratory conditions. Extensive computer simulations show that the evolution of phenotypic variance in a replicated experimental evolution setting can distinguish between oligogenic and polygenic adaptive architectures...

INTRODUCTION: Senescence refers to a state of permanent cell growth arrest and is regarded as a tumor suppressive mechanism, whereas accumulative evidence demonstrate that senescent cells play an adverse role during cancer progression. The scarcity of specific and reliable markers reflecting senescence level in cancer impede our understanding of this biological basis. OBJECTIVES: Senescence-related genes (SRGs) were collected for integrative analysis to reveal the role of senescence in hepatocellular carcinoma (HCC)...