Functional Assays to Screen and Dissect Genomic Hits: Doubling Down on the National Investment in Genomic Research

RARG variant predictive of doxorubicin-induced cardiotoxicity identifies a cardioprotective therapy

Doxorubicin is an anthracycline chemotherapy agent effective in treating a wide range of malignancies, but its use is limited by dose-dependent cardiotoxicity. A recent genome-wide association study identified a SNP (rs2229774) in retinoic acid receptor-γ (RARG) as statistically associated with increased risk of anthracycline-induced cardiotoxicity. Here, we show that human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from patients with rs2229774 and who suffered doxorubicin-induced cardiotoxicity (DIC) are more sensitive to doxorubicin. We determine that the mechanism of this RARG variant effect is mediated via suppression of topoisomerase 2β (TOP2B) expression and activation of the cardioprotective extracellular regulated kinase (ERK) pathway. We use patient-specific hiPSC-CMs as a drug discovery platform, determining that the RARG agonist CD1530 attenuates DIC, and we confirm this cardioprotective effect in an established in vivo mouse model of DIC. This study provides a rationale for clinical prechemotherapy genetic screening for rs2229774 and a foundation for the clinical use of RARG agonist treatment to protect cancer patients from DIC.

AI models and the future of genomic research and medicine: True sons of knowledge?: Artificial intelligence needs to be integrated with causal conceptions in biomedicine to harness its societal benefits for the field

The increasing availability of large-scale, complex data has made research into how human genomes determine physiology in health and disease, as well as its application to drug development and medicine, an attractive field for artificial intelligence (AI) approaches. Looking at recent developments, we explore how such approaches interconnect and may conflict with needs for and notions of causal knowledge in molecular genetics and genomic medicine. We provide reasons to suggest that-while capable of generating predictive knowledge at unprecedented pace and scale-if and how these approaches will be integrated with prevailing causal concepts will not only determine the future of scientific understanding and self-conceptions in these fields. But these questions will also be key to develop differentiated policies, such as for education and regulation, in order to harness societal benefits of AI for genomic research and medicine.

Functional Genomics of ABCA3 Variants

Rare or private, biallelic variants in the ABCA3 (ATP-binding cassette transporter A3) gene are the most common monogenic cause of lethal neonatal respiratory failure and childhood interstitial lung disease. Functional characterization of fewer than 10% of over 200 disease-associated ABCA3 variants (majority missense) suggests either disruption of ABCA3 protein trafficking (type I) or of ATPase-mediated phospholipid transport (type II). Therapies remain limited and nonspecific. A scalable platform is required for functional characterization of ABCA3 variants and discovery of pharmacologic correctors. To address this need, we first silenced the endogenous ABCA3 locus in A549 cells with CRISPR/Cas9 genome editing. Next, to generate a parent cell line (A549/ABCA3^-/-) with a single recombination target site for genomic integration and stable expression of individual ABCA3 missense variant cDNAs, we used lentiviral-mediated integration of a LoxFAS cassette, FACS, and dilutional cloning. To assess the fidelity of this cell-based model, we compared functional characterization (ABCA3 protein processing, ABCA3 immunofluorescence colocalization with intracellular markers, ultrastructural vesicle phenotype) of two individual ABCA3 mutants (type I mutant, p.L101P; type II mutant, p.E292V) in A549/ABCA3^-/- cells and in both A549 cells and primary, human alveolar type II cells that transiently express each cDNA after adenoviral-mediated transduction. We also confirmed pharmacologic rescue of ABCA3 variant-encoded mistrafficking and vesicle diameter in A549/ABCA3^-/- cells that express p.G1421R (type I mutant). A549/ABCA3^-/- cells provide a scalable, genetically versatile, physiologically relevant functional genomics platform for discovery of variant-specific mechanisms that disrupt ABCA3 function and for screening of potential ABCA3 pharmacologic correctors.

PhenomeXcan: Mapping the genome to the phenome through the transcriptome

Large-scale genomic and transcriptomic initiatives offer unprecedented insight into complex traits, but clinical translation remains limited by variant-level associations without biological context and lack of analytic resources. Our resource, PhenomeXcan, synthesizes 8.87 million variants from genome-wide association study summary statistics on 4091 traits with transcriptomic data from 49 tissues in Genotype-Tissue Expression v8 into a gene-based, queryable platform including 22,515 genes. We developed a novel Bayesian colocalization method, fast enrichment estimation aided colocalization analysis (fastENLOC), to prioritize likely causal gene-trait associations. We successfully replicate associations from the phenome-wide association studies (PheWAS) catalog Online Mendelian Inheritance in Man, and an evidence-based curated gene list. Using PhenomeXcan results, we provide examples of novel and underreported genome-to-phenome associations, complex gene-trait clusters, shared causal genes between common and rare diseases via further integration of PhenomeXcan with ClinVar, and potential therapeutic targets. PhenomeXcan (phenomexcan.org) provides broad, user-friendly access to complex data for translational researchers.

Ambele M, S. Pepper M. Barriers to Implementing Clinical Pharmacogenetics Testing in Sub-Saharan Africa. A Critical Review

Clinical research in high-income countries is increasingly demonstrating the cost- effectiveness of clinical pharmacogenetic (PGx) testing in reducing the incidence of adverse drug reactions and improving overall patient care. Medications are prescribed based on an individual’s genotype (pharmacogenes), which underlies a specific phenotypic drug response. The advent of cost-effective high-throughput genotyping techniques coupled with the existence of Clinical Pharmacogenetics Implementation Consortium (CPIC) dosing guidelines for pharmacogenetic “actionable variants” have increased the clinical applicability of PGx testing. The implementation of clinical PGx testing in sub-Saharan African (SSA) countries can significantly improve health care delivery, considering the high incidence of communicable diseases, the increasing incidence of non-communicable diseases, and the high degree of genetic diversity in these populations. However, the implementation of PGx testing has been sluggish in SSA, prompting this review, the aim of which is to document the existing barriers. These include under-resourced clinical care logistics, a paucity of pharmacogenetics clinical trials, scientific and technical barriers to genotyping pharmacogene variants, and socio-cultural as well as ethical issues regarding health-care stakeholders, among other barriers. Investing in large-scale SSA PGx research and governance, establishing biobanks/bio-databases coupled with clinical electronic health systems, and encouraging the uptake of PGx knowledge by health-care stakeholders, will ensure the successful implementation of pharmacogenetically guided treatment in SSA.

Identifying adaptive alleles in the human genome: from selection mapping to functional validation

The suite of phenotypic diversity across geographically distributed human populations is the outcome of genetic drift, gene flow, and natural selection throughout human evolution. Human genetic variation underlying local biological adaptations to selective pressures is incompletely characterized. With the emergence of population genetics modeling of large-scale genomic data derived from diverse populations, scientists are able to map signatures of natural selection in the genome in a process known as selection mapping. Inferred selection signals further can be used to identify candidate functional alleles that underlie putative adaptive phenotypes. Phenotypic association, fine mapping, and functional experiments facilitate the identification of candidate adaptive alleles. Functional investigation of candidate adaptive variation using novel techniques in molecular biology is slowly beginning to unravel how selection signals translate to changes in biology that underlie the phenotypic spectrum of our species. In addition to informing evolutionary hypotheses of adaptation, the discovery and functional annotation of adaptive alleles also may be of clinical significance. While selection mapping efforts in non-European populations are growing, there remains a stark under-representation of diverse human populations in current public genomic databases, of both clinical and non-clinical cohorts. This lack of inclusion limits the study of human biological variation. Identifying and functionally validating candidate adaptive alleles in more global populations is necessary for understanding basic human biology and human disease.

Xenopus: Experimental Access to Cardiovascular Development, Regeneration Discovery, and Cardiovascular Heart-Defect Modeling

Xenopus has been used to study a wide array of developmental processes, benefiting from vast quantities of relatively large, externally developing eggs. Xenopus is particularly amenable to examining the cardiac system because many of the developmental processes and genes involved in cardiac specification, differentiation, and growth are conserved between Xenopus and human and have been characterized in detail. Furthermore, compared with other higher vertebrate models, Xenopus embryos can survive longer without a properly functioning heart or circulatory system, enabling investigation of later consequences of early embryological manipulations. This biology is complemented by experimental technology, such as embryonic explants to study the heart, microinjection of overexpression constructs, and, most recently, the generation of genetic mutations through gene-editing technologies. Recent investigations highlight Xenopus as a powerful experimental system for studying injury/repair and regeneration and for congenital heart disease (CHD) modeling, which reinforces why this model system remains ideal for studying heart development.

Molecular networks in Network Medicine: Development and applications

Network Medicine applies network science approaches to investigate disease pathogenesis. Many different analytical methods have been used to infer relevant molecular networks, including protein-protein interaction networks, correlation-based networks, gene regulatory networks, and Bayesian networks. Network Medicine applies these integrated approaches to Omics Big Data (including genetics, epigenetics, transcriptomics, metabolomics, and proteomics) using computational biology tools and, thereby, has the potential to provide improvements in the diagnosis, prognosis, and treatment of complex diseases. We discuss briefly the types of molecular data that are used in molecular network analyses, survey the analytical methods for inferring molecular networks, and review efforts to validate and visualize molecular networks. Successful applications of molecular network analysis have been reported in pulmonary arterial hypertension, coronary heart disease, diabetes mellitus, chronic lung diseases, and drug development. Important knowledge gaps in Network Medicine include incompleteness of the molecular interactome, challenges in identifying key genes within genetic association regions, and limited applications to human diseases. This article is categorized under: Models of Systems Properties and Processes > Mechanistic Models Translational, Genomic, and Systems Medicine > Translational Medicine Analytical and Computational Methods > Analytical Methods Analytical and Computational Methods > Computational Methods.

Genetic Insights Into Smooth Muscle Cell Contributions to Coronary Artery Disease

Coronary artery disease is a complex cardiovascular disease involving an interplay of genetic and environmental influences over a lifetime. Although considerable progress has been made in understanding lifestyle risk factors, genetic factors identified from genome-wide association studies may capture additional hidden risk undetected by traditional clinical tests. These genetic discoveries have highlighted many candidate genes and pathways dysregulated in the vessel wall, including those involving smooth muscle cell phenotypic modulation and injury responses. Here, we summarize experimental evidence for a few genome-wide significant loci supporting their roles in smooth muscle cell biology and disease. We also discuss molecular quantitative trait locus mapping as a powerful discovery and fine-mapping approach applied to smooth muscle cell and coronary artery disease-relevant tissues. We emphasize the critical need for alternative genetic strategies, including cis/trans-regulatory network analysis, genome editing, and perturbations, as well as single-cell sequencing in smooth muscle cell tissues and model organisms, under both normal and disease states. By integrating multiple experimental and analytical modalities, these multidimensional datasets should improve the interpretation of coronary artery disease genome-wide association studies and molecular quantitative trait locus signals and inform candidate targets for therapeutic intervention or risk prediction.

Applying Functional Genomics to Chronic Obstructive Pulmonary Disease

Genome-wide association studies (GWAS) have identified more than 20 genomic regions associated with chronic obstructive pulmonary disease (COPD) susceptibility. However, the functional genetic variants within these COPD GWAS loci remain largely unidentified, thus limiting translation of these GWAS discoveries to new disease insights. Whole-exome and whole-genome sequencing studies have the potential to identify rare genetic determinants of COPD. Efforts to understand the biological effects of novel COPD genetic loci include gene-targeted murine models, integration of additional omics data (including transcriptomics and epigenetics), and functional variant identification. COPD genetic determinants likely act through biological networks, and a variety of network-based approaches have been used to gain insights into COPD susceptibility and heterogeneity.

Conservation and divergence of protein pathways in the vertebrate heart

Heart disease is the leading cause of death in the western world. Attaining a mechanistic understanding of human heart development and homeostasis and the molecular basis of associated disease states relies on the use of animal models. Here, we present the cardiac proteomes of 4 model vertebrates with dual circulatory systems: the pig (Sus scrofa), the mouse (Mus musculus), and 2 frogs (Xenopus laevis and Xenopus tropicalis). Determination of which proteins and protein pathways are conserved and which have diverged within these species will aid in our ability to choose the appropriate models for determining protein function and to model human disease. We uncover mammalian- and amphibian-specific, as well as species-specific, enriched proteins and protein pathways. Among these, we find and validate an enrichment in cell-cycle–associated proteins within Xenopus laevis. To further investigate functional units within cardiac proteomes, we develop a computational approach to profile the abundance of protein complexes across species. Finally, we demonstrate the utility of these data sets for predicting appropriate model systems for studying given cardiac conditions by testing the role of Kielin/chordin-like protein (Kcp), a protein found as enriched in frog hearts compared to mammals. We establish that germ-line mutations in Kcp in Xenopus lead to valve defects and, ultimately, cardiac failure and death. Thus, integrating these findings with data on proteins responsible for cardiac disease should lead to the development of refined, species-specific models for protein function and disease states.

Comparison of cardiac proteomes across four vertebrate model systems reveals species-specific differentially enriched proteins and pathways, including the Xenopus-enriched Kielin/chordin-like protein (Kcp), which is shown to be important for proper heart development.

The Bardet-Biedl syndrome protein complex regulates cell migration and tissue repair through a Cullin-3/RhoA pathway

Cell motility and migration play critical roles in various physiological processes and disease states. Here, we show that the BBBsome, a macromolecule composed of eight Bardet-Biedl syndrome (BBS) proteins including BBS1, is a critical determinant of cell migration and wound healing. Fibroblast cells derived from mice or humans harboring a homozygous missense mutation (BBS1^M390R/M390R) that disrupt the BBSome exhibit defects in migration and wound healing. Furthermore, we demonstrate that BBS1^M390R/M390R mice have significantly delayed wound closure. In line with this, we provide data suggesting that BBS1^M390R/M390R fibroblasts have impaired platelet-derived growth factor-AA (PDGF) receptor-α signaling, a key regulator of directional cell migration acting as a chemoattractant during postnatal migration responses such as wound healing. In addition, we show that BBS1^M390R/M390R fibroblasts have upregulated RhoA expression and activity. The relevance of RhoA upregulation is demonstrated by the ability of RhoA-kinase inhibitor Y27632 to partially rescue the migration defect of BBS1^M390R/M390R fibroblasts cells. We also show that accumulation of RhoA protein in BBS1^M390R/M390R fibroblasts cells is associated with reduction and inactivation of the ubiquitin ligase Cullin-3. Consistent with this, Cullin-3 inhibition with MLN4924 is sufficient to reduce migration of normal fibroblasts. These data implicate the BBSome in cell motility and tissue repair through a mechanism that involves PDGF receptor signaling and Cullin-3-mediated control of RhoA.

The Transcriptomic Toolbox: Resources for Interpreting Large Gene Expression Data within a Precision Medicine Context for Metabolic Disease Atherosclerosis

As one of the most widespread metabolic diseases, atherosclerosis affects nearly everyone as they age; arteries gradually narrow from plaque accumulation over time reducing oxygenated blood flow to central and periphery causing heart disease, stroke, kidney problems, and even pulmonary disease. Personalized medicine promises to bring treatments based on individual genome sequencing that precisely target the molecular pathways underlying atherosclerosis and its symptoms, but to date only a few genotypes have been identified. A promising alternative to this genetic approach is the identification of pathways altered in atherosclerosis by transcriptome analysis of atherosclerotic tissues to target specific aspects of disease. Transcriptomics is a potentially useful tool for both diagnostics and discovery science, exposing novel cellular and molecular mechanisms in clinical and translational models, and depending on experimental design to identify and test novel therapeutics. The cost and time required for transcriptome analysis has been greatly reduced by the development of next generation sequencing. The goal of this resource article is to provide background and a guide to appropriate technologies and downstream analyses in transcriptomics experiments generating ever-increasing amounts of gene expression data.