A System for Phenotype Harmonization in the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Program.

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase statistical power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data-set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data-sharing mechanisms. This system was developed for the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other -omics data for more than 80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants (recruited in 1948-2012) from up to 17 studies per phenotype. Here we discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include 1) the software code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify, or extend these harmonizations to additional studies, and 2) the results of labeling thousands of phenotype variables with controlled vocabulary terms.

Portfolio Analysis of Research Grants in Data Science Funded by the National Heart, Lung, and Blood Institute.

Leveraging emerging opportunities in data science to open new frontiers in heart, lung, blood, and sleep research is one of the major strategic objectives of the National Heart, Lung, and Blood Institute (NHLBI), one of the 27 Institutes/Centers within the National Institutes of Health (NIH). To assess NHLBI's recent funding of research grants in data science and to identify its relative areas of focus within data science, a portfolio analysis from fiscal year 2008 to fiscal year 2017 was performed. In this portfolio analysis, an efficient and reliable methodology was used to identify data science research grants by utilizing several NIH databases and search technologies (iSearch, Query View Reporting system, and IN-SPIRE [Pacific Northwest National Laboratory, Richland, WA]). Six hundred thirty data science-focused extramural research grants supported by NHLBI were identified using keyword searches based primarily on NIH's working definitions of bioinformatics and computational biology. Further analysis characterized the distribution of these grants among the heart, lung, blood, and sleep disease areas as well as the subtypes of data science projects funded by NHLBI. Information was also collected for data science research grants funded by other NIH institutes/centers using the same search and analysis methodology. The funding comparison among different NIH institutes/centers highlighted relative data science areas of emphasis and further identified opportunities for potential data science areas in which NHLBI could foster research advances.

Author Correction: Association study in African-admixed populations across the Americas recapitulates asthma risk loci in non-African populations.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Association study in African-admixed populations across the Americas recapitulates asthma risk loci in non-African populations.

Asthma is a complex disease with striking disparities across racial and ethnic groups. Despite its relatively high burden, representation of individuals of African ancestry in asthma genome-wide association studies (GWAS) has been inadequate, and true associations in these underrepresented minority groups have been inconclusive. We report the results of a genome-wide meta-analysis from the Consortium on Asthma among African Ancestry Populations (CAAPA; 7009 asthma cases, 7645 controls). We find strong evidence for association at four previously reported asthma loci whose discovery was driven largely by non-African populations, including the chromosome 17q12-q21 locus and the chr12q13 region, a novel (and not previously replicated) asthma locus recently identified by the Trans-National Asthma Genetic Consortium (TAGC). An additional seven loci reported by TAGC show marginal evidence for association in CAAPA. We also identify two novel loci (8p23 and 8q24) that may be specific to asthma risk in African ancestry populations.

An admixture mapping meta-analysis implicates genetic variation at 18q21 with asthma susceptibility in Latinos.

BACKGROUND: Asthma is a common but complex disease with racial/ethnic differences in prevalence, morbidity, and response to therapies. OBJECTIVE: We sought to perform an analysis of genetic ancestry to identify new loci that contribute to asthma susceptibility. METHODS: We leveraged the mixed ancestry of 3902 Latinos and performed an admixture mapping meta-analysis for asthma susceptibility. We replicated associations in an independent study of 3774 Latinos, performed targeted sequencing for fine mapping, and tested for disease correlations with gene expression in the whole blood of more than 500 subjects from 3 racial/ethnic groups. RESULTS: We identified a genome-wide significant admixture mapping peak at 18q21 in Latinos (P = 6.8 × 10-6), where Native American ancestry was associated with increased risk of asthma (odds ratio [OR], 1.20; 95% CI, 1.07-1.34; P = .002) and European ancestry was associated with protection (OR, 0.86; 95% CI, 0.77-0.96; P = .008). Our findings were replicated in an independent childhood asthma study in Latinos (P = 5.3 × 10-3, combined P = 2.6 × 10-7). Fine mapping of 18q21 in 1978 Latinos identified a significant association with multiple variants 5' of SMAD family member 2 (SMAD2) in Mexicans, whereas a single rare variant in the same window was the top association in Puerto Ricans. Low versus high SMAD2 blood expression was correlated with case status (13.4% lower expression; OR, 3.93; 95% CI, 2.12-7.28; P < .001). In addition, lower expression of SMAD2 was associated with more frequent exacerbations among Puerto Ricans with asthma. CONCLUSION: Ancestry at 18q21 was significantly associated with asthma in Latinos and implicated multiple ancestry-informative noncoding variants upstream of SMAD2 with asthma susceptibility. Furthermore, decreased SMAD2 expression in blood was strongly associated with increased asthma risk and increased exacerbations.

The Intersection of Aging Biology and the Pathobiology of Lung Diseases: A Joint NHLBI/NIA Workshop.

Death from chronic lung disease is increasing and chronic obstructive pulmonary disease has become the third leading cause of death in the United States in the past decade. Both chronic and acute lung diseases disproportionately affect elderly individuals, making it likely that these diseases will become more frequent and severe as the worldwide population ages. Chronic lung diseases are associated with substantial morbidity, frequently resulting in exercise limiting dyspnea, immobilization, and isolation. Therefore, effective strategies to prevent or treat lung disease are likely to increase healthspan as well as life span. This review summarizes the findings of a joint workshop sponsored by the NIA and NHLBI that brought together investigators focused on aging and lung biology. These investigators encouraged the use of genetic systems and aged animals in the study of lung disease and the development of integrative systems-based platforms that can dynamically incorporate data sets that describe the genomics, transcriptomics, epigenomics, metabolomics, and proteomics of the aging lung in health and disease. Further research was recommended to integrate benchmark biological hallmarks of aging in the lung with the pathobiology of acute and chronic lung diseases with divergent pathologies for which advanced age is the most important risk factor.

Malfolded protein structure and proteostasis in lung diseases.

Recent discoveries indicate that disorders of protein folding and degradation play a particularly important role in the development of lung diseases and their associated complications. The overarching purpose of the National Heart, Lung, and Blood Institute workshop on "Malformed Protein Structure and Proteostasis in Lung Diseases" was to identify mechanistic and clinical research opportunities indicated by these recent discoveries in proteostasis science that will advance our molecular understanding of lung pathobiology and facilitate the development of new diagnostic and therapeutic strategies for the prevention and treatment of lung disease. The workshop's discussion focused on identifying gaps in scientific knowledge with respect to proteostasis and lung disease, discussing new research advances and opportunities in protein folding science, and highlighting novel technologies with potential therapeutic applications for diagnosis and treatment.

Genomic medicine and lung diseases.

The recent explosion of genomic data and technology points to opportunities to redefine lung diseases at the molecular level; to apply integrated genomic approaches to elucidate mechanisms of lung pathophysiology; and to improve early detection, diagnosis, and treatment of lung diseases. Research is needed to translate genomic discoveries into clinical applications, such as detecting preclinical disease, predicting patient outcomes, guiding treatment choices, and most of all identifying potential therapeutic targets for lung diseases. The Division of Lung Diseases in the National Heart, Lung, and Blood Institute convened a workshop, "Genomic Medicine and Lung Diseases," to discuss the potential for integrated genomics and systems approaches to advance 21st century pulmonary medicine and to evaluate the most promising opportunities for this next phase of genomics research to yield clinical benefit. Workshop sessions included (1) molecular phenotypes, molecular biomarkers, and therapeutics; (2) new technology and opportunity; (3) integrative genomics; (4) molecular anatomy of the lung; (5) novel data and information platforms; and (6) recommendations for exceptional research opportunities in lung genomics research.

Understanding the complexity of IgE-related phenotypes from childhood to young adulthood: a Mechanisms of the Development of Allergy (MeDALL) seminar.

Mechanisms of the Development of Allergy (MeDALL), a Seventh Framework Program European Union project, aims to generate novel knowledge on the mechanisms of initiation of allergy. Precise phenotypes of IgE-mediated allergic diseases will be defined in MeDALL. As part of MeDALL, a scientific seminar was held on January 24, 2011, to review current knowledge on the IgE-related phenotypes and to explore how a multidisciplinary effort could result in a new integrative translational approach. This article provides a summary of the meeting. It develops challenges in IgE-related phenotypes and new clinical and epidemiologic approaches to the investigation of allergic phenotypes, including cluster analysis, scale-free models, candidate biomarkers, and IgE microarrays; the particular case of severe asthma was reviewed. Then novel approaches to the IgE-associated phenotypes are reviewed from the individual mechanisms to the systems, including epigenetics, human in vitro immunology, systems biology, and animal models. The last chapter deals with the understanding of the population-based IgE-associated phenotypes in children and adolescents, including age effect in terms of maturation, observed effects of early-life exposures and shift of focus from early life to pregnancy, gene-environment interactions, cohort effects, and time trends in patients with allergic diseases. This review helps to define phenotypes of allergic diseases in MeDALL.

Getting from genes to function in lung disease: a National Heart, Lung, and Blood Institute workshop report.

Genome-wide association studies (GWAS) have revealed novel genes and pathways involved in lung disease, many of which are potential targets for therapy. However, despite numerous successes, a large proportion of the genetic variance in disease risk remains unexplained, and the function of the associated genetic variations identified by GWAS and the mechanisms by which they alter individual risk for disease or pathogenesis are still largely unknown. The National Heart, Lung, and Blood Institute (NHLBI) convened a 2-day workshop to address these shortcomings and to make recommendations for future research areas that will move the scientific community beyond gene discovery. Topics of individual sessions ranged from data integration and systems genetics to functional validation of genetic variations in humans and model systems. There was broad consensus among the participants for five high-priority areas for future research, including the following: (1) integrated approaches to characterize the function of genetic variations, (2) studies on the role of environment and mechanisms of transcriptional and post-transcriptional regulation, (3) development of model systems to study gene function in complex biological systems, (4) comparative phenomic studies across lung diseases, and (5) training in and applications of bioinformatic approaches for comprehensive mining of existing data sets. Last, it was agreed that future research on lung diseases should integrate approaches across "-omic" technologies and to include ethnically/racially diverse populations in human studies of lung disease whenever possible.

Molecular phenotyping for severe asthma.

Evaluation of: Brasier AR, Sundar V, Boetticher G et al.: Molecular phenotyping of severe asthma using pattern recognition of bronchoalveolar lavage-derived cytokines. J. Allergy Clin. Immunol. 121, 30-37 (2008). Asthma is a heterogeneous disorder presenting with many phenotypes. Precise phenotypic definition has eluded the medical research community for years, despite recognition of different disease subtypes. Brasier and colleagues sought to discriminate asthma phenotypes on the basis of cytokine profiles in bronchoalveolar lavage samples from 84 patients with mild-moderate and severe asthma. Their results demonstrated that this molecular phenotyping approach could be applied to categorizing asthma into subtypes based on pathobiology. This article will discuss the potential advantages of applying molecular phenotyping approaches to asthma and lung disease in general in the perspective of personalized medicine.

A comparison of whole-genome shotgun-derived mouse chromosome 16 and the human genome.

The high degree of similarity between the mouse and human genomes is demonstrated through analysis of the sequence of mouse chromosome 16 (Mmu 16), which was obtained as part of a whole-genome shotgun assembly of the mouse genome. The mouse genome is about 10% smaller than the human genome, owing to a lower repetitive DNA content. Comparison of the structure and protein-coding potential of Mmu 16 with that of the homologous segments of the human genome identifies regions of conserved synteny with human chromosomes (Hsa) 3, 8, 12, 16, 21, and 22. Gene content and order are highly conserved between Mmu 16 and the syntenic blocks of the human genome. Of the 731 predicted genes on Mmu 16, 509 align with orthologs on the corresponding portions of the human genome, 44 are likely paralogous to these genes, and 164 genes have homologs elsewhere in the human genome; there are 14 genes for which we could find no human counterpart.

Generation and comparative analysis of approximately 3.3 Mb of mouse genomic sequence orthologous to the region of human chromosome 7q11.23 implicated in Williams syndrome.

Williams syndrome is a complex developmental disorder that results from the heterozygous deletion of a approximately 1.6-Mb segment of human chromosome 7q11.23. These deletions are mediated by large (approximately 300 kb) duplicated blocks of DNA of near-identical sequence. Previously, we showed that the orthologous region of the mouse genome is devoid of such duplicated segments. Here, we extend our studies to include the generation of approximately 3.3 Mb of genomic sequence from the mouse Williams syndrome region, of which just over 1.4 Mb is finished to high accuracy. Comparative analyses of the mouse and human sequences within and immediately flanking the interval commonly deleted in Williams syndrome have facilitated the identification of nine previously unreported genes, provided detailed sequence-based information regarding 30 genes residing in the region, and revealed a number of potentially interesting conserved noncoding sequences. Finally, to facilitate comparative sequence analysis, we implemented several enhancements to the program, including the addition of links from annotated features within a generated percent-identity plot to specific records in public databases. Taken together, the results reported here provide an important comparative sequence resource that should catalyze additional studies of Williams syndrome, including those that aim to characterize genes within the commonly deleted interval and to develop mouse models of the disorder.