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Weiss S.T.,Harvard University | Weiss S.T.,Brigham and Womens Hospital | Weiss S.T.,Partners Center for Personalized Genetic Medicine
American Journal of Respiratory and Critical Care Medicine

Recently a series of genome-wide association study manuscripts in asthma and chronic obstructive pulmonary disease have been published. These papers suggest that, in part, asthma and chronic obstructive pulmonary disease have a common genetic origin, and that this common origin is due to polymorphism in genes that are involved with the development of the lung. This Pulmonary Perspective discusses what we are learning from genome-wide association studies, where the field of genetics and genomics is headed, and how this knowledge will ultimately be put to use in clinical medicine. Source

Park H.-W.,Harvard University | Park H.-W.,Seoul National University | Tantisira K.G.,Harvard University | Weiss S.T.,Harvard University | Weiss S.T.,Partners Center for Personalized Genetic Medicine
Annual Review of Pharmacology and Toxicology

The response to drug treatment in asthma is a complex trait and is markedly variable even in patients with apparently similar clinical features. Pharmaco-genomics, which is the study of variations of human genome characteristics as related to drug response, can play a role in asthma therapy. Both a traditional candidate-gene approach to conducting genetic association studies and genome-wide association studies have provided an increasing list of genes and variants associated with the three major classes of asthma medications: β2-agonists, inhaled corticosteroids, and leukotriene modifiers. Moreover, a recent integrative, systems-level approach has offered a promising opportunity to identify important pharmacogenomics loci in asthma treatment. However, we are still a long way away from making this discipline directly relevant to patients. The combination of network modeling, functional validation, and integrative omics technologies will likely be needed to move asthma pharmacogenomics closer to clinical relevance. ©2015 by Annual Reviews. All rights reserved. Source

Lehmann L.S.,Brigham and Womens Hospital | Lehmann L.S.,Harvard University | Kaufman D.J.,Johns Hopkins University | Sharp R.R.,Case Western Reserve University | And 4 more authors.
Genetics in Medicine

Purpose: To describe the process of structuring a partnership between academic researchers and two personalized genetic testing companies that would manage conflicts of interest while allowing researchers to study the impact of this nascent industry. Methods: We developed a transparent process of ongoing communication about the interests of all research partners to address challenges in establishing study goals, survey development, data collection, analysis, and manuscript preparation. Using the existing literature on conflicts of interest and our experience, we created a checklist for academic and industry researchers seeking to structure research partnerships. Results: Our checklist includes questions about the risk to research participants, sponsorship of the study, control of data analysis, freedom to publish results, the impact of the research on industry customers, openness to input from all partners, sharing results before publication, and publication of industry-specific data. Transparency is critical to building trust between partners. Involving all partners in the research development enhanced the quality of our research and provided an opportunity to manage conflicts early in the research process. Conclusion: Navigating relationships between academia and industry is complex and requires strategies that are transparent and responsive to the concerns of all. Employing a checklist of questions prior to beginning a research partnership may help to manage conflicts of interest. © American College of Medical Genetics. Source

Melen E.,Harvard University | Melen E.,Karolinska Institutet | Melen E.,Karolinska University Hospital | Himes B.E.,Harvard University | And 8 more authors.
Journal of Allergy and Clinical Immunology

Background: Epidemiologic studies consistently show associations between asthma and obesity. Shared genetics might account for this association. Objective: We sought to identify genetic variants associated with both asthma and obesity. Methods: On the basis of a literature search, we identified genes from (1) genome-wide association studies (GWASs) of body mass index (BMI; n = 17 genes), (2) GWASs of asthma (n = 14), and (3) candidate gene studies of BMI and asthma (n = 7). We used GWAS data from the Childhood Asthma Management Program to analyze associations between single nucleotide polymorphisms (SNPs) in these genes and asthma (n = 359 subjects) and BMI (n = 537). Results: One top BMI GWAS SNP from the literature, rs10938397 near glucosamine-6-phosphate deaminase 2 (GNPDA2), was associated with both BMI (P = 4 × 10-4) and asthma (P = .03). Of the top asthma GWAS SNPs and the candidate gene SNPs, none was found to be associated with both BMI and asthma. Gene-based analyses that included all available SNPs in each gene found associations (P < .05) with both phenotypes for several genes: neuronal growth regulator 1 (NEGR1); roundabout, axon guidance receptor, homolog 1 (ROBO1); diacylglycerol kinase, gamma (DGKG); Fas apoptotic inhibitory molecule 2 (FAIM2); fat mass and obesity associated (FTO); and carbohydrate (N-acetylgalactosamine 4-0) sulfotransferase 8 (CHST8) among the BMI GWAS genes; interleukin 1 receptor-like 1 / interleukin 18 receptor 1 (IL1RL1/IL18R1), dipeptidyl-peptidase 10 (DPP10), phosphodiesterase 4D (PDE4D), V-myb myeloblastosis viral oncogene homolog (MYB), PDE10A, IL33, and especially protein tyrosine phosphatase, receptor type D (PTPRD) among the asthma GWAS genes; and protein kinase C, alpha (PRKCA) among the BMI and asthma candidate genes. Conclusions: SNPs within several genes showed associations to BMI and asthma at a genetic level, but none of these associations were significant after correction for multiple testing. Our analysis of known candidate genes reveals some evidence for shared genetics between asthma and obesity, but other shared genetic determinants are likely to be identified in novel loci. © 2010 American Academy of Allergy, Asthma & Immunology. Source

Holm I.A.,Boston Childrens Hospital | Holm I.A.,Harvard University | Savage S.K.,Boston Childrens Hospital | Green R.C.,Partners Center for Personalized Genetic Medicine | And 7 more authors.
Genetics in Medicine

Purpose:Approaches to return individual results to participants in genomic research variably focus on actionability, duty to share, or participants' preferences. Our group at Boston Children's Hospital has prioritized participants' preferences by implementing the Gene Partnership, a genomic research repository, based on the "Informed Cohort" model that offers return of results in accordance with participant preferences. Recognizing that ethical oversight is essential, the Gene Partnership Informed Cohort Oversight Board was convened in 2009.Methods:Over 3 years, the Informed Cohort Oversight Board developed guidelines for the return of individual genomic research results.Results:The Informed Cohort Oversight Board defined its guiding principles as follows: to respect the developing autonomy of pediatric participants and parental decision-making authority by returning results consistent with participants' preferences and to protect participants from harm. Potential harms and strategies to eliminate harm were identified. Guidelines were developed for participant preferences that consider the child's development and family dynamics. The Informed Cohort Oversight Board agreed that to prevent harm, including harms related to interfering with a child's future autonomy, there will be results that should not be returned regardless of participant preferences.Conclusion:The Informed Cohort Oversight Board developed guidelines for the return of results that respect the preferences of parents, children, and adult participants while seeking to protect against harm.Genet Med 16 7, 547-552. © American College of Medical Genetics and Genomics. Source

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