Childrens Hospital Informatics Program

Boston, MA, United States

Childrens Hospital Informatics Program

Boston, MA, United States
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Shea B.S.,Harvard University | Kho A.T.,Harvard Massachusetts Institute of Technology Division of Health Sciences and Technology | Kho A.T.,Childrens Hospital Informatics Program | Tager A.M.,Harvard University
Journal of Cell Biology | Year: 2010

Tissue stiffening is a hallmark of fibrotic disorders but has traditionally been regarded as an outcome of fibrosis, not a contributing factor to pathogenesis. In this study, we show that fibrosis induced by bleomycin injury in the murine lung locally increases median tissue stiffness sixfold relative to normal lung parenchyma. Across this pathophysiological stiffness range, cultured lung fibroblasts transition from a surprisingly quiescent state to progressive increases in proliferation and matrix synthesis, accompanied by coordinated decreases in matrix proteolytic gene expression. Increasing matrix stiffness strongly suppresses fibroblast expression of COX-2 (cyclooxygenase-2) and synthesis of prostaglandin E2 (PGE2), an autocrine inhibitor of fibrogenesis. Exogenous PGE2 or an agonist of the prostanoid EP2 receptor completely counteracts the proliferative and matrix synthetic effects caused by increased stiffness. Together, these results demonstrate a dominant role for normal tissue compliance, acting in part through autocrine PGE2, in maintaining fibroblast quiescence and reveal a feedback relationship between matrix stiffening, COX-2 suppression, and fibroblast activation that promotes and amplifies progressive fibrosis. © 2010 Liu et al.


Kim T.-M.,Harvard University | Xi R.,Harvard University | Xi R.,Peking University | Luquette L.J.,Harvard University | And 5 more authors.
Genome Research | Year: 2013

A large database of copy number profiles from cancer genomes can facilitate the identification of recurrent chromosomal alterations that often contain key cancer-related genes. It can also be used to explore low-prevalence genomic events such as chromothripsis. In this study, we report an analysis of 8227 human cancer copy number profiles obtained from 107 array comparative genomic hybridization (CGH) studies. Our analysis reveals similarity of chromosomal arm-level alterations among developmentally related tumor types as well as a number of co-occurring pairs of arm-level alterations. Recurrent ("pan-lineage") focal alterations identified across diverse tumor types show an enrichment of known cancerrelated genes and genes with relevant functions in cancer-associated phenotypes (e.g., kinase and cell cycle). Tumor typespecific ("lineage-restricted") alterations and their enriched functional categories were also identified. Furthermore, we developed an algorithm for detecting regions in which the copy number oscillates rapidly between fixed levels, indicative of chromothripsis. We observed these massive genomic rearrangements in 1%-2% of the samples with variable tumor type-specific incidence rates. Taken together, our comprehensive view of copy number alterations provides a framework for understanding the functional significance of various genomic alterations in cancer genomes. © 2013, Published by Cold Spring Harbor Laboratory Press.


Gluskin R.T.,Childrens Hospital Informatics Program | Johansson M.A.,Centers for Disease Control and Prevention | Santillana M.,Harvard University | Brownstein J.S.,Childrens Hospital Informatics Program
PLoS Neglected Tropical Diseases | Year: 2014

Dengue is a common and growing problem worldwide, with an estimated 70-140 million cases per year. Traditional, healthcare-based, government-implemented dengue surveillance is resource intensive and slow. As global Internet use has increased, novel, Internet-based disease monitoring tools have emerged. Google Dengue Trends (GDT) uses near real-time search query data to create an index of dengue incidence that is a linear proxy for traditional surveillance. Studies have shown that GDT correlates highly with dengue incidence in multiple countries on a large spatial scale. This study addresses the heterogeneity of GDT at smaller spatial scales, assessing its accuracy at the state-level in Mexico and identifying factors that are associated with its accuracy. We used Pearson correlation to estimate the association between GDT and traditional dengue surveillance data for Mexico at the national level and for 17 Mexican states. Nationally, GDT captured approximately 83% of the variability in reported cases over the 9 study years. The correlation between GDT and reported cases varied from state to state, capturing anywhere from 1% of the variability in Baja California to 88% in Chiapas, with higher accuracy in states with higher dengue average annual incidence. A model including annual average maximum temperature, precipitation, and their interaction accounted for 81% of the variability in GDT accuracy between states. This climate model was the best indicator of GDT accuracy, suggesting that GDT works best in areas with intense transmission, particularly where local climate is well suited for transmission. Internet accessibility (average ∼36%) did not appear to affect GDT accuracy. While GDT seems to be a less robust indicator of local transmission in areas of low incidence and unfavorable climate, it may indicate cases among travelers in those areas. Identifying the strengths and limitations of novel surveillance is critical for these types of data to be used to make public health decisions and forecasting models. © 2014.


Wilson K.,Ottawa Health Research Institute | Brownstein J.S.,Childrens Hospital Informatics Program | Brownstein J.S.,Harvard University | Fidler D.P.,Indiana University Bloomington
Health Policy and Planning | Year: 2010

The International Health Regulations (2005) [IHR(2005)] represent a potentially revolutionary change in global health governance. The use of the regulations by the World Health Organization (WHO) to respond to the outbreak of pandemic influenza A 2009-H1N1 highlights the importance of the regulations to protecting global health security. As the 2009-H1N1 pandemic illustrated, the IHR(2005) have provided a more robust framework for responding to public health emergencies of international concern (PHEICs), through requiring reporting of serious disease events, strengthening how countries and WHO communicate concerning health threats, empowering the WHO Director-General to declare the existence of PHEICs and to issue temporary recommendations for responding to them, and requiring countries not to implement measures that unnecessarily restrict trade and travel or infringe on human rights. However, limitations to the effectiveness of the IHR(2005) revealed in the 2009-H1N1 pandemic include continuing inadequacies in surveillance and response capacities within some countries, violations of IHR(2005) rules and a potentially narrowing scope of application only to influenza-like pandemic events. These limitations could undermine the IHR(2005)'s potential to contribute to national and global efforts to detect and mitigate future public health emergencies. Support for the IHR(2005) should be broadened and deepened to improve their utility as a tool to strengthen global health security. © The Author 2010; all rights reserved.


Weitzman E.R.,Childrens Hospital Informatics Program
BMC medical informatics and decision making | Year: 2012

Data stored in personally controlled health records (PCHRs) may hold value for clinicians and public health entities, if patients and their families will share them. We sought to characterize consumer willingness and unwillingness (reticence) to share PCHR data across health topics, and with different stakeholders, to advance understanding of this issue. Cross-sectional 2009 Web survey of repeat PCHR users who were patients over 18 years old or parents of patients, to assess willingness to share their PCHR data with an-out-of-hospital provider to support care, and the state/local public health authority to support monitoring; the odds of reticence to share PCHR information about ten exemplary health topics were estimated using a repeated measures approach. Of 261 respondents (56% response rate), more reported they would share all information with the state/local public health authority (63.3%) than with an out-of-hospital provider (54.1%) (OR 1.5, 95% CI 1.1, 1.9; p = .005); few would not share any information with these parties (respectively, 7.9% and 5.2%). For public health sharing, reticence was higher for most topics compared to contagious illness (ORs 4.9 to 1.4, all p-values < .05), and reflected concern about anonymity (47.2%), government insensitivity (41.5%), discrimination (24%). For provider sharing, reticence was higher for all topics compared to contagious illness (ORs 6.3 to 1.5, all p-values < .05), and reflected concern for relevance (52%), disclosure to insurance (47.6%) and/or family (20.5%). Pediatric patients and their families are often willing to share electronic health information to support health improvement, but remain cautious. Robust trust models for PCHR sharing are needed.


Kohane I.S.,Childrens Hospital Informatics Program | Kohane I.S.,Harvard University | Hsing M.,Childrens Hospital Informatics Program | Hsing M.,Harvard University | And 2 more authors.
Genetics in Medicine | Year: 2012

Purpose: With the advent of whole-genome sequencing made clinically available, the number of incidental findings is likely to rise. The false-positive incidental findings are of particular clinical concern. We provide estimates on the size of these false-positive findings and classify them into four broad categories. Methods: Whole-genome sequences (WGS) of nine individuals were scanned with several comprehensive public annotation databases and average estimates for the number of findings. These estimates were then evaluated in the perspective of various sources of false-positive annotation errors. Results: At present there are four main sources of false-positive incidental findings: erroneous annotations, sequencing error, incorrect penetrance estimates, and multiple hypothesis testing. Of these, the first two are likely to be addressed in the near term. Conservatively, current methods deliver hundreds of false-positive incidental findings per individual. Conclusion: The burden of false-positives in whole-genome sequence interpretation threatens current capabilities to deliver clinical-grade whole-genome clinical interpretation. A new generation of population studies and retooling of the clinical decision-support approach will be required to overcome this threat. ©American College of Medical Genetics and Genomics.


Nsoesie E.O.,Childrens Hospital Informatics Program | Nsoesie E.O.,Harvard University | Kluberg S.A.,Childrens Hospital Informatics Program | Brownstein J.S.,Childrens Hospital Informatics Program | And 2 more authors.
Preventive Medicine | Year: 2014

Objective: Traditional surveillance systems capture only a fraction of the estimated 48. million yearly cases of foodborne illness in the United States. We assessed whether foodservice reviews on Yelp.com (a business review site) can be used to support foodborne illness surveillance efforts. Methods: We obtained reviews from 2005 to 2012 of 5824 foodservice businesses closest to 29 colleges. After extracting recent reviews describing episodes of foodborne illness, we compared implicated foods to foods in outbreak reports from the U.S. Centers for Disease Control and Prevention (CDC). Results: Broadly, the distribution of implicated foods across five categories was as follows: aquatic (16% Yelp, 12% CDC), dairy-eggs (23% Yelp, 23% CDC), fruits-nuts (7% Yelp, 7% CDC), meat-poultry (32% Yelp, 33% CDC), and vegetables (22% Yelp, 25% CDC). The distribution of foods across 19 more specific food categories was also similar, with Spearman correlations ranging from 0.60 to 0.85 for 2006-2011. The most implicated food categories in both Yelp and CDC were beef, dairy, grains-beans, poultry and vine-stalk. Conclusions: Based on observations in this study and the increased usage of social media, we posit that online illness reports could complement traditional surveillance systems by providing near real-time information on foodborne illnesses, implicated foods and locations. © 2014.


Agarwal S.,University of Wisconsin - Milwaukee | Yu H.,University of Wisconsin - Milwaukee | Kohane I.,Childrens Hospital Informatics Program
BMC Bioinformatics | Year: 2011

Background: Negated biomedical events are often ignored by text-mining applications; however, such events carry scientific significance. We report on the development of BioN∅T, a database of negated sentences that can be used to extract such negated events.Description: Currently BioN∅T incorporates ≈32 million negated sentences, extracted from over 336 million biomedical sentences from three resources: ≈2 million full-text biomedical articles in Elsevier and the PubMed Central, as well as ≈20 million abstracts in PubMed. We evaluated BioN∅T on three important genetic disorders: autism, Alzheimer's disease and Parkinson's disease, and found that BioN∅T is able to capture negated events that may be ignored by experts.Conclusions: The BioN∅T database can be a useful resource for biomedical researchers. BioN∅T is freely available at http://bionot.askhermes.org/. In future work, we will develop semantic web related technologies to enrich BioN∅T. © 2011 Agarwal et al; licensee BioMed Central Ltd.


Tong M.Y.,Harvard University | Cassa C.A.,Childrens Hospital Informatics Program | Kohane I.S.,Harvard University | Kohane I.S.,Childrens Hospital Informatics Program
Bioinformatics | Year: 2011

Summary: Accurate annotations of genomic variants are necessary to achieve full-genome clinical interpretations that are scientifically sound and medically relevant. Many disease associations, especially those reported before the completion of the HGP, are limited in applicability because of potential inconsistencies with our current standards for genomic coordinates, nomenclature and gene structure. In an effort to validate and link variants from the medical genetics literature to an unambiguous reference for each variant, we developed a software pipeline and reviewed 68 641 single amino acid mutations from Online Mendelian Inheritance in Man (OMIM), Human Gene Mutation Database (HGMD) and dbSNP. The frequency of unresolved mutation annotations varied widely among the databases, ranging from 4 to 23%. A taxonomy of primary causes for unresolved mutations was produced. © The Author(s) 2011. Published by Oxford University Press.


Jonikas M.A.,Childrens Hospital Informatics Program | Mandl K.D.,Childrens Hospital Informatics Program | Mandl K.D.,Harvard University
Journal of the American Medical Informatics Association | Year: 2012

Background We sought to measure population-level adherence to antihyperlipidemics, antihypertensives, and oral hypoglycemics, and to develop a model for early identification of subjects at high risk of long-term poor adherence. Methods Prescription-filling data for 2 million subjects derived from a payor's insurance claims were used to evaluate adherence to three chronic drugs over 1 year. We relied on patterns of prescription fills, including the length of gaps in medication possession, to measure adherence among subjects and to build models for predicting poor long-term adherence. Results All prescription fills for a specific drug were sequenced chronologically into drug eras. 61.3% to 66.5% of the prescription patterns contained medication gaps >30 days during the first year of drug use. These interrupted drug eras include long-term discontinuations, where the subject never again filled a prescription for any drug in that category in the dataset, which represent 23.7% to 29.1% of all drug eras. Among the prescription-filling patterns without large medication gaps, 0.8% to 1.3% exhibited long-term poor adherence. Our models identified these subjects as early as 60 days after the first prescription fill, with an area under the curve (AUC) of 0.81. Model performance improved as the predictions were made at later time-points, with AUC values increasing to 0.93 at the 120-day time-point. Conclusions Dispensed medication histories (widely available in real time) are useful for alerting providers about poorly adherent patients and those who will be non-adherent several months later. Efforts to use these data in point of care and decision support facilitating patient are warranted.

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