A systems biology and proteomics-based approach identifies SRC and VEGFA as biomarkers in risk factor mediated coronary heart disease.

Mol Biosyst. 2016 Jun 9;

Authors: V A, Nayar PG, Murugesan R, S S, Krishnan J, Ahmed SS

Abstract
Coronary heart disease (CHD) is the most common cause of death worldwide. The burden of CHD increases with risk factors such as smoking, hypertension, obesity and diabetes. Several studies have demonstrated the association of these classical risk factors with CHD. However, the mechanisms of these associations remain largely unclear due to the complexity of disease pathophysiology and the lack of an integrative approach that fails to provide a definite understanding of molecular linkage. To overcome these problems, we propose a novel systems biology approach that relates causative genes, interactomes and pathways to elucidate the risk factors mediating the molecular mechanisms and biomarkers for feasible diagnosis. The literature was mined to retrieve the causative genes of each risk factor and CHD to construct protein interactomes. The interactomes were examined to identify 298 common molecular signatures. The common signatures were mapped to the tissue network to synthesize a sub-network consisting of 82 proteins. Further, the dissection of the sub-network provides functional modules representing a diverse range of molecular functions, including the AKT/p13k, MAPK and wnt pathways. Also, the prioritization of functional modules identifies SRC, VEGFA and HIF1A as potential candidate markers. Further, we validate these candidates with the existing markers CRP, NOS3 and VCAM1 in the serum of 63 individuals, 33 with CHD and 30 controls, using ELISA. SRC, VEGFA, H1F1A, CRP and NOS3 were significantly altered in patients compared to controls. These results support the utility of these candidate markers for the diagnosis of CHD. Overall, our molecular observations indicate the influence of risk factors in the pathophysiology of CHD and identify serum markers for diagnosis.

PMID: 27279347 [PubMed - as supplied by publisher]

Global, quantitative and dynamic mapping of protein subcellular localization.

Elife. 2016 Jun 9;5

Authors: Itzhak DN, Tyanova S, Cox J, Borner GH

Abstract
Subcellular localization critically influences protein function, and cells control protein localization to regulate biological processes. We have developed and applied Dynamic Organellar Maps, a proteomic method that allows global mapping of protein translocation events. We initially used maps statically to generate a database with localization and absolute copy number information for over 8,700 proteins from HeLa cells, approaching comprehensive coverage. All major organelles were resolved, with exceptional prediction accuracy (estimated at >92%). Combining spatial and abundance information yielded an unprecedented quantitative view of HeLa cell anatomy and organellar composition, at the protein level. We subsequently demonstrated the dynamic capabilities of the approach by capturing translocation events following EGF stimulation, which we integrated into a quantitative model. Dynamic Organellar Maps enable the proteome-wide analysis of physiological protein movements, without requiring any reagents specific to the investigated process, and will thus be widely applicable in cell biology.

PMID: 27278775 [PubMed - as supplied by publisher]

Applying NGS Data to Find Evolutionary Network Biomarkers from the Early and Late Stages of Hepatocellular Carcinoma.

Biomed Res Int. 2015;2015:391475

Authors: Wong YH, Wu CC, Lin CL, Chen TS, Chang TH, Chen BS

Abstract
Hepatocellular carcinoma (HCC) is a major liver tumor (~80%), besides hepatoblastomas, angiosarcomas, and cholangiocarcinomas. In this study, we used a systems biology approach to construct protein-protein interaction networks (PPINs) for early-stage and late-stage liver cancer. By comparing the networks of these two stages, we found that the two networks showed some common mechanisms and some significantly different mechanisms. To obtain differential network structures between cancer and noncancer PPINs, we constructed cancer PPIN and noncancer PPIN network structures for the two stages of liver cancer by systems biology method using NGS data from cancer cells and adjacent noncancer cells. Using carcinogenesis relevance values (CRVs), we identified 43 and 80 significant proteins and their PPINs (network markers) for early-stage and late-stage liver cancer. To investigate the evolution of network biomarkers in the carcinogenesis process, a primary pathway analysis showed that common pathways of the early and late stages were those related to ordinary cancer mechanisms. A pathway specific to the early stage was the mismatch repair pathway, while pathways specific to the late stage were the spliceosome pathway, lysine degradation pathway, and progesterone-mediated oocyte maturation pathway. This study provides a new direction for cancer-targeted therapies at different stages.

PMID: 26366411 [PubMed - indexed for MEDLINE]

Mining clinical attributes of genomic variants through assisted literature curation in Egas.

Database (Oxford). 2016;2016

Authors: Matos S, Campos D, Pinho R, Silva RM, Mort M, Cooper DN, Oliveira JL

Abstract
The veritable deluge of biological data over recent years has led to the establishment of a considerable number of knowledge resources that compile curated information extracted from the literature and store it in structured form, facilitating its use and exploitation. In this article, we focus on the curation of inherited genetic variants and associated clinical attributes, such as zygosity, penetrance or inheritance mode, and describe the use of Egas for this task. Egas is a web-based platform for text-mining assisted literature curation that focuses on usability through modern design solutions and simple user interactions. Egas offers a flexible and customizable tool that allows defining the concept types and relations of interest for a given annotation task, as well as the ontologies used for normalizing each concept type. Further, annotations may be performed on raw documents or on the results of automated concept identification and relation extraction tools. Users can inspect, correct or remove automatic text-mining results, manually add new annotations, and export the results to standard formats. Egas is compatible with the most recent versions of Google Chrome, Mozilla Firefox, Internet Explorer and Safari and is available for use at https://demo.bmd-software.com/egas/Database URL: https://demo.bmd-software.com/egas/.

PMID: 27278817 [PubMed - in process]

Overlap in drug-disease associations between clinical practice guidelines and drug structured product label indications.

J Biomed Semantics. 2016;7:37

Authors: Leung TI, Dumontier M

Abstract
BACKGROUND: Clinical practice guidelines (CPGs) recommend pharmacologic treatments for clinical conditions, and drug structured product labels (SPLs) summarize approved treatment indications. Both resources are intended to promote evidence-based medical practices and guide clinicians' prescribing decisions. However, it is unclear how well CPG recommendations about pharmacologic therapies match SPL indications for recommended drugs. In this study, we perform text mining of CPG summaries to examine drug-disease associations in CPG recommendations and in SPL treatment indications for 15 common chronic conditions.
METHODS: We constructed an initial text corpus of guideline summaries from the National Guideline Clearinghouse (NGC) from a set of manually selected ICD-9 codes for each of the 15 conditions. We obtained 377 relevant guideline summaries and their Major Recommendations section, which excludes guidelines for pediatric patients, pregnant or breastfeeding women, or for medical diagnoses not meeting inclusion criteria. A vocabulary of drug terms was derived from five medical taxonomies. We used named entity recognition, in combination with dictionary-based and ontology-based methods, to identify drug term occurrences in the text corpus and construct drug-disease associations. The ATC (Anatomical Therapeutic Chemical Classification) was utilized to perform drug name and drug class matching to construct the drug-disease associations from CPGs. We then obtained drug-disease associations from SPLs using conditions mentioned in their Indications section in SIDER. The primary outcomes were the frequency of drug-disease associations in CPGs and SPLs, and the frequency of overlap between the two sets of drug-disease associations, with and without using taxonomic information from ATC.
RESULTS: Without taxonomic information, we identified 1444 drug-disease associations across CPGs and SPLs for 15 common chronic conditions. Of these, 195 drug-disease associations overlapped between CPGs and SPLs, 917 associations occurred in CPGs only and 332 associations occurred in SPLs only. With taxonomic information, 859 unique drug-disease associations were identified, of which 152 of these drug-disease associations overlapped between CPGs and SPLs, 541 associations occurred in CPGs only, and 166 associations occurred in SPLs only.
CONCLUSIONS: Our results suggest that CPG-recommended pharmacologic therapies and SPL indications do not overlap frequently when identifying drug-disease associations using named entity recognition, although incorporating taxonomic relationships between drug names and drug classes into the approach improves the overlap. This has important implications in practice because conflicting or inconsistent evidence may complicate clinical decision making and implementation or measurement of best practices.

PMID: 27277160 [PubMed - in process]

Systematic Analysis of Endometrial Cancer-Associated Hub Proteins Based on Text Mining.

Biomed Res Int. 2015;2015:615825

Authors: Gao H, Zhang Z

Abstract
OBJECTIVE: The aim of this study was to systematically characterize the expression of endometrial cancer- (EC-) associated genes and to analysis the functions, pathways, and networks of EC-associated hub proteins.
METHODS: Gene data for EC were extracted from the PubMed (MEDLINE) database using text mining based on NLP. PPI networks and pathways were integrated and obtained from the KEGG and other databases. Proteins that interacted with at least 10 other proteins were identified as the hub proteins of the EC-related genes network.
RESULTS: A total of 489 genes were identified as EC-related with P < 0.05, and 32 pathways were identified as significant (P < 0.05, FDR < 0.05). A network of EC-related proteins that included 271 interactions was constructed. The 17 proteins that interact with 10 or more other proteins (P < 0.05, FDR < 0.05) were identified as the hub proteins of this PPI network of EC-related genes. These 17 proteins are EGFR, MET, PDGFRB, CCND1, JUN, FGFR2, MYC, PIK3CA, PIK3R1, PIK3R2, KRAS, MAPK3, CTNNB1, RELA, JAK2, AKT1, and AKT2.
CONCLUSION: Our data may help to reveal the molecular mechanisms of EC development and provide implications for targeted therapy for EC. However, corrections between certain proteins and EC continue to require additional exploration.

PMID: 26366417 [PubMed - indexed for MEDLINE]

31 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

("orphan disease" OR "rare disease" OR "orphan diseases" OR "rare diseases")

These pubmed results were generated on 2016/06/09

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

12 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

Pharmacogenomics[Title/Abstract] AND ("2005/01/01"[PDAT] : "3000"[PDAT])

These pubmed results were generated on 2016/06/09

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

21 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Cystic Fibrosis"

These pubmed results were generated on 2016/06/09

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

15 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Systems Biology"[Title/Abstract] AND ("2005/01/01"[PDAT] : "3000"[PDAT])

These pubmed results were generated on 2016/06/09

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

The role of drug profiles as similarity metrics: applications to repurposing, adverse effects detection and drug-drug interactions.

Brief Bioinform. 2016 Jun 5;

Authors: Vilar S, Hripcsak G

Abstract
Explosion of the availability of big data sources along with the development in computational methods provides a useful framework to study drugs' actions, such as interactions with pharmacological targets and off-targets. Databases related to protein interactions, adverse effects and genomic profiles are available to be used for the construction of computational models. In this article, we focus on the description of biological profiles for drugs that can be used as a system to compare similarity and create methods to predict and analyze drugs' actions. We highlight profiles constructed with different biological data, such as target-protein interactions, gene expression measurements, adverse effects and disease profiles. We focus on the discovery of new targets or pathways for drugs already in the pharmaceutical market, also called drug repurposing, in the interaction with off-targets responsible for adverse reactions and in drug-drug interaction analysis. The current and future applications, strengths and challenges facing all these methods are also discussed. Biological profiles or signatures are an important source of data generation to deeply analyze biological actions with important implications in drug-related studies.

PMID: 27273288 [PubMed - as supplied by publisher]

A Platform to Enable the Pharmacological Profiling of Small Molecules in Gel-Based Electrophoretic Mobility Shift Assays.

J Biomol Screen. 2016 Jun 6;

Authors: Foley TL, Dorjsuren D, Dexheimer TS, Burkart MD, Wight WC, Simeonov A

Abstract
We describe a polyacrylamide gel casting cassette that overcomes limitations of commercially available gel electrophoresis equipment. This apparatus molds a single polyacrylamide gel that can evaluate more than 200 samples in parallel, is loaded with a multichannel pipettor, and is flexible with respect to composition of the separating matrix. We demonstrate its use to characterize inhibitors of enzymes that modify protein and nucleic acid substrates. Throughputs of greater than 1000 samples per day were achieved when this system was paired with a quantitative laser-based imaging system, yielding data of remarkable quality.

PMID: 27269812 [PubMed - as supplied by publisher]

Treatment of Disseminated Leishmaniasis With Liposomal Amphotericin B.

Clin Infect Dis. 2015 Sep 15;61(6):945-9

Authors: Machado PR, Rosa ME, Guimarães LH, Prates FV, Queiroz A, Schriefer A, Carvalho EM

Abstract
BACKGROUND: Disseminated leishmaniasis (DL) is a severe and emerging form of American tegumentary leishmaniasis, associated primarily with infection by Leishmania brasiliensis. DL is defined by the presence of ≥10 mixed-type lesions such as inflammatory papules and ulcers, located in ≥2 body parts. Most patients have hundreds of lesions all over the body, and mucosal involvement is detected in up to 44% of cases. DL is a difficult to cure disease and pentavalent antimony (Sb(v)) is used as standard treatment, its highest dosage being 20 mg/kg/day, for 30 days. However, less than 25% of DL cases will be cured after standard therapy, and the majority of cases will require more than one course of Sb(v) for a cure. In this context, new therapies are needed that offer a higher cure rate and a better safety profile, with convenience in drug administration.
METHODS: We have evaluated liposomal amphotericin B in 20 patients with DL in an open clinical trial. The total dose ranged from 17 to 37 mg/kg, used in 7 to 14 days of treatment.
RESULTS: Cure rate at 3 months after therapy was 70%. One relapse was documented 4 months after treatment, producing a final cure rate of 65%. Although liposomal amphotericin B was considered well tolerated, mild adverse events were documented in 75% of the patients.
CONCLUSIONS: Liposomal amphotericin B is an effective therapy for DL, with a higher final cure rate of 75% observed when used in a total dose above 30 mg/kg.
CLINICAL TRIALS REGISTRATION: NCT02025491.

PMID: 26048961 [PubMed - indexed for MEDLINE]

Pharmacological inhibition of apical sodium-dependent bile acid transporter changes bile composition and blocks progression of sclerosing cholangitis in multidrug resistance 2 knockout mice.

Hepatology. 2016 Feb;63(2):512-23

Authors: Miethke AG, Zhang W, Simmons J, Taylor AE, Shi T, Shanmukhappa SK, Karns R, White S, Jegga AG, Lages CS, Nkinin S, Keller BT, Setchell KD

Abstract
UNLABELLED: Deficiency of multidrug resistance 2 (mdr2), a canalicular phospholipid floppase, leads to excretion of low-phospholipid "toxic" bile causing progressive cholestasis. We hypothesize that pharmacological inhibition of the ileal, apical sodium-dependent bile acid transporter (ASBT), blocks progression of sclerosing cholangitis in mdr2(-/-) mice. Thirty-day-old, female mdr2(-/-) mice were fed high-fat chow containing 0.006% SC-435, a minimally absorbed, potent inhibitor of ASBT, providing, on average, 11 mg/kg/day of compound. Bile acids (BAs) and phospholipids were measured by mass spectrometry. Compared with untreated mdr2(-/-) mice, SC-435 treatment for 14 days increased fecal BA excretion by 8-fold, lowered total BA concentration in liver by 65%, reduced total BA and individual hydrophobic BA concentrations in serum by >98%, and decreased plasma alanine aminotransferase, total bilirubin, and serum alkaline phosphatase levels by 86%, 93%, and 55%, respectively. Liver histology of sclerosing cholangitis improved, and extent of fibrosis decreased concomitant with reduction of hepatic profibrogenic gene expression. Biliary BA concentrations significantly decreased and phospholipids remained low and unchanged with treatment. The phosphatidylcholine (PC)/BA ratio in treated mice corrected toward a ratio of 0.28 found in wild-type mice, indicating decreased bile toxicity. Hepatic RNA sequencing studies revealed up-regulation of putative anti-inflammatory and antifibrogenic genes, including Ppara and Igf1, and down-regulation of several proinflammatory genes, including Ccl2 and Lcn2, implicated in leukocyte recruitment. Flow cytometric analysis revealed significant reduction of frequencies of hepatic CD11b(+) F4/80(+) Kupffer cells and CD11b(+) Gr1(+) neutrophils, accompanied by expansion of anti-inflammatory Ly6C(-) monocytes in treated mdr2(-/-) mice.
CONCLUSION: Inhibition of ASBT reduces BA pool size and retention of hydrophobic BA, favorably alters the biliary PC/BA ratio, profoundly changes the hepatic transcriptome, attenuates recruitment of leukocytes, and abrogates progression of murine sclerosing cholangitis.

PMID: 26172874 [PubMed - indexed for MEDLINE]

Metabolic effects of bariatric surgery in mouse models of circadian disruption.

Int J Obes (Lond). 2015 Aug;39(8):1310-8

Authors: Arble DM, Sandoval DA, Turek FW, Woods SC, Seeley RJ

Abstract
BACKGROUND/OBJECTIVES: Mounting evidence supports a link between circadian disruption and metabolic disease. Humans with circadian disruption (for example, night-shift workers) have an increased risk of obesity and cardiometabolic diseases compared with the non-disrupted population. However, it is unclear whether the obesity and obesity-related disorders associated with circadian disruption respond to therapeutic treatments as well as individuals with other types of obesity.
SUBJECTS/METHODS: Here, we test the effectiveness of the commonly used bariatric surgical procedure, Vertical Sleeve Gastrectomy (VSG), in mouse models of genetic and environmental circadian disruption.
RESULTS: VSG led to a reduction in body weight and fat mass in both Clock(Δ19) mutant and constant-light mouse models (P<0.05), resulting in an overall metabolic improvement independent of circadian disruption. Interestingly, the decrease in body weight occurred without altering diurnal feeding or activity patterns (P>0.05). Within circadian-disrupted models, VSG also led to improved glucose tolerance and lipid handling (P<0.05).
CONCLUSIONS: Together these data demonstrate that VSG is an effective treatment for the obesity associated with circadian disruption, and that the potent effects of bariatric surgery are orthogonal to circadian biology. However, as the effects of bariatric surgery are independent of circadian disruption, VSG cannot be considered a cure for circadian disruption. These data have important implications for circadian-disrupted obese patients. Moreover, these results reveal new information about the metabolic pathways governing the effects of bariatric surgery as well as of circadian disruption.

PMID: 25869599 [PubMed - indexed for MEDLINE]

The SBOL Stack: A Platform for Storing, Publishing, and Sharing Synthetic Biology Designs.

ACS Synth Biol. 2016 Jun 7;

Authors: Madsen C, McLaughlin JA, Misirli G, Pocock M, Flanagan K, Hallinan J, Wipat A

Abstract
Recently, synthetic biologists have developed the Synthetic Biology Open Language (SBOL), a data exchange standard for descriptions of genetic parts, devices, modules, and systems. The goals of this standard are to allow scientists to exchange designs of biological parts and systems, to facilitate the storage of genetic designs in repositories, and to facilitate the description of genetic designs in publications. In order to achieve these goals, the development of an infrastructure to store, retrieve, and exchange SBOL data is necessary. To address this problem, we have developed the SBOL Stack, a Resource Description Framework (RDF) database specifically designed for the storage, integration, and publication of SBOL data. This database allows users to define a library of synthetic parts and designs as a service, to share SBOL data with collaborators, and to store designs of biological systems locally. The database also allows external data sources to be integrated by mapping them to the SBOL data model. The SBOL Stack includes two Web interfaces: the SBOL Stack API and SynBioHub. While the former is designed for developers, the latter allows users to upload new SBOL biological designs, download SBOL documents, search by keyword, and visualize SBOL data. Since the SBOL Stack is based on semantic Web technology, the inherent distributed querying functionality of RDF databases can be used to allow different SBOL stack databases to be queried simultaneously, and therefore, data can be shared between different institutes, centers, or other users.

PMID: 27268205 [PubMed - as supplied by publisher]

Passage-Based Bibliographic Coupling: An Inter-Article Similarity Measure for Biomedical Articles.

PLoS One. 2015;10(10):e0139245

Authors: Liu RL

Abstract
Biomedical literature is an essential source of biomedical evidence. To translate the evidence for biomedicine study, researchers often need to carefully read multiple articles about specific biomedical issues. These articles thus need to be highly related to each other. They should share similar core contents, including research goals, methods, and findings. However, given an article r, it is challenging for search engines to retrieve highly related articles for r. In this paper, we present a technique PBC (Passage-based Bibliographic Coupling) that estimates inter-article similarity by seamlessly integrating bibliographic coupling with the information collected from context passages around important out-link citations (references) in each article. Empirical evaluation shows that PBC can significantly improve the retrieval of those articles that biomedical experts believe to be highly related to specific articles about gene-disease associations. PBC can thus be used to improve search engines in retrieving the highly related articles for any given article r, even when r is cited by very few (or even no) articles. The contribution is essential for those researchers and text mining systems that aim at cross-validating the evidence about specific gene-disease associations.

PMID: 26440794 [PubMed - indexed for MEDLINE]

Analysis of the human diseasome using phenotype similarity between common, genetic, and infectious diseases.

Sci Rep. 2015;5:10888

Authors: Hoehndorf R, Schofield PN, Gkoutos GV

Abstract
Phenotypes are the observable characteristics of an organism arising from its response to the environment. Phenotypes associated with engineered and natural genetic variation are widely recorded using phenotype ontologies in model organisms, as are signs and symptoms of human Mendelian diseases in databases such as OMIM and Orphanet. Exploiting these resources, several computational methods have been developed for integration and analysis of phenotype data to identify the genetic etiology of diseases or suggest plausible interventions. A similar resource would be highly useful not only for rare and Mendelian diseases, but also for common, complex and infectious diseases. We apply a semantic text-mining approach to identify the phenotypes (signs and symptoms) associated with over 6,000 diseases. We evaluate our text-mined phenotypes by demonstrating that they can correctly identify known disease-associated genes in mice and humans with high accuracy. Using a phenotypic similarity measure, we generate a human disease network in which diseases that have similar signs and symptoms cluster together, and we use this network to identify closely related diseases based on common etiological, anatomical as well as physiological underpinnings.

PMID: 26051359 [PubMed - indexed for MEDLINE]

Nontuberculous mycobacteria in cystic fibrosis patients on the Island of Gran Canaria. A population study.

J Infect Chemother. 2016 Jun 1;

Authors: Campos-Herrero MI, Chamizo FJ, Caminero JA, Gilarranz R, Cabrera G, Cuyás J

Abstract
OBJECTIVE: To determine the prevalence of nontuberculous mycobacteria (NTM) colonization and disease in cystic fibrosis (CF) patients.
PATIENTS AND METHODS: All the CF patients followed-up from 2002 to 2012 with three acid-fast bacilli (AFB) cultures were included. The American Thoracic Society (ATS) criteria for NTM lung disease were applied.
RESULTS: Forty-four of the 53 patients being followed-up were included. The mean time of follow-up was 7.0 years. A total of 18 patients (40.9%) were NTM positive. The NTN mean annual prevalence was 14.1%. The risk of Mycobacterium abscessus complex was higher in the group of 10-14 years-old (p < 0.001). Ten patients (22.7% of the entire cohort) met the ATS microbiological criteria. The mean annual prevalence of NTM disease was 10.4%. Seven patients (four with Mycobacterium simiae and three with M. abscessus complex) with multiple positive cultures, positive AFB smears and clinical worsening were treated. Three patients with M. simiae and none of those with M. abscessus were cured.
CONCLUSIONS: Overall NTM prevalence of colonization and disease were high in our CF patients. Patients <15 years old had a higher risk of M. abscessus complex colonization. Multiple positive cultures or positive AFB smears were associated with disease.

PMID: 27262751 [PubMed - as supplied by publisher]

Cystic fibrosis in Latin America-Improving the awareness.

J Cyst Fibros. 2016 Jun 1;

Authors: Silva Filho LV, Castaños C, Ruíz HH

Abstract
The burden of cystic fibrosis (CF) in Latin America is being increasingly recognized and is significant compared with other regions of the world. In this short communication, we assess the current situation in some Latin American countries and make suggestions for possible directions for future focus. We discuss the work that remains in deciphering how the various genetic, environmental and medical factors interact and influence outcomes in different ethnic groups. We also consider the need for consistency in both research and access to services across Latin America, including CF registries, neonatal screening programs, access to specialized CF healthcare practitioners, transition to adult clinics and treatment regimens. Progress in these areas is likely to build on the advances to date, and improve the lives of patients in Latin America who are affected by this debilitating and life-limiting disorder.

PMID: 27262748 [PubMed - as supplied by publisher]