The Pharmacogenomics of Bipolar Disorder study (PGBD): identification of genes for lithium response in a prospective sample.

BMC Psychiatry. 2016;16(1):129

Authors: Oedegaard KJ, Alda M, Anand A, Andreassen OA, Balaraman Y, Berrettini WH, Bhattacharjee A, Brennand KJ, Burdick KE, Calabrese JR, Calkin CV, Claasen A, Coryell WH, Craig D, DeModena A, Frye M, Gage FH, Gao K, Garnham J, Gershon E, Jakobsen P, Leckband SG, McCarthy MJ, McInnis MG, Maihofer AX, Mertens J, Morken G, Nievergelt CM, Nurnberger J, Pham S, Schoeyen H, Shekhtman T, Shilling PD, Szelinger S, Tarwater B, Yao J, Zandi PP, Kelsoe JR

Abstract
BACKGROUND: Bipolar disorder is a serious and common psychiatric disorder characterized by manic and depressive mood switches and a relapsing and remitting course. The cornerstone of clinical management is stabilization and prophylaxis using mood-stabilizing medications to reduce both manic and depressive symptoms. Lithium remains the gold standard of treatment with the strongest data for both efficacy and suicide prevention. However, many patients do not respond to this medication, and clinically there is a great need for tools to aid the clinician in selecting the correct treatment. Large genome wide association studies (GWAS) investigating retrospectively the effect of lithium response are in the pipeline; however, few large prospective studies on genetic predictors to of lithium response have yet been conducted. The purpose of this project is to identify genes that are associated with lithium response in a large prospective cohort of bipolar patients and to better understand the mechanism of action of lithium and the variation in the genome that influences clinical response.
METHODS/DESIGN: This study is an 11-site prospective non-randomized open trial of lithium designed to ascertain a cohort of 700 subjects with bipolar I disorder who experience protocol-defined relapse prevention as a result of treatment with lithium monotherapy. All patients will be diagnosed using the Diagnostic Interview for Genetic Studies (DIGS) and will then enter a 2-year follow-up period on lithium monotherapy if and when they exhibit a score of 1 (normal, not ill), 2 (minimally ill) or 3 (mildly ill) on the Clinical Global Impressions of Severity Scale for Bipolar Disorder (CGI-S-BP Overall Bipolar Illness) for 4 of the 5 preceding weeks. Lithium will be titrated as clinically appropriate, not to exceed serum levels of 1.2 mEq/L. The sample will be evaluated longitudinally using a wide range of clinical scales, cognitive assessments and laboratory tests. On relapse, patients will be discontinued or crossed-over to treatment with valproic acid (VPA) or treatment as usual (TAU). Relapse is defined as a DSM-IV manic, major depressive or mixed episode or if the treating physician decides a change in medication is clinically necessary. The sample will be genotyped for GWAS. The outcome for lithium response will be analyzed as a time to event, where the event is defined as clinical relapse, using a Cox Proportional Hazards model. Positive single nucleotide polymorphisms (SNPs) from past genetic retrospective studies of lithium response, the Consortium on Lithium Genetics (ConLiGen), will be tested in this prospective study sample; a meta-analysis of these samples will then be performed. Finally, neurons will be derived from pluripotent stem cells from lithium responders and non-responders and tested in vivo for response to lithium by gene expression studies. SNPs in genes identified in these cellular studies will also be tested for association to response.
DISCUSSION: Lithium is an extraordinarily important therapeutic drug in the clinical management of patients suffering from bipolar disorder. However, a significant proportion of patients, 30-40 %, fail to respond, and there is currently no method to identify the good lithium responders before initiation of treatment. Converging evidence suggests that genetic factors play a strong role in the variation of response to lithium, but only a few genes have been tested and the samples have largely been retrospective or quite small. The current study will collect an entirely unique sample of 700 patients with bipolar disorder to be stabilized on lithium monotherapy and followed for up to 2 years. This study will produce useful information to improve the understanding of the mechanism of action of lithium and will add to the development of a method to predict individual response to lithium, thereby accelerating recovery and reducing suffering and cost.
TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01272531 Registered: January 6, 2011.

PMID: 27150464 [PubMed - in process]

Genome-wide association study identifies common variants associated with pharmacokinetics of psychotropic drugs.

J Psychopharmacol. 2015 Aug;29(8):884-91

Authors: Athanasiu L, Smorr LL, Tesli M, Røssberg JI, Sønderby IE, Spigset O, Djurovic S, Andreassen OA

Abstract
Individual variation in pharmacokinetics of psychotropic drugs, particularly metabolism, is an important factor to consider in pharmacological treatment in psychiatry. A large proportion of this variance is still not accounted for, but evidence so far suggests the involvement of genetic factors. We performed a genome-wide association study (GWAS) with concentration dose ratio (CDR) as sub-phenotype to assess metabolism rate of psychotropic drugs in a homogenous Norwegian sample of 1334 individuals diagnosed with a severe mental disorder. The GWAS revealed one genome-wide significant marker (rs16935279, p-value=3.95×10(-10), pperm=7.5×10(-4)) located in an intronic region of the lncRNA LOC100505718. Carriers of the minor allele have a lower metabolism rate of antiepileptic drugs compared to major allele carriers. In addition, several nominally significant associations between single nucleotide polymorphisms (SNPs) and CDR for antipsychotic, antidepressant and antiepileptic drugs were disclosed. We consider standardised CDR to be a useful measure of the metabolism rate of a drug. The present findings indicate that common gene variants could affect the metabolism of psychotropic drugs. This warrants further investigations into the functional mechanisms involved as it may lead to identification of predictive markers as well as novel drug targets.

PMID: 25944848 [PubMed - indexed for MEDLINE]

Building a glaucoma interaction network using a text mining approach.

BioData Min. 2016;9:17

Authors: Soliman M, Nasraoui O, Cooper NG

Abstract
BACKGROUND: The volume of biomedical literature and its underlying knowledge base is rapidly expanding, making it beyond the ability of a single human being to read through all the literature. Several automated methods have been developed to help make sense of this dilemma. The present study reports on the results of a text mining approach to extract gene interactions from the data warehouse of published experimental results which are then used to benchmark an interaction network associated with glaucoma. To the best of our knowledge, there is, as yet, no glaucoma interaction network derived solely from text mining approaches. The presence of such a network could provide a useful summative knowledge base to complement other forms of clinical information related to this disease.
RESULTS: A glaucoma corpus was constructed from PubMed Central and a text mining approach was applied to extract genes and their relations from this corpus. The extracted relations between genes were checked using reference interaction databases and classified generally as known or new relations. The extracted genes and relations were then used to construct a glaucoma interaction network. Analysis of the resulting network indicated that it bears the characteristics of a small world interaction network. Our analysis showed the presence of seven glaucoma linked genes that defined the network modularity. A web-based system for browsing and visualizing the extracted glaucoma related interaction networks is made available at http://neurogene.spd.louisville.edu/GlaucomaINViewer/Form1.aspx.
CONCLUSIONS: This study has reported the first version of a glaucoma interaction network using a text mining approach. The power of such an approach is in its ability to cover a wide range of glaucoma related studies published over many years. Hence, a bigger picture of the disease can be established. To the best of our knowledge, this is the first glaucoma interaction network to summarize the known literature. The major findings were a set of relations that could not be found in existing interaction databases and that were found to be new, in addition to a smaller subnetwork consisting of interconnected clusters of seven glaucoma genes. Future improvements can be applied towards obtaining a better version of this network.

PMID: 27152122 [PubMed]

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Inhibition of Cholesterol Esterification in the Adrenal Gland by ATR101/PD132301-2, A Promising Case of Drug Repurposing.

Endocrinology. 2016 May;157(5):1719-1721

Authors: Kroiss M, Fassnacht M

PMID: 27149038 [PubMed - as supplied by publisher]

How Reliable Are Ligand-Centric Methods for Target Fishing?

Front Chem. 2016;4:15

Authors: Peón A, Dang CC, Ballester PJ

Abstract
Computational methods for Target Fishing (TF), also known as Target Prediction or Polypharmacology Prediction, can be used to discover new targets for small-molecule drugs. This may result in repositioning the drug in a new indication or improving our current understanding of its efficacy and side effects. While there is a substantial body of research on TF methods, there is still a need to improve their validation, which is often limited to a small part of the available targets and not easily interpretable by the user. Here we discuss how target-centric TF methods are inherently limited by the number of targets that can possibly predict (this number is by construction much larger in ligand-centric techniques). We also propose a new benchmark to validate TF methods, which is particularly suited to analyse how predictive performance varies with the query molecule. On average over approved drugs, we estimate that only five predicted targets will have to be tested to find two true targets with submicromolar potency (a strong variability in performance is however observed). In addition, we find that an approved drug has currently an average of eight known targets, which reinforces the notion that polypharmacology is a common and strong event. Furthermore, with the assistance of a control group of randomly-selected molecules, we show that the targets of approved drugs are generally harder to predict. The benchmark and a simple target prediction method to use as a performance baseline are available at http://ballester.marseille.inserm.fr/TF-benchmark.tar.gz.

PMID: 27148522 [PubMed]

Chloroquine-containing compounds: a patent review (2010 - 2014).

Expert Opin Ther Pat. 2015;25(9):1003-24

Authors: Njaria PM, Okombo J, Njuguna NM, Chibale K

Abstract
INTRODUCTION: Chloroquine (CQ) has been well known for its antimalarial effects since World War II. However, it is gradually being phased out from clinical use against malaria due to emergence of CQ-resistant Plasmodium falciparum strains. Besides low cost and tolerability, ongoing research has revealed interesting biochemical properties of CQ that have inspired its repurposing/repositioning in the management of various infectious/noninfectious diseases. Consequently, several novel compounds and compositions based on its scaffold have been studied and patented.
AREAS COVERED: In this review, patents describing CQ and its derivatives/compositions over the last 5 years are analyzed. The review highlights the rationale, chemical structures, biological evaluation and potential therapeutic application of CQ, its derivatives and compositions.
EXPERT OPINION: Repurposing efforts have dominantly focused on racemic CQ with no studies exploring the effect of the (R) and (S) enantiomers, which might potentially have additional benefits in other diseases. Additionally, evaluating other similarly acting antimalarials in clinical use and structural analogs could help maximize the intrinsic value of the 4-aminoquinolines. With regard to cancer therapy, successful repurposing of CQ-containing compounds will require linking the mode of action of these antimalarials with the signaling pathways that drive cancer cell proliferation to facilitate the development of a 4-amino-7-chloroquinoline that can be used as a synergistic partner in anticancer combination chemotherapy.

PMID: 26013494 [PubMed - indexed for MEDLINE]

Complex media and enzymatic kinetics.

Anal Chem. 2016 May 5;

Authors: Bakalis EO, Soldà A, Kosmas MK, Rapino S, Zerbetto F

Abstract
Enzymatic reactions in complex environments often take place with concentrations of enzyme comparable to that of substrate molecules. Two such cases occur when an enzyme is used to detect low concentrations of substrate/analyte or inside a living cell. Such concentrations do not agree with standard in-vitro conditions, aimed at satisfying one of the founding hypothesis of the Michaelis-Menten reaction scheme, MM. It would be desirable to generalize the classical approach, and show its applicability to complex systems. A permeable micrometrically-structured hydrogel matrix was fabricated by protein cross-linking. Glucose oxidase enzyme (GOx) was embedded in the matrix and used as a prototypical system. The concentration of H2O2 was monitored in time and fitted by an accurate solution of the enzymatic kinetic scheme, which is expressed in terms of simple functions. The approach can also find applications in digital micro-fluidics and in systems biology where the kinetics response in the linear regimes often employed must be replaced.

PMID: 27149003 [PubMed - as supplied by publisher]

Understanding the Causes and Implications of Endothelial Metabolic Variation in Cardiovascular Disease through Genome-Scale Metabolic Modeling.

Front Cardiovasc Med. 2016;3:10

Authors: McGarrity S, Halldórsson H, Palsson S, Johansson PI, Rolfsson Ó

Abstract
High-throughput biochemical profiling has led to a requirement for advanced data interpretation techniques capable of integrating the analysis of gene, protein, and metabolic profiles to shed light on genotype-phenotype relationships. Herein, we consider the current state of knowledge of endothelial cell (EC) metabolism and its connections to cardiovascular disease (CVD) and explore the use of genome-scale metabolic models (GEMs) for integrating metabolic and genomic data. GEMs combine gene expression and metabolic data acting as frameworks for their analysis and, ultimately, afford mechanistic understanding of how genetic variation impacts metabolism. We demonstrate how GEMs can be used to investigate CVD-related genetic variation, drug resistance mechanisms, and novel metabolic pathways in ECs. The application of GEMs in personalized medicine is also highlighted. Particularly, we focus on the potential of GEMs to identify metabolic biomarkers of endothelial dysfunction and to discover methods of stratifying treatments for CVDs based on individual genetic markers. Recent advances in systems biology methodology, and how these methodologies can be applied to understand EC metabolism in both health and disease, are thus highlighted.

PMID: 27148541 [PubMed]

Corrigendum: Synechocystis: not just a plug-bug for CO2, but a green E. coli.

Front Bioeng Biotechnol. 2016;4:32

Authors: Branco Dos Santos F, Du W, Hellingwerf KJ

Abstract
[This corrects the article on p. 36 in vol. 2, PMID: 25279375.].

PMID: 27148526 [PubMed - as supplied by publisher]

Data-based Reconstruction of Gene Regulatory Networks of Fungal Pathogens.

Front Microbiol. 2016;7:570

Authors: Guthke R, Gerber S, Conrad T, Vlaic S, Durmuş S, Çakır T, Sevilgen FE, Shelest E, Linde J

Abstract
In the emerging field of systems biology of fungal infection, one of the central roles belongs to the modeling of gene regulatory networks (GRNs). Utilizing omics-data, GRNs can be predicted by mathematical modeling. Here, we review current advances of data-based reconstruction of both small-scale and large-scale GRNs for human pathogenic fungi. The advantage of large-scale genome-wide modeling is the possibility to predict central (hub) genes and thereby indicate potential biomarkers and drug targets. In contrast, small-scale GRN models provide hypotheses on the mode of gene regulatory interactions, which have to be validated experimentally. Due to the lack of sufficient quantity and quality of both experimental data and prior knowledge about regulator-target gene relations, the genome-wide modeling still remains problematic for fungal pathogens. While a first genome-wide GRN model has already been published for Candida albicans, the feasibility of such modeling for Aspergillus fumigatus is evaluated in the present article. Based on this evaluation, opinions are drawn on future directions of GRN modeling of fungal pathogens. The crucial point of genome-wide GRN modeling is the experimental evidence, both used for inferring the networks (omics 'first-hand' data as well as literature data used as prior knowledge) and for validation and evaluation of the inferred network models.

PMID: 27148247 [PubMed]

Research Infrastructure for Collaborative Team Science: Challenges in Technology-Supported Workflows in and Across Laboratories, Institutions, and Geographies.

Semin Nephrol. 2015 May;35(3):291-302

Authors: Mirel B, Luo A, Harris M

Abstract
Collaborative research has many challenges. One under-researched challenge is how to align collaborators' research practices and evolving analytical reasoning with technologies and configurations of technologies that best support them. The goal of such alignment is to enhance collaborative problem solving capabilities in research. Toward this end, we draw on our own research and a synthesis of the literature to characterize the workflow of collaborating scientists in systems-level renal disease research. We describe the various phases of a hypothetical workflow among diverse collaborators within and across laboratories, extending from their primary analysis through secondary analysis. For each phase, we highlight required technology supports, and. At time, complementary organizational supports. This survey of supports matching collaborators' analysis practices and needs in research projects to technological support is preliminary, aimed ultimately at developing a research capability framework that can help scientists and technologists mutually understand workflows and technologies that can help enable and enhance them.

PMID: 26215866 [PubMed - indexed for MEDLINE]

APOL1 Kidney Disease Risk Variants: An Evolving Landscape.

Semin Nephrol. 2015 May;35(3):222-36

Authors: Dummer PD, Limou S, Rosenberg AZ, Heymann J, Nelson G, Winkler CA, Kopp JB

Abstract
Apolipoprotein L1 (APOL1) genetic variants account for much of the excess risk of chronic and end-stage kidney disease, which results in a significant global health disparity for persons of African ancestry. We estimate the lifetime risk of kidney disease in APOL1 dual-risk allele individuals to be at least 15%. Experimental evidence suggests a direct role of APOL1 in pore formation, cellular injury, and programmed cell death in renal injury. The APOL1 BH3 motif, often associated with cell death, is unlikely to play a role in APOL1-induced cytotoxicity because it is not conserved within the APOL family and is dispensable for cell death in vitro. We discuss two models for APOL1 trypanolytic activity: one involving lysosome permeabilization and another involving colloid-osmotic swelling of the cell body, as well as their relevance to human pathophysiology. Experimental evidence from human cell culture models suggests that both mechanisms may be operative. A systems biology approach whereby APOL1-associated perturbations in gene and protein expression in affected individuals are correlated with molecular pathways may be productive to elucidate APOL1 function in vivo.

PMID: 26215860 [PubMed - indexed for MEDLINE]

Data-based Reconstruction of Gene Regulatory Networks of Fungal Pathogens.

Front Microbiol. 2016;7:570

Authors: Guthke R, Gerber S, Conrad T, Vlaic S, Durmuş S, Çakır T, Sevilgen FE, Shelest E, Linde J

Abstract
In the emerging field of systems biology of fungal infection, one of the central roles belongs to the modeling of gene regulatory networks (GRNs). Utilizing omics-data, GRNs can be predicted by mathematical modeling. Here, we review current advances of data-based reconstruction of both small-scale and large-scale GRNs for human pathogenic fungi. The advantage of large-scale genome-wide modeling is the possibility to predict central (hub) genes and thereby indicate potential biomarkers and drug targets. In contrast, small-scale GRN models provide hypotheses on the mode of gene regulatory interactions, which have to be validated experimentally. Due to the lack of sufficient quantity and quality of both experimental data and prior knowledge about regulator-target gene relations, the genome-wide modeling still remains problematic for fungal pathogens. While a first genome-wide GRN model has already been published for Candida albicans, the feasibility of such modeling for Aspergillus fumigatus is evaluated in the present article. Based on this evaluation, opinions are drawn on future directions of GRN modeling of fungal pathogens. The crucial point of genome-wide GRN modeling is the experimental evidence, both used for inferring the networks (omics 'first-hand' data as well as literature data used as prior knowledge) and for validation and evaluation of the inferred network models.

PMID: 27148247 [PubMed]

Disease models for the development of therapies for lysosomal storage diseases.

Ann N Y Acad Sci. 2016 May 4;

Authors: Xu M, Motabar O, Ferrer M, Marugan JJ, Zheng W, Ottinger EA

Abstract
Lysosomal storage diseases (LSDs) are a group of rare diseases in which the function of the lysosome is disrupted by the accumulation of macromolecules. The complexity underlying the pathogenesis of LSDs and the small, often pediatric, population of patients make the development of therapies for these diseases challenging. Current treatments are only available for a small subset of LSDs and have not been effective at treating neurological symptoms. Disease-relevant cellular and animal models with high clinical predictability are critical for the discovery and development of new treatments for LSDs. In this paper, we review how LSD patient primary cells and induced pluripotent stem cell-derived cellular models are providing novel assay systems in which phenotypes are more similar to those of the human LSD physiology. Furthermore, larger animal disease models are providing additional tools for evaluation of the efficacy of drug candidates. Early predictors of efficacy and better understanding of disease biology can significantly affect the translational process by focusing efforts on those therapies with the higher probability of success, thus decreasing overall time and cost spent in clinical development and increasing the overall positive outcomes in clinical trials.

PMID: 27144735 [PubMed - as supplied by publisher]

Exploring Rare Diseases in South Africa, a Personal Journey: Time for Electronic Record-keeping.

Ann Med Health Sci Res. 2016 Jan-Feb;6(1):1-3

Authors: Ross IL

PMID: 27144070 [PubMed]

Successful Surgical Excision of a Large Cardiac Fibroma in an Asymptomatic Child: A Case Report.

World J Pediatr Congenit Heart Surg. 2016 May 3;

Authors: Borodinova O, Ostras O, Raad T, Yemets I

Abstract
Cardiac fibroma is a rare disease, and the management of asymptomatic patients is controversial. We report a case of successful surgical excision of a large cardiac fibroma in an asymptomatic child. Surgery should be considered for such a patient, as sudden cardiac death may occur in the absence of premonitory symptoms.

PMID: 27143716 [PubMed - as supplied by publisher]

Natural history of mevalonate kinase deficiency: a literature review.

Pediatr Rheumatol Online J. 2016;14(1):30

Authors: Zhang S

Abstract
Mevalonate kinase deficiency (MKD), a very rare autosomal recessive autoinflammatory disease with multiple organ involvement, presents clinically as hyperimmunoglobulinemia D syndrome (HIDS), a less severe phenotype and more common form, and mevalonic aciduria (MVA), a more severe phenotype and rare form. MKD is characterized by recurrent febrile attacks that are frequently accompanied by lymphadenopathy, gastrointestinal symptoms, arthralgia, myalgia, skin rash, and aphthous ulcers. Patients with MVA also have intrauterine growth retardation, congenital defects (cataracts, shortened limbs, and dysmorphic craniofacial features), neurological disease, and failure to thrive. Mean age at onset of symptoms is within the first year of life. There is a delay by several years between symptom onset and diagnosis, which is in part attributable to the initial misdiagnosis due to the rarity and nonspecific clinical manifestations of disease. The frequency of recurrent febrile attacks is highest in childhood and gradually decreases after adolescence. MKD is associated with rare long-term complications such as type AA amyloidosis, joint contractures, abdominal adhesions, renal angiomyolipoma, and severe pneumococcal infections. Frequent febrile attacks significantly impair several aspects of patients' and caregivers' quality of life, with an adverse impact on patients' daily activities, education, and employment. Lifespan is generally normal for HIDS whereas MVA can be fatal in early childhood.

PMID: 27142780 [PubMed - in process]

Enrichment of rare variants in population isolates: single AICDA mutation responsible for hyper-IgM syndrome type 2 in Finland.

Eur J Hum Genet. 2016 May 4;

Authors: Trotta L, Hautala T, Hämäläinen S, Syrjänen J, Viskari H, Almusa H, Lepisto M, Kaustio M, Porkka K, Palotie A, Seppänen M, Saarela J

Abstract
Antibody class-switch recombination and somatic hypermutation critically depend on the function of activation-induced cytidine deaminase (AID). Rare variants in its gene AICDA have been reported to cause autosomal recessive AID deficiency (autosomal recessive hyper-IgM syndrome type 2 (HIGM2)). Exome sequencing of a multicase Finnish family with an HIGM2 phenotype identified a rare, homozygous, variant (c.416T>C, p.(Met139Thr)) in the AICDA gene, found to be significantly enriched in the Finnish population compared with other populations of European origin (38.56-fold, P<0.001). The population history of Finland, characterized by a restricted number of founders, isolation and several population bottlenecks, has caused enrichment of certain rare disease-causing variants and losses of others, as part of a phenomenon called the Finnish Disease Heritage. Accordingly, rare founder mutations cause the majority of observed Finnish cases in these mostly autosomal recessive disorders that consequently are more frequent in Finland than elsewhere. Screening of all currently known Finnish patients with an HIGM2 phenotype showed them to be homozygous for p.(Met139Thr). All the Finnish p.(Met139Thr) carriers with available data on their geographic descent originated from the eastern and northeastern parts of Finland. They were observed to share more of their genome identity by descent (IBD) than Finns in general (P<0.001), and they all carried a 207.5-kb ancestral haplotype containing the variant. In conclusion, the identified p.(Met139Thr) variant is significantly enriched in Finns and explains all thus far found AID deficiencies in Finland.European Journal of Human Genetics advance online publication, 4 May 2016; doi:10.1038/ejhg.2016.37.

PMID: 27142677 [PubMed - as supplied by publisher]

Fatal Primary Capillary Leak Syndrome in a Late Preterm Newborn.

Indian J Pediatr. 2016 May 4;

Authors: Kulihova K, Prochazkova M, Semberova J, Janota J

Abstract
Primary capillary leak syndrome is a rare disease of unknown etiology, characterized by episodes of vascular collapse and plasma extravasation, which may lead to multiple organ failure. Primary capillary leak is extremely rare in children. The authors report a case of a late preterm newborn with fatal capillary leak syndrome of unknown etiology, manifesting as hypotension unresponsive to treatment, extravasation leading to generalised edema, disseminated intravascular coagulation and finally, multiple organ dysfunction syndrome. Aggressive volumotherapy and a combination of inotropes and high doses of terlipressin did not influence systemic vascular collapse and plasma extravasation. The newborn developed multiple organ failure and died on day 27 of life. Investigations performed failed to reveal any specific cause of capillary leak. This is the first report of a fatal primary capillary leak syndrome in a newborn.

PMID: 27142601 [PubMed - as supplied by publisher]