Cardiopulmonary exercise testing in adolescence following extremely premature birth

BACKGROUND

Although extremely premature birth disrupts lung development, adolescent survivors of extreme prematurity show good clinical and physiologic outcomes. Cardiopulmonary limitations may not be clinically evident at rest. Data regarding exercise limitation in adolescents following preterm birth in the postsurfactant era are limited.

RESEARCH QUESTION

What are the long-term effects of bronchopulmonary dysplasia (BPD) and extreme prematurity (<29 weeks) on ventilatory response during exercise in adolescents in the postsurfactant era?

STUDY DESIGN AND METHODS

We followed a longitudinally recruited cohort of children aged 13-19 years who were born at a gestational age of <29 weeks (study group - SG). We compared the cardiopulmonary exercise testing (CPET) results of those with and without BPD, to their own CPET results from elementary school age (mean 9.09 ± 1.05 years).

RESULTS

Thirty-seven children aged 15.73 ± 1.31 years, mean gestational age 26 weeks ( ± 1.19), completed the study. CPET parameters in adolescence were within the normal range for age, including mean V̇O2 peak of 91% predicted. The BPD and non-BPD subgroups had similar results. In the longitudinal analysis of the SG, improvement was observed in adolescence, compared with elementary school age, in breathing reserve (36.37 ± 18.99 vs. 26.58 ± 17.92, p = 0.044), tidal volume as a fraction of vital capacity achieved at maximal load (0.51 ± 0.13 vs. 0.37 ± 0.08, p < 0.001), and respiratory exchange ratio at maximal load (1.18 ± 0.13 vs. 1.11 ± 0.10, p = 0.021).

INTERPRETATION

In the current cohort, adolescents born extremely premature have essentially normal ventilatory response during exercise, unrelated to BPD diagnosis. CPET results in this population improve over time.

The Human Phenotype Ontology in 2024: phenotypes around the world

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.

The Medical Action Ontology: A tool for annotating and analyzing treatments and clinical management of human disease

BACKGROUND

Navigating the clinical literature to determine the optimal clinical management for rare diseases presents significant challenges. We introduce the Medical Action Ontology (MAxO), an ontology specifically designed to organize medical procedures, therapies, and interventions.

METHODS

MAxO incorporates logical structures that link MAxO terms to numerous other ontologies within the OBO Foundry. Term development involves a blend of manual and semi-automated processes. Additionally, we have generated annotations detailing diagnostic modalities for specific phenotypic abnormalities defined by the Human Phenotype Ontology (HPO). We introduce a web application, POET, that facilitates MAxO annotations for specific medical actions for diseases using the Mondo Disease Ontology.

FINDINGS

MAxO encompasses 1,757 terms spanning a wide range of biomedical domains, from human anatomy and investigations to the chemical and protein entities involved in biological processes. These terms annotate phenotypic features associated with specific disease (using HPO and Mondo). Presently, there are over 16,000 MAxO diagnostic annotations that target HPO terms. Through POET, we have created 413 MAxO annotations specifying treatments for 189 rare diseases.

CONCLUSIONS

MAxO offers a computational representation of treatments and other actions taken for the clinical management of patients. Its development is closely coupled to Mondo and HPO, broadening the scope of our computational modeling of diseases and phenotypic features. We invite the community to contribute disease annotations using POET (https://poet.jax.org/). MAxO is available under the open-source CC-BY 4.0 license (https://github.com/monarch-initiative/MAxO).

FUNDING

NHGRI 1U24HG011449-01A1 and NHGRI 5RM1HG010860-04.

De novo TRPM3 missense variant associated with neurodevelopmental delay and manifestations of cerebral palsy

We identified a de novo heterozygous transient receptor potential cation channel subfamily M (melastatin) member 3 (TRPM3) missense variant, p.(Asn1126Asp), in a patient with developmental delay and manifestations of cerebral palsy (CP) using phenotype-driven prioritization analysis of whole-genome sequencing data with Exomiser. The variant is localized in the functionally important ion transport domain of the TRPM3 protein and predicted to impact the protein structure. Our report adds TRPM3 to the list of Mendelian disease-associated genes that can be associated with CP and provides further evidence for the pathogenicity of the variant p.(Asn1126Asp).

The new face of cystic fibrosis in the era of population genetic carrier screening

BACKGROUND

Population genetic carrier screening (PGCS) for cystic fibrosis (CF) has been offered to couples in Israel since 1999 and was included in a fully subsidized national program in 2008. We evaluated the impact of PGCS on CF incidence, genetic and clinical features.

METHODS

This was a retrospective national study. Demographic and clinical characteristics of children with CF born in Israel between 2008 and 2018 were obtained from the national CF registry and from patients' medical records. Data on CF births, preimplantation genetic testing (PGT), pregnancy termination and de-identified data from the PGCS program were collected.

RESULTS

CF births per 100,000 live births decreased from 8.29 in 2008 to 0.54 in 2018 (IRR = 0.84, p < 0.001). The CF pregnancy termination rate did not change (IRR = 1, p=  0.9) while the CF-related PGT rate increased markedly (IRR = 1.33, p < 0.001). One hundred and two children were born with CF between 2008 and 2018 with a median age at diagnosis of 4.8 months, range 0-111 months. Unlike the generally high uptake nationally, 65/102 had not performed PGCS. Even if all had utilized PGCS, only 51 would have been detected by the existing genetic screening panel. Clinically, 34 % of children were pancreatic sufficient compared to 23 % before 2008 (p = 0.04).

CONCLUSIONS

Since institution of a nationwide PGCS program, the birth of children with CF decreased markedly. Residual function variants and pancreatic sufficiency were more common. A broader genetic screening panel and increased PGCS utilization may further decrease the birth of children with CF.

Predictive models of long COVID

BACKGROUND

The cause and symptoms of long COVID are poorly understood. It is challenging to predict whether a given COVID-19 patient will develop long COVID in the future.

METHODS

We used electronic health record (EHR) data from the National COVID Cohort Collaborative to predict the incidence of long COVID. We trained two machine learning (ML) models - logistic regression (LR) and random forest (RF). Features used to train predictors included symptoms and drugs ordered during acute infection, measures of COVID-19 treatment, pre-COVID comorbidities, and demographic information. We assigned the 'long COVID' label to patients diagnosed with the U09.9 ICD10-CM code. The cohorts included patients with (a) EHRs reported from data partners using U09.9 ICD10-CM code and (b) at least one EHR in each feature category. We analysed three cohorts: all patients (n = 2,190,579; diagnosed with long COVID = 17,036), inpatients (149,319; 3,295), and outpatients (2,041,260; 13,741).

FINDINGS

LR and RF models yielded median AUROC of 0.76 and 0.75, respectively. Ablation study revealed that drugs had the highest influence on the prediction task. The SHAP method identified age, gender, cough, fatigue, albuterol, obesity, diabetes, and chronic lung disease as explanatory features. Models trained on data from one N3C partner and tested on data from the other partners had average AUROC of 0.75.

INTERPRETATION

ML-based classification using EHR information from the acute infection period is effective in predicting long COVID. SHAP methods identified important features for prediction. Cross-site analysis demonstrated the generalizability of the proposed methodology.

FUNDING

NCATS U24 TR002306, NCATS UL1 TR003015, Axle Informatics Subcontract: NCATS-P00438-B, NIH/NIDDK/OD, PSR2015-1720GVALE_01, G43C22001320007, and Director, Office of Science, Office of Basic Energy Sciences of the U.S. Department of Energy Contract No. DE-AC02-05CH11231.

Dynamic Hyperinflation While Exercising-A Potential Predictor of Pulmonary Deterioration in Cystic Fibrosis

BACKGROUND

Lung function deterioration in cystic fibrosis (CF) is typically measured by a decline in the forced expiratory volume in one second (FEV1%), which is thought to be a late marker of lung disease. Dynamic hyperinflation (DH) is seen in obstructive lung diseases while exercising. Our aim was to assess whether DH could predict pulmonary deterioration in CF; a secondary measure was the peak VO2.

METHODS

A retrospective study was conducted of people with CF who performed cardiopulmonary exercise tests (CPETs) during 2012-2018. The tests were classified as those demonstrating DH non-DH. Demographic, genetic, and clinical data until 12.2022 were extracted from patient charts.

RESULTS

A total of 33 patients aged 10-61 years performed 41 valid CPETs with valid DH measurements; sixteen (39%) demonstrated DH. At the time of the CPETs, there was no difference in the FEV1% measurements between the DH and non-DH groups (median 83.5% vs. 87.6%, respectively; p = 0.174). The FEV1% trend over 4 years showed a decline in the DH group compared to the non-DH group (p = 0.009). A correlation was found between DH and the lung clearance index (LCI), as well as the FEV1% (r = 0.36 and p = 0.019 and r = -0.55 and p = 0.004, respectively). Intravenous (IV) antibiotic courses during the 4 years after the CPETs were significantly more frequent in the DH group (p = 0.046). The peak VO2 also correlated with the FEV1% and LCI (r = 0.36 and p = 0.02 and r = -0.46 and p = 0.014, respectively) as well as with the IV antibiotic courses (r = -0.46 and p = 0.014).

CONCLUSIONS

In our cohort, the DH and peak VO2 were both associated with lung function deterioration and more frequent pulmonary exacerbations. DH may serve as a marker to predict pulmonary deterioration in people with CF.

The Medical Action Ontology: A Tool for Annotating and Analyzing Treatments and Clinical Management of Human Disease

Navigating the vast landscape of clinical literature to find optimal treatments and management strategies can be a challenging task, especially for rare diseases. To address this task, we introduce the Medical Action Ontology (MAxO), the first ontology specifically designed to organize medical procedures, therapies, and interventions in a structured way. Currently, MAxO contains 1757 medical action terms added through a combination of manual and semi-automated processes. MAxO was developed with logical structures that make it compatible with several other ontologies within the Open Biological and Biomedical Ontologies (OBO) Foundry. These cover a wide range of biomedical domains, from human anatomy and investigations to the chemical and protein entities involved in biological processes. We have created a database of over 16000 annotations that describe diagnostic modalities for specific phenotypic abnormalities as defined by the Human Phenotype Ontology (HPO). Additionally, 413 annotations are provided for medical actions for 189 rare diseases. We have developed a web application called POET (https://poet.jax.org/) for the community to use to contribute MAxO annotations. MAxO provides a computational representation of treatments and other actions taken for the clinical management of patients. The development of MAxO is closely coupled to the Mondo Disease Ontology (Mondo) and the Human Phenotype Ontology (HPO) and expands the scope of our computational modeling of diseases and phenotypic features to include diagnostics and therapeutic actions. MAxO is available under the open-source CC-BY 4.0 license (https://github.com/monarch-initiative/MAxO).

The association between Attention-Deficit-Hyperactivity-Disorder (ADHD) symptoms and disease severity in people with Cystic Fibrosis (pwCF)

BACKGROUND

The hallmarks of Cystic fibrosis (CF), chronic infection and inflammation, require intensive daily treatment to maintain and improve quality of life and outcome. The incidence of Attention Deficit/Hyperactivity Disorder (ADHD) is increased in chronic inflammatory diseases. Previous studies suggested that the prevalence of ADHD in people with CF (pwCF) is higher than in the general population. The objective of this study was to evaluate the association between ADHD symptoms and parameters of CF disease severity, measured by demographic and clinical data.

METHODS

Based on our previous study, the results of ADHD questionnaires and the MOXOCPT (continuous performance task) from 143 pwCF (7-68 years old) were analyzed and linked to patient data such as forced expiratory volume in 1 second (FEV1)%predicted, body mass index (BMI), number of pulmonary exacerbations, days of antibiotic (Abx) treatment and serum inflammatory markers.

RESULTS

A positive correlation between FEV1 and ADHD questionnaire's score (p = 0.046) was observed in the children's group. Furthermore, BMI, white blood cells (WBC) count, and days of Abx treatment showed a positive correlation with some of the MOXOCPT parameters.

CONCLUSION

There is an association between ADHD symptoms and some parameters of CF disease severity. These results highlight the need for an early diagnosis of ADHD in pwCF, which have the potential to improve their ability to deal with the burden of their disease and consequently their quality of life. Additional research is needed to understand the full spectrum of ADHD pathophysiology and the relationship with chronic inflammatory diseases such as CF.

A method for comparing multiple imputation techniques: A case study on the U.S. national COVID cohort collaborative

Healthcare datasets obtained from Electronic Health Records have proven to be extremely useful for assessing associations between patients' predictors and outcomes of interest. However, these datasets often suffer from missing values in a high proportion of cases, whose removal may introduce severe bias. Several multiple imputation algorithms have been proposed to attempt to recover the missing information under an assumed missingness mechanism. Each algorithm presents strengths and weaknesses, and there is currently no consensus on which multiple imputation algorithm works best in a given scenario. Furthermore, the selection of each algorithm's parameters and data-related modeling choices are also both crucial and challenging. In this paper we propose a novel framework to numerically evaluate strategies for handling missing data in the context of statistical analysis, with a particular focus on multiple imputation techniques. We demonstrate the feasibility of our approach on a large cohort of type-2 diabetes patients provided by the National COVID Cohort Collaborative (N3C) Enclave, where we explored the influence of various patient characteristics on outcomes related to COVID-19. Our analysis included classic multiple imputation techniques as well as simple complete-case Inverse Probability Weighted models. Extensive experiments show that our approach can effectively highlight the most promising and performant missing-data handling strategy for our case study. Moreover, our methodology allowed a better understanding of the behavior of the different models and of how it changed as we modified their parameters. Our method is general and can be applied to different research fields and on datasets containing heterogeneous types.

Generalisable long COVID subtypes: findings from the NIH N3C and RECOVER programmes

BACKGROUND

Stratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies. However, long COVID is incompletely understood and characterised by a wide range of manifestations that are difficult to analyse computationally. Additionally, the generalisability of machine learning classification of COVID-19 clinical outcomes has rarely been tested.

METHODS

We present a method for computationally modelling PASC phenotype data based on electronic healthcare records (EHRs) and for assessing pairwise phenotypic similarity between patients using semantic similarity. Our approach defines a nonlinear similarity function that maps from a feature space of phenotypic abnormalities to a matrix of pairwise patient similarity that can be clustered using unsupervised machine learning.

FINDINGS

We found six clusters of PASC patients, each with distinct profiles of phenotypic abnormalities, including clusters with distinct pulmonary, neuropsychiatric, and cardiovascular abnormalities, and a cluster associated with broad, severe manifestations and increased mortality. There was significant association of cluster membership with a range of pre-existing conditions and measures of severity during acute COVID-19. We assigned new patients from other healthcare centres to clusters by maximum semantic similarity to the original patients, and showed that the clusters were generalisable across different hospital systems. The increased mortality rate originally identified in one cluster was consistently observed in patients assigned to that cluster in other hospital systems.

INTERPRETATION

Semantic phenotypic clustering provides a foundation for assigning patients to stratified subgroups for natural history or therapy studies on PASC.

FUNDING

NIH (TR002306/OT2HL161847-01/OD011883/HG010860), U.S.D.O.E. (DE-AC02-05CH11231), Donald A. Roux Family Fund at Jackson Laboratory, Marsico Family at CU Anschutz.

Metformin is associated with reduced COVID-19 severity in patients with prediabetes

AIMS

Studies suggest that metformin is associated with reduced COVID-19 severity in individuals with diabetes compared to other antihyperglycemics. We assessed if metformin is associated with reduced incidence of severe COVID-19 for patients with prediabetes or polycystic ovary syndrome (PCOS), common diseases that increase the risk of severe COVID-19.

METHODS

This observational, retrospective study utilized EHR data from 52 hospitals for COVID-19 patients with PCOS or prediabetes treated with metformin or levothyroxine/ondansetron (controls). After balancing via inverse probability score weighting, associations with COVID-19 severity were assessed by logistic regression.

RESULTS

In the prediabetes cohort, when compared to levothyroxine, metformin was associated with a significantly lower incidence of COVID-19 with "mild-ED" or worse (OR [95% CI]: 0.636, [0.455-0.888]) and "moderate" or worse severity (0.493 [0.339-0.718]). Compared to ondansetron, metformin was associated with lower incidence of "mild-ED" or worse severity (0.039 [0.026-0.057]), "moderate" or worse (0.045 [0.03-0.069]), "severe" or worse (0.183 [0.077-0.431]), and "mortality/hospice" (0.223 [0.071-0.694]). For PCOS, metformin showed no significant differences in severity compared to levothyroxine, but was associated with a significantly lower incidence of "mild-ED" or worse (0.101 [0.061-0.166]), and "moderate" or worse (0.094 [0.049-0.18]) COVID-19 outcome compared to ondansetron.

CONCLUSIONS

Metformin use is associated with less severe COVID-19 in patients with prediabetes or PCOS.

Post-COVID Phenotypic Manifestations are Associated with New-Onset Psychiatric Disease: Findings from the NIH N3C and RECOVER Studies

Acute COVID-19 infection can be followed by diverse clinical manifestations referred to as Post Acute Sequelae of SARS-CoV2 Infection (PASC). Studies have shown an increased risk of being diagnosed with new-onset psychiatric disease following a diagnosis of acute COVID-19. However, it was unclear whether non-psychiatric PASC-associated manifestations (PASC-AMs) are associated with an increased risk of new-onset psychiatric disease following COVID-19. A retrospective EHR cohort study of 1,603,767 individuals with acute COVID-19 was performed to evaluate whether non-psychiatric PASC-AMs are associated with new-onset psychiatric disease. Data were obtained from the National COVID Cohort Collaborative (N3C), which has EHR data from 65 clinical organizations. EHR codes were mapped to 151 non-psychiatric PASC-AMs recorded 28-120 days following SARS-CoV-2 diagnosis and before diagnosis of new-onset psychiatric disease. Association of newly diagnosed psychiatric disease with age, sex, race, pre-existing comorbidities, and PASC-AMs in seven categories was assessed by logistic regression. There was a significant association between six categories and newly diagnosed anxiety, mood, and psychotic disorders, with odds ratios highest for cardiovascular (1.35, 1.27-1.42) PASC-AMs. Secondary analysis revealed that the proportions of 95 individual clinical features significantly differed between patients diagnosed with different psychiatric disorders. Our study provides evidence for association between non-psychiatric PASC-AMs and the incidence of newly diagnosed psychiatric disease. Significant associations were found for features related to multiple organ systems. This information could prove useful in understanding risk stratification for new-onset psychiatric disease following COVID-19. Prospective studies are needed to corroborate these findings.

FUNDING

NCATS U24 TR002306.

Metformin is Associated with Reduced COVID-19 Severity in Patients with Prediabetes

Background

With the continuing COVID-19 pandemic, identifying medications that improve COVID-19 outcomes is crucial. Studies suggest that use of metformin, an oral antihyperglycemic, is associated with reduced COVID-19 severity in individuals with diabetes compared to other antihyperglycemic medications. Some patients without diabetes, including those with polycystic ovary syndrome (PCOS) and prediabetes, are prescribed metformin for off-label use, which provides an opportunity to further investigate the effect of metformin on COVID-19.

Participants

In this observational, retrospective analysis, we leveraged the harmonized electronic health record data from 53 hospitals to construct cohorts of COVID-19 positive, metformin users without diabetes and propensity-weighted control users of levothyroxine (a medication for hypothyroidism that is not known to affect COVID-19 outcome) who had either PCOS (n = 282) or prediabetes (n = 3136). The primary outcome of interest was COVID-19 severity, which was classified as: mild, mild ED (emergency department), moderate, severe, or mortality/hospice.

Results

In the prediabetes cohort, metformin use was associated with a lower rate of COVID-19 with severity of mild ED or worse (OR: 0.630, 95% CI 0.450 - 0.882, p < 0.05) and a lower rate of COVID-19 with severity of moderate or worse (OR: 0.490, 95% CI 0.336 - 0.715, p < 0.001). In patients with PCOS, we found no significant association between metformin use and COVID-19 severity, although the number of patients was relatively small.

Conclusions

Metformin was associated with less severe COVID-19 in patients with prediabetes, as seen in previous studies of patients with diabetes. This is an important finding, since prediabetes affects between 19 and 38% of the US population, and COVID-19 is an ongoing public health emergency. Further observational and prospective studies will clarify the relationship between metformin and COVID-19 severity in patients with prediabetes, and whether metformin usage may reduce COVID-19 severity.

Generalizable Long COVID Subtypes: Findings from the NIH N3C and RECOVER Programs

Accurate stratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies. However, the natural history of long COVID is incompletely understood and characterized by an extremely wide range of manifestations that are difficult to analyze computationally. In addition, the generalizability of machine learning classification of COVID-19 clinical outcomes has rarely been tested. We present a method for computationally modeling PASC phenotype data based on electronic healthcare records (EHRs) and for assessing pairwise phenotypic similarity between patients using semantic similarity. Our approach defines a nonlinear similarity function that maps from a feature space of phenotypic abnormalities to a matrix of pairwise patient similarity that can be clustered using unsupervised machine learning procedures. Using k-means clustering of this similarity matrix, we found six distinct clusters of PASC patients, each with distinct profiles of phenotypic abnormalities. There was a significant association of cluster membership with a range of pre-existing conditions and with measures of severity during acute COVID-19. Two of the clusters were associated with severe manifestations and displayed increased mortality. We assigned new patients from other healthcare centers to one of the six clusters on the basis of maximum semantic similarity to the original patients. We show that the identified clusters were generalizable across different hospital systems and that the increased mortality rate was consistently observed in two of the clusters. Semantic phenotypic clustering can provide a foundation for assigning patients to stratified subgroups for natural history or therapy studies on PASC.

Videofluoroscopy compared with clinical feeding evaluation in children with suspected aspiration

Aim

Videofluoroscopy swallow studies (VFSS) are gold standard to diagnose aspiration in children but require resources and radiation compared with clinical feeding evaluation (CFE). We evaluated their added value for diagnosis, feeding management and clinical status.

Methods

A retrospective single‐centre cross‐sectional study of children aged 0–18 years, with respiratory morbidity, referred for VFSS at a tertiary pediatric hospital.

Results

A total of 113 children, median age (range) 2.2 years (0.1–17.9), underwent VFSS. Diagnosis included chronic pulmonary aspiration (CPA), 87 (77%); neurological, 73 (64%); gastrointestinal, 73 (64%) and congenital heart disease, 42 (37%), not mutually exclusive. Forty‐six (41%) aspirated, 9 (8%) only overtly and 37 (33%) including silent aspirations. Those with CPA or cerebral palsy were more likely to have VFSS aspiration, OR 3.2 and 9.8 respectively.

Feeding recommendations after VFSS differed significantly from those based on prior CFE, p < 0.001: The rate of exclusively orally fed children rose from 65% to 79%, p = 0.006; exclusively enterally fed children from 10% to 14%; p = 0.005. During the year after VFSS, there were significantly less antibiotic courses, total and respiratory admissions.

Conclusion

In this population with high prevalence of clinically suspected CPA, VFSS altered feeding management compared with CFE and may have contributed to subsequent clinical improvement.

NSAID use and clinical outcomes in COVID-19 patients: a 38-center retrospective cohort study

BACKGROUND

Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used to reduce pain, fever, and inflammation but have been associated with complications in community-acquired pneumonia. Observations shortly after the start of the COVID-19 pandemic in 2020 suggested that ibuprofen was associated with an increased risk of adverse events in COVID-19 patients, but subsequent observational studies failed to demonstrate increased risk and in one case showed reduced risk associated with NSAID use.

METHODS

A 38-center retrospective cohort study was performed that leveraged the harmonized, high-granularity electronic health record data of the National COVID Cohort Collaborative. A propensity-matched cohort of 19,746 COVID-19 inpatients was constructed by matching cases (treated with NSAIDs at the time of admission) and 19,746 controls (not treated) from 857,061 patients with COVID-19 available for analysis. The primary outcome of interest was COVID-19 severity in hospitalized patients, which was classified as: moderate, severe, or mortality/hospice. Secondary outcomes were acute kidney injury (AKI), extracorporeal membrane oxygenation (ECMO), invasive ventilation, and all-cause mortality at any time following COVID-19 diagnosis.

RESULTS

Logistic regression showed that NSAID use was not associated with increased COVID-19 severity (OR: 0.57 95% CI: 0.53-0.61). Analysis of secondary outcomes using logistic regression showed that NSAID use was not associated with increased risk of all-cause mortality (OR 0.51 95% CI: 0.47-0.56), invasive ventilation (OR: 0.59 95% CI: 0.55-0.64), AKI (OR: 0.67 95% CI: 0.63-0.72), or ECMO (OR: 0.51 95% CI: 0.36-0.7). In contrast, the odds ratios indicate reduced risk of these outcomes, but our quantitative bias analysis showed E-values of between 1.9 and 3.3 for these associations, indicating that comparatively weak or moderate confounder associations could explain away the observed associations.

CONCLUSIONS

Study interpretation is limited by the observational design. Recording of NSAID use may have been incomplete. Our study demonstrates that NSAID use is not associated with increased COVID-19 severity, all-cause mortality, invasive ventilation, AKI, or ECMO in COVID-19 inpatients. A conservative interpretation in light of the quantitative bias analysis is that there is no evidence that NSAID use is associated with risk of increased severity or the other measured outcomes. Our results confirm and extend analogous findings in previous observational studies using a large cohort of patients drawn from 38 centers in a nationally representative multicenter database.

NSAID use and clinical outcomes in COVID-19 patients: A 38-center retrospective cohort study

BACKGROUND

Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used to reduce pain, fever, and inflammation but have been associated with complications in community-acquired pneumonia. Observations shortly after the start of the COVID-19 pandemic in 2020 suggested that ibuprofen was associated with an increased risk of adverse events in COVID-19 patients, but subsequent observational studies failed to demonstrate increased risk and in one case showed reduced risk associated with NSAID use.

METHODS

A 38-center retrospective cohort study was performed that leveraged the harmonized, high-granularity electronic health record data of the National COVID Cohort Collaborative. A propensity-matched cohort of COVID-19 inpatients was constructed by matching cases (treated with NSAIDs) and controls (not treated) from 857,061 patients with COVID-19. The primary outcome of interest was COVID-19 severity in hospitalized patients, which was classified as: moderate, severe, or mortality/hospice. Secondary outcomes were acute kidney injury (AKI), extracorporeal membrane oxygenation (ECMO), invasive ventilation, and all-cause mortality at any time following COVID-19 diagnosis.

RESULTS

Logistic regression showed that NSAID use was not associated with increased COVID-19 severity (OR: 0.57 95% CI: 0.53-0.61). Analysis of secondary outcomes using logistic regression showed that NSAID use was not associated with increased risk of all-cause mortality (OR 0.51 95% CI: 0.47-0.56), invasive ventilation (OR: 0.59 95% CI: 0.55-0.64), AKI (OR: 0.67 95% CI: 0.63-0.72), or ECMO (OR: 0.51 95% CI: 0.36-0.7). In contrast, the odds ratios indicate reduced risk of these outcomes, but our quantitative bias analysis showed E-values of between 1.9 and 3.3 for these associations, indicating that comparatively weak or moderate confounder associations could explain away the observed associations.

CONCLUSIONS

Study interpretation is limited by the observational design. Recording of NSAID use may have been incomplete. Our study demonstrates that NSAID use is not associated with increased COVID-19 severity, all-cause mortality, invasive ventilation, AKI, or ECMO in COVID-19 inpatients. A conservative interpretation in light of the quantitative bias analysis is that there is no evidence that NSAID use is associated with risk of increased severity or the other measured outcomes. Our findings are the largest EHR-based analysis of the effect of NSAIDs on outcome in COVID-19 patients to date. Our results confirm and extend analogous findings in previous observational studies using a large cohort of patients drawn from 38 centers in a nationally representative multicenter database.

Increased risk of psychiatric sequelae of COVID-19 is highest early in the clinical course

Background

COVID-19 has been shown to increase the risk of adverse mental health consequences. A recent electronic health record (EHR)-based observational study showed an almost two-fold increased risk of new-onset mental illness in the first 90 days following a diagnosis of acute COVID-19.

Methods

We used the National COVID Cohort Collaborative, a harmonized EHR repository with 2,965,506 COVID-19 positive patients, and compared cohorts of COVID-19 patients with comparable controls. Patients were propensity score-matched to control for confounding factors. We estimated the hazard ratio (COVID-19:control) for new-onset of mental illness for the first year following diagnosis. We additionally estimated the change in risk for new-onset mental illness between the periods of 21-120 and 121-365 days following infection.

Findings

We find a significant increase in incidence of new-onset mental disorders in the period of 21-120 days following COVID-19 (3.8%, 3.6-4.0) compared to patients with respiratory tract infections (3%, 2.8-3.2). We further show that the risk for new-onset mental illness decreases over the first year following COVID-19 diagnosis compared to other respiratory tract infections and demonstrate a reduced (non-significant) hazard ratio over the period of 121-365 days following diagnosis. Similar findings are seen for new-onset anxiety disorders but not for mood disorders.

Interpretation

Patients who have recovered from COVID-19 are at an increased risk for developing new-onset mental illness, especially anxiety disorders. This risk is most prominent in the first 120 days following infection.

Funding

National Center for Advancing Translational Sciences (NCATS).

Supervised learning with word embeddings derived from PubMed captures latent knowledge about protein kinases and cancer

Inhibiting protein kinases (PKs) that cause cancers has been an important topic in cancer therapy for years. So far, almost 8% of >530 PKs have been targeted by FDA-approved medications, and around 150 protein kinase inhibitors (PKIs) have been tested in clinical trials. We present an approach based on natural language processing and machine learning to investigate the relations between PKs and cancers, predicting PKs whose inhibition would be efficacious to treat a certain cancer. Our approach represents PKs and cancers as semantically meaningful 100-dimensional vectors based on word and concept neighborhoods in PubMed abstracts. We use information about phase I-IV trials in ClinicalTrials.gov to construct a training set for random forest classification. Our results with historical data show that associations between PKs and specific cancers can be predicted years in advance with good accuracy. Our tool can be used to predict the relevance of inhibiting PKs for specific cancers and to support the design of well-focused clinical trials to discover novel PKIs for cancer therapy.

Efficacy of Problem-Solving Intervention to Improve Adherence in Adolescents and Adults with Cystic Fibrosis

BACKGROUND

Adherence to treatment by adolescents and adults with cystic fibrosis (CF) is often poor.

OBJECTIVES

To assess the impact of a focused clinical intervention on adherence in individual patients, including help in problem-solving key barriers to adherence. To implement a patient-centered problem-solving intervention using CF My Way tools. To identify and overcome a selected barrier to adherence.

METHODS

Medication possession ratios (MPRs), number of airway clearance sessions, forced expiratory volume (FEV1), body mass index (BMI), and health-related quality of life (HRQoL) were measured before and after the intervention.

RESULTS

Sixteen patients with CF, aged 23.4 ± 6.7 years, participated. MPR increased for colistimethate sodium and tobramycin inhalations from a median of 21 (range 0-100) to 56 (range 0-100), P = 0.04 and 20 (range 0-100) to 33.3 (range 25-100), P = 0.03, respectively. BMI standard deviation score rose from -0.37 to -0.21, P = 0.05. No significant improvements were found in FEV1, airway clearance, or HRQoL scores.

CONCLUSIONS

The CF My Way problem-solving intervention increased adherence to medical treatments by removing barriers directly related to the needs and goals of young adults with CF.

Risk factors for respiratory syncytial virus bronchiolitis hospitalizations in children with chronic diseases

BACKGROUND

Respiratory syncytial virus (RSV) bronchiolitis is the most common lower respiratory tract disorder causing hospitalization in infants. Due to decreased hospitalization rates of premature infants following Palivizumab immune prophylaxis, the proportion of infants with chronic diseases not eligible for Palivizumab has increased.

AIM

To characterize infants hospitalized during 2014-2018 with RSV bronchiolitis, to compare between those with and without chronic conditions, and to identify risk factors for severe disease.

METHODS

This retrospective study analyzed demographic and clinical data of patients younger than 2 years admitted with bronchiolitis during four consecutive RSV seasons.

RESULTS

Of 1124 hospitalizations due to RSV bronchiolitis, 244 (22%) were in infants with chronic diseases. Although 20/1124 qualified for RSV prophylaxis, only eight received immune prophylaxis. Compared to otherwise healthy infants, children with chronic diseases had longer hospitalizations, median 4.8 days (interquartile range [IQR]: 3.4-8.3) versus 3.7 days (IQR: 2.7-5.1), p < .001; and higher pediatric intensive care unit (PICU) and readmission rates (9% vs. 4.5%, p = .007% and 3% vs. 1%, p = .055, respectively). Children with Down's syndrome comprised 2% of all hospitalizations, but 8% of PICU admissions; their median length of hospitalization was 10.7 days (IQR: 6.6-17.6). Respiratory tract malformations were present in 2% of hospitalizations, and comprised 4% of PICU admissions.

CONCLUSION

Among infants admitted with RSV bronchiolitis, those with chronic diseases had longer hospitalizations and higher rates of transfer to the PICU. Children with multiple comorbidities, and especially those with Down's syndrome, are at particularly high risk for severe hospitalization and may benefit from RSV immune prophylaxis.

KG-COVID-19: A Framework to Produce Customized Knowledge Graphs for COVID-19 Response

Integrated, up-to-date data about SARS-CoV-2 and COVID-19 is crucial for the ongoing response to the COVID-19 pandemic by the biomedical research community. While rich biological knowledge exists for SARS-CoV-2 and related viruses (SARS-CoV, MERS-CoV), integrating this knowledge is difficult and time-consuming, since much of it is in siloed databases or in textual format. Furthermore, the data required by the research community vary drastically for different tasks; the optimal data for a machine learning task, for example, is much different from the data used to populate a browsable user interface for clinicians. To address these challenges, we created KG-COVID-19, a flexible framework that ingests and integrates heterogeneous biomedical data to produce knowledge graphs (KGs), and applied it to create a KG for COVID-19 response. This KG framework also can be applied to other problems in which siloed biomedical data must be quickly integrated for different research applications, including future pandemics.

Diagnostic value of sputum cultures in children under 2 years of age with chronic suppurative lung diseases

BACKGROUND

Acquiring sputum cultures from infants is considered challenging. We describe their yield in infants with cystic fibrosis (CF) and other chronic suppurative lung diseases (CSLDs).

METHODS

Retrospective medical record review over a 4-year period, for infants aged 0-2 years with ≥2 airway bacterial cultures acquired by deep suction or induced sputum ≥4 weeks apart. Data included demographics, culture results, and clinical status.

RESULTS

A total of 98 infants (16 CF) were evaluated and 534 sputum cultures acquired, 201 in CF and 333 in CSLD. There were 12 (2-23), median (range) cultures/CF infant, and 3 (2-21)/CSLD infant. Age at first culture was 3.8 (1-19.5) months for CF and 10.4 (0.5-22) months for CSLD; p = .016. In total, 360 cultures (67%) were positive for any bacteria, with 170/234 (73%) positive during exacerbations, compared with 190/300 (63%) during routine visits; p = .05. More infants with CF than CSLD had cultures positive for Staphylococcus aureus (SA; 75% vs. 34%; p = .004) throughout the period. Pseudomonas aeruginosa (PA) was common in both CF and CSLD (56% and 44%, respectively; p = .42) and increased over time for CF but was high throughout for CSLD. The number of hospital days before PA acquisition was 6 (10.2) for CF and 28.8 (38.7) for CSLD (p = .003). No CF but 6/82 (7%) CSLD infants had chronic PA (p = .56).

CONCLUSIONS

Sputum cultures showed that infection, in particular PA, is common in CF and CSLD whereas SA is more common in CF. Prospective studies are warranted to elucidate the role of active surveillance in guiding antibiotic therapy.

KG-COVID-19: A Framework to Produce Customized Knowledge Graphs for COVID-19 Response

Integrated, up-to-date data about SARS-CoV-2 and COVID-19 is crucial for the ongoing response to the COVID-19 pandemic by the biomedical research community. While rich biological knowledge exists for SARS-CoV-2 and related viruses (SARS-CoV, MERS-CoV), integrating this knowledge is difficult and time-consuming, since much of it is in siloed databases or in textual format. Furthermore, the data required by the research community vary drastically for different tasks; the optimal data for a machine learning task, for example, is much different from the data used to populate a browsable user interface for clinicians. To address these challenges, we created KG-COVID-19, a flexible framework that ingests and integrates heterogeneous biomedical data to produce knowledge graphs (KGs), and applied it to create a KG for COVID-19 response. This KG framework also can be applied to other problems in which siloed biomedical data must be quickly integrated for different research applications, including future pandemics.

Baseline Cystic fibrosis disease severity has an adverse impact on pregnancy and infant outcomes, but does not impact disease progression

BACKGROUND

With increasing longevity and quality of life in adults with Cystic fibrosis (CF), growing maternity rates are reported. Women with severe CF are becoming pregnant, with unpredictable maternal and fetal outcomes.

AIM

To determine how baseline disease severity, pancreatic insufficiency (PI) and Pseudomonas aeruginosa (PA) infection affect fertility, the pregnancy course, delivery, neonatal outcome, and subsequent disease progression.

METHODS

A multicenter-retrospective cohort study. Data on patients that had been pregnant between 1986-2018 was collected from ten CF centers worldwide. Disease severity [mild or moderate-severe (mod-sev)] was defined according to forced expiratory volume % predicted in 1 second (FEV₁) and body mass index (BMI). Three time periods were compared, 12 months prior to conception, the pregnancy itself and the 12 months thereafter.

RESULTS

Data was available on 171 pregnancies in 128 patients aged 18-45 years; 55.1% with mod-sev disease, 43.1% with PI and 40.3% with PA. Women with mod-sev disease had more CF-related complications during and after pregnancy and delivered more preterm newborns. However, FEV₁ and BMI decline were no different between the mild and mod-sev groups. A more rapid decline in FEV₁ was observed during pregnancy in PI and PA infected patients, though stabilizing thereafter. PI was associated with increased risk for small for gestational age infants.

CONCLUSION

Baseline disease severity, PA infection and PI have an adverse impact on infant outcomes, but do not impact significantly on disease progression during and after pregnancy. Consequently, pregnancies in severe CF patients can have a good prognosis.

KG-COVID-19: a framework to produce customized knowledge graphs for COVID-19 response

Integrated, up-to-date data about SARS-CoV-2 and coronavirus disease 2019 (COVID-19) is crucial for the ongoing response to the COVID-19 pandemic by the biomedical research community. While rich biological knowledge exists for SARS-CoV-2 and related viruses (SARS-CoV, MERS-CoV), integrating this knowledge is difficult and time consuming, since much of it is in siloed databases or in textual format. Furthermore, the data required by the research community varies drastically for different tasks - the optimal data for a machine learning task, for example, is much different from the data used to populate a browsable user interface for clinicians. To address these challenges, we created KG-COVID-19, a flexible framework that ingests and integrates biomedical data to produce knowledge graphs (KGs) for COVID-19 response. This KG framework can also be applied to other problems in which siloed biomedical data must be quickly integrated for different research applications, including future pandemics.

BIGGER PICTURE

An effective response to the COVID-19 pandemic relies on integration of many different types of data available about SARS-CoV-2 and related viruses. KG-COVID-19 is a framework for producing knowledge graphs that can be customized for downstream applications including machine learning tasks, hypothesis-based querying, and browsable user interface to enable researchers to explore COVID-19 data and discover relationships.

Brief report: International perspectives on the pediatric COVID-19 experience

The 2019 novel coronavirus (SARS-CoV-2) is endangering human health worldwide; scarcity of published pediatric cases and current literature and the absence of evidence-based guidelines necessitate international sharing of experience and personal communication. On 31 March 2020 the International Committee of the American Thoracic Society Pediatrics Assembly recorded an online podcast, during which pediatric pulmonologists worldwide shared their experience on the novel coronavirus disease (COVID-19) in children. The aim was to share personal experience in organizing pediatric care in different health care settings globally, protecting health care workers, and isolation practices. This manuscript summarizes the common themes of the podcast which centered around three main topics: more benign clinical disease and progression in pediatric cases compared to adults, a strong need for strategies to protect health care workers, and social or economic disparities as a barrier to successful pandemic control.

The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources

The Human Phenotype Ontology (HPO)—a standardized vocabulary of phenotypic abnormalities associated with 7000+ diseases—is used by thousands of researchers, clinicians, informaticians and electronic health record systems around the world. Its detailed descriptions of clinical abnormalities and computable disease definitions have made HPO the de facto standard for deep phenotyping in the field of rare disease. The HPO’s interoperability with other ontologies has enabled it to be used to improve diagnostic accuracy by incorporating model organism data. It also plays a key role in the popular Exomiser tool, which identifies potential disease-causing variants from whole-exome or whole-genome sequencing data. Since the HPO was first introduced in 2008, its users have become both more numerous and more diverse. To meet these emerging needs, the project has added new content, language translations, mappings and computational tooling, as well as integrations with external community data. The HPO continues to collaborate with clinical adopters to improve specific areas of the ontology and extend standardized disease descriptions. The newly redesigned HPO website (www.human-phenotype-ontology.org) simplifies browsing terms and exploring clinical features, diseases, and human genes.

Palivizumab Following Extremely Premature Birth Does Not Affect Pulmonary Outcomes in Adolescence

BACKGROUND

Prematurity is a risk factor for impaired lung function. We sought to assess the long-term effect of palivizumab immunization and extreme prematurity (<29 weeks gestation) on respiratory symptoms and pulmonary function in adolescence.

RESEARCH QUESTION

What is the long-term effect of palivizumab immunization and extreme prematurity (<29 weeks) on respiratory symptoms and pulmonary function in adolescence?

STUDY DESIGN AND METHODS

We examined survivors of extreme prematurity (<29 weeks gestation) at 13 to 18 years of age (study group). Study group babies who were born immediately before palivizumab immunization (nonpalivizumab group [NPG]) were compared with those babies who were born just after implementation (PG) and with a control group. For study group patients, lung function in adolescence was further compared longitudinally with that at primary school age.

RESULTS

Sixty-four adolescents aged 15.76 ± 1.52 years were included: 46 in the study group (17 PG and 29 NPG) and 18 in the control group. For the study group, wheezing episodes, inhaler use, and hospitalizations were uncommon. For the study group compared with the control group, FEV₁ percent predicted was 82.60% ± 13.54% vs 105.83% ± 13.12% (P < .001), and the lung clearance index was 7.67 ± 1.02 vs 7.46 ± 0.70 (P = .48), respectively. Study group adolescents with bronchopulmonary dysplasia had a higher lung clearance index than did adolescents with no bronchopulmonary dysplasia (7.94 ± 1.11 vs 7.20 ± 0.60; P = .002). PG and NPG adolescents were not significantly different. Comparing the study group in adolescence with primary school age, we found improvement in mean FEV₁ percent predicted bronchodilator response (0.37% ± 9.98% vs 5.67% ± 9.87%; P = .036) and mean provocative concentration causing 20% decline in FEV₁ (12.16 ± 4.71 mg/mL vs 4.14 ± 4.51 mg/mL, respectively; P < .001).

INTERPRETATION

Palivizumab did not provide any discernable long-term protective effect. Nevertheless, adolescent survivors of extreme prematurity showed good clinical and physiologic outcomes, except for mildly raised lung clearance index in patients with bronchopulmonary dysplasia. Airway hyperreactivity detected at primary school age, decreased by adolescence.

Significantly different clinical phenotypes associated with mutations in synthesis and transamidase+remodeling glycosylphosphatidylinositol (GPI)-anchor biosynthesis genes

BACKGROUND

Defects in the glycosylphosphatidylinositol (GPI) biosynthesis pathway can result in a group of congenital disorders of glycosylation known as the inherited GPI deficiencies (IGDs). To date, defects in 22 of the 29 genes in the GPI biosynthesis pathway have been identified in IGDs. The early phase of the biosynthetic pathway assembles the GPI anchor (Synthesis stage) and the late phase transfers the GPI anchor to a nascent peptide in the endoplasmic reticulum (ER) (Transamidase stage), stabilizes the anchor in the ER membrane using fatty acid remodeling and then traffics the GPI-anchored protein to the cell surface (Remodeling stage).

RESULTS

We addressed the hypothesis that disease-associated variants in either the Synthesis stage or Transamidase+Remodeling-stage GPI pathway genes have distinct phenotypic spectra. We reviewed clinical data from 58 publications describing 152 individual patients and encoded the phenotypic information using the Human Phenotype Ontology (HPO). We showed statistically significant differences between the Synthesis and Transamidase+Remodeling Groups in the frequencies of phenotypes in the musculoskeletal system, cleft palate, nose phenotypes, and cognitive disability. Finally, we hypothesized that phenotypic defects in the IGDs are likely to be at least partially related to defective GPI anchoring of their target proteins. Twenty-two of one hundred forty-two proteins that receive a GPI anchor are associated with one or more Mendelian diseases and 12 show some phenotypic overlap with the IGDs, represented by 34 HPO terms. Interestingly, GPC3 and GPC6, members of the glypican family of heparan sulfate proteoglycans bound to the plasma membrane through a covalent GPI linkage, are associated with 25 of these phenotypic abnormalities.

CONCLUSIONS

IGDs associated with Synthesis and Transamidase+Remodeling stages of the GPI biosynthesis pathway have significantly different phenotypic spectra. GPC2 and GPC6 genes may represent a GPI target of general disruption to the GPI biosynthesis pathway that contributes to the phenotypes of some IGDs.

Healthcare utilization in infants and toddlers with asthma-like symptoms

BACKGROUND

Recurrent asthma-like symptoms are common in infants, but few population studies describe diagnostic and treatment practice.

METHODS

Using the electronic data repository of Clalit Health Services, the largest integrated health care provider in Israel, we evaluated children born 2005-2012, who before 3 years of age had >3 episodes of asthma-like symptoms and/or >2 bronchodilator purchases within a year. We described health care utilization and the odds ratio for subsequent utilization after 3 and 12 months' controller therapy. The primary outcome measure was respiratory-related doctor visits. Linear and categorical regression analysis measured overall effectiveness of therapy.

RESULTS

Among 689 171 infants, 262 900 (38.1%) had > 3 asthma-like episodes/year during at least 1 year. Of those, 26 108 (10%) purchased controller therapy: 20 316 (77.8%) inhaled corticosteroids (ICS) with or without leukotriene receptor antagonists (LTRA), and 5792 (22.2%) LTRA alone. For these 26 108 over 3 months there were 93 845 respiratory-related doctor visits, 3110 hospital admissions, 5568 diagnoses of pneumonia, 9960 chest X-rays, 37 127 purchases for oral steroids, and 45 142 for antibiotics courses. Healthcare utilization decreased following ICS ± LTRA and LTRA alone, respectively, as follows: doctor visits 7% and 3%, chest X-rays 16% and 17%, bronchodilators 20% and 11%, systemic steroids 17% and 12%, and antibiotics by 35% and 22%, (P < .001 for all). Twelve months' therapy remained effective.

CONCLUSIONS

Asthma-like symptoms are common in infants. Health care utilization is very high and physician practices should be reassessed. Following controller therapy, health care utilization decreased. Yet controllers were prescribed in only a minority of eligible children.

GOPHER: Generator Of Probes for capture Hi-C Experiments at high Resolution

BACKGROUND

Target enrichment combined with chromosome conformation capturing methodologies such as capture Hi-C (CHC) can be used to investigate spatial layouts of genomic regions with high resolution and at scalable costs. A common application of CHC is the investigation of regulatory elements that are in contact with promoters, but CHC can be used for a range of other applications. Therefore, probe design for CHC needs to be adapted to experimental needs, but no flexible tool is currently available for this purpose.

RESULTS

We present a Java desktop application called GOPHER (Generator Of Probes for capture Hi-C Experiments at high Resolution) that implements three strategies for CHC probe design. GOPHER's simple approach is similar to the probe design of previous approaches that employ CHC to investigate all promoters, with one probe being placed at each margin of a single digest that overlaps the transcription start site (TSS) of each promoter. GOPHER's simple-patched approach extends this methodology with a heuristic that improves coverage of viewpoints in which the TSS is located near to one of the boundaries of the digest. GOPHER's extended approach is intended mainly for focused investigations of smaller gene sets. GOPHER can also be used to design probes for regions other than TSS such as GWAS hits or large blocks of genomic sequence. GOPHER additionally provides a number of features that allow users to visualize and edit viewpoints, and outputs a range of files useful for documentation, ordering probes, and downstream analysis.

CONCLUSION

GOPHER is an easy-to-use and robust desktop application for CHC probe design. Source code and a precompiled executable can be downloaded from the GOPHER GitHub page at https://github.com/TheJacksonLaboratory/Gopher .

Inspiromatic-safety and efficacy study of a new generation dry powder inhaler in asthmatic children

BACKGROUND

Dry powder inhalers (DPI) are effective but forceful inhalation required to fluidize the powder may be difficult for children and patients with airway disease. Inspiromatic is a new generation active DPI that actively suspends drugs in synchrony with inhalation. We evaluated safety and efficacy of Formoterol delivery via Inspiromatic, compared to Aerolizer, a conventional DPI, in pediatric asthmatic subjects.

METHODS

A phase I/II, randomized, single-center, double-blind, double-dummy, placebo-controlled, cross-over study. Subjects aged 8-18 years with FEV₁ 40-80% predicted were included. Patients were randomized to inhale Formoterol via the Inspiromatic, immediately followed by the placebo via the Aerolizer or vice versa, in a double-blind fashion. Spirometry, blood pressure, and heart rate were measured at baseline and 15, 30, and 60 min after drug administration. Capsule emptying, comfort of use, confidence in efficacy, and patient satisfaction were assessed. At a subsequent visit, three months later, patients inhaled the active drug via the other DPI.

RESULTS

Twenty-nine patients, aged 12.6 (±2.3) years, mean (SD), completed the study. Baseline FEV₁ was 69.1 (±6.7) % at visit one and 65.3 (±9) % at visit two. Maximal FEV₁ increase was 16.6 (±7.1) % with Inspiromatic and 15.5 (±7.5) % with Aerolizer (P = 0.47). No differences in heart rate or blood pressure were observed; 24/28 capsules were emptied using the Inspiromatic and 19/28 with the Aerolizer (P = 0.5); 21/28 preferred the Inspiromatic and 7/28 the Aerolizer (P < 0.001). There were no adverse events.

CONCLUSIONS

Formoterol inhalation via the Inspiromatic is safe and as efficacious as with the Aerolizer. The device is well accepted by asthmatic subjects.

The Q359K/T360K mutation causes cystic fibrosis in Georgian Jews

BACKGROUND

The Q359K/T360K mutation, described in Jewish CF patients of Georgian decent, is of questionable clinical significance.

METHODS

Clinical records of patients with the Q359K/T360K mutation from three CF centers were studied for phenotypic expression and putative mechanism of dysfunction. Computer models of mutant CFTR were constructed.

RESULTS

Nine patients (4 homozygous) of Georgian Jewish origin were included. Age at diagnosis was 9.4 (0.25-38.2) years, median (range). Sweat chloride was 106 ± 13 meq/L, mean ± SD. Nasal Potential Difference performed in three, was abnormal. All had pulmonary symptoms since early childhood and bronchiectasis. Median FEV₁ was 88 (40-121)%. Five had chronic mucoid P. aeruginosa. Homozygous patients were pancreatic insufficient. Enzyme supplementation was initiated at 3.8 (1-14.7) years, median (range). Structural models hint at possible interference of this mutation with transmembrane chloride transport.

CONCLUSION

In our cohort, the Q359K/T360K mutation resulted in a severe CF phenotype, although with residual early CFTR function. The CFTR2 database should consider defining this mutation as CF-causing.

Topical propranolol improves epistaxis in patients with hereditary hemorrhagic telangiectasia - a preliminary report

Background

Severe epistaxis is often difficult to control in patients with hereditary hemorrhagic telangiectasia (HHT). Propranolol has been shown to have antiangiogenic properties in vitro and in vivo and is commonly used to treat hemangiomas. We present our experience with topical nasal propranolol for the treatment of moderate to severe epistaxis in patients with HHT.

Methods

Retrospective case series. Six patients with HHT were treated with 0.5 cm³ of 1.5% propranolol gel, applied to each nostril twice daily for at least 12 weeks. Outcome measures were epistaxis severity score (ESS), hemoglobin level, and number of blood transfusions prior to and while on treatment. Local and systemic side effects were recorded.

Results

The mean duration of treatment was 30 ± 5.6 weeks. A significant improvement in the ESS was found in all patients, with a mean decrease from 6.4 ± 2.1 at treatment onset to 3.5 ± 1.7 at 12 weeks (p = 0.028). Hemoglobin level increased significantly from 8.4 ± 3.1 to 11.0 ± 1.8 g/dL at 12 weeks (p = 0.043). The mean number of blood transfusions decreased from 4.5 ± 4.9 before treatment to 2.5 ± 2.9 at 12 weeks and 0.3 ± 0.8 at 24 weeks, but the difference did not reach statistical significance (p = 0.109 for both). No significant side effects of treatment were recorded.

Conclusions

These preliminary results suggest that topical propranolol may be effective for the treatment of epistaxis in patients with HHT. A prospective controlled trial is required to confirm our findings.

Ivacaftor for the p.Ser549Arg (S549R) gating mutation - The Israeli experience

BACKGROUND

Ivacaftor is a drug that increases the probability of the cystic fibrosis transmembrane conductance regulator (CFTR) chloride channel remaining open. Information about the efficacy of ivacaftor in patients carrying the rare p.Ser549Arg (S549R) CFTR mutation is sparse.

AIM

Efficacy of ivacaftor treatment in patients carrying the p.Ser549Arg (S549R) CFTR mutation.

METHODS

Data obtained from CF patients receiving ivacaftor for one year.

RESULTS

Eight CF patients, mean age 21 ± 10 years, received ivacaftor. After one year, significant improvement was found in FEV₁, increasing from 74% to 88% (p < 0.001), FVC, 89% to 101% (p = 0.019), and FEF_25-75, 59%-76% (p = 0.019). Sweat chloride concentration decreased from 116 ± 8 mmol/L to 51 ± 17 mmol/L (p < 0.001), and BMI increased from 20 ± 3 to 22 ± 4 (p = 0.003). Glucose tolerance improved in five patients. There was no significant change in bacterial colonization.

CONCLUSIONS

Ivacaftor therapy resulted in significant clinical improvement in patients carrying the p.Ser549Arg (S549R) CFTR mutation.

Clinical impact of Pseudomonas aeruginosa colonization in patients with Primary Ciliary Dyskinesia

BACKGROUND

Airway infections in Primary Ciliary Dyskinesia (PCD) are caused by different microorganisms, including pseudomonas aeruginosa (PA). The aim of this study was to investigate the association of PA colonization and the progression of lung disease in PCD.

METHODS

Data from 11PCD centers were retrospectively collected from 2008 to 2013. Patients were considered colonized if PA grew on at least two separate sputum cultures; otherwise, they were classified as non-colonized. These two groups were compared on the lung function computed tomography (CT) Brody score and other clinical parameters.

RESULTS

Data were available from 217 patients; 60 (27.6%) of whom were assigned to the colonized group. Patients colonized with PA were older and were diagnosed at a later age. Baseline forced expiratory volume at 1 s (FEV₁) was lower in the colonized group (72.4 ± 22.0 vs. 80.1 ± 18.9, % predicted, p = 0.015), but FEV₁ declined throughout the study period was similar in both groups. The colonized group had significantly worse CT-Brody scores (36.07 ± 24.38 vs. 25.56 ± 24.2, p = 0.034). A subgroup analysis with more stringent definitions of colonization revealed similar results.

CONCLUSIONS

Lung PA colonization in PCD is associated with more severe disease as shown by the FEV₁ and CT score. However, the magnitude of decline in pulmonary function was similar in colonized and non-colonized PCD patients.

Propranolol treatment for infantile hemangioma does not increase risk of childhood wheezing

OBJECTIVE

Propranolol is the treatment of choice for infantile hemangiomas requiring medical intervention. Although contraindicated in asthma, its bronchoconstrictive effect in infants and children has not been extensively studied. We aimed to assess the incidence of wheezing episodes in infants and children treated with propranolol for infantile hemangiomas.

STUDY DESIGN

A retrospective case-control study.

SETTING

a tertiary pediatric hospital.

PATIENTS

All Children followed for infantile hemangioma between 2009 and 2014. Children followed conservatively served as control group and were matched 1:1 for gender and month of birth by random matching to children treated with propranolol.

INTERVENTIONS

All respiratory episodes (asthma, wheezing, stridor, and pneumonia) and respiratory associated hospitalizations were recorded from hospital records, from the primary care physician visits records and pharmacy prescriptions. The main outcome measure was the incidence of respiratory episodes in the treatment and the control groups.

RESULTS

A total of 1828 clinic visits were reviewed for 683 children. In addition, primary care physician visits records were available in 80% of them. Two hundred and sixteen children were treated with propranolol. Incidence of respiratory episodes and recurrent respiratory episodes was similar in the propranolol and control groups (8.3% vs 12%, P = 0.265; 3.7% vs 6.5%, P = 0.274, respectively). Time to first episode was similar in the treatment and control groups (5.03 ± 3.32 vs 4.45 ± 3.21 months, respectively, P = 0.09). Respiratory hospital admission rate was similar in both groups.

CONCLUSIONS

Propranolol treatment does not exacerbate wheezing episodes in infants and children.

Feasibility of multiple breath washout measurements in infants with bronchiolitis: A pilot study

BACKGROUND

Lung clearance index (LCI) reflects ventilation inhomogeneity and is raised in obstructive airway disease. Feasibility of multiple breath washout (MBW) measurement during acute lung disease in infants is unknown. As a further measure of disease, exhaled nitric oxide (eNO) may paradoxically decrease in acute bronchiolitis. We hypothesized that MBW measurements were attainable in infants with bronchiolitis and that LCI was raised and eNO reduced, compared to normal controls.

METHODS

Infants with acute bronchiolitis were tested with sulfur hexafluoride (SF₆ ) MBW during hospitalization and compared to controls. Tidal breathing and eNO parameters were obtained. Measurements were performed during natural sleep.

RESULTS

Twenty-nine infants with bronchiolitis aged 3.7 ± 2.3 months (mean ± SD) and 23 controls aged 4.2 ± 2.5 months (P = 0.07) were evaluated. Fifteen of 29 (52%) infants with bronchiolitis and 19/23 (83%) controls achieved ≥2 valid MBW measurements. Reasons for test failure included waking up during facemask application and an irregular respiratory pattern. LCI was 8.4 ± 0.8 in the study group and 7.3 ± 0.7 in controls (P < 0.001). ENO was 2.3 ± 2.7 ppb in the study group and 7.9 ± 6.9 ppb in controls (P = 0.004).

CONCLUSION

MBW measurements during natural sleep are feasible but technically challenging in infants with acute bronchiolitis. LCI is raised compared to healthy controls. Larger trials, possibly using sedation protocols and shortened washout periods, are required to corroborate these findings. LCI can potentially serve as an objective indicator of severity and could be considered as a biomarker for future interventional trials.