Single Nucleotide Polymorphisms (SNPs) in PRKG1 & SPATA13-AS1 are associated with bronchodilator response: a pilot study during acute asthma exacerbations in African American children.

OBJECTIVE: Inhaled bronchodilators are the first-line treatment for asthma exacerbations, but individual bronchodilator response (BDR) varies by race and ethnicity. Studies have examined BDR's genetic underpinnings, but many did not include children or were not conducted during an asthma exacerbation. This pilot study tested single-nucleotide polymorphisms' (SNPs') association with pediatric African American BDR during an acute asthma exacerbation. METHODS: This was a study of pediatric asthma patients in the age group 2-18 years treated in the emergency department for an asthma exacerbation. We measured BDR before and after inhaled bronchodilator treatments using both the Pediatric Asthma Severity Score (PASS) and asthma severity score. We collected genomic DNA and examined whether 21 candidate SNPs from a review of the literature were associated with BDR using crude odds ratios (OR) and adjusted analysis. RESULTS: The final sample population was 53 children, with an average age of 7.2 years. The average initial PASS score (scale of ascending severity from 0 to 6) was 2.5. After adjusting for BMI, age category, gender and smoke exposure, rs912142 was associated with decreased odds of having low BDR (OR, 0.20; 95% confidence interval (CI), 0.02-0.92), and rs7081864 and rs7903366 were associated with decreased odds of having high BDR (OR, 0.097; 95% CI, 0.009-0.62). CONCLUSIONS: We found three SNPs significantly associated with pediatric African American BDR that provide information regarding a child's potential response to emergency asthma exacerbation treatment. Once validated in larger studies, such information could guide pharmacogenomic evidence-based emergency asthma treatment to improve patient outcomes.

A hypolipoprotein sepsis phenotype indicates reduced lipoprotein antioxidant capacity, increased endothelial dysfunction and organ failure, and worse clinical outcomes.

OBJECTIVE: Approximately one-third of sepsis patients experience poor outcomes including chronic critical illness (CCI, intensive care unit (ICU) stay > 14 days) or early death (in-hospital death within 14 days). We sought to characterize lipoprotein predictive ability for poor outcomes and contribution to sepsis heterogeneity. DESIGN: Prospective cohort study with independent replication cohort. SETTING: Emergency department and surgical ICU at two hospitals. PATIENTS: Sepsis patients presenting within 24 h. METHODS: Measures included cholesterol levels (total cholesterol, high density lipoprotein cholesterol [HDL-C], low density lipoprotein cholesterol [LDL-C]), triglycerides, paraoxonase-1 (PON-1), and apolipoprotein A-I (Apo A-I) in the first 24 h. Inflammatory and endothelial markers, and sequential organ failure assessment (SOFA) scores were also measured. LASSO selection assessed predictive ability for outcomes. Unsupervised clustering was used to investigate the contribution of lipid variation to sepsis heterogeneity. MEASUREMENTS AND MAIN RESULTS: 172 patients were enrolled. Most (~ 67%, 114/172) rapidly recovered, while ~ 23% (41/172) developed CCI, and ~ 10% (17/172) had early death. ApoA-I, LDL-C, mechanical ventilation, vasopressor use, and Charlson Comorbidity Score were significant predictors of CCI/early death in LASSO models. Unsupervised clustering yielded two discernible phenotypes. The Hypolipoprotein phenotype was characterized by lower lipoprotein levels, increased endothelial dysfunction (ICAM-1), higher SOFA scores, and worse clinical outcomes (45% rapid recovery, 40% CCI, 16% early death; 28-day mortality, 21%). The Normolipoprotein cluster patients had higher cholesterol levels, less endothelial dysfunction, lower SOFA scores and better outcomes (79% rapid recovery, 15% CCI, 6% early death; 28-day mortality, 15%). Phenotypes were validated in an independent replication cohort (N = 86) with greater sepsis severity, which similarly demonstrated lower HDL-C, ApoA-I, and higher ICAM-1 in the Hypolipoprotein cluster and worse outcomes (46% rapid recovery, 23% CCI, 31% early death; 28-day mortality, 42%). Normolipoprotein patients in the replication cohort had better outcomes (55% rapid recovery, 32% CCI, 13% early death; 28-day mortality, 28%) Top features for cluster discrimination were HDL-C, ApoA-I, total SOFA score, total cholesterol level, and ICAM-1. CONCLUSIONS: Lipoproteins predicted poor sepsis outcomes. A Hypolipoprotein sepsis phenotype was identified and characterized by lower lipoprotein levels, increased endothelial dysfunction (ICAM-1) and organ failure, and worse clinical outcomes.

Algorithm-Driven Electronic Health Record Notification Enhances the Detection of Turner Syndrome.

Early diagnosis of Turner syndrome enhances care, but in routine practice, even within larger referral centers, diagnosis is delayed. Our study examines the utility of an electronic health record algorithm in identifying patients at high risk for Turner syndrome. Six percent of those identified had missed diagnoses of Turner syndrome.

Characterization and phosphoproteomic analysis of a human immortalized podocyte model of Fabry disease generated using CRISPR/Cas9 technology.

Fabry nephropathy is a major cause of morbidity and premature death in patients with Fabry disease (FD), a rare X-linked lysosomal storage disorder. Gb3, the main substrate of α-galactosidase A (α-Gal A), progressively accumulates within cells in a variety of tissues. Establishment of cell models has been useful as a tool for testing hypotheses of disease pathogenesis. We applied CRISPR/Cas9 genome editing technology to the GLA gene to develop human kidney cell models of FD in human immortalized podocytes, which are the main affected renal cell type. Our podocytes lack detectable α-Gal A activity and have increased levels of Gb3. To explore different pathways that could have distinct patterns of activation under conditions of α-gal A deficiency, we used a high-throughput antibody array to perform phosphorylation profiling of CRISPR/Cas9-edited and control podocytes. Changes in both total protein levels and in phosphorylation status per site were observed. Analysis of our candidate proteins suggests that multiple signaling pathways are impaired in FD.

DHCR7 Expression Predicts Poor Outcomes and Mortality from Sepsis.

Objective: Sepsis patients experience poor outcomes including chronic critical illness (CCI) or early death (within 14 days). We investigated lipid metabolic gene expression differences by outcome to discover therapeutic targets. Design: Secondary analysis of samples from prospectively enrolled sepsis patients and a zebrafish sepsis model for drug discovery. Setting: Emergency department or ICU at an urban teaching hospital. Patients: Sepsis patients presenting within 24 hours. Methods: Enrollment samples from sepsis patients were analyzed. Clinical data and cholesterol levels were recorded. Leukocytes were processed for RNA sequencing (RNA-seq) and reverse transcriptase polymerase chain reaction (RT-qPCR). A lipopolysaccharide (LPS) zebrafish sepsis model was used for confirmation of human transcriptomic findings and drug discovery. Measurements and Main Results: There were 96 samples in the derivation (76 sepsis, 20 controls) and 52 in the validation cohort (sepsis only). The cholesterol metabolism gene 7-Dehydrocholesterol Reductase ( DHCR7) was significantly upregulated in both derivation and validation cohorts in poor outcome sepsis compared to rapid recovery patients and in 90-day non-survivors (validation only) and validated using RT-qPCR analysis. Our zebrafish sepsis model showed upregulation of dhcr7 and several of the same lipid genes upregulated in poor outcome human sepsis (dhcr24, sqlea, cyp51, msmo1 , ldlra) compared to controls. We then tested six lipid-based drugs in the zebrafish sepsis model. Of these, only the Dhcr7 inhibitor AY9944 completely rescued zebrafish from LPS death in a model with 100% lethality. Conclusions: DHCR7, an important cholesterol metabolism gene, was upregulated in poor outcome sepsis patients warranting external validation. This pathway may serve as a potential therapeutic target to improve sepsis outcomes.

DHCR7 Expression Predicts Poor Outcomes and Mortality From Sepsis.

This is a study of lipid metabolic gene expression patterns to discover precision medicine for sepsis. OBJECTIVES: Sepsis patients experience poor outcomes including chronic critical illness (CCI) or early death (within 14 d). We investigated lipid metabolic gene expression differences by outcome to discover therapeutic targets. DESIGN SETTING AND PARTICITPANTS: Secondary analysis of samples from prospectively enrolled sepsis patients (first 24 hr) and a zebrafish endotoxemia model for drug discovery. Patients were enrolled from the emergency department or ICU at an urban teaching hospital. Enrollment samples from sepsis patients were analyzed. Clinical data and cholesterol levels were recorded. Leukocytes were processed for RNA sequencing and reverse transcriptase polymerase chain reaction. A lipopolysaccharide zebrafish endotoxemia model was used for confirmation of human transcriptomic findings and drug discovery. MAIN OUTCOMES AND MEASURES: The derivation cohort included 96 patients and controls (12 early death, 13 CCI, 51 rapid recovery, and 20 controls) and the validation cohort had 52 patients (6 early death, 8 CCI, and 38 rapid recovery). RESULTS: The cholesterol metabolism gene 7-dehydrocholesterol reductase (DHCR7) was significantly up-regulated in both derivation and validation cohorts in poor outcome sepsis compared with rapid recovery patients and in 90-day nonsurvivors (validation only) and validated using RT-qPCR analysis. Our zebrafish sepsis model showed up-regulation of dhcr7 and several of the same lipid genes up-regulated in poor outcome human sepsis (dhcr24, sqlea, cyp51, msmo1, and ldlra) compared with controls. We then tested six lipid-based drugs in the zebrafish endotoxemia model. Of these, only the Dhcr7 inhibitor AY9944 completely rescued zebrafish from lipopolysaccharide death in a model with 100% lethality. CONCLUSIONS: DHCR7, an important cholesterol metabolism gene, was up-regulated in poor outcome sepsis patients warranting external validation. This pathway may serve as a potential therapeutic target to improve sepsis outcomes.

Targeted Searches of the Electronic Health Record and Genomics Identify an Etiology in Three Patients with Short Stature and High IGF-I Levels.

INTRODUCTION: Short stature is one of the most common reasons for referral to a pediatric endocrinologist and can result from many etiologies. However, many patients with short stature do not receive a definitive diagnosis. OBJECTIVE: To ascertain whether integrating targeted bioinformatics searches of electronic health records (EHRs) combined with genomic studies could identify patients with previously undiagnosed rare genetic etiologies of short stature. We focused on a specific rare phenotypic subgroup: patients with short stature and elevated IGF-I levels. METHODS: We performed a cross-sectional cohort study at three large academic pediatric healthcare networks. Eligible subjects included children with heights below -2 SD, IGF-I levels >90th percentile, and no known etiology for short stature. We performed a search of the EHRs to identify eligible patients. Patients were then recruited for phenotyping followed by exome sequencing and in vitro assays of IGF1R function. RESULTS: A total of 234 patients were identified by the bioinformatics algorithm with 39 deemed eligible after manual review (17%). Of those, 9 were successfully recruited. A genetic etiology was identified in 3 of the 9 patients including 2 novel variants in IGF1R and a de novo variant in CHD2. In vitro studies supported the pathogenicity of the IGF1R variants. CONCLUSIONS: This study provides proof of principle that patients with rare phenotypic subgroups can be identified based on discrete data elements in the EHRs. Although limitations exist to fully automating this approach, these searches may help find patients with previously unidentified rare genetic disorders.

Paternally Inherited DLK1 Deletion Associated With Familial Central Precocious Puberty.

Context: Central precocious puberty (CPP) results from premature activation of the hypothalamic-pituitary-gonadal axis. Few genetic causes of CPP have been identified, with the most common being mutations in the paternally expressed imprinted gene MKRN3. Objective: To identify the genetic etiology of CPP in a large multigenerational family. Design: Linkage analysis followed by whole-genome sequencing was performed in a family with five female members with nonsyndromic CPP. Detailed phenotyping was performed at the time of initial diagnosis and long-term follow-up, and circulating levels of Delta-like 1 homolog (DLK1) were measured in affected individuals. Expression of DLK1 was measured in mouse hypothalamus and in kisspeptin-secreting neuronal cell lines in vitro. Setting: Endocrine clinic of an academic medical center. Patients: Patients with familial CPP were studied. Results: A complex defect of DLK1 (∼14-kb deletion and 269-bp duplication) was identified in this family. This deletion included the 5' untranslated region and the first exon of DLK1, including the translational start site. Only family members who inherited the defect from their father have precocious puberty, consistent with the known imprinting of DLK1. The patients did not demonstrate additional features of the imprinted disorder Temple syndrome except for increased fat mass. Serum DLK1 levels were undetectable in all affected individuals. Dlk1 was expressed in mouse hypothalamus and in kisspeptin neuron-derived cell lines. Conclusion: We identified a genomic defect in DLK1 associated with isolated familial CPP. MKRN3 and DLK1 are both paternally expressed imprinted genes. These findings suggest a role of genomic imprinting in regulating the timing of human puberty.