Blood RNA analysis can increase clinical diagnostic rate and resolve variants of uncertain significance

Purpose: Diagnosis of genetic disorders is hampered by large numbers of variants of uncertain significance (VUSs) identified through next-generation sequencing. Many such variants may disrupt normal RNA splicing. We examined effects on splicing of a large cohort of clinically identified variants and compared performance of bioinformatic splicing prediction tools commonly used in diagnostic laboratories. Methods: Two hundred fifty-seven variants (coding and noncoding) were referred for analysis across three laboratories. Blood RNA samples underwent targeted reverse transcription polymerase chain reaction (RT-PCR) analysis with Sanger sequencing of PCR products and agarose gel electrophoresis. Seventeen samples also underwent transcriptome-wide RNA sequencing with targeted splicing analysis based on Sashimi plot visualization. Bioinformatic splicing predictions were obtained using Alamut, HSF 3.1, and SpliceAI software. Results: Eighty-five variants (33%) were associated with abnormal splicing. The most frequent abnormality was upstream exon skipping (39/85 variants), which was most often associated with splice donor region variants. SpliceAI had greatest accuracy in predicting splicing abnormalities (0.91) and outperformed other tools in sensitivity and specificity. Conclusion: Splicing analysis of blood RNA identifies diagnostically important splicing abnormalities and clarifies functional effects of a significant proportion of VUSs. Bioinformatic predictions are improving but still make significant errors. RNA analysis should therefore be routinely considered in genetic disease diagnostics.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.This research was funded by National Institute for Health Research (NIHR) and the NewLife Foundation. The Baralle lab is supported by NIHR Research Professorship to D.B. (RP-2016-07-011).published version, accepted version (6 month embargo), submitted versio

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Maternal obesity during pregnancy alters daily activity and feeding cycles, and hypothalamic clock gene expression in adult male mouse offspring

An obesogenic diet adversely affects the endogenous mammalian circadian clock, altering daily activity and metabolism, and resulting in obesity. We investigated whether an obese pregnancy can alter the molecular clock in the offspring hypothalamus, resulting in changes to their activity and feeding rhythms. Female mice were fed a control (C, 7% kcal fat) or high fat diet (HF, 45% kcal fat) before mating and throughout pregnancy. Male offspring were fed the C or HF diet postweaning, resulting in four offspring groups: C/C, C/HF, HF/C, and HF/HF. Daily activity and food intake were monitored, and at 15 weeks of age were killed at six time-points over 24 h. The clock genes Clock, Bmal1, Per2, and Cry2 in the suprachiasmatic nucleus (SCN) and appetite genes Npy and Pomc in the arcuate nucleus (ARC) were measured. Daily activity and feeding cycles in the HF/C, C/HF, and HF/HF offspring were altered, with increased feeding bouts and activity during the day and increased food intake but reduced activity at night. Gene expression patterns and levels of Clock, Bmal1, Per2, and Cry2 in the SCN and Npy and Pomc in the ARC were altered in HF diet-exposed offspring. The altered expression of hypothalamic molecular clock components and appetite genes, together with changes in activity and feeding rhythms, could be contributing to offspring obesity