Predictive signature of murine and human host response to typical and atypical pneumonia.

BACKGROUND: Pneumonia due to typical bacterial, atypical bacterial and viral pathogens can be difficult to clinically differentiate. Host response-based diagnostics are emerging as a complementary diagnostic strategy to pathogen detection. METHODS: We used murine models of typical bacterial, atypical bacterial and viral pneumonia to develop diagnostic signatures and understand the host's response to these types of infections. Mice were intranasally inoculated with Streptococcus pneumoniae, Mycoplasma pneumoniae, influenza or saline as a control. Peripheral blood gene expression analysis was performed at multiple time points. Differentially expressed genes were used to perform gene set enrichment analysis and generate diagnostic signatures. These murine-derived signatures were externally validated in silico using human gene expression data. The response to S. pneumoniae was the most rapid and robust. RESULTS: Mice infected with M. pneumoniae had a delayed response more similar to influenza-infected animals. Diagnostic signatures for the three types of infection had 0.94-1.00 area under the receiver operator curve (auROC). Validation in five human gene expression datasets revealed auROC of 0.82-0.96. DISCUSSION: This study identified discrete host responses to typical bacterial, atypical bacterial and viral aetiologies of pneumonia in mice. These signatures validated well in humans, highlighting the conserved nature of the host response to these pathogen classes.

Implementing a pragmatic clinical trial to tailor opioids for chronic pain on behalf of the IGNITE ADOPT PGx investigators.

Chronic pain is a prevalent condition with enormous economic burden. Opioids such as tramadol, codeine, and hydrocodone are commonly used to treat chronic pain; these drugs are activated to more potent opioid receptor agonists by the hepatic CYP2D6 enzyme. Results from clinical studies and mechanistic understandings suggest that CYP2D6-guided therapy will improve pain control and reduce adverse drug events. However, CYP2D6 is rarely used in clinical practice due in part to the demand for additional clinical trial evidence. Thus, we designed the ADOPT-PGx (A Depression and Opioid Pragmatic Trial in Pharmacogenetics) chronic pain study, a multicenter, pragmatic, randomized controlled clinical trial, to assess the effect of CYP2D6 testing on pain management. The study enrolled 1048 participants who are taking or being considered for treatment with CYP2D6-impacted opioids for their chronic pain. Participants were randomized to receive immediate or delayed (by 6 months) genotyping of CYP2D6 with clinical decision support (CDS). CDS encouraged the providers to follow the CYP2D6-guided trial recommendations. The primary study outcome is the 3-month absolute change in the composite pain intensity score assessed using Patient-Reported Outcomes Measurement Information System (PROMIS) measures. Follow-up will be completed in July 2024. Herein, we describe the design of this trial along with challenges encountered during enrollment.

Weight, habitual fibre intake, and microbiome composition predict tolerance to fructan supplementation.

Fructans are commonly used as dietary fibre supplements for their ability to promote the growth of beneficial gut microbes. However, fructan consumption has been associated with various dosage-dependent side effects. We characterised side effects in an exploratory analysis of a randomised trial in healthy adults (n = 40) who consumed 18 g/day inulin or placebo. We found that individuals weighing more or habitually consuming higher fibre exhibited the best tolerance. Furthermore, we identified associations between gut microbiome composition and host tolerance. Specifically, higher levels of Christensenellaceae R-7 group were associated with gastrointestinal discomfort, and a machine-learning-based approach successfully predicted high levels of flatulence, with [Ruminococcus] torques group and (Oscillospiraceae) UCG-002 sp. identified as key predictive taxa. These data reveal trends that can help guide personalised recommendations for initial inulin dosage. Our results support prior ecological findings indicating that fibre supplementation has the greatest impact on individuals whose baseline fibre intake is lowest.

Rationale and design for a pragmatic randomized trial to assess gene-based prescribing for SSRIs in the treatment of depression.

Specific selective serotonin reuptake inhibitors (SSRIs) metabolism is strongly influenced by two pharmacogenes, CYP2D6 and CYP2C19. However, the effectiveness of prospectively using pharmacogenetic variants to select or dose SSRIs for depression is uncertain in routine clinical practice. The objective of this prospective, multicenter, pragmatic randomized controlled trial is to determine the effectiveness of genotype-guided selection and dosing of antidepressants on control of depression in participants who are 8 years or older with ≥3 months of depressive symptoms who require new or revised therapy. Those randomized to the intervention arm undergo pharmacogenetic testing at baseline and receive a pharmacy consult and/or automated clinical decision support intervention based on an actionable phenotype, while those randomized to the control arm have pharmacogenetic testing at the end of 6-months. In both groups, depression and drug tolerability outcomes are assessed at baseline, 1 month, 3 months (primary), and 6 months. The primary end point is defined by change in Patient-Reported Outcomes Measurement Information System (PROMIS) Depression score assessed at 3 months versus baseline. Secondary end points include change inpatient health questionnaire (PHQ-8) measure of depression severity, remission rates defined by PROMIS score < 16, medication adherence, and medication side effects. The primary analysis will compare the PROMIS score difference between trial arms among those with an actionable CYP2D6 or CYP2C19 genetic result or a CYP2D6 drug-drug interaction. The trial has completed accrual of 1461 participants, of which 562 were found to have an actionable phenotype to date, and follow-up will be complete in April of 2024.

Lipoprotein subclasses are associated with Hepatic steatosis: insights from the prospective multicenter imaging study for the evaluation of chest pain (PROMISE) clinical trial.

Objectives: To determine the relationship between lipoprotein particle size/number with hepatic steatosis (HS), given its association with traditional lipoproteins and coronary atherosclerosis. Methods: Individuals with available CT data and blood samples enrolled in the PROMISE trial were studied. HS was defined based on CT attenuation. Lipoprotein particle size/number were measured by nuclear magnetic resonance spectroscopy. Principal components analysis (PCA) was used for dimensionality reduction. The association of PCA factors and individual lipoprotein particle size/number with HS were assessed in multivariable regression models. Associations were validated in an independent cohort of 59 individuals with histopathology defined HS. Results: Individuals with HS (n=410/1,509) vs those without (n=1,099/1,509), were younger (59±8 vs 61±8 years) and less often females (47.6 % vs 55.9 %). All PCA factors were associated with HS: factor 1 (OR:1.36, 95 %CI:1.21-1.53), factor 3 (OR:1.75, 95 %CI:1.53-2.02) and factor 4 (OR:1.49; 95 %CI:1.32-1.68) were weighted heavily with small low density lipoprotein (LDL) and triglyceride-rich (TRL) particles, while factor 2 (OR:0.86, 95 %CI:0.77-0.97) and factor 5 (OR:0.74, 95 %CI:0.65-0.84) were heavily loaded with high density lipoprotein (HDL) and larger LDL particles. These observations were confirmed with the analysis of individual lipoprotein particles in PROMISE. In the validation cohort, association between HS and large TRL (OR: 8.16, 95 %CI:1.82-61.98), and mean sizes of TRL- (OR: 2.82, 95 %CI:1.14-9.29) and HDL (OR:0.35, 95 %CI:0.13-0.72) were confirmed. Conclusions: Large TRL, mean sizes of TRL-, and HDL were associated with radiographic and histopathologic HS. The use of lipoprotein particle size/number could improve cardiovascular risk assessment in HS.

Implementation of a Prospective Index-Cluster Sampling Strategy for the Detection of Presymptomatic Viral Respiratory Infection in Undergraduate Students.

Background: Index-cluster studies may help characterize the spread of communicable infections in the presymptomatic state. We describe a prospective index-cluster sampling strategy (ICSS) to detect presymptomatic respiratory viral illness and its implementation in a college population. Methods: We enrolled an annual cohort of first-year undergraduates who completed daily electronic symptom diaries to identify index cases (ICs) with respiratory illness. Investigators then selected 5-10 potentially exposed, asymptomatic close contacts (CCs) who were geographically co-located to follow for infections. Symptoms and nasopharyngeal samples were collected for 5 days. Logistic regression model-based predictions for proportions of self-reported illness were compared graphically for the whole cohort sampling group and the CC group. Results: We enrolled 1379 participants between 2009 and 2015, including 288 ICs and 882 CCs. The median number of CCs per IC was 6 (interquartile range, 3-8). Among the 882 CCs, 111 (13%) developed acute respiratory illnesses. Viral etiology testing in 246 ICs (85%) and 719 CCs (82%) identified a pathogen in 57% of ICs and 15% of CCs. Among those with detectable virus, rhinovirus was the most common (IC: 18%; CC: 6%) followed by coxsackievirus/echovirus (IC: 11%; CC: 4%). Among 106 CCs with a detected virus, only 18% had the same virus as their associated IC. Graphically, CCs did not have a higher frequency of self-reported illness relative to the whole cohort sampling group. Conclusions: Establishing clusters by geographic proximity did not enrich for cases of viral transmission, suggesting that ICSS may be a less effective strategy to detect spread of respiratory infection.

Remote digital health technologies for improving the care of people with respiratory disorders.

Respiratory diseases are a leading cause of morbidity and mortality globally. However, existing systems of care, built around scheduled appointments, are not well designed to support the needs of people with chronic and acute respiratory conditions that can change rapidly and unexpectedly. Home-based and personal digital health technologies (DHTs) allow implementation of new models of care catering to the unique needs of individuals. The high number of respiratory triggers and unique responses to them require a personalised solution for each patient. The real-world, repetitive monitoring capabilities of DHTs enable identification of the normal operating characteristics for each individual and, therefore, recognition of the earliest deviations from that state. However, despite this potential, the number of clinical efficacy studies of DHTs is quite small. Evaluation of clinical effectiveness of DHTs in improving health quality in real-world settings is urgently needed.

Platelet RNA Biomarker of Ticagrelor-Responsive Genes Is Associated With Platelet Function and Cardiovascular Events.

BACKGROUND: Identifying patients with the optimal risk:benefit for ticagrelor is challenging. The aim was to identify ticagrelor-responsive platelet transcripts as biomarkers of platelet function and cardiovascular risk. METHODS: Healthy volunteers (n=58, discovery; n=49, validation) were exposed to 4 weeks of ticagrelor with platelet RNA data, platelet function, and self-reported bleeding measured pre-/post-ticagrelor. RNA sequencing was used to discover platelet genes affected by ticagrelor, and a subset of the most informative was summarized into a composite score and tested for validation. This score was further analyzed (1) in CD34+ megakaryocytes exposed to an P2Y12 inhibitor in vitro, (2) with baseline platelet function in healthy controls, (3) in peripheral artery disease patients (n=139) versus patient controls (n=30) without atherosclerosis, and (4) in patients with peripheral artery disease for correlation with atherosclerosis severity and risk of incident major adverse cardiovascular and limb events. RESULTS: Ticagrelor exposure differentially expressed 3409 platelet transcripts. Of these, 111 were prioritized to calculate a Ticagrelor Exposure Signature score, which ticagrelor reproducibly increased in discovery and validation cohorts. Ticagrelor's effects on platelets transcripts positively correlated with effects of P2Y12 inhibition in primary megakaryocytes. In healthy controls, higher baseline scores correlated with lower baseline platelet function and with minor bleeding while receiving ticagrelor. In patients, lower scores independently associated with both the presence and extent of atherosclerosis and incident ischemic events. CONCLUSIONS: Ticagrelor-responsive platelet transcripts are a biomarker for platelet function and cardiovascular risk and may have clinical utility for selecting patients with optimal risk:benefit for ticagrelor use.

Data-driven science and diversity in the All of Us Research Program.

The National Institutes of Health's All of Us Research Program is an accessible platform that hosts genomic and phenotypic data to be collected from 1 million participants in the United States. Its mission is to accelerate medical research and clinical breakthroughs with a special emphasis on diversity.

Host-response transcriptional biomarkers accurately discriminate bacterial and viral infections of global relevance.

Diagnostic limitations challenge management of clinically indistinguishable acute infectious illness globally. Gene expression classification models show great promise distinguishing causes of fever. We generated transcriptional data for a 294-participant (USA, Sri Lanka) discovery cohort with adjudicated viral or bacterial infections of diverse etiology or non-infectious disease mimics. We then derived and cross-validated gene expression classifiers including: 1) a single model to distinguish bacterial vs. viral (Global Fever-Bacterial/Viral [GF-B/V]) and 2) a two-model system to discriminate bacterial and viral in the context of noninfection (Global Fever-Bacterial/Viral/Non-infectious [GF-B/V/N]). We then translated to a multiplex RT-PCR assay and independent validation involved 101 participants (USA, Sri Lanka, Australia, Cambodia, Tanzania). The GF-B/V model discriminated bacterial from viral infection in the discovery cohort an area under the receiver operator curve (AUROC) of 0.93. Validation in an independent cohort demonstrated the GF-B/V model had an AUROC of 0.84 (95% CI 0.76-0.90) with overall accuracy of 81.6% (95% CI 72.7-88.5). Performance did not vary with age, demographics, or site. Host transcriptional response diagnostics distinguish bacterial and viral illness across global sites with diverse endemic pathogens.

Branched-Chain Amino Acids in Computed Tomography-Defined Adipose Depots and Coronary Artery Disease: A PROMISE Trial Biomarker Substudy.

Background The interplay between branched-chain amino acid (BCAA) metabolism, an important pathway in adiposity and cardiometabolic disease, and visceral adipose depots such as hepatic steatosis (HS) and epicardial adipose tissue is unknown. We leveraged the PROMISE clinical trial with centrally adjudicated coronary computed tomography angiography imaging to determine relationships between adipose depots, BCAA dysregulation, and coronary artery disease (CAD). Methods and Results The PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) trial randomized 10 003 outpatients with stable chest pain to computed tomography angiography versus standard-of-care diagnostics. For this study, we included 1798 participants with available computed tomography angiography data and biospecimens. Linear and logistic regression were used to determine associations between a molar sum of BCAAs measured by nuclear magnetic resonance spectroscopy with body mass index, adipose traits, and obstructive CAD. Mendelian randomization was then used to determine if BCAAs are in the causal pathway for adipose depots or CAD. The study sample had a mean age of 60 years (SD, 8.0), body mass index of 30.6 (SD, 5.9), and epicardial adipose tissue volume of 57.3 (SD, 21.3) cm3/m2; 27% had HS, and 14% had obstructive CAD. BCAAs were associated with body mass index (multivariable beta 0.12 per SD increase in BCAA [95% CI, 0.08-0.17]; P=4×10-8). BCAAs were also associated with HS (multivariable odds ratio [OR], 1.46 per SD increase in BCAAs [95% CI, 1.28-1.67]; P=2×10-8), but BCAAs were associated only with epicardial adipose tissue volume (odds ratio, 1.18 [95% CI, 1.07-1.32]; P=0.002) and obstructive CAD (OR, 1.18 [95% CI, 1.04-1.34]; P=0.009) in univariable models. Two-sample Mendelian randomization did not support the role of BCAAs as within the causal pathways for HS or CAD. Conclusions BCAAs have been implicated in the pathogenesis of cardiometabolic diseases, and adipose depots have been associated with the risk of CAD. Leveraging a large clinical trial, we further establish the role of dysregulated BCAA catabolism in HS and CAD, although BCAAs did not appear to be in the causal pathway of either disease. This suggests that BCAAs may serve as an independent circulating biomarker of HS and CAD but that their association with these cardiometabolic diseases is mediated through other pathways.

An antiplatelet response gene expression signature is associated with bleeding.

AIMS: Gene expression biosignatures may hold promise to individualize antiplatelet therapy in conjunction with current guidelines and risk scores. The Aspirin Response Signature (ARS) score is comprised of a weighted sum of correlated, pro-thrombotic gene transcripts measured in whole blood. In prior work where volunteers were exposed to aspirin 325 mg daily, higher ARS score was associated with lower platelet function; separately, in a clinical cohort of patients, higher ARS scores were associated with increased risk of adverse cardiovascular events. To better understand this apparent paradox, we measured ARS gene expression and score in volunteers to determine aspirin dose-response and ticagrelor relationships with ARS score and separately in patients to assess whether ARS is associated with incident bleeding. METHODS AND RESULTS: Blood samples were collected from volunteers (N = 188) who were exposed to 4 weeks of daily aspirin 81 mg, daily aspirin 325 mg, and/or twice-daily ticagrelor 90 mg. ARS scores were calculated from whole blood RNA qPCR, and platelet function and protein expression were assessed in platelet-rich plasma. In mixed linear regression models, aspirin 81 mg exposure was not associated with changes in ARS gene expression or score. Aspirin 325 mg exposure resulted in a 6.0% increase in ARS gene expression (P = 7.5 × 10-9 vs. baseline, P = 2.1 × 10-4 vs. aspirin 81 mg) and an increase in expression of platelet proteins corresponding to ARS genes. Ticagrelor exposure resulted in a 30.7% increase in ARS gene expression (P < 1 × 10-10 vs. baseline and each aspirin dose) and ARS score (P = 7.0 × 10-7 vs. baseline, P = 3.6 × 10-6 and 5.59 × 10-4 vs. aspirin 81 and 325 mg, respectively). Increases in ARS gene expression or score were associated with the magnitude of platelet inhibition across agents. To assess the association between ARS scores and incident bleeding, ARS scores were calculated in patients undergoing cardiac catheterization (N = 1421), of whom 25.4% experienced bleeding events over a median 6.2 years of follow-up. In a Cox model adjusting for demographics and baseline antithrombotic medication use, patients with ARS scores above the median had a higher risk of incident bleeding [hazard ratio 1.26 (95% CI 1.01-1.56), P = 0.038]. CONCLUSIONS: The ARS is an Antiplatelet Response Signature that increases in response to greater platelet inhibition due to antiplatelet therapy and may represent a homeostatic mechanism to prevent bleeding. ARS scores could inform future strategies to prevent bleeding while maintaining antiplatelet therapy's benefit of ischaemic cardiovascular event protection.