Saliva microRNA Biomarkers of Cumulative Concussion.

Recurrent concussions increase risk for persistent post-concussion symptoms, and may lead to chronic neurocognitive deficits. Little is known about the molecular pathways that contribute to persistent concussion symptoms. We hypothesized that salivary measurement of microribonucleic acids (miRNAs), a class of epitranscriptional molecules implicated in concussion pathophysiology, would provide insights about the molecular cascade resulting from recurrent concussions. This hypothesis was tested in a case-control study involving 13 former professional football athletes with a history of recurrent concussion, and 18 age/sex-matched peers. Molecules of interest were further validated in a cross-sectional study of 310 younger individuals with a history of no concussion (n = 230), a single concussion (n = 56), or recurrent concussions (n = 24). There was no difference in neurocognitive performance between the former professional athletes and their peers, or among younger individuals with varying concussion exposures. However, younger individuals without prior concussion outperformed peers with prior concussion on three balance assessments. Twenty salivary miRNAs differed (adj. p < 0.05) between former professional athletes and their peers. Two of these (miR-28-3p and miR-339-3p) demonstrated relationships (p < 0.05) with the number of prior concussions reported by younger individuals. miR-28-3p and miR-339-5p may play a role in the pathophysiologic mechanism involved in cumulative concussion effects.

Clinical validation of a cell-free DNA fragmentome assay for augmentation of lung cancer early detection.

Lung cancer screening via annual low-dose computed tomography (LDCT) has poor adoption. We conducted a prospective case-control study among 958 individuals eligible for lung cancer screening to develop a blood-based lung cancer detection test that when positive is followed by an LDCT. Changes in genome-wide cell-free DNA (cfDNA) fragmentation profiles (fragmentomes) in peripheral blood reflected genomic and chromatin characteristics of lung cancer. We applied machine learning to fragmentome features to identify individuals who were more or less likely to have lung cancer. We trained the classifier using 576 cases and controls from study samples, and then validated it in a held-out group of 382 cases and controls. The validation demonstrated high sensitivity for lung cancer, and consistency across demographic groups and comorbid conditions. Applying test performance to the screening eligible population in a five-year model with modest utilization assumptions suggested the potential to prevent thousands of lung cancer deaths.

Saliva RNA biomarkers predict concussion duration and detect symptom recovery: a comparison with balance and cognitive testing.

OBJECTIVE: The goals of this study were to assess the ability of salivary non-coding RNA (ncRNA) levels to predict post-concussion symptoms lasting ≥ 21 days, and to examine the ability of ncRNAs to identify recovery compared to cognition and balance. METHODS: RNA sequencing was performed on 505 saliva samples obtained longitudinally from 112 individuals (8-24-years-old) with mild traumatic brain injury (mTBI). Initial samples were obtained ≤ 14 days post-injury, and follow-up samples were obtained ≥ 21 days post-injury. Computerized balance and cognitive test performance were assessed at initial and follow-up time-points. Machine learning was used to define: (1) a model employing initial ncRNA levels to predict persistent post-concussion symptoms (PPCS) ≥ 21 days post-injury; and (2) a model employing follow-up ncRNA levels to identify symptom recovery. Performance of the models was compared against a validated clinical prediction rule, and balance/cognitive test performance, respectively. RESULTS: An algorithm using age and 16 ncRNAs predicted PPCS with greater accuracy than the validated clinical tool and demonstrated additive combined utility (area under the curve (AUC) 0.86; 95% CI 0.84-0.88). Initial balance and cognitive test performance did not differ between PPCS and non-PPCS groups (p > 0.05). Follow-up balance and cognitive test performance identified symptom recovery with similar accuracy to a model using 11 ncRNAs and age. A combined model (ncRNAs, balance, cognition) most accurately identified recovery (AUC 0.86; 95% CI 0.83-0.89). CONCLUSIONS: ncRNA biomarkers show promise for tracking recovery from mTBI, and for predicting who will have prolonged symptoms. They could provide accurate expectations for recovery, stratify need for intervention, and guide safe return-to-activities.

Prediction of optimal contrast times post-imaging agent administration to inform personalized fluorescence-guided surgery.

SIGNIFICANCE: Fluorescence guidance in cancer surgery (FGS) using molecular-targeted contrast agents is accelerating, yet the influence of individual patients' physiology on the optimal time to perform surgery post-agent-injection is not fully understood. AIM: Develop a mathematical framework and analytical expressions to estimate patient-specific time-to-maximum contrast after imaging agent administration for single- and paired-agent (coadministration of targeted and control agents) protocols. APPROACH: The framework was validated in mouse subcutaneous xenograft studies for three classes of imaging agents: peptide, antibody mimetic, and antibody. Analytical expressions estimating time-to-maximum-tumor-discrimination potential were evaluated over a range of parameters using the validated framework for human cancer parameters. RESULTS: Correlations were observed between simulations and matched experiments and metrics of tumor discrimination potential (p < 0.05). Based on human cancer physiology, times-to-maximum contrast for peptide and antibody mimetic agents were <200 min, >15 h for antibodies, on average. The analytical estimates of time-to-maximum tumor discrimination performance exhibited errors of <10 % on average, whereas patient-to-patient variance is expected to be greater than 100%. CONCLUSION: We demonstrated that analytical estimates of time-to-maximum contrast in FGS carried out patient-to-patient can outperform the population average time-to-maximum contrast used currently in clinical trials. Such estimates can be made with preoperative DCE-MRI (or similar) and knowledge of the targeted agent's binding affinity.

Diagnosing mild traumatic brain injury using saliva RNA compared to cognitive and balance testing.

BACKGROUND: Early, accurate diagnosis of mild traumatic brain injury (mTBI) can improve clinical outcomes for patients, but mTBI remains difficult to diagnose because of reliance on subjective symptom reports. An objective biomarker could increase diagnostic accuracy and improve clinical outcomes. The aim of this study was to assess the ability of salivary noncoding RNA (ncRNA) to serve as a diagnostic adjunct to current clinical tools. We hypothesized that saliva ncRNA levels would demonstrate comparable accuracy for identifying mTBI as measures of symptom burden, neurocognition, and balance. METHODS: This case-control study involved 538 individuals. Participants included 251 individuals with mTBI, enrolled ≤14 days postinjury, from 11 clinical sites. Saliva samples (n = 679) were collected at five time points (≤3, 4-7, 8-14, 15-30, and 31-60 days post-mTBI). Levels of ncRNAs (microRNAs, small nucleolar RNAs, and piwi-interacting RNAs) were quantified within each sample using RNA sequencing. The first sample from each mTBI participant was compared to saliva samples from 287 controls. Samples were divided into testing (n = 430; mTBI = 201 and control = 239) and training sets (n = 108; mTBI = 50 and control = 58). The test set was used to identify ncRNA diagnostic candidates and create a diagnostic model. Model accuracy was assessed in the naïve test set. RESULTS: A model utilizing seven ncRNA ratios, along with participant age and chronic headache status, differentiated mTBI and control participants with a cross-validated area under the curve (AUC) of .857 in the training set (95% CI, .816-.903) and .823 in the naïve test set. In a subset of participants (n = 321; mTBI = 176 and control = 145) assessed for symptom burden (Post-Concussion Symptom Scale), as well as neurocognition and balance (ClearEdge System), these clinical measures yielded cross-validated AUC of .835 (95% CI, .782-.880) and .853 (95% CI, .803-.899), respectively. A model employing symptom burden and four neurocognitive measures identified mTBI participants with similar AUC (.888; CI, .845-.925) as symptom burden and four ncRNAs (.932; 95% CI, .890-.965). CONCLUSION: Salivary ncRNA levels represent a noninvasive, biologic measure that can aid objective, accurate diagnosis of mTBI.