Evidence-based use of scalable biomarkers to increase diagnostic efficiency and decrease the lifetime costs of autism.

Challenges associated with the current screening and diagnostic process for autism spectrum disorder (ASD) in the US cause a significant delay in the initiation of evidence-based interventions at an early age when treatments are most effective. The present study shows how implementing a second-order diagnostic measure to high risk cases initially flagged positive from screening tools can further inform clinical judgment and substantially improve early identification. We use two example measures for the purposes of this demonstration; a saliva test and eye-tracking technology, both scalable and easy-to-implement biomarkers recently introduced in ASD research. Results of the current cost-savings analysis indicate that lifetime societal cost savings in special education, medical and residential care are estimated to be nearly $580,000 per ASD child, with annual cost savings in education exceeding $13.3 billion, and annual cost savings in medical and residential care exceeding $23.8 billion (of these, nearly $11.2 billion are attributable to Medicaid). These savings total more than $37 billion/year in societal savings in the US. Initiating appropriate interventions faster and reducing the number of unnecessary diagnostic evaluations can decrease the lifetime costs of ASD to society. We demonstrate the value of implementing a scalable highly accurate diagnostic in terms of cost savings to the US. LAY SUMMARY: This paper demonstrates how biomarkers with high accuracy for detecting autism spectrum disorder (ASD) could be used to increase the efficiency of early diagnosis. Results also show that, if more children with ASD are identified early and referred for early intervention services, the system would realize substantial costs savings across the lifespan.

The oral microbiome of early stage Parkinson's disease and its relationship with functional measures of motor and non-motor function.

Changes in the function and microbiome of the upper and lower gastrointestinal tract have been documented in Parkinson's disease (PD), although most studies have examined merely fecal microbiome profiles and patients with advanced disease states. In the present study we sought to identify sensitive and specific biomarkers of changes in the oral microbiome of early stage PD through shotgun metatranscriptomic profiling. We recruited 48 PD subjects and 36 age- and gender-matched healthy controls. Subjects completed detailed assessments of motor, cognitive, balance, autonomic and chemosensory (smell and taste) functions to determine their disease stage. We also obtained a saliva sample for profiling of microbial RNA and host mRNA using next generation sequencing. We found no differences in overall alpha and beta diversity between subject groups. However, changes in specific microbial taxa were observed, including primarily bacteria, but also yeast and phage. Nearly half of our findings were consistent with prior studies in the field obtained through profiling of fecal samples, with others representing highly novel candidates for detection of early stage PD. Testing of the diagnostic utility of the microbiome data revealed potentially robust performance with as few as 11 taxonomic features achieving a cross-validated area under the ROC curve of 0.90 and overall accuracy of 84.5%. Bioinformatic analysis of 167 different metabolic pathways supported shifts in a small set of distinct pathways involved in amino acid and energy metabolism among the organisms comprising the oral microbiome. In parallel with the microbial analysis, we also examined the evidence for changes in human salivary mRNAs in the same subjects. This revealed significant changes in a set of 9 host mRNAs, several of which mapped to various brain functions and showed correlations with some of the significantly changed microbial taxa. Unexpectedly, we also observed robust correlations between many of the microbiota and functional measures, including those reflecting cognition, balance, and disease duration. These results suggest that the oral microbiome may represent a highly-accessible and informative microenvironment that offers new insights in the pathophysiology of early stage PD.

Comparison of serum and saliva miRNAs for identification and characterization of mTBI in adult mixed martial arts fighters.

Traumatic brain injury (TBI) is a major cause of death and disability worldwide, with mild TBI (mTBI) accounting for 85% of cases. mTBI is also implicated in serious long-term sequelae including second impact syndrome and chronic traumatic encephalopathy. mTBI often goes undiagnosed due to delayed symptom onset and limited sensitivity of conventional assessment measures compared with severe TBI. Current efforts seek to identify accurate and reliable non-invasive biomarkers associated with functional measures relevant to long-term outcomes. Here we evaluated the utility of serum and salivary microRNAs (miRNAs) to serve as sensitive and specific peripheral biomarkers of possible mTBI. Our primary objectives were to establish the relationship between peripheral measures of miRNA, objective quantification of head impacts, and sensitive indices of balance and cognitive function in healthy young adult athletes. A secondary objective was to compare the sensitivity of miRNA versus commonly used blood-based protein biomarkers. 50 amateur mixed martial arts (MMA) fighters participated. 216 saliva and serum samples were collected at multiple time points, both pre- and post-fight. Levels of 10 serum proteins were compared in a subset of the fighters (n = 24). Levels of miRNAs were obtained by next generation sequencing. Functional outcomes were evaluated using a computerized assessment system that measured cognitive performance, body sway, and combined cognitive performance and body sway during dual task completion. Data were analyzed using multivariate logistic regression for predictive classification, analysis of variance, correlation analysis and principal component analysis. We identified a subset of salivary and serum miRNAs that showed robust utility at predicting TBI likelihood and demonstrated quantitative associations with head impacts as well as cognitive and balance measures. In contrast, serum proteins demonstrated far less utility. We also found that the timing of the responses varies in saliva and serum, which is a critical observation for biomarker studies to consider.

Oral microbiome activity in children with autism spectrum disorder.

Autism spectrum disorder (ASD) is associated with several oropharyngeal abnormalities, including buccal sensory sensitivity, taste and texture aversions, speech apraxia, and salivary transcriptome alterations. Furthermore, the oropharynx represents the sole entry point to the gastrointestinal (GI) tract. GI disturbances and alterations in the GI microbiome are established features of ASD, and may impact behavior through the "microbial-gut-brain axis." Most studies of the ASD microbiome have used fecal samples. Here, we identified changes in the salivary microbiome of children aged 2-6 years across three developmental profiles: ASD (n = 180), nonautistic developmental delay (DD; n = 60), and typically developing (TD; n = 106) children. After RNA extraction and shotgun sequencing, actively transcribing taxa were quantified and tested for differences between groups and within ASD endophenotypes. A total of 12 taxa were altered between the developmental groups and 28 taxa were identified that distinguished ASD patients with and without GI disturbance, providing further evidence for the role of the gut-brain axis in ASD. Group classification accuracy was visualized with receiver operating characteristic curves and validated using a 50/50 hold-out procedure. Five microbial ratios distinguished ASD from TD participants (79.5% accuracy), three distinguished ASD from DD (76.5%), and three distinguished ASD children with/without GI disturbance (85.7%). Taxonomic pathways were assessed using the Kyoto Encyclopedia of Genes and Genomes microbial database and compared with one-way analysis of variance, revealing significant differences within energy metabolism and lysine degradation. Together, these results indicate that GI microbiome disruption in ASD extends to the oropharynx, and suggests oral microbiome profiling as a potential tool to evaluate ASD status. Autism Res 2018, 11: 1286-1299. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Previous research suggests that the bacteria living in the human gut may influence autistic behavior. This study examined genetic activity of microbes living in the mouth of over 300 children. The microbes with differences in children with autism were involved in energy processing and showed potential for identifying autism status.

Diurnal oscillations in human salivary microRNA and microbial transcription: Implications for human health and disease.

The microbiome plays a vital role in human health and disease. Interaction between human hosts and the microbiome occurs through a number of mechanisms, including transcriptomic regulation by microRNA (miRNA). In animal models, circadian variations in miRNA and microbiome elements have been described, but patterns of co-expression and potential diurnal interaction in humans have not. We investigated daily oscillations in salivary miRNA and microbial RNA to explore relationships between these components of the gut-brain-axis and their implications in human health. Nine subjects provided 120 saliva samples at designated times, on repeated days. Samples were divided into three sets for exploration and cross-validation. Identification and quantification of host miRNA and microbial RNA was performed using next generation sequencing. Three stages of statistical analyses were used to identify circadian oscillators: 1) a two-way analysis of variance in the first two sample sets identified host miRNAs and microbial RNAs whose abundance varied with collection time (but not day); 2) multivariate modeling identified subsets of these miRNAs and microbial RNAs strongly-associated with collection time, and evaluated their predictive ability in an independent hold-out sample set; 3) regulation of circadian miRNAs and microbial RNAs was explored in data from autistic children with disordered sleep (n = 77), relative to autistic peers with typical sleep (n = 63). Eleven miRNAs and 11 microbial RNAs demonstrated consistent diurnal oscillation across sample sets and accurately predicted collection time in the hold-out set. Associations among five circadian miRNAs and four circadian microbial RNAs were observed. We termed the 11 miRNAs CircaMiRs. These CircaMiRs had 1,127 predicted gene targets, with enrichment for both circadian gene targets and metabolic signaling processes. Four CircaMiRs had "altered" expression patterns among children with disordered sleep. Thus, novel and correlated circadian oscillations in human miRNA and microbial RNA exist and may have distinct implications in human health and disease.