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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Comprehensive Urine Proteome Database Generated From Patients With Various Renal Conditions and Prostate Cancer

Urine proteins can serve as viable biomarkers for diagnosing and monitoring various diseases. A comprehensive urine proteome database, generated from a variety of urine samples with different disease conditions, can serve as a reference resource for facilitating discovery of potential urine protein biomarkers. Herein, we present a urine proteome database generated from multiple datasets using 2D LC-MS/MS proteome profiling of urine samples from healthy individuals (HI), renal transplant patients with acute rejection (AR) and stable graft (STA), patients with non-specific proteinuria (NS), and patients with prostate cancer (PC). A total of ~28,000 unique peptides spanning ~2,200 unique proteins were identified with a false discovery rate of <0.5% at the protein level. Over one third of the annotated proteins were plasma membrane proteins and another one third were extracellular proteins according to gene ontology analysis. Ingenuity Pathway Analysis of these proteins revealed 349 potential biomarkers in the literature-curated database. Forty-three percentage of all known cluster of differentiation (CD) proteins were identified in the various human urine samples. Interestingly, following comparisons with five recently published urine proteome profiling studies, which applied similar approaches, there are still ~400 proteins which are unique to this current study. These may represent potential disease-associated proteins. Among them, several proteins such as serpin B3, renin receptor, and periostin have been reported as pathological markers for renal failure and prostate cancer, respectively. Taken together, our data should provide valuable information for future discovery and validation studies of urine protein biomarkers for various diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Targeted metabolomic analysis identifies increased serum levels of GABA and branched chain amino acids in canine diabetes

Introduction Dogs with naturally occurring diabetes mellitus represent a potential model for human type 1 diabetes, yet signifcant knowledge voids exist in terms of the pathogenic mechanisms underlying the canine disorder. Untargeted metabolomic studies from a limited number of diabetic dogs identifed similarities to humans with the disease. Objective To expand and validate earlier metabolomic studies, identify metabolites that difer consistently between diabetic and healthy dogs, and address whether certain metabolites might serve as disease biomarkers. Methods Untargeted metabolomic analysis via liquid chromatography-mass spectrometry was performed on serum from diabetic (n=15) and control (n=15) dogs. Results were combined with those of our previously published studies using identical methods (12 diabetic and 12 control dogs) to identify metabolites consistently diferent between the groups in all 54 dogs. Thirty-two candidate biomarkers were quantifed using targeted metabolomics. Biomarker concentrations were compared between the groups using multiple linear regression (corrected P<0.0051 considered signifcant). Results Untargeted metabolomics identifed multiple persistent diferences in serum metabolites in diabetic dogs compared with previous studies. Therefore, targeted metabolomics showed increases in gamma amino butyric acid, valine, leucine, isoleucine, citramalate, and 2-hydroxyisobutyric acid in diabetic versus control dogs while indoxyl sulfate, N-acetyl-L-aspartic acid, kynurenine, anthranilic acid, tyrosine, glutamine, and tauroursodeoxycholic acid were decreased. Conclusion Several of these fndings parallel metabolomic studies in both human diabetes and other animal models of this disease. Given recent studies on the role of GABA and branched chain amino acids in human diabetes, the increase in serum concentrations in canine diabetes warrants further study of these metabolites as potential biomarkers, and to identify similarity in mechanisms underlying this disease in humans and dogs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The Role of Circulating Tumor Cells in Breast Cancer and Implications for Radiation Treatment Decisions

Tumor biomarkers are used routinely in oncology to assign risk categorization, screen and assist in diagnosis of malignancy, allow for prognostication and prediction of outcomes and treatment response, and allow for monitoring of patients after treatment completion. Although tissue-based biomarkers have a long history of use, the emergence of liquid-based biomarkers, including circulating tumor cells (CTCs), may soon revolutionize the management of patients with cancer. Here, we review the discovery of CTCs and their role as prognostic and predictive biomarkers, with an emphasis on breast cancer. We discuss the platforms for CTC enumeration and focus on studies using the only US Food and Drug Administration–approved platform for CTC enumeration (CellSearch). In addition, we examine the role of CTCs in women with metastatic, inflammatory, and nonmetastatic breast cancer, as well as the clinical evidence for their use as a surrogate for radiation treatment response as well as surveillance after treatment. Finally, we conclude by investigating ongoing clinical studies assessing CTCs as radiation response predictors and discuss unanswered questions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Quantitative Proteomics and Quantitative PCR as Predictors of cis -1,2-Dichlorethene and Vinyl Chloride Reductive Dechlorination Rates in Bioaugmented Aquifer Microcosms

Quantitative measurement of process-specific biomarker genes of Dehalococcoides mccartyi (Dhc) supports monitoring at chlorinated ethene contaminated sites. In this study, we varied Dhc cell abundances from ~103 to 108 cells/mL in aquifer microcosms and correlated the corresponding reductive dehalogenase (RDase) gene and RDase protein abundances with measured reductive dechlorination (RD) rates of cis-1,2-dichloroethene (cDCE) and vinyl chloride (VC). An additional set of microcosms tested the RD rate-predictive power of the regression analyses. These efforts revealed (1) that targeted proteomics quantifies Dhc biomarker proteins (e.g., TceA and VcrA, OmeA) over a relevant range of Dhc cell densities, and (2) that protein and gene abundances can predict RD rates. Protein detection limits translated to a rate coefficient of 10 –4 day –1 (0.04 year –1 ) for both k cDCE and k vc , which is within the range observed at sites undergoing monitored natural attenuation (MNA) (i.e., without the implementation of enhanced bioremediation treatment). Rates predicted using a combination of quantitative biomarker gene and protein measurements generally resulted in the best match with experimentally determined rate constants. These new findings provide evidence that quantitative biomarker measurements may be useful predictors of in situ RD rates, which would constitute a major advance for the cost-effective management of contaminated sites.

42 ENGINEERING↗
DOE OSTI2022

Data-driven causal model discovery and personalized prediction in Alzheimer's disease

Abstract With the explosive growth of biomarker data in Alzheimer’s disease (AD) clinical trials, numerous mathematical models have been developed to characterize disease-relevant biomarker trajectories over time. While some of these models are purely empiric, others are causal, built upon various hypotheses of AD pathophysiology, a complex and incompletely understood area of research. One of the most challenging problems in computational causal modeling is using a purely data-driven approach to derive the model’s parameters and the mathematical model itself, without any prior hypothesis bias. In this paper, we develop an innovative data-driven modeling approach to build and parameterize a causal model to characterize the trajectories of AD biomarkers. This approach integrates causal model learning, population parameterization, parameter sensitivity analysis, and personalized prediction. By applying this integrated approach to a large multicenter database of AD biomarkers, the Alzheimer’s Disease Neuroimaging Initiative, several causal models for different AD stages are revealed. In addition, personalized models for each subject are calibrated and provide accurate predictions of future cognitive status.

Zheng, Haoyang (ORCID:0000000168358242)↗
DOE OSTI2024

Multi-modal characterisation of early-stage, subclinical cardiac deterioration in patients with type 2 diabetes

Abstract Background Type 2 diabetes mellitus (T2DM) is a major risk factor for heart failure with preserved ejection fraction and cardiac arrhythmias. Precursors of these complications, such as diabetic cardiomyopathy, remain incompletely understood and underdiagnosed. Detection of early signs of cardiac deterioration in T2DM patients is critical for prevention. Our goal is to quantify T2DM-driven abnormalities in ECG and cardiac imaging biomarkers leading to cardiovascular disease. Methods We quantified ECG and cardiac magnetic resonance imaging biomarkers in two matched cohorts of 1781 UK Biobank participants, with and without T2DM, and no diagnosed cardiovascular disease at the time of assessment. We performed a pair-matched cross-sectional study to compare cardiac biomarkers in both cohorts, and examined the association between T2DM and these biomarkers. We built multivariate multiple linear regression models sequentially adjusted for socio-demographic, lifestyle, and clinical covariates. Results Participants with T2DM had a higher resting heart rate (66 vs. 61 beats per minute,p < 0.001), longer QTc interval (424 vs. 420ms,p < 0.001), reduced T wave amplitude (0.33 vs. 0.37mV,p < 0.001), lower stroke volume (72 vs. 78ml,p < 0.001) and thicker left ventricular wall (6.1 vs. 5.9mm,p < 0.001) despite a decreased Sokolow-Lyon index (19.1 vs. 20.2mm,p < 0.001). T2DM was independently associated with higher heart rate (beta = 3.11, 95% CI = [2.11,4.10],p < 0.001), lower stroke volume (beta = −4.11, 95% CI = [−6.03, −2.19],p < 0.001) and higher left ventricular wall thickness (beta = 0.133, 95% CI = [0.081,0.186],p < 0.001). Trends were consistent in subgroups of different sex, age and body mass index. Fewer significant differences were observed in participants of non-white ethnic background. QRS duration and Sokolow-Lyon index showed a positive association with the development of cardiovascular disease in cohorts with and without T2DM, respectively. A higher left ventricular mass and wall thickness were associated with cardiovascular outcomes in both groups. Conclusion T2DM prior to cardiovascular disease was linked with a higher heart rate, QTc prolongation, T wave amplitude reduction, as well as lower stroke volume and increased left ventricular wall thickness. Increased QRS duration and left ventricular wall thickness and mass were most strongly associated with future cardiovascular disease. Although subclinical, these changes may indicate the presence of autonomic dysfunction and diabetic cardiomyopathy. Graphical Abstract

Cardiovascular System & Cardiology↗
DOE OSTI2022

Xanthohumol microbiome and signature in adults with Crohn’s disease (the XMaS trial): a protocol for a phase II triple-masked, placebo-controlled clinical trial

Xanthohumol (XN), a bioactive flavonoid from Humulus lupulus with anti-inflammatory properties, has potential benefits for patients with Crohn’s disease (CD), a type of inflammatory bowel disease. We recently completed and published results of a placebo-controlled phase I clinical trial demonstrating the safety and tolerability of 24 mg XN daily for 8 weeks. The present study aims to evaluate the safety and tolerability of the same dose of XN adults with clinically active CD in a placebo-controlled phase II clinical trial. Additional aims will assess the impact of XN on inflammatory biomarkers, platelet function, CD clinical activity, and stool microbial composition. The metabolism of XN will also be evaluated. This article provides a model protocol for consideration in investigations of XN or other natural products in disease states. A triple-masked, randomized, placebo-controlled trial will be conducted in adults with clinically active CD. Participants (n ≤ 32) will be randomized to either 24 mg encapsulated XN per day or placebo and followed for 8 weeks. Throughout the trial, participants will be queried for adverse events. Biomarkers of clinical safety, blood and stool markers of inflammation, platelet function, Crohn’s Disease Activity Index score, stool microbial composition, and XN metabolite profiles in blood, urine, and stool will be assessed every 2 weeks. We describe the protocol for a phase II clinical trial that evaluates the safety and tolerability of XN in adults with active CD, as well as evaluate metabolism and mechanisms that are relevant to CD and other diseases with underlying inflammation and/or gut permeability. The effects of XN on inflammatory biomarkers, platelet function, the microbiota, and multi-omics biomarkers measured in this phase II trial of adults with CD will be compared to the effects of XN in healthy adults in our previous phase I trial. The results of the study will advance the evidence guiding the use of XN in patients with CD.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Adverse Neurological Effects of Wildfire Smoke

The respiratory and cardiovascular effects of smoke exposure are well documented from cigarette smoking and particulate matter (PM) associated with air-pollution studies, but epidemiological data also suggests exposure to high levels of woodsmoke correlate with central-nervous-system (CNS) dysfunction, including elevated rates of Alzheimer’s disease (AD) and dementia. Neuro-inflammation is believed to initiate the majority of Alzheimer’s and other neurodegenerative diseases attributed to environmental factors. We investigated whether inhaled PM and specific classes of compounds in wildfire smoke condensate extract (WSE) reach the brain and cause neuro-inflammation that can lead to progressive neurological degeneration, using isotope tracing of labeled particulate matter and major compound classes, biomarkers of blood-brain barrier (BBB) integrity, and biomarkers of neuro-inflammation. This project showed that inhalation exposure to PM and major compound classes present in WSE reached the brain through absorption in the nasal cavity and systemic circulation across the BBB. Twenty-four exposures of WSE to brain endothelial cells that form the main physical barrier of the BBB produced dose-dependent increases in biomarkers of inflammation and decreases in tight junction markers between cells. Intranasal exposure to WSE caused inflammatory disfunction in lung and brain. Biomarkers of inflammation increased and an enzyme inhibiting inflammation decreased. Similar patterns of chemical-induced changes in the lung and brain suggest either: (1) chemicals may act through shared molecular pathways upon entering lung and brain, or (2) that mediators originating in the lung circulate systemically to the brain and drive neuroinflammation. These findings warrant further mechanistic studies to delineate the temporal sequence of events to establish the lung-brain axis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

BRAVE_EBC-TMT.1.0

Exhaled breath condensate (EBC) represents a low-cost and non-invasive means of examining respiratory health. EBC has been used to discover and validate exhaled volatile and non-volatile biomarkers of disease related to the respiratory system distress such as asthma, COPD, lung cancer, and secondary infections. One newly emerging utilization of EBC, is proteomics analysis, which can provide an unbiased snapshot into ongoing biological processes in the airway. Fully characterizing the biological landscape of EBC collections is challenging though, due to sample variability, and low detection sensitivity. EBC is primarily composed of condensed water, causing technical challenges with detecting key macromolecules from the dilute sample matrix; therefore, high sensitivity techniques are required to unlock the full capability of EBC as a method for non-invasive biomarker detection. To overcome some of these technical challenges for proteomic analyses, we applied our recently developed microscale proteomic techniques and developed a novel TMT based approach which enabled reliable, relative quantification with significantly improved detection of low abundance peptides/proteins across multiple healthy volunteer EBC samples. Our EBC collection design includes longitudinal EBC collections from five individual healthy volunteers on three separate days of the week with triplicate, back-to-back donations each day. Here, we report a total of 235 quantifiable proteins corresponding to 1,877 non-redundant peptides for evaluating sample collection reproducibility and establishing a healthy (human host) baseline EBC biomarker proteome studies. This work will pave the way for further investigations of EBC protein expression profiles and showcase the value of using non-invasive collection method techniques for clinically relevant biomarker discovery. This research was supported by the LDRD Biomedical Resilience And Readiness in AdVerse Operating Environments (BRAVE) Project (73748), and was conducted at Pacific Northwest National Laboratory (PNNL) in Richland, WA. PNNL is a multiprogram national laboratory operated by Battelle for the Department of Energy (DOE) under Contract DE-AC05-76RLO 1830.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Concentration-response gene expression analysis in zebrafish reveals phenotypically-anchored transcriptional responses to retene

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental contaminants and are associated with human disease. Canonically, many PAHs induce toxicity via activation of the aryl hydrocarbon receptor (AHR) pathway. While the interaction between PAHs and the AHR is well-established, understanding which AHR-regulated transcriptional effects directly result in observable phenotypes and which are adaptive or benign is important to better understand PAH toxicity. Retene is a frequently detected PAH in environmental sampling and has been associated with AHR2-dependent developmental toxicity in zebrafish, though its mechanism of toxicity has not been fully elucidated. To interrogate transcriptional changes causally associated with retene toxicity, we conducted whole-animal RNA sequencing at 48 hours post-fertilization after exposure to eight retene concentrations. The concentrations were selected to produce effects ranging from no phenotype to mortality and malformations in 100% of animals at 5 days post-fertilization. We identified a concentration-response relationship between retene teratogenicity and differential gene expression in both number of DEGs and magnitude of expression change. Elevated expression of cyp1a at retene concentrations below the threshold for teratogenicity suggested that while cyp1a expression is a sensitive biomarker of AHR activation, it may be too sensitive to serve as a biomarker of AHR-dependent teratogenicity. Genes differentially expressed at only non-teratogenic concentrations were enriched for transforming growth factor-ß (TGF-ß) signaling pathway disruption while DEGs identified at only teratogenic concentrations were significantly enriched for response to xenobiotic stimulus and reduction-oxidation reaction activity. DEGs which spanned both non-teratogenic and teratogenic concentrations showed similar disrupted biological processes to those unique to teratogenic concentrations, indicating these processes were disrupted at low exposure concentrations. Gene co-expression network analysis identified several gene modules, including those associated with PAHs and AHR2 activation. One, Module 7, was strongly enriched for AHR2-associated genes and contained the strongest responses to retene. Benchmark concentration (BMC) of Module 7 genes identified a median BMC of 7.5 µM, nearly the highest retene concentration with no associated teratogenicity, supporting the hypothesis that Module 7 genes are largely responsible for retene toxicity.

Toxin, Zebrafish, Retene, Transcriptomics, network↗
DOE OSTI2024

Serum bile acid and unsaturated fatty acid profiles of non-alcoholic fatty liver disease in type 2 diabetic patients

The understanding of bile acid (BA) and unsaturated fatty acid (UFA) profiles, as well as their dysregulation, remains elusive in individuals with type 2 diabetes mellitus (T2DM) coexisting with non-alcoholic fatty liver disease (NAFLD). Investigating these metabolites could offer valuable insights into the pathophy-siology of NAFLD in T2DM. Our aim is to identify potential metabolite biomarkers capable of distinguishing between NAFLD and T2DM. A training model was developed involving 399 participants, comprising 113 healthy controls (HCs), 134 individuals with T2DM without NAFLD, and 152 individuals with T2DM and NAFLD. External validation encompassed 172 participants. NAFLD patients were divided based on liver fibrosis scores. The analytical approach employed univariate testing, orthogonal partial least squares-discriminant analysis, logistic regression, receiver operating characteristic curve analysis, and decision curve analysis to pinpoint and assess the diagnostic value of serum biomarkers. Compared to HCs, both T2DM and NAFLD groups exhibited diminished levels of specific BAs. In UFAs, particular acids exhibited a positive correlation with NAFLD risk in T2DM, while the ω-6:ω-3 UFA ratio demonstrated a negative correlation. Levels of α-linolenic acid and γ-linolenic acid were linked to significant liver fibrosis in NAFLD. The validation cohort substantiated the predictive efficacy of these biomarkers for assessing NAFLD risk in T2DM patients. This study underscores the connection between altered BA and UFA profiles and the presence of NAFLD in individuals with T2DM, proposing their potential as biomarkers in the pathogenesis of NAFLD.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Pan-cancer evaluation of clinical value of mitotic network activity index (MNAI) and its predictive value for immunotherapy

Increased mitotic activity is associated with the genesis and aggressiveness of many cancers. To assess the clinical value of mitotic activity as prognostic biomarker, we performed a pan-cancer study on the mitotic network activity index (MNAI) constructed based on 54-gene mitotic apparatus network. Our pan-cancer assessment on TCGA (33 tumor types, 10,061 patients) and validation on other publicly available cohorts (23 tumor types, 9,209 patients) confirmed the significant association of MNAI with overall survival, progression-free survival, and other prognostic endpoints in multiple cancer types, including lower-grade gliomas (LGG), breast invasive carcinoma (BRCA), as well as many others. We also showed significant association between MNAI and genetic instability, which provides a biological explanation of its prognostic impact at pan-cancer landscape. Our association analysis revealed that patients with high MNAI benefitted more from anti-PD-1 and Anti-CTLA-4 treatment. In addition, we demonstrated that multimodal integration of MNAI and the AI-empowered Cellular Morphometric Subtypes (CMS) significantly improved the predictive power of prognosis compared to using MNAI and CMS alone. Our results suggest that MNAI can be used as a potential prognostic biomarker for different tumor types toward different clinical endpoints, and multimodal integration of MNAI and CMS exceeds individual biomarker for precision prognosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

A fast and sensitive size-exclusion chromatography method for plasma extracellular vesicle proteomic analysis

Extracellular vesicles (EVs) carry diverse biomolecules derived from their parental cells, making their components excellent biomarker candidates. However, purifying EVs is a major hurdle in biomarker discovery since current methods require large amounts of samples, are time-consuming and typically have poor reproducibility. Here we describe a simple, fast, and sensitive EV fractionation method using size exclusion chromatography (SEC) on a fast protein liquid chromatography (FPLC) system. Our method uses a Superose 6 Increase 5/150, which has a bed volume of 2.9 mL. The FPLC system and small column size enable reproducible separation of only 50 µL of human plasma in 15 min. To demonstrate the utility of our method, we used longitudinal samples from a group of individuals who underwent intense exercise. A total of 838 proteins were identified, of which, 261 were previously characterized as EV proteins, including classical markers, such as cluster of differentiation (CD)9 and CD81. Quantitative analysis showed low technical variability with correlation coefficients greater than 0.9 between replicates. The analysis captured differences in relevant EV proteins involved in response to physical activity. Our method enables fast and sensitive fractionation of plasma EVs with low variability, which will facilitate biomarker studies in large clinical cohorts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Geochemical advances in Arctic Alaska oil typing – North Slope oil correlation and charge history

The Arctic Alaska petroleum province is geologically and geochemically complex. Mixed hydrocarbon charge from multiple source rocks and/or levels of thermal maturity is common within an individual oil pool. Biomarker and chemometric statistical analyses were used to correlate twenty-nine oils to five oil families derived from: (1) Triassic Shublik Formation (calcareous organofacies), (2) Triassic Shublik Formation (shaly organofacies), (3) Jurassic Kingak Shale, (4) Cretaceous shale (pebble shale unit and Hue Shale), and (5) Paleogene shale (Canning Formation). Age-diagnostic and source-related oil biomarker parameters establish clear genetic relationships between the normal oil-window components and their putative source designations. However, application of diamondoid analyses reveals mixed-oil accumulations with postmature charge contributions (diamondoid-rich and biomarker-poor) in many oils. Most sampled reservoirs contain a predominant charge derived from a single oil-window source plus a minor contribution from one or more higher maturity source(s). Variations in source organofacies also are recognized in the Shublik, Kingak, and Cretaceous oil families. In some cases, oils from multiple pools within a single field display relatively homogeneous geochemical profiles, suggesting a common source and migration pathway. For example, oil from the significant Pikka discovery is inferred to originate mainly from the calcareous Shublik Formation. In other cases, variability among oils from multiple pools within a single field (e.g., Milne Point, Colville River, and Northstar) likely indicates a more complex source, migration, and charge history. The results of this study may be useful for anticipating the composition of oil charge in stratigraphic traps with low-permeability sandstone reservoirs, where oil gravity and other chemical parameters may influence economic viability.

58 GEOSCIENCES↗
DOE OSTI2023

A proteomic meta-analysis refinement of plasma extracellular vesicles

Extracellular vesicles play major roles in cell-to-cell communication and are excellent biomarker candidates. However, studying plasma extracellular vesicles is challenging due to contaminants. Here, we performed a proteomics meta-analysis of public data to refine the plasma EV composition by separating EV proteins and contaminants into different clusters. We obtained two clusters with a total of 1717 proteins that were depleted of known contaminants and enriched in EV markers with independently validated 71% true-positive. These clusters had 133 clusters of differentiation (CD) antigens and were enriched with proteins from cell-to-cell communication and signaling. We compared our data with the proteins deposited in PeptideAtlas, making our refined EV protein list a resource for mechanistic and biomarker studies. As a use case example for this resource, we validated the type 1 diabetes biomarker proplatelet basic protein in EVs and showed that it regulates apoptosis of β cells and macrophages, two key players in the disease development. Our approach provides a refinement of the EV composition and a resource for the scientific community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Pediatric Tuberculosis: The Impact of “Omics” on Diagnostics Development

Tuberculosis (TB) is a major public health concern for all ages. However, the disease presents a larger challenge in pediatric populations, partially owing to the lack of reliable diagnostic standards for the early identification of infection. Currently, there are no biomarkers that have been clinically validated for use in pediatric TB diagnosis. Identification and validation of biomarkers could provide critical information on prognosis of disease, and response to treatment. In this review, we discuss how the “omics” approach has influenced biomarker discovery and the advancement of a next generation rapid point-of-care diagnostic for TB, with special emphasis on pediatric disease. Limitations of current published studies and the barriers to their implementation into the field will be thoroughly reviewed within this article in hopes of highlighting future avenues and needs for combating the problem of pediatric tuberculosis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Linking Pharmacogenomic Information on Drug Safety and Efficacy with Ethnic Minority Populations

Numerous prescription drugs’ labeling contains pharmacogenomic (PGx) information to aid health providers and patients in the safe and effective use of drugs. However, clinical studies for such PGx biomarkers and related drug doses are generally not conducted in diverse ethnic populations. Thus, it is urgently important to incorporate PGx information with genetic characteristics of racial and ethnic minority populations and utilize it to promote minority health. In this project a bioinformatics approach was developed to enhance the collection of PGx information related to ethnic minorities to pave the way toward understanding the population-wide utility of PGx information. To address this challenge, we first gathered PGx information from drug labels. Second, we extracted data on the allele frequency information of genetic variants in ethnic minority groups from public resources. Then, we collected published research articles on PGx biomarkers and related drugs for reference. Finally, the data were integrated and formatted to build a new PGx database containing information on known drugs and biomarkers for ethnic minority groups. This database provides scientific information needed to evaluate available PGx information to enhance drug dose selection and drug safety for ethnic minority populations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Evaluation of Plasma Phosphorylated Tau217 for Differentiation Between Alzheimer Disease and Frontotemporal Lobar Degeneration Subtypes Among Patients With Corticobasal Syndrome

Plasma phosphorylated tau217 (p-tau217), a biomarker of Alzheimer disease (AD), is of special interest in corticobasal syndrome (CBS) because autopsy studies have revealed AD is the driving neuropathology in up to 40% of cases. This differentiates CBS from other 4-repeat tauopathy (4RT)–associated syndromes, such as progressive supranuclear palsy Richardson syndrome (PSP-RS) and nonfluent primary progressive aphasia (nfvPPA), where underlying frontotemporal lobar degeneration (FTLD) is typically the primary neuropathology. To validate plasma p-tau217 against positron emission tomography (PET) in 4RT-associated syndromes, especially CBS. This multicohort study with 6, 12, and 24-month follow-up recruited adult participants between January 2011 and September 2020 from 8 tertiary care centers in the 4RT Neuroimaging Initiative (4RTNI). All participants with CBS (n = 113), PSP-RS (n = 121), and nfvPPA (n = 39) were included; other diagnoses were excluded due to rarity (n = 29). Individuals with PET-confirmed AD (n = 54) and PET-negative cognitively normal control individuals (n = 59) were evaluated at University of California San Francisco. Operators were blinded to the cohort. Plasma p-tau217, measured by Meso Scale Discovery electrochemiluminescence, was validated against amyloid-β (Aβ) and flortaucipir (FTP) PET. Imaging analyses used voxel-based morphometry and bayesian linear mixed-effects modeling. Clinical biomarker associations were evaluated using longitudinal mixed-effect modeling. Of 386 participants, 199 (52%) were female, and the mean (SD) age was 68 (8) years. Plasma p-tau217 was elevated in patients with CBS with positive Aβ PET results (mean [SD], 0.57 [0.43] pg/mL) or FTP PET (mean [SD], 0.75 [0.30] pg/mL) to concentrations comparable to control individuals with AD (mean [SD], 0.72 [0.37]), whereas PSP-RS and nfvPPA showed no increase relative to control. Within CBS, p-tau217 had excellent diagnostic performance with area under the receiver operating characteristic curve (AUC) for Aβ PET of 0.87 (95% CI, 0.76-0.98; P < .001) and FTP PET of 0.93 (95% CI, 0.83-1.00; P < .001). At baseline, individuals with CBS-AD (n = 12), defined by a PET-validated plasma p-tau217 cutoff 0.25 pg/mL or greater, had increased temporoparietal atrophy at baseline compared to individuals with CBS-FTLD (n = 39), whereas longitudinally, individuals with CBS-FTLD had faster brainstem atrophy rates. Individuals with CBS-FTLD also progressed more rapidly on a modified version of the PSP Rating Scale than those with CBS-AD (mean [SD], 3.5 [0.5] vs 0.8 [0.8] points/year; P = .005). In this cohort study, plasma p-tau217 had excellent diagnostic performance for identifying Aβ or FTP PET positivity within CBS with likely underlying AD pathology. Plasma P-tau217 may be a useful and inexpensive biomarker to select patients for CBS clinical trials.

59 BASIC BIOLOGICAL SCIENCES↗