Circulating immune cell landscape in patients who had mild ischaemic stroke.

INTRODUCTION: Patients who had a mild ischaemic stroke who present with subtle or resolving symptoms sometimes go undiagnosed, are excluded from treatment and in some cases clinically worsen. Circulating immune cells are potential biomarkers that can assist with diagnosis in ischaemic stroke. Understanding the transcriptomic changes of each cell population caused by ischaemic stroke is critical because they work closely in a complicated relationship. In this study, we investigated peripheral blood mononuclear cells (PBMCs) transcriptomics of patients who had a stroke using a single-cell RNA sequencing to understand peripheral immune response after mild stroke based on the gene expression in an unbiased way. METHODS: Transcriptomes of PBMCsfrom 10 patients who had an acute ischaemic stroke within 24 hours after stroke onset were compared with 9 race-matched/age-matched/gender-matched controls. Individual PBMCs were prepared with ddSeqTM (Illumina-BioRad) and sequenced on the Illumina NovaSeq 6000 platform. RESULTS: Notable population changes were observed in patients who had a stroke, especially in NK cells and CD14+ monocytes. The number of NK cells was increased, which was further confirmed by flow cytometry. Functional analysis implied that the activity of NK cells also is enhanced in patients who had a stroke. CD14+ monocytes were clustered into two groups; dendritic cell-related CD14+ monocytes and NK cell-related CD14+ monocytes. We found CD14+ monocyte subclusters were dramatically reduced in patients who had a stroke. DISCUSSION: This is the first study demonstrating the increased number of NK cells and new monocyte subclusters of mild ischaemic stroke based on the transcriptomic analysis. Our findings provide the dynamics of circulating immune response that could assist diagnosis and potential therapeutic development of mild ischaemic stroke.

Development of a COVID-19 alternate care site from ground zero: A nursing perspective.

The novel coronavirus disease SARS-CoV-2 (COVID-19) outbreak rapidly generated an unprecedented global, national, and state public health crisis with the need to rapidly develop alternate care sites (ACS) to care for COVID-19 patients within an overburdened health care system. A hospital care model ACS to increase the health care capacity, provide care for mild to moderately symptomatic patients, and offer local self-sustainment for a surge of patients was developed in Memphis, Tennessee located in Shelby County. We completed a temporary conversion of a large unused newspaper publication building to a health care facility for COVID-19 patients. Developing an ACS from ground zero was met with many challenges, and throughout the process important lessons were learned. With the goal to complete the building conversion within a 28-day timeframe, collaboration among the numerous governmental, health care, and private agencies was critical and nursing leadership was key to this process. The purpose of this paper is to describe the development of a COVID-19 ACS in Memphis, TN, which has a large at-risk population with limited access to health care. Specifically, we will discuss the strong leadership role of nursing faculty, key challenges, and lessons learned, as well as provide checklists and models for others in similar circumstances.

The Possible Influence of Mediterranean Diet on Extracellular Vesicle miRNA Expression in Breast Cancer Survivors.

The Mediterranean diet (MD) has been reported to have beneficial effects on breast cancer and cardiovascular diseases. Recently, microRNAs (miRNAs) have been suggested as biomarkers for the diagnosis and disease prognosis in cancer and cardiovascular diseases. We evaluated the influence of the MD on the plasma-derived extracellular vesicle miRNA signature of overweight breast cancer survivors. Sixteen participants instructed to adhere to the MD for eight weeks were included in this study. To curate differentially expressed miRNAs after MD intervention, we employed two methods: significance analysis of microarrays and DESeq2. The selected miRNAs were analyzed using ingenuity pathway analysis. After an eight-week intervention, body mass index, waist circumference, fasting glucose, fasting insulin, and homeostatic model assessment for insulin resistance were significantly improved. Expression levels of 798 miRNAs were comprehensively analyzed, and 42 extracellular vesicle miRNAs were significantly differentially regulated after the eight-week MD (36 were up and 6 were down-regulated). We also identified enriched pathways in genes regulated by differentially expressed 42 miRNAs, which include signaling associated with breast cancer, energy metabolism, glucose metabolism, and insulin. Our study indicates that extracellular vesicle miRNAs differentially expressed as a result of the MD might be involved in the mechanisms that relate to cardiometabolic risk factors in overweight breast cancer survivors.

Gene co-expression networks are associated with obesity-related traits in kidney transplant recipients.

BACKGROUND: Obesity is common among kidney transplant recipients; However biological mediators of obesity are not well understood in this population. Because subcutaneous adipose tissue can be easily obtained during kidney transplant surgery, it provides a unique avenue for studying the mechanisms of obesity for this group. Although differential gene expression patterns were previously profiled for kidney transplant patients, gene co-expression patterns can shed light on gene modules not yet explored on the coordinative behaviors of gene transcription in biological and disease processes from a systems perspective. METHODS: In this study, we collected 29 demographic and clinical variables and matching microarray expression data for 26 kidney transplant patients. We conducted Weighted Gene Correlation Network Analysis (WGCNA) for 5758 genes with the highest average expression levels and related gene co-expression to clinical traits. RESULTS: A total of 35 co-expression modules were detected, two of which showed associations with obesity-related traits, mainly at baseline. Gene Ontology (GO) enrichment was found for these two clinical trait-associated modules. One module consisting of 129 genes was enriched for a variety of processes, including cellular homeostasis and immune responses. The other module consisting of 36 genes was enriched for tissue development processes. CONCLUSIONS: Our study generated gene co-expression modules associated with obesity-related traits in kidney transplant patients and provided new insights regarding the cellular biological processes underlying obesity in this population.

Precision health: A nursing perspective.

Precision health refers to personalized healthcare based on a person's unique genetic, genomic, or omic composition within the context of lifestyle, social, economic, cultural and environmental influences to help individuals achieve well-being and optimal health. Precision health utilizes big data sets that combine omics (i.e. genomic sequence, protein, metabolite, and microbiome information) with clinical information and health outcomes to optimize disease diagnosis, treatment and prevention specific to each patient. Successful implementation of precision health requires interprofessional collaboration, community outreach efforts, and coordination of care, a mission that nurses are well-positioned to lead. Despite the surge of interest and attention to precision health, most nurses are not well-versed in precision health or its implications for the nursing profession. Based on a critical analysis of literature and expert opinions, this paper provides an overview of precision health and the importance of engaging the nursing profession for its implementation. Other topics reviewed in this paper include big data and omics, information science, integration of family health history in precision health, and nursing omics research in symptom science. The paper concludes with recommendations for nurse leaders in research, education, clinical practice, nursing administration and policy settings for which to develop strategic plans to implement precision health.

Establishing the Omics Nursing Science & Education Network.

PURPOSE: To establish a website to advance nursing research and education involving omics technologies and methodologies through facilitating collaborations, use of existing data and samples, mentoring, and access to training opportunities. METHODS: The Omics Nursing Science & Education Network (ONSEN) website was established following identification of gaps in omics nursing infrastructure and resources that could be addressed via a concerted, collaborative effort. ONSEN content was created using input from a workgroup of experts in genomics and other omics, education, practice, and nursing research. Alpha testing was conducted with workgroup members, followed by website refinements and enhancements, and subsequent beta testing by potential end users. ONSEN was launched in August 2018. FINDINGS: ONSEN has three main sections. The Education and Training section provides information on mentoring and pre- or postdoctoral opportunities in addition to a knowledge matrix to advance education and skills in genomic nursing science. The Research Collaborations section promotes awareness of ongoing omics nursing research in order to foster collaborations and sharing of samples or data among investigators with programs in omics nursing research or an interest in developing such programs. The Common Data Elements (CDE) section provides information on the benefits of incorporating CDEs into nursing science as well as links to National Institutes of Health resources to facilitate use of CDEs. CONCLUSIONS: ONSEN provides opportunities for nurse scientists and trainees to leverage samples and datasets, locate mentors and pre- or postdoctoral positions, further the use of CDEs, and enhance education and skills for integrating omics into nursing science. CLINICAL RELEVANCE: Advancing omics nursing science via ONSEN resources will accelerate the elucidation of the molecular underpinnings of disease and associated symptoms as well as inform the development of rapidly translatable, personalized intervention strategies, grounded in biological mechanisms, for improved health outcomes across populations and the lifespan.

Exosomal Protein Profiles as Novel Biomarkers in Weight Gain After Kidney Transplantation: A Pilot Study

Purpose@#Weight gain after kidney transplantation is a critical factor that can lead to poor outcomes with cardiovascular complications. Many studies have been conducted to identify predictive markers of future weight changes at the time of transplant. Recently, circulating exosomes and its contents including miRNAs and proteins have attracted attention as potential biomarkers. In this pilot study, we investigated exosomal proteins and weight change after kidney transplant. @*Methods@#Recipients (n=10) were classified into two groups; weight gainers (n=5, 9.7±4.4kg) and weight losers (n=5, -6.4±1.8kg) based on their weight changes at 12-months posttransplant. Based on the exosomal protein profiles obtained by the LC-MS/MS, differentially expressed proteins were identified between the groups. @*Results@#Concentration and the mean size of exosomes significantly increased at 12-months compared to the baseline (p=.009) in the total group. Eleven exosomal proteins were found at the baseline as differentially expressed between the two groups. In the weight gain group, complement proteins including HV169, C3, C4B, and C4A, were significantly upregulated. @*Conclusion@#Our pilot study suggests that exosomal complementary proteins are associated with weight gain after kidney transplantation. Further studies are needed to clarify the role of these exosomal proteins in the underlying mechanisms of weight changes in kidney transplant recipients.

Advocacy and actions to address disparities in access to genomic health care: A report on a National Academies workshop.

BACKGROUND: In the United States, access to genomic risk assessment, testing, and follow up care is most easily obtained by those who have sufficient financial, educational, and social resources. Multiple barriers limit the ability of populations without those resources to benefit from health care that integrates genomics in assessment of disease risk, diagnosis, and targeted treatment. PURPOSE: To summarize barriers and potential actions to reduce genomic health care disparities. METHOD: Summarize authors' views on discussions at a workshop hosted by the National Academy of Medicine. DISCUSSION: Barriers include access to health care providers that utilize genomics, genetic literacy of providers and patients, and absence of evidence of gene variants importance in ancestrally diverse underserved populations. CONCLUSION: Engagement between underserved communities, health care providers, and policy makers is an essential component to raise awareness and seek solutions to barriers in access to genomic health care for all populations.

The impact of plasma brain-derived neurotrophic factor concentration and weight gain after kidney transplantation.

Obesity and its related complications continue to be significant challenges for kidney transplant recipients. In previous studies, researchers have reported that brain-derived neurotrophic factor (BDNF) is closely associated with metabolic imbalance and obesity, but the role of BDNF in weight gain after kidney transplant has not been elucidated. The purpose of this pilot study was to explore the relationship between plasma BDNF levels and weight change. We examined associations between plasma BDNF levels measured at transplantation and 12 months later and measures of weight change during these 12 months in a sample of 55 kidney recipients (mean age of 48 years, 60% male, 56% African American). Of the 55 recipients, 49 had BDNF levels measured at baseline, 33 had BDNF levels measured at 12 months, and 27 had BDNF levels measured at both time points. We found that plasma BDNF levels at baseline (n = 49), but not at 12 months (n = 33), were significantly and positively correlated with the body mass index change (p = 0.037) and percentage weight change (p = 0.036). In addition, average plasma BDNF value at 12 months (307 ± 254 pg/ml) was significantly lower than at baseline (452 ± 345 pg/ml) in the 27 recipients with BDNF levels measured at both time points. Findings from this pilot work suggest that BDNF might serve as a regulator of weight change for kidney transplant related obesity.

Altered DNA Methylation Patterns Associated With Clinically Relevant Increases in PTSD Symptoms and PTSD Symptom Profiles in Military Personnel.

Military personnel experience posttraumatic stress disorder (PTSD), which is associated with differential DNA methylation across the whole genome. However, the relationship between these DNA methylation patterns and clinically relevant increases in PTSD severity is not yet clearly understood. The purpose of this study was to identify differences in DNA methylation associated with PTSD symptoms and investigate DNA methylation changes related to increases in the severity of PTSD in military personnel. In this pilot study, a cross-sectional comparison was made between military personnel with PTSD (n = 8) and combat-matched controls without PTSD (n = 6). Symptom measures were obtained, and genome-wide DNA methylation was measured using methylated DNA immunoprecipitation (MeDIP-seq) from whole blood samples at baseline and 3 months later. A longitudinal comparison measured DNA methylation changes in military personnel with clinically relevant increases in PTSD symptoms between time points (PTSD onset) and compared methylation patterns to controls with no clinical changes in PTSD. In military personnel with elevated PTSD symptoms 3 months following baseline, 119 genes exhibited reduced methylation and 8 genes exhibited increased methylation. Genes with reduced methylation in the PTSD-onset group relate to the canonical pathways of netrin signaling, Wnt/Ca+ pathway, and axonal guidance signaling. These gene pathways relate to neurological disorders, and the current findings suggest that these epigenetic changes potentially relate to PTSD symptomology. This study provides some novel insights into the role of epigenetic changes in PTSD symptoms and the progression of PTSD symptoms in military personnel.

Moderate blast exposure alters gene expression and levels of amyloid precursor protein.

OBJECTIVE: To explore gene expression after moderate blast exposure (vs baseline) and proteomic changes after moderate- (vs low-) blast exposure. METHODS: Military personnel (N = 69) donated blood for quantification of protein level, and peak pressure exposures were detected by helmet sensors before and during a blast training program (10 days total). On day 7, some participants (n = 29) sustained a moderate blast (mean peak pressure = 7.9 psi) and were matched to participants with no/low-blast exposure during the training (n = 40). PAXgene tubes were collected from one training site at baseline and day 10; RNA-sequencing day 10 expression was compared with each participant's own baseline samples to identify genes and pathways differentially expressed in moderate blast-exposed participants. Changes in amyloid precursor protein (APP) from baseline to the day of blast and following 2 days were evaluated. Symptoms were assessed using a self-reported form. RESULTS: We identified 1,803 differentially expressed genes after moderate blast exposure; the most altered network was APP. Significantly reduced levels of peripheral APP were detected the day after the moderate blast exposure and the following day. Protein concentrations correlated with the magnitude of the moderate blast exposure on days 8 and 9. APP concentrations returned to baseline levels 3 days following the blast, likely due to increases in the genetic expression of APP. Onset of concentration problems and headaches occurred after moderate blast. CONCLUSIONS: Moderate blast exposure results in a signature biological profile that includes acute APP reductions, followed by genetic expression increases and normalization of APP levels; these changes likely influence neuronal recovery.

Characterization of Body Composition and Fat Mass Distribution 1 Year After Kidney Transplantation.

PURPOSE: In some recipients, significant weight gain occurs after kidney transplantation. Weight gain is associated with poor outcomes, particularly increased cardiovascular risk. In this study, we characterized changes in body mass index and body fat mass and compared them based on gender and race. METHODS: Fifty-two kidney transplant recipients (aged ≥18 years old, 50% men, 58% African American) were enrolled into a prospective study. Body mass index and body fat mass were measured at baseline and 12 months posttransplant. Body fat mass was determined by dual-energy X-ray absorptiometry. RESULTS: The mean increase in body weight was 3.7kg at 12 months; 36.5% (n=19) gained at least 10% of their baseline body weight. Body mass index, percentage of total body fat, and trunk fat were significantly increased. In subgroups, women and African American showed significant increases in body mass index and body fat measures. More participants were classified as obese based on total body fat compared to body mass index. Calories from fat were significantly increased at 12 months and associated with increased body mass index, total body fat, and trunk fat. Days of physical activity were significantly increased. CONCLUSION: Both body mass index and total body fat mass were significantly increased at 12 months following kidney transplantation, especially for women and African Americans. Importantly, more participants were classified as obese based on total body fat compared to body mass index. Relevant nutrition and physical intervention should be provided, and both body mass index and body fat mass should be evaluated when monitoring weight gain.

Older Age Results in Differential Gene Expression after Mild Traumatic Brain Injury and Is Linked to Imaging Differences at Acute Follow-up.

Older age consistently relates to a lesser ability to fully recover from a traumatic brain injury (TBI); however, there is limited data to explicate the nature of age-related risks. This study was undertaken to determine the relationship of age on gene-activity following a TBI, and how this biomarker relates to changes in neuroimaging findings. A young group (between the ages of 19 and 35 years), and an old group (between the ages of 60 and 89 years) were compared on global gene-activity within 48 h following a TBI, and then at follow-up within 1-week. At each time-point, gene expression profiles, and imaging findings from both magnetic resonance imaging (MRI) and computed tomography were obtained and compared. The young group was found to have greater gene expression of inflammatory regulatory genes at 48 h and 1-week in genes such as basic leucine zipper transcription factor 2 (BACH2), leucine-rich repeat neuronal 3 (LRRN3), and lymphoid enhancer-binding factor 1 (LEF1) compared to the old group. In the old group, there was increased activity in genes within S100 family, including calcium binding protein P (S100P) and S100 calcium binding protein A8 (S100A8), which previous studies have linked to poor recovery from TBI. The old group also had reduced activity of the noggin (NOG) gene, which is a member of the transforming growth factor-ß superfamily and is linked to neurorecovery and neuroregeneration compared to the young group. We link these gene expression findings that were validated to neuroimaging, reporting that in the old group with a MRI finding of TBI-related damage, there was a lesser likelihood to then have a negative MRI finding at follow-up compared to the young group. Together, these data indicate that age impacts gene activity following a TBI, and suggest that this differential activity related to immune regulation and neurorecovery contributes to a lesser likelihood of neuronal recovery in older patients as indicated through neuroimaging.

National Institutes of Health Symptom Science Model sheds light on patient symptoms.

Since the establishment of the nursing profession, identifying and alleviating the subjective symptoms experienced by patients has been at the core of nursing practice. In supporting the scientific foundation for clinical practice, nursing science has maintained a consistent commitment to prevent, manage, and eliminate symptoms. Scientists from the intramural research program at the National Institute of Nursing Research (NINR), a component of the National Institutes of Health, developed a National Institutes of Health Symptom Science Model (NIH-SSM) to guide symptom science research programs engaged in the use of emerging "omic" methods such as the genotyping of symptom phenotypes. The NIH-SSM was developed based on the NINR intramural research program's success in designing and implementing methods for examining identified symptoms or symptom clusters. The NIH-SSM identifies the research process of characterizing symptom phenotypes, identifying and testing biomarkers, and ultimately developing clinical interventions in cancer-related fatigue, gastrointestinal disorders, and traumatic brain injuries. The purpose of this article was to demonstrate how scientists can apply the NIH-SSM, leading the broader scientific community in advancing personalized and precise clinical interventions.