PCOM Library / Archive for "Hot Topics in Research"

Category: Hot Topics in Research

Hot Topics: Anesthesiology Should Look to Neuroscience and Nociception

Jackie Werner Hot Topics in Research, Neurology, Surgery

Multimodal General Anesthesia: Theory and Practice

Brown EN, Pavone KJ, Naranjo M. Multimodal general anesthesia: Theory and practice. Anesthesia & Analgesia. http://dx.doi.org/10.1213/ANE.0000000000003668

Balanced general anesthesia, the most common management strategy used in anesthesia care, entails the administration of different drugs together to create the anesthetic state. Anesthesiologists developed this approach to avoid sole reliance on ether for general anesthesia maintenance. Balanced general anesthesia uses less of each drug than if the drug were administered alone, thereby increasing the likelihood of its desired effects and reducing the likelihood of its side effects. To manage nociception intraoperatively and pain postoperatively, the current practice of balanced general anesthesia relies almost exclusively on opioids. While opioids are the most effective antinociceptive agents, they have undesirable side effects. Moreover, overreliance on opioids has contributed to the opioid epidemic in the United States. Spurred by concern of opioid overuse, balanced general anesthesia strategies are now using more agents to create the anesthetic state. Under these approaches, called “multimodal general anesthesia,” the additional drugs may include agents with specific central nervous system targets such as dexmedetomidine and ones with less specific targets, such as magnesium. It is postulated that use of more agents at smaller doses further maximizes desired effects while minimizing side effects. Although this approach appears to maximize the benefit-to-side effect ratio, no rational strategy has been provided for choosing the drug combinations. Nociception induced by surgery is the primary reason for placing a patient in a state of general anesthesia. Hence, any rational strategy should focus on nociception control intraoperatively and pain control postoperatively. In this Special Article, we review the anatomy and physiology of the nociceptive and arousal circuits, and the mechanisms through which commonly used anesthetics and anesthetic adjuncts act in these systems. We propose a rational strategy for multimodal general anesthesia predicated on choosing a combination of agents that act at different targets in the nociceptive system to control nociception intraoperatively and pain postoperatively. Because these agents also decrease arousal, the doses of hypnotics and/or inhaled ethers needed to control unconsciousness are reduced. Effective use of this strategy requires simultaneous monitoring of antinociception and level of unconsciousness. We illustrate the application of this strategy by summarizing anesthetic management for 4 representative surgeries.

Hot Topics: Health-Related Quality of Life Not Sufficiently Measured in Oncology Studies

Jackie Werner Hot Topics in Research, Oncology, Research and Scholarly Communication

Evaluating Progression-Free Survival as a Surrogate Outcome for Health-Related Quality of Life in Oncology: A Systematic Review and Quantitative Analysis

Kovic B, Jin X, Kennedy S, et al. Evaluating progression-free survival as a surrogate outcome for health-related quality of life in oncology: A systematic review and quantitative analysis. JAMA Internal Medicine. 2018. http://doi.org/10.1001/jamainternmed.2018.4710.

Importance  Progression-free survival (PFS) has become a commonly used outcome to assess the efficacy of new cancer drugs. However, it is not clear if delay in progression leads to improved quality of life with or without overall survival benefit.

Objective  To evaluate the association between PFS and health-related quality of life (HRQoL) in oncology through a systematic review and quantitative analysis of published randomized clinical trials. Eligible trials addressed oral, intravenous, intraperitoneal, or intrapleural chemotherapy or biological treatments, and reported PFS or health-related quality of life.

Data Sources  For this systematic review and quantitative analysis of randomized clinical trials of patients with cancer, we searched Medline, Embase, and the Cochrane Central Register of Controlled Trials from January 1, 2000, through May 4, 2016.

Study Selection  Paired reviewers independently screened citations, extracted data, and assessed risk of bias of included studies.

Data Extraction and Synthesis  We examined the association of difference in median PFS duration (in months) between treatment groups with difference in global, physical, and emotional HRQoL scores between groups (standardized to a range of 0-100, with higher scores representing better HRQoL) using weighted simple regressions.

Main Outcome and Measure  The association between PFS duration and HRQoL.

Results  Of 35 960 records screened, 52 articles reporting on 38 randomized clinical trials involving 13 979 patients across 12 cancer types using 6 different HRQoL instruments were included. The mean (SD) difference in median PFS between the intervention and the control arms was 1.91 (3.35) months. The mean (SD) differences in change of HRQoL adjusted to per-month values were −0.39 (3.59) for the global domain, 0.26 (5.56) for the physical domain, and 1.08 (3.49) for the emotional domain. The slope of the association between the difference in median PFS and the difference in change for global HRQoL (n = 30 trials) was 0.12 (95% CI, −0.27 to 0.52); for physical HRQoL (n = 20 trials) it was −0.20 (95% CI, −0.62 to 0.23); and for emotional HRQoL (n = 13 trials) it was 0.78 (95% CI, −0.05 to 1.60).

Conclusions and Relevance  We failed to find a significant association between PFS and HRQoL in cancer clinical trials. These findings raise questions regarding the assumption that interventions prolonging PFS also improve HRQoL in patients with cancer. Therefore, to ensure that patients are truly obtaining important benefit from cancer therapies, clinical trial investigators should measure HRQoL directly and accurately, ensuring adequate duration and follow-up.

Hot Topics: Assessment Identifies Patients At Risk for Cardiac-Induced PTSD

Jackie Werner Cardiology, Hot Topics in Research, Psychology and Psychiatry

Development and Validation of a Measure to Assess Patients’ Threat Perceptions in the Emergency Department

Cornelius T, Agarwal S, Garcia O, Chaplin W, Edmondson D, Chang BP. Development and validation of a measure to assess patients’ threat perceptions in the emergency department. Acad Emerg Med. 2018;0. https://doi.org/10.1111/acem.13513.


Threat perceptions in the Emergency Department (ED) (e.g., patients’ subjective feelings of helplessness or lack of control) during evaluation for an acute coronary syndrome (ACS) are associated with the development of posttraumatic stress disorder (PTSD), and PTSD has been associated with medication nonadherence, cardiac event recurrence, and mortality. This study reports the development and validation of a 7‐item measure of ED Threat Perceptions in English‐ and Spanish‐speaking patients evaluated for ACS.


Participants were drawn from an observational cohort study of 1,000 patients evaluated for ACS between 2013‐2016 in a large, New York City hospital. Participants reported on threat perceptions in the ED and during inpatient stay (using 12 items previously identified as predictive of PTSD) and reported on cardiac‐induced PTSD one month post‐discharge. Exploratory and confirmatory factor analyses were used to establish the factor structure and test measurement invariance. Validity and reliability were examined, as was the association of ED Threat Perceptions with cardiac‐induced PTSD.


Factor analyses identified a 7‐item measure of ED Threat Perceptions (e.g., “I feel helpless,” “I am worried that I am going to die”) for both English‐ and Spanish‐speaking patients. ED Threat Perceptions demonstrated convergent validity, correlating with ED stress and ED crowdedness (rs = .29, .14), good internal consistency (α = .82), and stability (r = .61). Threat Perceptions were associated with cardiac‐induced acute stress at inpatient and PTSD symptoms at one month (rs = .43, .39).


This brief tool assessing ED Threat Perceptions has clinical utility for providers to identify patients at risk for developing cardiac‐induced PTSD and is critical to inform research on whether threat may be modified in‐ED to reduce PTSD incidence.

Hot Topics: Dementia Risk Doubled After Stroke

Jackie Werner Dementia, Hot Topics in Research, Neurology

Stroke and dementia risk: A systematic review and meta-analysis

Kuźma E, Lourida I, Moore SF, Levine DA, Ukoumunne OC, Llewellyn DJ. Stroke and dementia risk: A systematic review and meta-analysis. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association. . https://doi.org/10.1016/j.jalz.2018.06.3061.

Stroke is an established risk factor for all-cause dementia, though meta-analyses are needed to quantify this risk.

We searched Medline, PsycINFO, and Embase for studies assessing prevalent or incident stroke versus a no-stroke comparison group and the risk of all-cause dementia. Random effects meta-analysis was used to pool adjusted estimates across studies, and meta-regression was used to investigate potential effect modifiers.

We identified 36 studies of prevalent stroke (1.9 million participants) and 12 studies of incident stroke (1.3 million participants). For prevalent stroke, the pooled hazard ratio for all-cause dementia was 1.69 (95% confidence interval: 1.49–1.92; P < .00001; I2 = 87%). For incident stroke, the pooled risk ratio was 2.18 (95% confidence interval: 1.90–2.50; P < .00001; I2 = 88%). Study characteristics did not modify these associations, with the exception of sex which explained 50.2% of between-study heterogeneity for prevalent stroke.

Stroke is a strong, independent, and potentially modifiable risk factor for all-cause dementia.

Hot Topics: AI Model Better Predicts Heart Disease Deaths

Jackie Werner Cardiology, Hot Topics in Research

Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease

Steele AJ, Denaxas SC, Shah AD, Hemingway H, Luscombe NM. Machine learning models in electronic health records can outperform conventional survival models for predicting patient mortality in coronary artery disease. PLOS ONE. 2018;13(8):e0202344. https://doi.org/10.1371/journal.pone.0202344.

Prognostic modelling is important in clinical practice and epidemiology for patient management and research. Electronic health records (EHR) provide large quantities of data for such models, but conventional epidemiological approaches require significant researcher time to implement. Expert selection of variables, fine-tuning of variable transformations and interactions, and imputing missing values are time-consuming and could bias subsequent analysis, particularly given that missingness in EHR is both high, and may carry meaning. Using a cohort of 80,000 patients from the CALIBER programme, we compared traditional modelling and machine-learning approaches in EHR. First, we used Cox models and random survival forests with and without imputation on 27 expert-selected, preprocessed variables to predict all-cause mortality. We then used Cox models, random forests and elastic net regression on an extended dataset with 586 variables to build prognostic models and identify novel prognostic factors without prior expert input. We observed that data-driven models used on an extended dataset can outperform conventional models for prognosis, without data preprocessing or imputing missing values. An elastic net Cox regression based with 586 unimputed variables with continuous values discretised achieved a C-index of 0.801 (bootstrapped 95% CI 0.799 to 0.802), compared to 0.793 (0.791 to 0.794) for a traditional Cox model comprising 27 expert-selected variables with imputation for missing values. We also found that data-driven models allow identification of novel prognostic variables; that the absence of values for particular variables carries meaning, and can have significant implications for prognosis; and that variables often have a nonlinear association with mortality, which discretised Cox models and random forests can elucidate. This demonstrates that machine-learning approaches applied to raw EHR data can be used to build models for use in research and clinical practice, and identify novel predictive variables and their effects to inform future research.

Hot Topics: New Sensor Speedily Detects Receptor Activation

Jackie Werner Hot Topics in Research, Pharmaceutical Sciences

A universal bioluminescence resonance energy transfer sensor design enables high-sensitivity screening of GPCR activation dynamics

Schihada H, Vandenabeele S, Zabel U, Frank M, Lohse MJ, Maiellaro I. A universal bioluminescence resonance energy transfer sensor design enables high-sensitivity screening of GPCR activation dynamics. Communications Biology. 2018;1(1):105. https://doi.org/10.1038/s42003-018-0072-0.

G-protein-coupled receptors (GPCRs) represent one of the most important classes of drug targets. The discovery of new GCPR therapeutics would greatly benefit from the development of a generalizable high-throughput assay to directly monitor their activation or de-activation. Here we screened a variety of labels inserted into the third intracellular loop and the C-terminus of the α2A-adrenergic receptor and used fluorescence (FRET) and bioluminescence resonance energy transfer (BRET) to monitor ligand-binding and activation dynamics. We then developed a universal intramolecular BRET receptor sensor design to quantify efficacy and potency of GPCR ligands in intact cells and real time. We demonstrate the transferability of the sensor design by cloning β2-adrenergic and PTH1-receptor BRET sensors and monitored their efficacy and potency. For all biosensors, the Z factors were well above 0.5 showing the suitability of such design for microtiter plate assays. This technology will aid the identification of novel types of GPCR ligands.

Hot Topics: Nuclear Medicine Imaging Targets Cancer

Jackie Werner Hot Topics in Research, Oncology, Radiology

A Tumor-Imaging Method Targeting Cancer-Associated Fibroblasts

Loktev A, Lindner T, Mier W, et al. A tumor-imaging method targeting cancer-associated fibroblasts. Journal of Nuclear Medicine. 2018;59(9):1423-1429. http://dx.doi.org/10.2967/jnumed.118.210435.

The tumor stroma, which accounts for a large part of the tumor mass, represents an attractive target for the delivery of diagnostic and therapeutic compounds. Here, the focus is notably on a subpopulation of stromal cells, known as cancer-associated fibroblasts, which are present in more than 90% of epithelial carcinomas, including pancreatic, colon, and breast cancer. Cancer-associated fibroblasts feature high expression of fibroblast activation protein (FAP), which is not detectable in adult normal tissue but is associated with a poor prognosis in cancer patients. Methods: We developed an iodinated and a DOTA-coupled radiotracer based on a FAP-specific enzyme inhibitor (FAPI) and evaluated them in vitro using uptake, competition, and efflux studies as well as confocal microscopy of a fluorescence-labeled variant. Furthermore, we performed imaging and biodistribution studies on tumor-bearing animals. Finally, proof of concept was realized by imaging patients with 68Ga-labeled FAPI. Results: Both FAPIs showed high specificity, affinity, and rapid internalization into FAP-expressing cells in vitro and in vivo. Biodistribution studies on tumor-bearing mice and on the first cancer patients demonstrated high intratumoral uptake of the tracer and fast body clearance, resulting in high-contrast images and negligible exposure of healthy tissue to radiation. A comparison with the commonly used radiotracer 18F-FDG in a patient with locally advanced lung adenocarcinoma revealed that the new FAP ligand was clearly superior. Conclusion: Radiolabeled FAPIs allow fast imaging with very high contrast in tumors having a high stromal content and may therefore serve as pantumor agents. Coupling of these molecules to DOTA or other chelators allows labeling not only with 68Ga but also with therapeutic isotopes such as 177Lu or 90Y.

Hot Topics: Genetic Cause of Final Blood Group System Discovered

Jackie Werner Blood, Cardiology, Hot Topics in Research

Disruption of a GATA1-binding motif upstream of XG/PBDX abolishes Xga expression and resolves the Xg blood group system

Möller M, Lee YQ, Vidovic K, et al. Disruption of a GATA1-binding motif upstream of XG/PBDX abolishes Xga expression and resolves the Xg blood group system. Blood. 2018. http://dx.doi.org/10.1182/blood-2018-03-842542.

The Xga blood group is differentially expressed on erythrocytes from males and females. The underlying gene, PBDX, was identified already in 1994 but the molecular background for Xga expression remains undefined. This gene, now designated XG, partly resides in the pseudoautosomal region 1 and encodes a protein of unknown function from the X chromosome. By comparing calculated Xgaallele frequencies in different populations to 2,612 genetic variants in the XG region, rs311103 showed the strongest correlation to the expected distribution. The same SNP had the most significant impact on XG transcript levels in whole blood (P=2.0×10-22). The minor allele, rs311103C, disrupts a GATA-binding motif 3.7 kb upstream of the transcription start point. This silences erythroid XG-mRNA expression and causes the Xg(a–) phenotype, a finding corroborated by SNP genotyping in 119 blood donors. Binding of GATA1 to biotinylated oligonucleotide probes with rs311103G but not rs311103C was observed by EMSA and proven by mass spectrometry. Finally, a luciferase reporter assay indicated this GATA motif to be active for rs311103G but not rs311103C in HEL cells. By using an integrated bioinformatics and molecular biology approach, we elucidated the underlying genetic basis for the last unresolved blood group system and made Xga genotyping possible.

Hot Topics: Drug Effectiveness Predicted by Brain “Fingerprint”

Jackie Werner Hot Topics in Research, Neurology, Pharmaceutical Sciences

Multimodal imaging-based therapeutic fingerprints for optimizing personalized interventions: Application to neurodegeneration

Iturria-Medina Y, Carbonell FM, Evans AC. Multimodal imaging-based therapeutic fingerprints for optimizing personalized interventions: Application to neurodegeneration. NeuroImage. 2018;179:40-50. http://dx.doi.org/10.1016/j.neuroimage.2018.06.028.

Personalized Medicine (PM) seeks to assist the patients according to their specific treatment needs and potential intervention responses. However, in the neurological context, this approach is limited by crucial methodological challenges, such as the requirement for an understanding of the causal disease mechanisms and the inability to predict the brain’s response to therapeutic interventions. Here, we introduce and validate the concept of the personalized Therapeutic Intervention Fingerprint (pTIF), which predicts the effectiveness of potential interventions for controlling a patient’s disease evolution. Each subject’s pTIF can be inferred from multimodal longitudinal imaging (e.g. amyloid-β, metabolic and tau PET; vascular, functional and structural MRI). We studied an aging population (N = 331) comprising cognitively normal and neurodegenerative patients, longitudinally scanned using six different neuroimaging modalities. We found that the resulting pTIF vastly outperforms cognitive and clinical evaluations on predicting individual variability in gene expression (GE) profiles. Furthermore, after regrouping the patients according to their predicted primary single-target interventions, we observed that these pTIF-based subgroups present distinctively altered molecular pathway signatures, supporting the across-population identification of dissimilar pathological stages, in active correspondence with different therapeutic needs. The results further evidence the imprecision of using broad clinical categories for understanding individual molecular alterations and selecting appropriate therapeutic needs. To our knowledge, this is the first study highlighting the direct link between multifactorial brain dynamics, predicted treatment responses, and molecular alterations at the patient level. Inspired by the principles of PM, the proposed pTIF framework is a promising step towards biomarker-driven assisted therapeutic interventions, with additional important implications for selective enrollment of patients in clinical trials.

Hot Topics: New Techniques Examine Parkinson’s Damage to Heart

Jackie Werner Central Nervous System Disorders, Hot Topics in Research, Neurology

In vivo imaging of inflammation and oxidative stress in a nonhuman primate model of cardiac sympathetic neurodegeneration

Metzger JM, Moore CF, Boettcher CA, et al. In vivo imaging of inflammation and oxidative stress in a nonhuman primate model of cardiac sympathetic neurodegeneration. npj Parkinson’s Disease. 2018;4(1):22. https://doi.org/10.1038/s41531-018-0057-1.

Loss of cardiac postganglionic sympathetic innervation is a characteristic pathology of Parkinson’s disease (PD). It progresses over time independently of motor symptoms and is not responsive to typical anti-parkinsonian therapies. Cardiac sympathetic neurodegeneration can be mimicked in animals using systemic dosing of the neurotoxin 6-hydroxydopamine (6-OHDA). As in PD, 6-OHDA-induced neuronal loss is associated with increased inflammation and oxidative stress. To assess the feasibility of detecting changes over time in cardiac catecholaminergic innervation, inflammation, and oxidative stress, myocardial positron emission tomography with the radioligands [11C]meta-hydroxyephedrine (MHED), [11C]PBR28 (PBR28), and [61Cu]diacetyl-bis(N(4))-methylthiosemicarbazone (ATSM) was performed in 6-OHDA-intoxicated adult, male rhesus macaques (n = 10; 50 mg/kg i.v.). The peroxisome proliferator-activated receptor gamma (PPARγ) agonist pioglitazone, which is known to have anti-inflammatory and anti-oxidative stress properties, was administered to five animals (5 mg/kg, PO); the other five were placebo-treated. One week after 6-OHDA, cardiac MHED uptake was significantly reduced in both groups (placebo, 86% decrease; pioglitazone, 82%); PBR28 and ATSM uptake increased in both groups but were attenuated in pioglitazone-treated animals (PBR28 Treatment × Level ANOVA p < 0.002; ATSM Mann–Whitney p = 0.032). At 12 weeks, partial recovery of MHED uptake was significantly greater in the pioglitazone-treated group, dependent on left ventricle circumferential region and axial level (Treatment × Region × Level ANOVA p = 0.034); 12-week MHED uptake significantly correlated with tyrosine hydroxylase immunoreactivity across cardiac anatomy (p < 0.000002). PBR28 and ATSM uptake returned to baseline levels by 12 weeks. These radioligands thus hold potential as in vivo biomarkers of mechanisms of cardiac neurodegeneration and neuroprotection.